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Career Development International

ISSN : 1362-0436

Article publication date: 25 January 2022

Issue publication date: 18 February 2022

The field of careers studies is complex and fragmented. The aim of this paper is to detail why it is important to study careers, what we study and how we study key issues in this evolving field.

Design/methodology/approach

Key theories, concepts and models are briefly reviewed to lay the groundwork for offering an agenda for future research.

The authors recommend ten key directions for future research and offer specific questions for further study.

Research limitations/implications

This paper contributes to the development of the theoretical underpinning of career studies.

Practical implications

The authors hope that the proposed agenda for future research will help advance the field and encourage more research on understudied, but important, topics.

Originality/value

This paper presents a comprehensive view of research on contemporary careers.

• Career studies
• Contemporary careers
• Future research agenda

Acknowledgements

The authors thank the two anonymous reviewers and Editor Jim Jawahar for their insightful comments.

Baruch, Y. and Sullivan, S.E. (2022), "The why, what and how of career research: a review and recommendations for future study", Career Development International , Vol. 27 No. 1, pp. 135-159. https://doi.org/10.1108/CDI-10-2021-0251

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SYSTEMATIC REVIEW article

The effects of technological developments on work and their implications for continuous vocational education and training: a systematic review.

• Faculty of Human Sciences, University of Regensburg, Regensburg, Germany

Technology is changing the way organizations and their employees need to accomplish their work. Empirical evidence on this topic is scarce. The aim of this study is to provide an overview of the effects of technological developments on work characteristics and to derive the implications for work demands and continuous vocational education and training (CVET). The following research questions are answered: What are the effects of new technologies on work characteristics? What are the implications thereof for continuous vocational education and training? Technologies, defined as digital, electrical or mechanical tools that affect the accomplishment of work tasks, are considered in various disciplines, such as sociology or psychology. A theoretical framework based on theories from these disciplines (e.g., upskilling, task-based approach) was developed and statements on the relationships between technology and work characteristics, such as complexity, autonomy, or meaningfulness, were derived. A systematic literature review was conducted by searching databases from the fields of psychology, sociology, economics and educational science. Twenty-one studies met the inclusion criteria. Empirical evidence was extracted and its implications for work demands and CVET were derived by using a model that illustrates the components of learning environments. Evidence indicates an increase in complexity and mental work, especially while working with automated systems and robots. Manual work is reported to decrease on many occasions. Workload and workflow interruptions increase simultaneously with autonomy, especially with regard to digital communication devices. Role expectations and opportunities for development depend on how the profession and the technology relate to each other, especially when working with automated systems. The implications for the work demands necessary to deal with changes in work characteristics include knowledge about technology, openness toward change and technology, skills for self- and time management and for further professional and career development. Implications for the design of formal learning environments (i.e., the content, method, assessment, and guidance) include that the work demands mentioned must be part of the content of the trainings, the teachers/trainers must be equipped to promote those work demands, and that instruction models used for the learning environments must be flexible in their application.

Introduction

In the face of technology-driven disruptive changes in societal and organizational practices, continuous vocational education and training (CVET) lacks information on how the impact of technologies on work must be considered from an educational perspective ( Cascio and Montealegre, 2016 ). Research on workplace technologies, i.e., tools or systems that have the potential to replace or supplement work tasks, typically are concerned with one out of two areas of interest: First, economic and sociological research repeatedly raises the question on technological mass-unemployment and societal inequality as a result of technological advances ( Brynjolfsson and McAfee, 2014 ; Ford, 2015 ; Frey and Osborne, 2017 ). And second, management literature questions the suitability of prevailing organizational structures in the face of the so-called “fourth industrial revolution” ( Schwab, 2017 ), taking visionary leaps into a fully automated future of digital value creation ( Roblek et al., 2016 ).

Many of the contributions of scholars discuss the enormous potential of new technologies for work and society at a hypothetical level, which led to a large number of position papers. Moreover, the question on what consequences recent developments, such as working with robots, automated systems or artificial intelligence will have for different professions remain largely unclear. By examining what workplace technologies actually “do” in the work environment, it was suggested that work tasks change because of technological developments ( Autor et al., 2003 ; Autor, 2015 ). This is due to technologies substituting different operations or entire tasks and thus leave room for other activities. Jobs are defined by the work tasks and the conditions under which the tasks have to be performed. This in turn defines the necessary competences, that is the potential capacity to carry out a job (e.g., Ellström, 1997 ). Therefore, CVET needs to be informed on the changes that technology causes in work tasks and the consequential characteristics of work. Only then CVET is able to derive the required competences of employees and organize learning environments that foster the acquirement of these competences. These insights can be used to determine the implications thereof for the components of formal learning environments: content, didactics, trainer behavior, assessment, and resources (e.g., Mulder et al., 2015 ).

The aim of this systematic literature review is to get insight into the effects of new technological developments on work characteristics in order to derive the necessary work demands and their implications for the design of formal learning environments in CVET.

Therefore, the following research questions will be answered:

RQ 1 : What are the effects of new technologies on work characteristics?

RQ 2 : What are the implications thereof for continuous vocational education and training?

Theoretical considerations on the relationships between technology and work characteristics are presented before the methods for searching, selecting and analyzing suitable studies are described. Regarding the results section, the structure is based on the three main steps of analyzing the included studies: First, the variables identified within the selected studies are clustered and defined in terms of work characteristics. Second, a comprehensive overview of evidence on the relationships between technologies and work characteristics is displayed. Third, the evidence is evaluated regarding the work demands that result from technologies changing work characteristics. Finally, the implications for CVET and future research as well as the limitations of this study will be discussed.

Theoretical Framework

In this section, a conceptualization of technology and theoretical assumptions on relationships between technology and work characteristics will be outlined. Research within various disciplines, such as sociology, management, economics, educational science, and psychology was considered to inform us on the role of technology within work. Completing this section, an overview of the various components of learning environments is provided to be used as a basis for the analyses of the empirical evidence.

Outlining Technology and Recent Technological Developments

A clear definition of technology often lacks in studies, what may be due to the fact that the word itself is an “equivoque” ( Weick, 1990 , p. 1) and a “repository of overlapping inconsistent meanings” ( McOmber, 1999 , p. 149). A suitable definition can be provided by analyzing what technologies actually “do” ( Autor et al., 2003 , p. 1,280). The primary goal of technology at work is to save or enhance labor in the form of work tasks, defined as “a unit of work activity that produces output” ( Autor, 2013 , p. 186). Technology can therefore be defined as mechanical or digital devices, tools or systems. These are used to replace work tasks or complement the execution of work tasks (e.g., McOmber, 1999 ; Autor et al., 2003 ). According to this view, technology is conceptualized according to “its status as a tool” (“instrumentality”; McOmber, 1999 , p. 141). Alternatively, technology is understood as “the product of a specific historical time and place,” reflecting a stage of development within a predefined historical process (“industrialization”; McOmber, 1999 , p. 143) or as the “newest or latest instrumental products of human imagination” (“novelty”; McOmber, 1999 , p. 143), reflecting its nature that is rapidly replacing and “outdating” its predecessors. The definition according to “instrumentality” is particularly suitable for this research, as the interest focuses on individual-level effects of technologies and its use for accomplishing work. Therefore, the technology needs to be mentioned explicitly (e.g., “robot” instead of “digital transformation”) and described specifically in the form with which the employee is confronted at the workplace. Different definitions may reflect different perspectives on the role of technology for society and work. These perspectives in the form of paradigmatic views ( Liker et al., 1999 ) include philosophical and cultural beliefs as well as ideas on organizational design and labor relations. They differ with regard to the complexity in which the social context is believed to determine the impact of technology on society. Listed in accordance to increasing social complexity, the impact may be determined by technology itself (i.e., “technological determinism”), established power relations (i.e., “political interest”), managerial decisions (i.e., “management of technology”), or the interaction between technology and its social context (i.e., “interpretivist”) ( Liker et al., 1999 ). Later research added an even more complex perspective, according to which the effects of technology on society and organizations are determined by the relations between the actors themselves (i.e., “sociomateriality”; Orlikowski and Scott, 2008 ). Paradigmatic views may guide research in terms of content, purpose and goals, which in turn is likely to affect the methods and approach to research and may be specific to disciplines. For instance, Marxist sociological research following the view of “political interest” or research in information systems following the view of “management of technology.”

New technological developments are widely discussed in various disciplines. For instance, Ghobakhloo (2018) summarizes the expected areas of application of various technological concepts within the “smart factory” in the manufacturing industry: The internet of things as an umbrella term for independent communication of physical objects, big data as procedure to analyse enormous amounts of data to predict the consequences of operative, administrative, and strategic actions, blockchain as the basis for independent, transparent, secure, and trustworthy transaction executed by humans or machines, and cloud computing as an internet-based flexible infrastructure to manage all these processes simultaneously ( Cascio and Montealegre, 2016 ; Ghobakhloo, 2018 ). The central question to guide the next section is to what extent these new technologies, and also well-established technologies such as information and communication technologies (ICT), which are constantly being expanded with new functions, could influence work characteristics on a theoretical basis.

Theories on the Relationships Between Technology and Work Characteristics

A central discussion on technology can be found in the sociological literature on deskilling vs. upgrading ( Heisig, 2009 ). The definition of “skill” in empirical studies on this subject varies regarding its content by describing either the level of complexity that an employee is faced with at work, or the level of autonomy that employees are able to make use of Spenner (1990) . Theories advocating the deskilling of work (e.g., labor process theory; Braverman, 1998 ) propose that technology is used to undermine workers' skill, sense of control, and freedom. Employees need to support a mechanized workflow under constant surveillance in order to maximize production efficiency ( Braverman, 1998 ). Other authors, advocating “upskilling” ( Blauner, 1967 ; Bell, 1976 ; Zuboff, 1988 ), propose the opposite by claiming that technology frees employee's from strenuous tasks, leaving them with more challenging and fulfilling tasks ( Francis, 1986 ). In addition, issues of identity at work were raised by Blauner (1967) who acknowledged that employees may feel “alienated” as soon as technologies change or substitute work that is meaningful to them, leaving them with a feeling of powerlessness, meaninglessness, or self-estrangement ( Shepard, 1977 ). In sum, sociological theories suggest that technology has an impact on the level of freedom, power and privacy of employees, determining their identity at work and the level of alienation they experience.

According to contingency theories ( Burns and Stalker, 1994 ; Liker et al., 1999 ) technology is a means to reduce uncertainty and increase competitiveness for organizations ( Parker et al., 2017 ). Therefore, the effects of technology on the employee depend on strategic decisions that fit the organizational environment best. When operational uncertainty is high, organizations get more competitive by using technology to enhance the flexibility of employees in order to enable a self-organized adaption to the changing environment ( Cherns, 1976 ). This increases employee's flexibility by allowing them to identify and decide on new ways to add value to the organization (“organic organization”; Burns and Stalker, 1994 ). When operational uncertainty is low, organizations formalize and standardize procedures in order to optimize the workflow and make outputs more calculable (“mechanistic organization”; Burns and Stalker, 1994 ). This leads to less opportunities for individual decision-making and less flexibility for the employees. In sum, contingency theories suggest, that the effects of technology depend on the uncertainty and competitiveness in the external environment and may increase or decrease employee's flexibility and opportunities for decision-making and self-organization.

Economic research following the task-based approach from Autor et al. (2003) suggests, that technology substitutes routine tasks and complements complex (or “non-routine”) ones. Routine manual and cognitive tasks usually follow a defined set of explicit rules, which makes them susceptible to automation. By analyzing qualification requirements in relation to employment rates and wage development, it was argued that workplace automation substitutes routine and low-skill tasks and thus favors individuals who can carry out high-skilled complex work due to their education and cognitive abilities ( Card and DiNardo, 2002 ; Autor et al., 2003 ). This means, that the accomplishment of tasks “demanding flexibility, creativity, generalized problem-solving, and complex communications” ( Autor et al., 2003 , p. 1,284) becomes more important. Complex tasks, so far, posed a challenge for automation, because they required procedural and often implicit knowledge ( Polanyi, 1966 ; Autor, 2015 ). However, recent technological developments such as machine learning, are capable of delivering heuristic responses to complex cognitive tasks by applying inductive thinking or big data analysis ( Autor, 2015 ). Regarding complex manual tasks, mobile robots are increasingly equipped with advanced sensors which enable them to navigate through dynamic environments and interactively collaborate with human employees ( Cascio and Montealegre, 2016 ). In sum, economic research following the task-based approach argues that technology affects the routineness and complexity of work by substituting routine tasks. However, new technologies may be able to increasingly substitute and complement not only routine tasks, but complex tasks as well. According to the theories, this will again increase the complexity of work by creating new demands for problem-solving and reviewing the technology's activity.

Useful insights can be gained from psychological theories that explicitly take the role of work characteristics into account. Work characteristics are often mentioned by for instance sociological theories (e.g., autonomy and meaningfulness) without clearly defining the concepts. Particularly the job characteristics model of Hackman and Oldham (1975) and the job-demand-control model of Karasek (1979) and Karasek et al. (1998) are consulted to further clarify the meaning of autonomy and meaningfulness at work. With regard to autonomy, Hackman and Oldham's model 1975 conceptualizes autonomy as a work characteristic, defined as “the degree to which the job provides substantial freedom, independence, and discretion to the employee in scheduling the work and in determining the procedures to be used in carrying it out” ( Hackman and Oldham, 1975 , p. 162). According to the authors, autonomy facilitates various work outcomes, such as motivation and performance. In a similar vein, Karasek et al. (1998) stress the role of autonomy in the form of “decision authority” that interacts with more demanding work characteristics, such as workload or frequent interruptions and therefore enables a prediction of job strain and stress ( Karasek et al., 1998 ). With regard to meaningfulness, Hackman and Oldham (1975) clarify that different core job dimensions, such as the significance of one's own work results for the work and lives of other people, the direct contribution to a common goal with visible outcomes, and the employment of various skills, talents and activities all enhance the perception of meaningfulness at work. In sum, psychological theories on employee motivation and stress clarify the concepts of autonomy and meaningfulness by illustrating the factors that contribute to their experience in relation to challenging and rewarding aspects of work.

Components of CVET

In order to formulate the implications for CVET of the studied effects of technology on work characteristics, a framework with the different components of CVET is needed. The objective of the VET system and continuous education is to qualify people by supporting the acquirement of required competences, for instance by providing training. Competences refer to the potential capacity of an individual in order to successfully carry out work tasks ( Ellström, 1997 ). They contain various components such as work-related knowledge and social skills (e.g., Sonntag, 1992 ). Competences are considered here as “the combination of knowledge, skills and attitude, in relation to one another and in relation to (future) jobs” ( Mulder and Baumann, 2005 , p. 106; e.g., Baartman and de Bruijn, 2011 ).

Participants in CVET enter the system with competences, such as prior knowledge, motivation, and expectations. It is argued that these have to be considered when designing learning environments for CVET. Next to making the distinction between the different components of learning environments content, guidance, method, and assessment, it is considered important that these components are coherent and consistent ( Mulder et al., 2015 ). For instance, the content of the training needs to fit to the objectives and the background of the participants. The same goes for the method or didactics used (e.g., co-operative learning, frontal instruction) and the guidance of teachers, mentors or trainers. In addition, assessment needs to be consistent with all these components. For instance, problem based learning or competence based training requires other forms of assessment than more classical teacher centered forms of didactics, which makes a classic multiple choice test not fitting ( Gulikers et al., 2004 ). Figure 1 contains an overview of the components of learning environments for CVET.

Figure 1 . Components of CVET learning environments (adapted from Mulder et al., 2015 , p. 501).

Three steps are necessary to answer the research questions. Firstly, a systematic search and review of empirical studies reporting evidence on the direct relationships between new technologies and work characteristics. Secondly, an analysis of the evidence with regard to its implications for work demands. Thirdly, deriving the work demands and their implications for CVET.

Systematic Search Strategy

Due to the interdisciplinary nature of our research, specific databases were selected for each of the disciplines involved: Business Source Premier (business and management research) and PsycArticles (psychology) were searched via EBSCOhost, and ERIC (educational science), and Sociological Abstracts (sociology) were searched via ProQuest.

Identifying suitable keywords for technological concepts is challenging due to the rapidly changing and inconsistent terminology and the nested nature of technological concepts ( Huang et al., 2015 ). Therefore, technological terms were systematically mapped by using the different thesauri provided by each of the chosen databases. After exploding a basic term within a thesaurus, the resulting narrower terms and related terms were documented and examined within the following procedure: (a) Checking the compatibility with our definition of technology reflecting its instrumentality, (b) Adjustment of keywords that are too broad or too narrow, (c) Disassembling nested concepts. The procedure was repeated stepwise for each of the databases. Finally, 45 terms that reflect new technologies were documented and used for the database search.

Keywords reflecting work characteristics are derived from the theoretical conceptualizations previously outlined. Synonyms for different concepts within the relevant theories were identified and included. In order to narrow our search results, additionally operators for empirical studies conducted in a workplace setting were added.

In order to avoid unnecessary redundancy, the use of asterisks was carefully considered, provided that the search results did not lose significantly in precision or the number of hits did not grow to an unmanageable number of studies. The final search string is shown in Table 1 .

Table 1 . Final search string.

Eligibility Criteria and Study Selection

Technical criteria included methodological adequacy. This was ensured by only including studies published in peer-reviewed journals. In addition, the studies had to provide quantitative or qualitative data on relationships between technology and work characteristics. Only English-language studies were considered, because most of the studies are published in English and therefore the most complete overview of the existing knowledge on this topic can be obtained. This also enables as many readers as possible to have access to the original studies and analyse the findings of the empirical studies themselves.

Concerning technology, variables had to express the direct consequence or interaction with a certain technology (e.g., the amount of computer-use or experience with robots in the workplace) and indirect psychological states that conceptually resulted from the presence of the technology (e.g., a feeling of increased expectations concerning availability). Regarding work characteristics, variables had to describe work-related aspects associated with our conceptualization of work characteristics (e.g., a change in flexibility or the perception of complexity).

Regarding the direction of effects, only studies that focused on the implementation or use of technologies for work-related purposes were included. Studies were excluded, if they (a) tested particular designs or features of technologies and evaluated them without considering effects on work characteristics, (b) regarded technology not as a specific tool but an abstract process (e.g., “digital transformation”), (c) were published before 1990 due to the fact that the extent of usability and usefulness of technologies before that time should be substantially limited compared to today (e.g., Gattiker et al., 1988 ), and (d) investigated the impact of technologies on society in general without a specific relation to professional contexts (e.g., McClure, 2018 ).

Studies that were found but that did not report empirical findings on the relationships between technology and work characteristics, but rather on the relationships between technology and work demands (e.g., specific knowledge or skills) or work outcomes (e.g., performance, job satisfaction) were documented. Since the aim for this study was to derive the work demands from the work characteristics in any case, the studies that reported a direct empirical relationship between technology and work demands were analyzed separately ( N = 7).

Data Extraction

The variables expressing technology and work characteristics were listed in a table, including the quantitative or qualitative data on the relationships. Pearson's r correlations were preferred over regression results to ensure comparability. For qualitative data, the relevant passages documenting data were included. Finally, methodological information as well as sample characteristics and size are listed.

Analysis of the Results

Firstly, the variables containing work-related aspects are clustered thematically into a comprehensive final set of work characteristics. This is necessary to reduce complexity due to variations in naming, operationalization and measurement and to make any patterns in the data more visible. Deviations from the theoretically expected clusters are noted and discussed before synthesizing the evidence narratively in accordance to the research questions ( Rodgers et al., 2009 ). As proposed, the evidence on changing work characteristics is analyzed with respect to the resulting work demands in the sense of knowledge, skills, attitude and behavior, which in turn are used to determine the implications for the different components of CVET.

Figure 2 depicts a flowchart documenting the literature search. In sum, 21 studies providing evidence on relationships between technology and work characteristics were included. In addition, seven supplementary studies containing empirical evidence on relationships between technology and specific work demands were identified. These studies are taken into account when deriving the work requirements. Next, the descriptive characteristics of the included studies will be reported. After that, the evidence on relationships between technologies and work characteristics of the 21 included studies will be summarized, before finally deriving the work demands based on the evidence found.

Figure 2 . Flowchart of literature search process.

Characteristics of Studies

Table 2 contains an overview of the characteristics of selected studies. Most of the studies were published between 2015 and 2019 (52%). Nearly half of the studies were conducted in Europe (48%), followed by North America (33%). Most of the studies reported qualitative data collected with methods such as interviews (62%).

Table 2 . Characteristics of the studies.

The studies investigated a variety of technologies, such as computers (1, 7), various forms of Information and Communication technologies (ICTs; 2, 3, 17, 18, 21) in a broad sense, including specific examples of work-extending technologies and other tools for digital communication, information technology (IT) systems supporting information dissemination and retrieval within organizations (4, 9), automated systems supporting predominantly physical work procedures (5, 6, 11, 12, 13, 14, 20), robots (15, 19), social media enabling professional networking and participation in organizational and societal practices (8, 16), and more domain-specific technologies such as clinical technology supporting professional decisions (9) and field technology for labor management (10).

Relationships Between Technology and Work Characteristics

In sum, nine work characteristics were identified and defined distinctively. Table 3 contains the operational definitions of the final work characteristics and the work-related aspects they consist of. The final work characteristics are: Workflow interruptions, workload, manual work, mental work, privacy, autonomy, complexity, role expectations, and opportunities for development.

Table 3 . Overview for final work characteristics and the exemplary work-related aspects assigned to them.

The complete overview of the selected studies and results for the relationships between technology and work characteristics is provided in Table 4 (for quantitative data) and Table 5 (for qualitative data). To further increase comprehensibility, the variables within the tables were labeled according to their function in the respective study (e.g., independent variable, mediating variable, dependent variable; see notes).

Table 4 . Studies providing quantitative evidence for the relationship between technology and work-related aspects.

Table 5 . Studies providing qualitative evidence for the relationship between technology and work-related aspects.

There is quantitative evidence on positive relationships between IT system use and complexity reported by two studies (4, 9). On a similar note, qualitative evidence suggests lower situational awareness within automated systems indicating an increase in complexity (12), and clinical technology being associated with an increase in complexity for nurses (9).

There is mixed quantitative evidence on the relationships between computer work and autonomy (1). The amount of computer work is positively related to autonomy, while technological pacing is negatively related to autonomy. Working within automated systems is negatively (5, 6) or not related (6) to different measures of autonomy. ICT use shows mixed relationships with job decision latitude (3) depending on ICT features that describe negative or positive effects of use. Evidence indicates a positive relationship between social media use and autonomy. Qualitative evidence suggests that ICT use increases autonomy (21) and flexibility (17, 18, 21).

Quantitative studies indicate strong positive relationships between computer work (1) and ICT use (2) and workload. The relationships are not consistent due to the fact that certain ICT features differ in their effects on workload. ICT characteristics such as presenteeism and pace of change are positively related to feelings of increasing workload, while a feeling of anonymity is negatively associated with workload. Evidence indicates positive relationships between time or workload pressure in the context of computer work (7), working in an automated system (5), as well as social media use (8) and provide evidence for positive relationships between various technologies and workload. Qualitative studies report similar outcomes. ICT use (18), automated systems (12, 13) as well as clinical technology (9) are reported to increase the workload.

Workflow Interruptions

Quantitative evidence indicates positive relationships between computer work and increasing levels of interruptions as well as an increasing demand for multitasking (7). Qualitative evidence suggests that ICT use is positively associated with an increased level of interruptions on the one hand and workflow support on the other hand (21). Further qualitative evidence suggests that robots at the workplace have positive effects on workflow support (19), and automated systems seem to increase the level of multitasking required in general (12).

Manual Work

Qualitative evidence suggests a decrease in the amount of physically demanding tasks when working with automated systems (11) and robots (15). In one study, qualitative evidence suggests an increase in manual work for technical jobs where automated systems are used (14).

Mental Work

Quantitative evidence indicates no relationships between monitoring tasks or problem-solving demands for technical jobs within automated systems (6). Qualitative evidence however suggests positive relationships between work within automated systems and various cognitive tasks and demands, such as problem-solving and monitoring (11, 13), while working with robots increases the amount of new and challenging mental tasks (15).

Quantitative evidence indicates that different ICT characteristics show different relationships with invasion of privacy (2). Some features are negatively related to invasion of privacy (anonymity) and others are positively related to it (presenteeism, pace of change). Qualitative evidence suggests that IT systems are not related to the perception of managerial surveillance (9), while social media is positively related to peer-monitoring (16), and field technology is negatively related to employee data control (10).

Role Expectations

Quantitative evidence indicates that ICT use is inconsistently related to role ambiguity depending on specific characteristics of the technology (2). Regarding automated systems, quantitative evidence indicates no relationship between working in an automated system and opportunities for role expansion in the form of an increased perceived responsibility (6). Qualitative evidence suggests that ICT use increases the expectations for availability and connectivity (21), and social media positively affects networking pressure (16). Qualitative evidence suggests that IT systems (9) decrease meaningful job content and role expansion. Qualitative evidence suggests that automated systems vary with regard to enhancing meaningfulness at work, dependent on whether the work tasks are complemented by the system or revolve around maintaining the system (20).

Opportunities for Development

Qualitative evidence suggests that ICT use (12) as well as working with an automated system (17) increase the demands for continuing qualification. Qualitative evidence suggests that opportunities for learning and development are prevalent with clinical technology (9) and absent when working with robots (19). Mixed qualitative evidence regarding automated systems and learning opportunities suggests that the effects depend on the differences in work roles in relation to being supported by the system or supporting the system (20).

A comprehensive summary of the outcomes can be found in Table 6 . The information in this table gives a summary of the evidence found for the different technologies and their relationships to work characteristics, more specifically to work related aspects. Important distinctive characteristics such as sample characteristics are listed in Tables 4 , 5 .

Table 6 . Overview over identified relationships between technology and work characteristics.

Subsequently, the results shown are now used as a basis for the identification of work demands that lead to the need for adapting to changes in work characteristics.

Relationships Between Technologies and Work Demands

Three sources are considered for the identification of work demands: Work demands mentioned in the studies on technology and work characteristics, work demands mentioned by the supplementary studies found during the database search ( N = 7), and work demands analytically derived from the results.

Some studies that examined the effects of technology on work characteristics also reported concrete work demands. Regarding the increasing complexity and the associated mental work, qualitative evidence suggests an increasing demand for cognitive as well as digital skills (11) in automated systems. With regard to IT systems, quantitative evidence indicates positive relationships with computer literacy (9), and analytical skills (4). With regard to the increase in workflow interruptions and the role expectations for constant availability and connectivity, time and attention management strategies are proposed in order to cope with the intrusive features of technology (2). Other strategies mentioned in the studies include self-discipline for disengaging from the ubiquitous availability resulting from mobile communication devices (18, 8) as well as the need for reflecting on individual responsiveness when working overtime due to self-imposed pressure to be available at all times (18, 21). Concerning opportunities for development, the willingness and ability to learn and adapt to technological changes and the associated changes in work (15, 4, 12) is emphasized. Moreover, employability is facilitated by using technological tools for professional networking (16).

The supplementary studies provide evidence on the direct relationships between technologies and work demands without the mediating consideration of work characteristics. This evidence is listed in Table 7 .

Table 7 . Supplementary studies on the relationship between technology and work-related demands.

There is quantitative evidence for positive relationships between the perception of controllability and exploratory use of computers (22), first-hand experience with robots and readiness for robotization (23, 24), and perceived usefulness and positive attitudes toward telemedicine technology (25), blockchain technology (26), and IT systems in general (27). Further quantitative evidence indicates mixed effects of perceived ease of use. Evidence indicates a positive relationship between perceived ease of use and perceived technological control with regard to telemedicine (25), no relationship between ease of use and attitude regarding blockchain technology (26), and a positive relationship between ease of use and attitude toward using IT systems (27). Quantitative evidence indicates that information processing enabled by technology is positively related to an increasing demand of cognitive skills (e.g., synthesizing and interpreting data) and interpersonal skills (e.g., coordinating and monitoring other people), but not related to an increasing demand in psychomotor skills (e.g., manual producing and precise assembling) (28). The level of standardization of work is positively related to interpersonal skills, but not related to cognitive and psychomotor skills (28). A high variety of tasks is positively related to the demand for cognitive skills and interpersonal skills and not related to psychomotor skills (28).

By analyzing the evidence on relationships between technology and work characteristics, further work demands can be derived. Knowledge about the specific technology at hand may be useful to decrease the perception of complexity as new technologies are introduced. This seems evident when comparing the effects of a simple computer with the effects of work within an automated system. For instance, while evidence indicates no relationship between computer work and complexity (6), work within an automated system is suggested to be associated with increasing complexity (12). Moreover, problem-solving skills (13) and cognitive skills such as diagnosing and monitoring (11, 15) increase when employees work within automated systems. Increasing autonomy suggests the need for personal skills regarding self-organizing and self-management due to greater flexibility and the associated possibilities for structuring work in many ways, particularly when working with ICTs (18, 21). Workflow interruptions and an increasing workload also increases the importance of communication skills for explicating the boundaries of one's own engagement to colleagues and leaders (17, 18, 21). Furthermore, reflecting the professional role at work may be critical due to changes in role expectations. The example of self-imposed need for availability underlines this argument (21). All this has implications for self-regulatory activities, such as reflection, and could benefit from experimenting and monitoring one's own strategies for time and attention management.

Implications for CVET: Objectives and Characteristics

The aforementioned studies describe several required behavioral aspects that are considered important due to technology at work. Emphasized is the need for components related to the organization of one's own work, namely self-discipline and time and attention management.

The identified need for reflection on one's own professional actions, for experimentation, and also for professional networking (for instance by using tools) can be seen as parts of further professional development by oneself or in interaction with others. In addition, the need for demonstrating employability is mentioned. From all these professional and career development aspects can be derived that problem-solving skills, self-regulation skills, and communication skills are required as well as proactive work behavior and coping and reflection strategies.

Various relevant skills, such as psychomotor skills, analytical skills, management skills, and interpersonal skills are mentioned. In addition, the need for diagnostic and monitoring skills as well as digital skills is emphasized. All these components can be used in relation to two explicitly mentioned needs: ability to learn and computer literacy. The demand for generic and transferable skills is emphasized. As a basis for the skills, knowledge is required, for instance on the technology itself, although not explicitly discussed in the studies. In contrast, several components of attitude are explicitly mentioned and considered to be a requirement for the ability to deal with challenges caused by new technologies at work. Firstly, the more generic willingness to learn, adaptability, and perceived behavioral control. Secondly, attitudes that are directly linked to technology, namely a positive attitude and trust, especially toward technology (e.g., robots), and technological readiness and acceptance.

Next to the opportunity of acquiring the mentioned components of competences at work, CVET can organize training interventions in the form of adequate learning environments to foster these. The ability of employees to carry out, develop and use the mentioned behavioral aspects, skills, knowledge, and attitudes, can be considered as required objectives of CVET and have concrete consequences for the characteristics of the learning environments.

As for the content of the learning environments, derived from the aforementioned requirements, it can be argued that attention should be paid to different categories of learning objectives: acquiring knowledge about and learning how to use technology, how to manage work and oneself, and how to continue one's own professional development. In addition, the relevance of attitude tells us that these components need to be fostered in the training and therefore need to be part of the content of the learning environments as well.

In relation to the methods or the didactics, only one study explicitly mentioned a suggestion, namely experience based learning for fostering adaptability (12). In relation to the guidance of trainers or teachers no suggestions are provided. The same goes for assessment, diagnoses or monitoring, and the coherence of components of the learning environments.

This systematic literature review aimed at identifying effects of new technological developments on work characteristics, identifying associated work demands, and determining their implications for the design of formal CVET learning environments.

Effects of New Technologies on Work Characteristics and Word Demands

Based on a systematic review focusing on empirical evidence, several effects of technology on work characteristics were found, thus answering RQ 1. Evidence suggests that complexity and mental work increases with ongoing automation and robotization of work, for instance due to the automatization of procedures which “hides” certain processes from employees. The automatization of tasks introduces new mental tasks, such as monitoring the machine's activities and solving problems. A decrease in manual work depends on the relation between the job and the technology in use (supporting vs. being supported).

Workload and workflow interruptions increase as a general consequence of the ubiquity of technology, mainly due to a higher level of job speed and the associated time and workload pressure. A higher level of autonomy seems to be associated with a higher workload and more workflow interruptions. This applies in particular to work with ICTs and domain-specific technologies, such as field technology.

Role expectations and opportunities for development depend on the relation between the job and the technology in use (supporting vs. being supported). With regard to role expectations, the need for being available or connected via digital devices and a new division of responsibilities between employees and technology are repeatedly mentioned in the studies. This applies particularly to work with automated systems, robots, and domain-specific technologies such as clinical technology.

With regard to work demands, employees need strategies to deal with higher levels of workload, autonomy, and complexity. Required skill demands contain mental, analytical, cognitive, and self-regulatory demands. In addition, opportunities for role expansion and learning, which do not seem to automatically result from the implementation and use of new technologies, need to be created (pro)actively by the employees. Employees need to take more responsibility with regard to their own development and professional work identity (for instance considering the pressure for constant availability). They need to be able to effectively deal with a high workload and number of interruptions, increasing flexibility, complexity, and autonomy, a demand for constant availability, changes in meaningfulness of tasks, changes in work roles, and the need to create and use learning opportunities. In the light of ongoing changes and challenges, skills to further develop and adapt one's own skills gain in importance. Regarding attitudes, the willingness to learn, adapt and experiment may be a central work demand.

Implications for the Practice of CVET

Various required objectives of CVET can be concluded from the reported results. For instance, developing the ability of employees to carry out the mentioned behaviors, as well as the skills, knowledge and attitudes that are necessary for those behaviors. These objectives have consequences for the content of CVET learning environments. From the empirical studies on the relationships between technology and work, we derived the need for employees to organize their own work, for instance through time management. Furthermore, many issues relating to own professional development and career development are important, to acquire individually and independently as well as by interacting with others. Ultimately, this refers to the skills of self-initiated learning and development. With regard to fostering helpful attitudes, raising awareness of the relevance of trust or training the social skills to promote trust in the workplace can be included in the content of CVET learning environments. In research on creating trust within organizations, regularly giving and receiving relevant information was shown to be important for creating trust toward co-workers, supervisors and top-management, which in turn fostered the perception of organizational openness and employee involvement as a result ( Thomas et al., 2009 ). In the research on creating trust in virtual teams, the importance of frequent interaction was important to develop trust on a cognitive as well as an affective level (e.g., Germain, 2011 ). These research results however need to be adapted to the context of technology at work.

Although there is no information provided on the guidance of employees, informal guidance through leadership ( Bass and Avolio, 1994 ) as well as formal guidance by trainers and teachers during interventions contain possibilities for fostering the required competences. Attention should be paid not only to acquiring relevant knowledge (digital literacy), but also to skills in applying the knowledge and therefore dealing with technology. Even more challenging might be the task of supporting attitude development (e.g., technological acceptance and openness to changes), fostering transfer of skills, and preparation for future development. Especially future professional development, which includes the ability to learn in relation to current and future changes, needs to be focused on. Teachers, trainers and mentors need to be equipped to be able to foster these competences.

In relation to the use of didactical methods, methods that do not merely focus on knowledge acquisition but also provide opportunities for skill acquisition and changes in attitude need to be applied. For example, one study explicitly suggested experience based learning for fostering the adaptability of employees when faced with ongoing technological developments. Other solutions for instruction models as a profound basis for learning environments may be found in more flexible approaches, for instance according to the cognitive flexibility theory ( Spiro et al., 2003 ), where learners are meant to find their own learning paths in ill-structured domains. By applying such models, that are often based on constructivist learning theories, in a coherent way, the development of strategies for self-organizing and self-regulation may be facilitated.

Furthermore, the use of technology within learning environments may have the potential to increase participants interactions, which are focused in for instance collaborative and co-operative learning ( Dillenbourg et al., 2009 ). Next to increasing interactions in learning and being able to co-operate, technology in learning environments can used to foster the other required competences, if adequately designed ( Vosniadou et al., 1996 ; Littlejohn and Margaryan, 2014 ).

When keeping in mind, that the coherence of components is an important requirement for the design of learning environments ( Mulder et al., 2015 ), the component that describes assessment needs further attention. There is evidence supporting the idea, that the type of assessment has an impact on how learning takes place ( Gulikers et al., 2004 ; Dolmans et al., 2005 ). Therefore, it can be used to deliberatively support and direct learning processes.

Only when all these aspects are considered can CVET interventions effectively and sustainably foster the mentioned objectives, such as promoting a willingness to change in relation to technologies, the effective use of technology, and personal development in the context of technological developments.

Limitations and Implications for Future Research

Regarding the search methods, the use of databases is challenging when investigating technologies ( Huang et al., 2015 ). Technological and technical terms are widespread outside the research in which they are regarded as the object of investigation. Therefore, it produces a large amount of studies that concern technology with diverse research objectives that can be difficult to sort. An interesting focus for future research would be the systematic mapping of journals dealing specifically with technology in order to identify research that could complement the results of the present study as well as consider specificities regarding the domains in which the data is collected and disciplines by which the research is conducted. For instance, domain-specific databases from healthcare or manufacturing might provide additional insights into the effects of technology on work. Another limitation is the absence of innovative new technologies, such as artificial intelligence, blockchain, or the internet of things as object of investigation. Broad technological categories, such as ICTs and social media have received some attention in research, especially in relation to questions beyond the scope of this review. Newer technological developments as discussed by Ghobakhloo (2018) are virtually not present in current research. This gap in empirical research needs to be filled. In addition, future research should ensure that it does not miss opportunities for research where effects of these innovative technologies can be examined in detail, for instance by conducting an accompanying case study of the implementation process. Research investigating changes over time regarding the use of technology and its effects is needed. In doing so, research could capture the actual dynamics of change and development of processes as they happen in order to inform truly effective interventions in practice. Moreover, a classification of technological characteristics according to their effects may be valuable by enabling a more in-depth analysis of new technologies and their effects on specific groups of employees and different types of organizations. These analyses will also allow a breakdown of effects in relation to differences in jobs, hierarchy levels and levels of qualification, which could be very important for organizations and employers in order to adapt the CVET strategy to the specific demands of specific groups of employees. The present review takes a first step in this direction by identifying work characteristics that are affected by different technologies. In addition, future research could also take into account non-English language research, which might increase insight in for instance cultural differences in the use and the effects of technology at work.

Regarding theory, some of the relevant theories considering technology stem from sociology (e.g., Braverman, 1998 ) or economics ( Autor et al., 2003 ). For instance, the task-based approach ( Autor et al., 2003 ) showed some explanatory value by suggesting that complexity may increase as a consequence of technology. Furthermore, it suggested that this effect may depend on job specifics. Those propositions are reflected in the aforementioned empirical evidence. Psychological theories on work characteristics do not conceptualize technology explicitly (e.g., Hackman and Oldham, 1975 ; Karasek, 1979 ). As of the present study, the large variation regarding the concepts and variables derived from theory might limit the comparability of results. To foster systematic research, further theory development needs to more explicitly consider the role of technology at multiple levels (i.e., individual level, team level, organizational level) and with regard to the characteristics and demands of work. In the context of theory, the paradigmatic views also deserve attention (e.g., Liker et al., 1999 ; Orlikowski and Scott, 2008 ). These views could be reflected in the subject of research, as exemplified for instance in the study of field technologies and its effects on privacy from a managerial control and power perspective, potentially reflecting the view of political interest ( Tranvik and Bråten, 2017 ). Most of the studies, however, do not take a clear stand on what exactly they mean when they investigate technology. This complicates interdisciplinary inquiry and integration, as it is not always clear which understanding of technology is prevalent. We therefore encourage future research to explicitly define technology, for instance as in the present paper using the proposed framework of McOmber (1999) . In doing so, characteristics of technology may be defined more clearly and distinctive which in turn would enable the formation of the strongly needed categorization of technologies, as was proposed earlier.

And, although there are theories and models on the use of technology in education (e.g., E-Learning, Technology enhanced learning), they are not focussing on fostering the competences required to deal with new technologies in a sustainable manner. In general, the same gap needs to be filled for instruction models and instructional design models, for instance to promote changes in attitude and professional development. In addition, there is hardly any attention for the consequences of new technologies at work for CVET yet ( Harteis, 2017 ). All this requires more systematic evaluation studies. The research gaps identified need to be filled in order to provide evidence-based support to employees in dealing with new technologies at work in a sustainable manner, taking charge of their own performance and health, as well as seeking and using opportunities for their own professional and career development.

Data Availability Statement

All datasets generated for this study are included in the article/supplementary material.

Author Contributions

PB and RM have jointly developed the article, and to a greater or lesser extent both have participated in all parts of the study (design, development of the theoretical framework, search, analyses, and writing). The authors approved this version and take full responsibility for the originality of the research.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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* Studies included in the systematic review.

** Supplementary studies.

Keywords: technology, work characteristics, continuous vocational education and training, automation, work demands, systematic review

Citation: Beer P and Mulder RH (2020) The Effects of Technological Developments on Work and Their Implications for Continuous Vocational Education and Training: A Systematic Review. Front. Psychol. 11:918. doi: 10.3389/fpsyg.2020.00918

Received: 14 February 2020; Accepted: 14 April 2020; Published: 08 May 2020.

Reviewed by:

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*Correspondence: Patrick Beer, patrick.beer@ur.de

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Impact of Information Technology on Job-Related Factors

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During the last two decades of the twenty-first century, information technology played a vital role on various companies and their work environments, employees, individuals and society. With the advancement and growth of telecommunications, customized business software as well as digital computing, there have been changes in the workplace scenario and effects on individual job characteristics. This paper tries to identify the effect of information technology on various job factors like job satisfaction, work–life Balance, health and safety, performance and productivity. Data was collected with the help of a survey questionnaire based on Likert scale from 100 IT employees. Exploratory factor analysis and regression analysis are used to identify the effect of information technology on job factors like job satisfaction, work–life balance, health and safety, performance and productivity.

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Virendra N. Chavda & Nehal A. Shah

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Vincenzo Piuri

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Hetalkumar N. Shah

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Rajan Patel

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Chavda, V.N., Shah, N.A. (2021). Impact of Information Technology on Job-Related Factors. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_15

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Research Article

Research on the relationship between CEO career variety, digital knowledge base extension, and digital transformation in the context of digital merger and acquisition: The case of China’s new generation of information technology firms

Contributed equally to this work with: Hongyang Li, Xu Yang

Roles Conceptualization, Writing – original draft

* E-mail: [email protected]

Affiliation School of Economics and Management, Harbin Engineering University, Harbin, China

Roles Data curation, Methodology, Validation

Roles Methodology, Writing – review & editing

Affiliation School of Economics and Management, Beijing Forestry University, Beijing, China

• Hongyang Li, 
• Xu Yang, 
• Mingming Meng

• Published: March 13, 2024
• https://doi.org/10.1371/journal.pone.0297044
• Peer Review
• Reader Comments

This study examines the relationship between CEO career variety, digital knowledge base extension, and digital transformation in a digital M&A context. An empirical test was conducted using regression analysis with the digital M&A events of the new generation of information technology firms in China as the research sample. The results reveal that CEO career variety has a positive effect on digital transformation in the digital M&A context and that digital knowledge-base extension plays a mediating role. Moreover, the heterogeneity impact analysis indicated that the moderating effects of geographical distance, knowledge disparity, and cultural difference between target and acquirer firms on the above relationships vary greatly: geographical distance has a negative moderating effect, cultural difference has a positive moderating effect, and the moderating effects of both geographical distance and cultural difference are realized through mediating effects, but none of the moderating effects of knowledge disparity are significant.

Citation: Li H, Yang X, Meng M (2024) Research on the relationship between CEO career variety, digital knowledge base extension, and digital transformation in the context of digital merger and acquisition: The case of China’s new generation of information technology firms. PLoS ONE 19(3): e0297044. https://doi.org/10.1371/journal.pone.0297044

Editor: José Antonio Clemente Almendros, Universidad Internacional de La Rioja, SPAIN

Received: August 1, 2023; Accepted: December 27, 2023; Published: March 13, 2024

Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by the National Natural Science Foundation of China [grant number 72274044]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

In recent years, artificial intelligence (AI), blockchain, cloud computing, big data, and other underlying digital technologies have driven the emergence and development of the digital economy, profoundly affecting the industrial structure system and economic growth patterns. Under the role of digital technology empowerment, digital transformation (DT) has become the key to industrial survival and development in the digital economy era. Digital technology is a combination of information, computing, communication, and connectivity technologies [ 1 ], and its core technologies (e.g., cloud computing and big data analysis) belong to the category of new generation of information technology (NGIT). Therefore, the NGIT industry has an inherent technical advantage in implementing DT. Since China listed NGIT as a strategic and emerging industry in the “12th Five-Year Plan,” China’s NGIT industry has been developing rapidly. The Central Cyberspace Affairs Commission issued the “14th Five-Year Plan for National Informatization,” which pointed out that the NGIT industry shoulders the essential tasks of promoting 1) the optimization and upgrading of traditional industries, 2) the convergence of informatization and industrialization, and 3) the development of intelligent manufacturing. Thus, whether the NGIT industry can take the lead in advancing DT becomes critical.

DT is the process of updating digital resources to improve business, enhance efficiency, transform organizational structures, and reshape innovation models [ 2 , 3 ]. Although the current development of China’s digital economy is robust and new business formats and patterns related to NGIT firms are constantly emerging, many NGIT firms still face difficulties in the actual DT process. From a theoretical point of view, the research and development (R&D) process of internal digital knowledge is often marked by path dependence. Moreover, it is not only time-consuming but also risky to rely on internal innovation when one’s digital knowledge base is immature. From a realistic perspective, NGIT firms generally encounter many problems such as unclear digital technology implementation paths, poor digital strategies, and shortages of highly educated digital talent. For this reason, numerous NGIT firms have started to turn their attention to outside firms by acquiring digital companies that fit their DT strategy to quickly and directly obtain digital assets to enhance transformation capabilities and control transformation costs. This type of strategic acquisition targeting digital economy firms is called “digital mergers and acquisitions” (M&A) [ 1 ]. However, while digital M&A has become an important strategic choice for an increasing number of NGIT firms [ 4 ], compared to the burgeoning digital M&A practice, digital M&A theoretical research is relatively lagging and weak. While there are numerous studies on DT in non-M&A settings [ 2 , 3 ], research into DT in the context of digital M&A has received little attention, and the specific paths and mechanisms promoting DT in digital M&A contexts remain unclear.

As an influential decision-maker and executive, the chief executive officer (CEO) is an important influencing factor in a firm’s DT [ 5 ]. As modern DT is marked by a complex and unstable internal and external environment, a high level of CEO digital awareness and digital leadership coupled with a keen insight into digital trends and industry development are required; these differences in CEO capabilities are important factors in the widening DT gap [ 6 ]. In this situation, compound talent meets firms’ requirements for overall CEO quality and tends to positively impact corporate innovation investment, corporate M&A, and other behaviors [ 7 ]. Wealthy career experience is an important way to shape compound talent [ 8 ]. For example, Ren Zhengfei, the founder of China’s Huawei, previously served in military and constructional engineering units and Shenzhen Nanhai Petroleum Industry Co., Ltd., which enabled him to develop Huawei into a world-renowned NGIT firm.

In the digital M&A context, this study considers DT a type of strategic decision-making and examines the influence of CEO career variety on DT. Considering the importance of digital knowledge-based extension (DKBE) in the digital M&A process to achieve DT [ 9 ], DKBE is employed as a mediating variable in the relationship between CEO career variety and DT. This study screens NGIT firms from Chinese A-share listed firms and collects their digital M&A events as the research sample. It empirically examines the mediating relationship between CEO career variety, DKBE, and DT using a regression analysis method and the moderating effects of geographical distance, knowledge disparity, and cultural differences on the above relationships are also explored in a heterogeneity analysis.

The analysis of the results reveals several theoretical implications. First, it adds value to the literature on CEO career variety and DT in the emerging digital M&A research context. The study of digital M&A and DT is still in its infancy; while previous literature has addressed the impact of executives and DT [ 10 , 11 ], few scholars have focused on the relationship between CEO career experience and DT. In response to firms’ actual demand for composite talent in the digital economy, this study clarifies the positive impact of CEO career variety on DT in the digital M&A context. This study provides an empirical basis for firms to utilize the dual advantages of CEO capabilities and resources to promote DT. Second, the study reveals that there is a bridging role between CEO career variety and DT, providing new insights for digital knowledge-based research. Notably, it is worth noting that this mechanism holds only in the digital M&A context. Although previous technology M&A studies focused on knowledge bases [ 12 , 13 ], detailed research on how DKBE is lacking. This study clarifies the mechanisms of CEO career variety, DKBE, and DT in the digital M&A context, opens a "black box" for DT, and complements firms’ DKBE problems. Finally, this study explores in-depth the factors that influence the relationship between CEO career variety and DT from the perspective of M&A parties’ heterogeneity. By exploring the moderating effects of geographic distance, knowledge disparity, and cultural differences, this study deepens the understanding of the different boundary effects of geographic, knowledge, and cultural factors between M&A parties in the digital M&A context, enriches theoretical research in the digital M&A field, and inspires NGIT firms to pay more attention to the target selection issue.

The remainder of the paper is structured as follows: Section 2 reviews the existing literature and derives the hypotheses. Section 3 explains the research design. Section 4 provides the empirical results, robustness tests, and heterogeneity analysis results. Section 5 presents the discussion. Finally, Section 6 presents the conclusions and policy suggestion.

2 Literature review and hypotheses

2.1 literature review.

The concept of digital M&A s is based on early research on technological M&A in the digital economy. Since Ahuja and Katila [ 14 ] introduced the concept of technology M&A in 2001, technology M&A research has developed rapidly, research on digital M&A is still in its infancy. Although some scholars have focused on general M&A research in the context of the digital economy [ 15 – 17 ], their focus differs somewhat from digital M&A. The term digital M&A was first introduced in a research note published by Bain and Company. Subsequently, the idea of “firm DT can be achieved through digital M&A” began to attract scholars’ attention [ 18 , 19 ]. However, to date, studies have focused only on the theoretical level of digital M&A. A search of the Web of Science database reveals only a handful of empirical studies on digital M&A. One such study is Hanelt et al. [ 1 ], who through systematic elaboration, theoretical conceptualization, and empirical testing of digital M&A, argued that digital M&A helps promote digital innovation and boosts firm performance. Additionally, Zhou et al. [ 9 ], using data of Chinese listed firms as a sample, verified the positive relationship between digital M&A and innovation performance. Yu and Yan [ 20 ] argued that digital finance development promotes the implementation of digital M&A by firms. Finally, Tang et al. [ 21 ] focused on the positive impact of digital M&A on the market value of Chinese listed firms. However, there is still a lack of research on how to achieve the goal of firm DT through digital M&A.

In the field of influencing factors of firm DT, early scholars focused on technical aspects such as digital resources and digital-related abilities [ 3 , 5 ]. However, as the internal obstacles to DT within firms continue to increase, the organizational element is gradually gaining attention. Scholars have investigated the role of typical organizational factors such as organizational structure, organizational culture, and organizational governance can influence firm DT [ 3 , 22 ], and in this process, the role of managers has gradually emerged. Previous studies have delved into two aspects: manager characteristics and manager abilities, and found that both psychological characteristics, cognitive structures, overseas backgrounds [ 10 , 11 , 23 ], and digital literacy, digital self-efficacy, and management abilities [ 24 – 26 ] have significant impacts on DT. Additionally, the impact of the Chief Digital Officer, a specialized senior management position, on DT has also received attention [ 27 , 28 ].

As the main decision-makers in the daily management of firms, CEOs have been the focus of attention in business and strategic management research. Traditional agency theory focuses on how to guide managers to make "pareto optimality" decisions to promote sustainable development, but the implied premise of managerial homogeneity does not easily match the real situation and is gaining increasingly more attention from scholars. Based on the upper echelons theory, CEOs, as the core of management, have career experiences that influence their cognitive and behavioral patterns, which, in turn, influences firms’ behavior. Previous research on CEO career variety has focused on the economic impacts of single specific career experiences such as military, R&D, and financial experience on firms [ 29 – 31 ]. However, different career types interact with each other to shape the management style of the CEO. Some studies have found that CEOs employ a combination of skills learned throughout their careers when making corporate decisions, and that CEOs with a wide range of career experiences are usually more strained, boundary-spanning, innovative, and adventurous [ 8 , 32 ]. However, current research has centered solely on the impact of CEO career variety on outcomes such as CEO compensation, investment decisions, and board tenure [ 8 , 33 , 34 ], and there is a lack of in-depth exploration into the consequences resulting from CEO career variety.

2.2 Hypotheses proposed

Ceo career variety and firm dt..

The upper echelons theory, first proposed by Hambrick and Mason [ 35 ], argues that management’s values and cognitive abilities and different executive characteristics significantly impact decision-making and execution in a firm. This study refers to Crossland et al.’s [ 7 ] concept of CEO career variety; That is, the array of distinct professional and institutional experiences that an executive has gained prior to becoming CEO. Considering that DT in the digital M&A context serves as an important growth strategy for firms, CEOs play a major role in decision-making and leadership. This implies that a firm’s DT in the digital M&A context is also influenced by the CEO’s career variety [ 11 ]. Thus, according to the upper echelons theory, this study conducts a theoretical analysis from the perspective of imprinting and resource effects.

From the imprinting effect perspective, CEOs’ work experiences in different organizations or environments influence their management thinking and decision preferences through cognitive and competence imprinting [ 36 ]. CEOs with diverse career experiences are more cognitively aware of DT and more capable of making relatively better DT decisions, thus enhancing the degree of firm DT. Achieving DT through digital M&A is both an opportunity and a challenge for firms. Firms are not only under pressure to integrate digital M&A, but also face serious problems such as unclear transformation goals and uncertainty about the direction in the process of DT. It has been shown that CEOs with varied careers have broader knowledge, stronger overall skills, and the capacity to identify major opportunities and challenges in a firm [ 33 ]. Therefore, when faced with DT opportunities, CEOs with greater career variety have more advanced cognitive skills and awareness than those with less career variety and are more likely to recognize the importance of DT to their organizations. They can seize major opportunities for digitalization and organizational restructuring, that enhance the value of their firms.

From the resource effect perspective, resource-based theory suggests that CEOs, by virtue of their social connections, can become valuable social resources by employing a greater range of information sources, improving information quality, and alleviating information asymmetry [ 33 , 37 ]. The embeddedness theory of new economic sociology also states that the economic behavior of CEOs in society is embedded in their social network ties, thus forming social capital prototypes [ 38 ]. As an important strategic decision, DT in the context of digital M&A has resource-dependent attributes, and firms need strong social capital to support their DT efforts, which are both high risk and high reward. Managers in different firms and industries inevitably expand the boundaries of interpersonal interactions and enrich their social relationships [ 39 ]. Abundant career experience can enable managers to accumulate many quality resources, including capital, talent, and knowledge. CEOs with career variety can leverage their rich career experience to bring in external social resources, especially financial ones, to better support their firms’ DT. Combining these two perspectives led us to propose the following hypotheses:

• H1: CEO career variety positively impacts DT in the context of digital M&A.

CEO career variety and DKBE.

A digital knowledge base is defined as the sum of all explicit and tacit aspects of a firm’s digital knowledge, including digitally relevant information, knowledge, and capabilities that inventors utilize to find innovative solutions [ 40 , 41 ]. The fundamental purpose of digital M&A is to acquire the digital knowledge of the target firm, gradually merging the digital knowledge bases of both firms and showing a trend of knowledge transfer from the target firm to the acquirer firm [ 1 ]. However, due to the inherent “stickiness” of knowledge, it is difficult to realize knowledge transfer through M&A [ 13 ]. Knowledge transfer is a complicated process involving bilateral interactions between the sender and receiver of knowledge. Accordingly, the motivation, capability, and opportunity of both target and acquirer firms directly influence effective knowledge transfer [ 42 ]. The CEO plays a major decision-making and driving role in the knowledge transfer process, and CEO career variety has a significant impact on DKBE.

Based on the imprinting effect perspective, CEOs with different career experiences interact with each other to form their own unique imprint, which significantly affects corporate decision-making and execution. CEOs with professional variety can effectively reduce semantic bias in the digital M&A integration process, facilitate idea sharing and understanding, more easily maintain a good relationship with the target firm, and promote mutual cooperation between the target and acquirer firm [ 36 , 43 ], and digital knowledge transfer. Considering the information asymmetry in the digital M&A process, CEOs with diverse careers can efficiently obtain more non-redundant information by virtue of their rich career experience, thus alleviating information asymmetry in corporate decision-making and facilitating digital knowledge transfer. Therefore, CEOs with career variety are better able to eliminate internal differences and gain the full trust and support of both firms, thus accelerating DKBE.

From the resource effect perspective, CEOs with career variety and who have worked in several different functions, businesses, geographies, and organizations can acquire more social resources and social network relationships for the firm [ 39 ]. As auxiliary resources, these social resources can effectively facilitate digital knowledge transfer and strengthen the construction of their own digital knowledge bases. Simultaneously, as an informal institutional arrangement, the resource allocation effect of social networks can help firms obtain scarce resources [ 44 ], thus facilitating DKBE. In addition, diverse career experiences endow CEOs with diverse and complex management knowledge bases and a pioneering sense of external perception, leading to a greater information advantage in decision-making, which significantly improves the quality of digital M&A decisions and facilitates DKBE. The following research hypothesis is proposed by combining the analyses of these two perspectives:

• H2: CEO career variety has a positive effect on DKBE in the context of digital M&A.

Mediating effects of DKBE.

From the above analysis, it is clear that based on the upper echelons and imprinting theories, the imprinting effect formed by the rich professional experience of CEOs not only helps firms promote digital knowledge transfer and expand their digital knowledge base but also enables them to better grasp the opportunities for DT and promote the degree of firm DT. In contrast, based on the resource-based and embeddedness theories, the resource effect of CEO’s rich past professional experience helps improve the quality of decision-making, accelerates the construction of a digital knowledge base, and helps alleviate the shortage of resources faced by firms in DT. Thus, it appears that CEO career variety in the digital M&A context can contribute to both DKBE and DT.

The construction of a digital knowledge base in the digital M&A process is crucial for achieving DT goals. A digital knowledge base not only enables firms to apply and combine this knowledge directly but also increases the acceptance of new external knowledge. Building a digital knowledge base enables firms to absorb and utilize external digital knowledge [ 1 ], which facilitates the DT process [ 45 ]. In addition, Zhou et al. [ 9 ] point out that in a digital M&A scenario, acquiring the digital knowledge of the target firm can effectively facilitate firm DT. Therefore, CEO career variety in digital M&A scenarios can facilitate DKBE and thus increase the degree of DT. This demonstrates that DKBE serves as a link between CEO career variety and DT. Based on the above analysis, the following hypotheses are proposed:

• H3: DKBE mediates the relationship between CEO career variety and DT in digital M&A.

3 Research design

3.1 research sample.

First, based on the Guidance List of Key Products and Services in Strategic Emerging Industries (2016 edition) published by China’s National Development and Reform Commission, we first matched the key directions and refined sub-directions of the NGIT industry with the concept board of listed firms in the Wind database and then defined listed firms that fit the business scope as NGIT listed firms. Second, we collected the equity M&A events for such firms from 2013 to 2017. Samples with too small quantities, failed M&A, and missing data were excluded. Finally, referring to the criteria for defining digital M&A proposed by Hanelt et al. [ 1 ], M&A events whose M&A targets are digital economy-type firms were screened out and defined as digital M&A events in this study. The “Statistical Classification of the Digital Economy and its Core Industries” (2021), issued by the National Bureau of Statistics (NBS), was used as the standard for judging digital economy-type firms. Specifically, the industry codes, business scope, and business description of the target firms were collected through Wind, Beijing Tianyancha Technology Co., Ltd. and Qichacha Tec Co., Ltd., and the industry code information of the target firms was matched with the national economic industry code of the statistical classification. The business scope and description information were matched with the industry description of the statistical classification. If the information about the target firm matched the statistical classification, the target firm was deemed a digital economy-type firm, and the sample was considered a digital M&A event. A total of 415 digital M&A were identified using the screening steps described above.

3.2 Measurement

Independent variable..

The DT variable reflects the firm’s degree of transformation through digital technology. Related studies typically use text mining and statistical word frequencies to measure this variable [ 46 ]. Referring to Chen [ 47 ] and based on the China Securities Market and Accounting Research (CSMAR) database on digital-related measures of listed firms, we illustrated the degree of firm DT in five dimensions (AI technology, blockchain, cloud computing, big data, and digital technology applications) and mined the frequency of the corresponding text words in the annual reports of listed firms. The word frequencies of these five dimensions were summed and logarithmically processed after adding one to depict the level of firm DT. At the same time, considering that there is a certain lag period from the role of CEO career variety to DT in the digital M&A context, the DT data were treated with a lag of four years.

Dependent variable.

Referring to Custódio et al. [ 8 ] and Crossland et al. [ 7 ], CEO career variety was measured by constructing a CEO career experience richness index. The following five aspects were considered in the index construction process: career type, number of firms, academic experience, financial institutions, and geographical type.

Career type is a variable measured by the aggregate number of different functions experienced by a CEO throughout his/her career. Considering the data sources, and based on the studies of Crossland et al. [ 7 ] and Schmid and Mitterreiter [ 34 ], we divided the occupation types into a total of nine types: production, R&D, design, human resources, management, marketing, financial market profession, financial management profession, and legal. Each occupation type was not counted twice; those who worked in the same occupation type in multiple firms were counted only once, and the data were obtained from the CSMAR database.

The number of firms was measured by the aggregate number of different firms in which a CEO has worked throughout his/her career. CEOs who have worked in multiple firms have a better understanding of how different firms operate and thus exhibit stronger management abilities. The number of firms was calibrated according to Crossland et al.’s [ 7 ] method. Multiple firms experienced by a CEO were considered the same if they belonged to a subsidiary of a business group or had a parent and subsidiary corporation relationship. The data for this variable were obtained by manually querying the Wind database for CEO biographies.

Academic experience was measured using the aggregate number of academic institutions the CEO has experienced throughout his/her career. CEOs with multiple academic backgrounds have relatively rich academic resources and higher social statuses. The statistical categories included teaching at universities, serving at research institutions, and conducting research at associations. The data were obtained from the CSMAR database.

Financial institutions was measured as the aggregate value of the number of different financial institutions that the CEO has experienced throughout his/her career. Referring to the CSMAR database’s financial institution classification criteria, the statistical scope includes supervision departments, policy banks, commercial banks, insurance companies, security companies, fund management companies, securities registration and settlement companies, futures companies, investment banks, trust companies, investment management companies, and stock exchange. The data were obtained from the CSMAR database.

Geographical type was measured the different types of geographical experience a CEO has had throughout his/her career. A CEO with overseas experience was assigned a value of one if he/she has worked or studied abroad, and zero otherwise. A CEO with overseas experience is likely to have a higher level of vision and more advanced ideas in firm decision-making owing to exposure to different cultures. Data were obtained from the CSMAR database.

After calculation, the KMO value of the samples is 0.716, and the chi-square value of Bartlett’s sphericity is 270.465, which is significant at the level of 1%, indicating that the samples are suitable for factor analysis. The common factor extraction degrees are all above 0.5, and the extraction degree of the original variables is relatively high. The common factors are extracted according to the standard that the characteristic root is greater than 1, and after rotation by the maximum variance method, the cumulative variance contribution rate is 62.044%, which can better represent most information of the original variables. Finally, the comprehensive score of CEO’s career experience richness index is calculated based on Formula ( 1 ).

Mediating variables.

DKBE refers to the degree of expansion of the digital knowledge base of acquirer firms after a digital M&A. Knowledge bases are typically measured using patent quantities [ 48 ]. Considering that invention patents have the characteristics of originality, exclusivity, and exclusivity and that the invention patent examination procedure is more stringent and requires more innovative products and technologies, this we used the number of digital invention patent applications to measure the size of the digital knowledge base. There is a lag period for DKBE relative to digital M&A. Referring to Stiebale’s [ 49 ] three-year lag period setting, we used the total number of digital invention patent applications in the three years after the digital M&A to represent the degree of expansion of the digital knowledge base of acquirer firms after a digital M&A [ 1 ].

The screening practices for digital invention patents were as follows. First, all patent IPC classification numbers of acquirer firms were searched and collected through the State Intellectual Property Office. Second, “the Reference Relationship Table Between International Patent Classification and Industrial Classification for National Economic Activities” (2018), which was issued by China National Intellectual Property Administration (CNIPA), was matched with the “Statistical Classification of Digital Economy and its Core Industries” (2021) promulgated by the National Bureau of Statistics to screen out the categories of the National Economic Industry Classification that are in line with the digital economy industry. Finally, all patent IPC classification numbers of each acquirer firm were compared with the National Economic Industry Classification, and invention patents that fit into the digital economy industry category were defined as digital invention patents.

Control variables.

The control variables were selected from the perspective of M&A parties’ firm differences and acquirer firm heterogeneity as follows:

Geographical distance . Referring to Sears [ 50 ], the geographic distance indicator was measured as the geographic straight-line distance between the locations of the target and acquirer firms.

Knowledge disparity . The knowledge disparity between target and acquirer firms is reflected in the difference in knowledge-based stocks. Considering that invention patents are more innovative than utility model and design patents, the ratio of the total number of invention patents granted between the target firm and the acquirer firm in the five years prior to the M&A was used as a measurement indicator. The larger the ratio, the larger the disparity between the target firm’s technological capability and that of the acquirer. Moreover, the closer the ratio is to one, the closer the technological capabilities of both parties.

Cultural differences . Many sociological studies have concluded that language has both social and cognitive functions and is an important carrier of regional culture [ 51 ]. Dialects contain different patterns of thinking and behavior, and organizations or individuals in a particular dialect environment are implicitly influenced by regional cultures. Therefore, this study used dialect differences between the regions where the target and acquirer firms are located to measure cultural differences [ 52 ]. Referring to the “Language Atlas of China” (2012), we counted the dialectal regions of the locations of M&A parties. If the locations of either party did not belong to the same dialectal region, it was recorded as three. If both locations belonged to the same dialectal region but not the same dialectal area, it was recorded as two. If the location of both parties belonged to the same dialectal area but not the same subdialect, it was recorded as one. If both locations belonged to the same subdialect, it was recorded as zero. This provides us with the degree of dialectal difference between M&A parties, where the larger the value, the larger the difference.

Firm size . Considering that an M&A event itself is affected by the size of the acquirer, creating an acquirer-size effect, it is necessary to identify possible biases in the results due to firm size. Firm size was measured as the natural logarithm of the acquirer’s total assets in the year before the merger.

Leverage . This study used the ratio of the total liabilities divided by the total assets of the acquirer firm in the year prior to the M&A to measure leverage.

Growth . Growth was measured using the growth rate of the acquirer’s operating income in the year prior to the M&A.

M&A experience . Referring to Zhou et al. [ 9 ], the combined number of times the acquirer firm went to acquire the target firm in the five years prior to the M&A was counted and used to measure the firm’s M&A experience.

Table 1 presents the names and measurements of each variable.

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https://doi.org/10.1371/journal.pone.0297044.t001

4.1 Descriptive statistics and correlation analysis

The descriptive statistics for each variable are shown in Table 2 . As shown in Table 2 , DT has a mean value of 2.837 and a standard deviation (SD) of 1.567, indicating that the degree of DT varies widely among firms. The CEO career variety indicator was obtained using the factor analysis method, which downscales the original five-dimensional indicators to a mean value of zero and a SD of 0.578. In addition, considering the possible problem of multicollinearity among variables, this study conducted a correlation analysis and variance inflation factor (VIF) test for each variable. Table 3 shows that the correlation coefficients of the core variables are all less than 0.3, and the VIFs fall below the standard of 10, indicating the absence of multicollinearity issues. Furthermore, we observed that there is generally no linear correlation between the core variables, which suggests the possibility of non-linear relationships within the data as well as heteroscedasticity issues that merit further investigation in subsequent analyses.

https://doi.org/10.1371/journal.pone.0297044.t002

https://doi.org/10.1371/journal.pone.0297044.t003

4.2 Baseline regression results

Based on the correlation analysis presented above, it is found that there is no significant linear relationship between the core variables, and unbalanced panel data is prone to heteroscedasticity. Therefore, we proceeded to the following steps to make a judgment. Firstly, all data were standardized to ensure consistency in the data magnitudes of all variables. Secondly, a White test is conducted to determine the presence of a heteroskedasticity problem in the data based on the significance of coefficients. The White test results show evidence of heteroscedasticity in the data. Finally, we further established that the data had the problem of inter-group heteroscedasticity using the Wald test, which is also a common issue in unbalanced panels. After a comprehensive analysis of the above studies, we selected the feasible generalized least squares (FGLS) model as the most suitable approach for addressing unbalanced panel data while accounting for heteroskedasticity issues. Table 4 presents the regression results, which show that the Wald chi squared values are all significant at the 1% level, indicating that the overall effect and stability of each model is good.

https://doi.org/10.1371/journal.pone.0297044.t004

Model 1 shows that CEO career variety has a significant positive effect on DT (β = 0.082, p<0.01), indicating that CEO career variety can promote firm DT degree in digital M&A context, thereby verifying H1. The results of Model 2 show that CEO career variety has a significant positive effect on DKBE (β = 0.040, p<0.01), which indicates that CEO career variety can also help firms rapidly expand their digital knowledge base in the digital M&A context, providing support for H2. The results of Model 3 show that DKBE has a significant positive effect on DT (β = 0.231, p<0.01), while the positive effect of CEO career variety on DT still holds, indicating that there is a partial mediating effect of DKBE between CEO career variety and DT, and H3 holds.

4.3 Robustness tests

This study conducted robustness tests from two aspects, namely variable substitution test and endogeneity test.

Variable substitution test.

In this study, the tests were conducted via the following variable substitutions: (1) changing the dimensionality reduction method of CEO career variety from the factor analysis method to the entropy method, (2) changing the DKBE measure from the original number of numerical invention patent applications to the number of numerical patent applications, and (3) using technicist as a control variable, measured by the total number of technicians of the acquirer in the year before the M&A. Regression analysis was performed based on the original model, the results of which are presented in Table 5 . None of the core variables of the model changed substantially and the results remained robust.

https://doi.org/10.1371/journal.pone.0297044.t005

Endogeneity test.

The characteristics of firms that choose digital M&A s may not be the same as those that do not; that is, whether a firm chooses M&A is not a random event [ 55 ]. To avoid bias in the estimation results, the Heckman two-stage method is used to test for endogeneity. First, we select a sample of new generation information technology listed companies from 2013 to 2017 and conduct a panel probit with whether the company conducted digital M&A in the current year as the explanatory variables, and a total of eight indicators, including firm size, total asset turnover, total asset return, return on net assets, gearing ratio, growth, number of technicians, and amount of R&D investment in the year before M&A as explanatory variables. The regression, and the Inverse Mills Ratio are calculated. Second, we put the Inverse Mills Ratio into the mediation test model as a control variable. As shown in Table 6 , the Inverse Mills Ratio values in the model are significant, indicating that there is a certain selection bias issue in the model. However, after controlling for Inverse Mills Ratio, the core variables in all models do not undergo substantial changes, indicating that the selection bias issue has a relatively small impact on the results and the study findings remain robust.

https://doi.org/10.1371/journal.pone.0297044.t006

4.4 Heterogeneous impact analysis

Considering that the digital M&A context involves two subjects—the acquirer firm and the target firm—the mediating effect process from CEO career variety, DKBE, and DT are not only influenced by the acquirer firm but also by the target firm; Thus, the boundary effect generated by the difference factors between the target and acquirer firms needs to be considered. Accordingly, in this study, geographical distance, knowledge disparity, and cultural differences between the M&A parties in the original control variables were used as moderating variables to conduct a heterogeneity impact analysis based on the original model. In addition to the original three models, the product terms of explanatory and moderating variables, namely, "CEO career variety x Geographical distance," "CEO career variety x Knowledge disparity,” and “CEO career variety x Cultural difference” were added. Table 7 shows the empirical results.

https://doi.org/10.1371/journal.pone.0297044.t007

The coefficient of "CEO career variety x Geographic distance" is negative in all three models and significant at the 1% level, indicating that geographic distance has a negative moderating effect on the relationship between CEO career variety and DT. This moderating effect is primarily achieved through the mediation of DKBE, particularly because in the M&A process, geographical distance hinders the efficiency of information communication between the target and acquirer firms, leads to communication complications, reduces the quality of information communication, and increases the negative impact of information asymmetry [ 56 ]. From the DKBE perspective, knowledge spillovers have obvious geographical limitations. The greater the intensity of tacit knowledge in the knowledge transfer process, the greater the need for face-to-face communication and contact [ 57 ]. Consequently, there is greater geographical distance, which makes digital knowledge transfer more difficult in digital M&A contexts. Therefore, for the geographical distance factor, a greater geographic distance between the M&A parties can hinder the CEO’s career variety role and is not conducive to expanding the digital knowledge base or enhancing the degree of DT in digital M&A.

The variable "CEO career variety x Knowledge disparity" is not significant in any of the three models, indicating that knowledge disparity does not moderate the relationship between CEO career variety and DT. The knowledge disparity factor, regardless of the size of knowledge disparity between the target and acquirer firms, does not affect the process of CEO career variety acting on DKBE and the degree of DT. Although scholars have suggested that too large a knowledge stock disparity between the target and acquirer firms may lead to the destruction of the organizational routine of the acquirer [ 14 ], digital knowledge differs from general knowledge in that the former is characterized by homogeneity and programmability and can be efficiently disseminated and reorganized across firm boundaries [ 2 ]. This lays the foundation for digital knowledge transfer by the target firm in the digital M&A process, resulting in the digital knowledge transfer in the digital M&A context being less affected by knowledge disparity.

The coefficient of "CEO career variety x Cultural difference" is positive in all three models and significant at the 1% or 5% level, indicating that cultural difference has a positive moderating effect on the relationship between CEO career variety and DT. This moderating effect is achieved mainly through the mediating variable DKBE because the degree of digital M&A integration is reduced compared to other M&A. To ensure the relative stability of the management team and the integrity of digital assets, the M&A parties do not integrate too much into target’s core digital R&D and operations, thus greatly reducing the cost burden of cultural differences. At the same time, multicultural integration enables firms with different cultural roots to seek richer cooperation and innovation in multiple dimensions, such as technology and products. In the case of large cultural differences, the acquirer broadens its digital knowledge boundaries and provides creative sources for subsequent digital activities [ 58 ]. Therefore, when large cultural differences exist between the target and acquirer firms, the CEO can take full advantage of professional variety to promote DKBE, thereby enhancing DT.

5 Discussion

Digital M&A has become a strategic choice for an increasing number of firms to cope with digital disruption and achieve DT and digital development [ 4 ]. Although Bughin et al. and Margiono have proposed the preliminary idea of "achieving enterprise DT through digital M&A," which has laid a foundation for subsequent research [ 18 , 19 ]. There is currently a lack of empirical research on the relationship between the two concepts, and the question of "how to do it" has not yet been resolved, i.e., how to achieve firm DT through digital M&A is still unclear. From the current study of firm DT, we can see that the main internal influences include technical and organizational aspects. According to the current research by Hanelt et al. and Zhou et al. on digital M&A, we find that the process of digital M&A itself includes the flow and transfer of digital resources and other technical aspects [ 1 , 9 ]. Therefore, we focus on the organizational level and pay attention to the relationship between CEO career variety and firm DT in the context of digital M&A, inspired by the research on managerial individual characteristics and DT [ 10 , 11 ]. Our study has found that CEO career variety has a positive impact on firm DT, which not only confirms the research by Zhu et al. and Hu et al. but also represents a breakthrough in studying the implementation path of firm DT in the context of digital M&A [ 1 , 9 ]. In addition, compared to existing research on CEO career variety, we first inherit the basic perspective of high-order theory that CEO career variety can affect their cognitive and behavioral patterns, thereby affecting firm behavior [ 7 , 8 ]. Subsequently, existing studies have mostly focused on the impact of CEO career variety on corporate governance [ 8 , 33 , 34 ], while we further verify its positive impact on DT based on this foundation, inspiring firms to pay more attention to CEO career experiences and individual characteristics.

In traditional M&A knowledge base research, scholars have mainly focused on the impact of M&A knowledge base integration on market value and innovation performance [ 12 , 59 ]. Based on the traditional knowledge-based viewpoint, Hanelt et al. further proposed the idea of "expanding digital knowledge bases through digital M&A" [ 1 ]. Inspired by Hanelt et al.’s view of digital knowledge bases, this study views DKBE as a unique phenomenon within the context of digital M&A. As tacit knowledge transfer between organizations is difficult, the focus of previous M&A knowledge base research has often been on reducing integration costs to facilitate knowledge transfer [ 12 , 59 ]. However, the dynamic and scalable nature of digital knowledge allows it to spread and restructure quickly and efficiently across firm boundaries [ 2 ]. The characteristics of digital knowledge make it possible to achieve DT through digital M&A. Therefore, this study connects DKBE as a CEO career variety and DT relationship, finding that DKBE plays a mediating effect therein. This finding not only inherits the traditional knowledge-based viewpoint, recognizing the importance of expanding the firm’s knowledge base through M&A [ 13 ], but also focuses on the important impact of DKBE on DT in the context of digital M&A. It forms a functional relationship that ranges from CEO career variety, DKBE to DT. This study provides a refined path plan for achieving DT in the context of digital M&A, and provides a new perspective on firm DT.

Through a subsequent heterogeneity analysis, we found significant differences in the moderating effects of three moderating variables—geographic distance, knowledge disparity, and cultural difference—in the original model. A closer geographic distance between the M&A parties facilitates communication, information transfer, and knowledge spillover [ 56 ]. Although some scholars argue that the emergence of information technology has weakened geospatial ties between firms, this study verifies that the role of CEO career variety in the digital M&A context is still limited by geographic distance and that geographic distance still has some negative effects on digital knowledge transfer and digital knowledge spillover. The knowledge disparity between M&A parties represents the contrast between the two parties’ knowledge stocks. While some have argued that excessive knowledge disparity between target and acquirer firms can lead to the disruption of their organizational routines [ 14 ], the results of this study show that the moderating effect of knowledge disparity is not significant, which reaffirms the above view that “the severity of knowledge matching and compatibility problems between the two parties is greatly diminished in the digital M&A field.” The research results on the impact of cultural differences on M&A outcomes are not uniform, with some scholars stating that greater cultural differences between M&A parties can increase acquisition costs and inhibit acquisitions. A large cultural difference can make it more difficult to search for a target and lead to higher cultural integration costs [ 55 ]. However, others have found that multicultural integration helps firms absorb and integrate diverse cultures, develop diverse products to meet different consumer needs, and thus contribute to their performance after an M&A [ 60 ]. The empirical results show that cultural differences have a positive moderating effect, indicating that the presence of cultural differences between the two parties in the digital M&A process helps CEOs play the advantages of professional diversity and promotes DKBE and DT.

6 Conclusion and policy suggestion

6.1 conclusion.

Using the emerging field of digital M&A as a research context and Chinese NGIT firms as research objects, this study investigates and explores the relationship between CEO career variety, DKBE, and DT. Our results confirm that CEO career variety can promote DKBE and thus enhance the degree of DT, indicating that firms need to pay attention to CEOs’ career diversity background when selecting them to improve the quality of CEO digital decisions. In the analysis of heterogeneity influence, geographic distance, knowledge disparity, and cultural differences between target and acquirer firms are introduced as boundary factors, revealing that a longer geographic distance and larger cultural differences have a suppressive and facilitating effect on the above relationship, respectively. However, the boundary effect of knowledge disparity was not significant. This study demonstrates the need to consider the heterogeneous effects of geographical distance and cultural differences between M&A parties in the process of promoting DT through CEO career variety and inspires firms to focus on the selection of target firms in the digital M&A decision-making process.

6.2 Policy suggestion

This study offers the following insights for NGIT and other emerging firms motivated by digital M&A and DT. First, it is important for CEOs to pay close attention to career variety. Firms need to emphasize the core position of the CEO in the process of digital M&A, implement sound training and selection mechanisms, and comprehensively consider all aspects of CEOs’ abilities. In turn, CEOs need to focus on the role of rich management practices to improve management ability, not adhere to a certain position or field of work inertia, learn different areas of thinking and management styles, and improve their own knowledge structure and management skills.

Second, regarding the digital knowledge-based expansion process, firms need to attach importance to digital knowledge integration in the process of digital M&A and continuously improve their digital capabilities to ensure effective acquisition, absorption, and utilization of the target party’s digital knowledge. Simultaneously, it is necessary to formulate reasonable knowledge integration strategies by combining the specific digital knowledge situations of both M&A parties, including specific choices such as rapid integration, delayed integration, and step-by-step integration.

Finally, appropriate target firm selection is important. Geographical distance and cultural differences can influence the final DT effect, and acquirer firms should take advantage of multiculturalism to promote digital knowledge transfer and applications. Acquirer firms must also consider and evaluate the impact of geographic distance on M&A integration when searching for and screening potential firms as M&A targets. When geographic distance is unavoidable, its negative impact is mitigated by the subsequent enhancement of management communication and information transfer.

Supporting information

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The Top 10 Most Interesting Technology Research Topics

With technological innovation streamlining processes in businesses at all levels and customers opting for digital interaction, adopting modern technologies have become critical for success in all industries. Technology continues to positively impact organizations , according to Statista, which is why technology research topics have become common among college-level students.

In this article, we have hand-picked the best examples of technology research topics and technology research questions to help you choose a direction to focus your research efforts. These technology research paper topics will inspire you to consider new ways to analyze technology and its evolving role in today’s world.

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What makes a strong technology research topic.

A strong research topic is clear, relevant, and original. It should intrigue readers to learn more about the role of technology through your research paper. A successful research topic meets the requirements of the assignment and isn’t too broad or narrow.

Technology research topics must identify a broad area of research on technologies, so an extremely technical topic can be overwhelming to write. Your technology research paper topic should be suitable for the academic level of your audience.

Tips for Choosing a Technology Research Topic

• Make sure it’s clear. Select a research topic with a clear main idea that you can explain in simple language. It should be able to capture the attention of the audience and keep them engaged in your research paper.
• Make sure it’s relevant. The technology research paper topic should be relevant to the understanding and academic level of the readers. It should enhance their knowledge of a specific technological topic, instead of simply providing vague, directionless ideas about different types of technologies.
• Employ approachable language. Even though you might be choosing a topic from complex technology research topics, the language should be simple. It can be field-specific, but the technical terms used must be basic and easy to understand for the readers.
• Discuss innovations. New technologies get introduced frequently, which adds to the variety of technology research paper topics. Your research topic shouldn’t be limited to old or common technologies. Along with the famous technologies, it should include evolving technologies and introduce them to the audience.
• Be creative . With the rapid growth of technological development, some technology research topics have become increasingly common. It can be challenging to be creative with a topic that has been exhausted through numerous research papers. Your research topic should provide unique information to the audience, which can attract them to your work.

What’s the Difference Between a Research Topic and a Research Question?

A research topic is a subject or a problem being studied by a researcher. It is the foundation of any research paper that sets the tone of the research. It should be broad with a wide range of information available for conducting research.

On the other hand, a research question is closely related to the research topic and is addressed in the study. The answer is formed through data analysis and interpretation. It is more field-specific and directs the research paper toward a specific aspect of a broad subject.

How to Create Strong Technology Research Questions

Technology research questions should be concise, specific, and original while showing a connection to the technology research paper topic. It should be researchable and answerable through analysis of a problem or issue. Make sure it is easy to understand and write within the given word limit and timeframe of the research paper.

Technology is an emerging field with several areas of study, so a strong research question is based on a specific part of a large technical field. For example, many technologies are used in branches of healthcare such as genetics and DNA. Therefore, a research paper about genetics technology should feature a research question that is exclusive to genetics technology only.

Top 10 Technology Research Paper Topics

1. the future of computer-assisted education.

The world shifted to digital learning in the last few years. Students were using the Internet to take online classes, online exams, and courses. Some people prefer distance learning courses over face-to-face classes now, as they only require modern technologies like laptops, mobile phones, and the Internet to study, complete assignments, and even attend lectures.

The demand for digital learning has increased, and it will be an essential part of the education system in the coming years. As a result of the increasing demand, the global digital learning market is expecting a growth of about 110 percent by 2026 .

2. Children’s Use of Social Media

Nowadays, parents allow their children to use the Internet from a very young age. A recent poll by C.S. Mott Children’s Hospital reported that 32 percent of parents allow their children aged seven to nine to use social media sites. This can expose them to cyber bullying and age-inappropriate content, as well as increase their dependence on technology.

Kids need to engage in physical activities and explore the world around them. Using social media sites in childhood can be negative for their personalities and brain health. Analyzing the advantages and disadvantages of the use of technology among young children can create an interesting research paper.

3. The Risks of Digital Voting

Digital voting is an easy way of casting and counting votes. It can save the cost and time associated with traveling to the polling station and getting a postal vote. However, it has a different set of security challenges. A research paper can list the major election security risks caused by digital voting.

Voting in an online format can expose your personal information and decisions to a hacker. As no computer device or software is completely unhackable, the voting system can be taken down, or the hacking may even go undetected.

4. Technology’s Impact on Society in 20 Years

Technological development has accelerated in the last decade. Current technology trends in innovation are focusing on artificial intelligence development, machine learning, and the development and implementation of robots.

Climate change has affected both human life and animal life. Climate technology can be used to deal with global warming in the coming years, and digital learning can make education available for everyone. This technology research paper can discuss the positive and negative effects of technology in 20 years.

5. The Reliability of Self-Driving Cars

Self-driving cars are one of the most exciting trends in technology today. It is a major technology of the future and one of the controversial technology topics. It is considered safer than human driving, but there are some risks involved. For example, edge cases are still common to experience while driving.

Edge cases are occasional and unpredictable situations that may lead to accidents and injuries. It includes difficult weather conditions, objects or animals on the road, and blocked roads. Self-driving cars may struggle to respond to edge cases appropriately, requiring the driver to employ common sense to handle the situation.

6. The Impact of Technology on Infertility

Assisted reproductive technology (ART) helps infertile couples get pregnant. It employs infertility techniques such as In-Vitro Fertilization (IVF) and Gamete Intrafallopian Transfer (GIFT).

Infertility technologies are included in the controversial technology topics because embryonic stem cell research requires extracted human embryos. So, the research can be considered unethical. It is an excellent research topic from the reproductive technology field.

7. Evolution of War Technology

Military technologies have improved throughout history. Modern technologies, such as airplanes, missiles, nuclear reactors, and drones, are essential for war management. Countries experience major innovation in technologies during wars to fulfill their military-specific needs.

Military technologies have controversial ideas and debates linked to them, as some people believe that it plays a role in wars. A research paper on war technology can help evaluate the role of technology in warfare.

8. Using Technology to Create Eco-Friendly Food Packaging

Food technologies and agricultural technologies are trying to manage climate change through eco-friendly food packaging. The materials used are biodegradable, sustainable, and have inbuilt technology that kills microbes harmful to human life.

Research on eco-friendly food packaging can discuss the ineffectiveness of current packaging strategies. The new food technologies used for packaging can be costly, but they are better for preserving foods and the environment.

9. Disease Diagnostics and Therapeutics Through DNA Cloning

Genetic engineering deals with genes and uses them as diagnostics and therapeutics. DNA cloning creates copies of genes or parts of DNA to study different characteristics. The findings are used for diagnosing different types of cancers and even hematological diseases.

Genetic engineering is also used for therapeutic cloning, which clones an embryo for studying diseases and treatments. DNA technology, gene editing, gene therapy, and similar topics are hot topics in technology research papers.

10. Artificial Intelligence in Mental Health Care

Mental health is a widely discussed topic around the world, making it perfect for technology research topics. The mental health care industry has more recently been using artificial intelligence tools and mental health technology like chatbots and virtual assistants to connect with patients.

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Artificial intelligence has the potential to improve the diagnosis and treatment of mental illness. It can help a health care provider with monitoring patient progress and assigning the right therapist based on provided data and information.

Other Examples of Technology Research Topics & Questions

Technology research topics.

• The connection between productivity and the use of digital tools
• The importance of medical technologies in the next years
• The consequences of addiction to technology
• The negative impact of social media
• The rise and future of blockchain technology

Technology Research Questions

• Is using technology in college classrooms a good or bad idea?
• What are the advantages of cloud technologies for pharmaceutical companies?
• Can new technologies help in treating morbid obesity?
• How to identify true and false information on social media
• Why is machine learning the future?

Choosing the Right Technology Research Topic

Since technology is a diverse field, it can be challenging to choose an interesting technology research topic. It is crucial to select a good research topic for a successful research paper. Any research is centered around the research topic, so it’s important to pick one carefully.

From cell phones to self-driving cars, technological development has completely transformed the world. It offers a wide range of topics to research, resulting in numerous options to choose from. We have compiled technology research topics from a variety of fields. You should select a topic that interests you, as you will be spending weeks researching and writing about it.

Technology Research Topics FAQ

Technology is important in education because it allows people to access educational opportunities globally through mobile technologies and the Internet. Students can enroll in online college degrees , courses, and attend online coding bootcamps . Technology has also made writing research papers easier with the tremendous amount of material available online.

Yes, technology can take over jobs as robotics and automation continue to evolve. However, the management of these technologies will still require human employees with technical backgrounds, such as artificial intelligence specialists, data scientists , and cloud engineers.

Solar panels and wind turbines are two forms of technology that help with climate change, as they convert energy efficiently without emitting greenhouse gases. Electric bikes run on lithium batteries and only take a few hours to charge, which makes them environmentally friendly. Carbon dioxide captures are a way of removing CO 2 from the atmosphere and storing it deep underground.

Technology helps companies manage client and employee data, store and protect important information, and develop strategies to stay ahead of competitors. Marketing technologies, such as Search Engine Optimization (SEO), are great for attracting customers online.

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Technology and careers.

Technology has had a powerful effect on the nature of work and what jobs are currently in demand. In fact, jobs that were never even imagined 20 years ago are being created today. In the past, there were stable, clearly classifiable jobs (blue collar, white collar), while today there are many rapidly changing types of jobs (multitiered, technical, professional, executive jobs). Career preparation, choices, and objectives are different now than they were years ago. For example, today many individuals are targeting smaller firms, skill-contracting agencies, or starting their own businesses rather than working for larger firms. In addition, career objectives have changed from simply climbing prescribed organizational ladders to more personal development in areas of expertise. Individuals are less likely to work their entire careers at the same firm and instead are employed at various firms and by contracting agencies.

Almost all aspects of an employee’s career are influenced by technology. From the time they are hired and selected (via Web site applications), trained (using online learning), mentored (via e-mentoring), evaluated (by computerized performance appraisals), as well as the type of work they do and where they do it (e.g., telework, virtual teams), they are exposed to some form of technology. Thus technology has also impacted how individuals apply for jobs, strategies used by employers to find employees and train them, and services provided by career counselors. Technology has also impacted vocational psychology and career guidance services. Counselors can provide future workers with a skills approach to their careers, thus enabling individuals to be transformed from powerless victims into knowledgeable, creative, self-initiated workers who can anticipate career shifts and plan for new career directions.

How Technology Has Changed The Nature Of Work And Skills Required Of Workers

Changing skills.

Technology is considered to be one of the most widely recognized forces affecting work and how it is changing. The technology of microelectronics, robotics, and computer-integrated manufacturing along with the explosion of digital telecommunications due to the growth of the Internet and the World Wide Web have brought the world to the verge of a transformation similar to an industrial revolution. It is expected that the Big Four information technologies—computer networks, imaging technology, massive data storage, and artificial intelligence—will continue to have revolutionary effects on shaping today’s occupations.

Computerization and the emerging information highway are transforming the American economy. Computers are changing the composition and distribution of labor, improving labor efficiency, and creating new markets and new forms of organizations. Technology shapes what people do and how they do it. Technological change often creates new occupations (e.g., computer scientists, programmers) and reduces or eliminates some existing occupations (e.g., telephone operators). In addition, digitization has changed the types of skills needed on jobs. It has increased the analytic and information-processing skills required on some jobs and decreased the manual and sensory-based skills of others.

Today, brainpower is replacing manual labor, and future workers must continually educate themselves and increase their skills to maintain their value in the workplace. Technology has reduced the number of workers required to maintain and operate high-tech factories and workplaces, has given rise to the need for “knowledge workers,” and has elevated the general education required for work. Few emerging occupations exist for people who cannot read, write, and do basic mathematics. Thus people who have weak educational backgrounds are likely to be increasingly vulnerable to unemployment. In fact, the growth of computer use is associated with increased employment of college graduates and decreased employment of high school graduates. In some industries, advanced technology has eliminated the need for some unskilled and semiskilled jobs and even some middle management jobs that tended to be the positions that collected and analyzed data for decision making. For future jobs, greater emphasis will be placed on cognitive, communications, and interactive skills.

With 76 million baby boomers heading toward retirement over the next three decades and only 46 million Generation Xers waiting in the wings, corporate America is facing a potentially large talent crunch. Labor-saving technology and immigration may help fill the gap, but by 2010 there may be a shortage of 4 to 6 million workers. Not enough Americans are trained for these jobs, since they lack computer literacy, leadership, critical thinking skills, and communication skills.

Technology has also made workplaces more information dependent in order to operate machines (e.g., robots, aircraft) for quality control and for decision making about inventory management and tracking distribution of products shipped. Employees at all levels of the organization have greater access to information and greater opportunities to make work decisions. For some jobs, computers have given employees more autonomy in their work. For others, the need for continuous data entry to computers and monitoring them to meet customers’ needs has imposed a new form of assembly line. In some cases, employees have greater concerns about invasion of privacy as managers use more sophisticated surveillance techniques to monitor productivity.

With the increasing technological advances, workers are able to do their jobs almost anywhere. Laptops, fax machines, cellular phones, networks, e-mail, and voice mail have made it possible for workers to essentially work 24 hours, seven days a week. Work can now be done without regard to space, time, or political boundaries. Americans, as a group, now work harder and longer than almost any other people on earth. Some studies have indicated that people have less free time and feel more pressed for time as compared to those in the past. Information technology (IT) is now used in 64 percent of women’s jobs, and by 2000, women using IT in their jobs worked 3.4 hours per week longer than nonusers. The economy, globalization, and 24-hour demand for goods and services have busted capacity in the 40-hour work week. Now, no longer are just police officers, nurses, taxi drivers, delivery personnel, factory employees, and security guards working at night. Today, all types of employees (e.g., stock brokers, building contractors, account reps, software fixers) are working at night. In fact, according to the Bureau of Labor Statistics, in 2000 it was estimated that 23 million people worked night, evening, or split shifts, up from 3.5 million working the night shift in 1997.

Changing Workplaces and Telework

Today, more workers are telecommuting. In fact, the innovations of telework and virtual teams are experiencing an annual growth rate of 5 percent to 10 percent. Telecommuting is the use of computers and telecommunications equipment to work at home or in other locations away from a conventional, centralized office. Careers and jobs are increasingly being seen as boundaryless, flexible, and virtual.

Telework has the benefits of allowing people to work from home (saving commuting time and costs as well as office space costs) and is purported to help employees better balance their home and work lives. However, some workers feel isolated and are worried that less visibility might negatively impact their career progression. In addition, work and home roles often become blurred, which can lead to greater role conflict and stress among workers. Given the 24/7 nature of many jobs, it becomes increasingly more important for employers to work with individuals to create jobs that meet the life needs of employees as well as the organization’s needs.

How Technology Has Changed Various Types Of Jobs

Technology has altered the nature of various types of jobs and the mix of skills that are required to do them. The cognitive complexity of work appears to be increasing for blue-collar and service workers. A major effect of information technology on blue-collar work has been to replace physical activity with mental and more abstract forms of analysis. The predominant trends in blue-collar work are for computer-integrated manufacturing technologies and team-based work, which increases the degree of control and task scope and requires higher cognitive and interactive skills and activities. It is estimated that one-third of the blue-collar workforce is changing in this way. Some of the blue-collar jobs that have undergone the greatest transformations have been the steel industry, auto industry, and the apparel industry. It should be noted that what is most important, however, is the combination of computer usage by blue-collar workers with innovative work practices and cooperative labor-management relations (i.e., computers alone do not improve productivity).

Service work (e.g., personal service, clerical and administrative support, sales) has also changed due to technology. Automation and routinization of work has expanded from the back office (typists, data processors, operators) to the front office (customer service and sales employees). Call centers now exist for telemarketing operations, banking, telecommunica­tions, and insurance. There is also evidence of an overall increase in technical skill requirements, computer usage, and cognitive complexity of service jobs.

Managerial workers consist of managers, executives, and administrators. It is expected that increased computer power may lead to a fall in managerial employment, since expert systems have reduced the need for some types of managers. Managers are more likely to be project managers than functional managers. Thus they manage the process and flow of work, rather than people. This means that they need greater skills in coordinating tasks and working horizontally across the internal and external boundaries of organizations.

Professional and technical workers (e.g., engineers, scientists, computer occupations, social scientists, lawyers, religious workers, teachers, counselors, health occupations, writers, artists, entertainers) continue to expand in the labor force. This is due to corporate growth, technological changes, demographic changes, and the commercialization of scientific knowledge. Technological changes have shifted the workforce by creating new occupations (e.g., computer operators, analysts, programmers, air traffic controllers, nuclear technicians). In addition, some occupations are experiencing greater autonomy, while at the same time, some are experiencing bureaucratic controls (e.g., health care physicians who are subject to restrictions by managed care firms). Technical and professional work has always entailed high cognitive content, but interpersonal interactions (e.g., communications, problem solving, negotiation skills) are becoming more important in many of these jobs.

Jobs For The Future

The Bureau of Labor Statistics projects that 8 of the 10 fastest-growing occupations between 2000 and 2010 will be computer related. These include jobs such as computer and information systems managers, computer programmers, computer and information scientists, computer system analysts, computer hardware and software engineers, computer support specialists, database administrators, network and computer systems administrators, and data communications analysts. Jobs requiring information technology skills are in high demand for the future, especially for the military, aerospace, and federal agencies. One important consideration is that because the skills in these jobs can become obsolete much faster than in other jobs, it is increasingly important for employers and government agencies to make it easier for IT professionals and those in computer-related fields to keep their skills current by lifelong learning efforts. In addition, some have suggested that soft skills such as communication and presentation skills are increasingly more important for IT professionals due to the greater need for them to explain technical issues to nontechnical people. It is also important for schools to attract more women to IT and computer-related fields, since traditionally few women express interest in IT or pursue these degrees. In addition, it is well documented that women often face barriers when pursuing academic careers in science, math, engineering, or technology.

Technology And Health In Careers

The technological evolution of the office environment has produced many benefits, yet it has also brought with it some negative outcomes. These include both physical health concerns as well as psychological concerns. Employers will need to continue to examine the impact of technological advances on the physical and psychological health of their employees and to make adjustments as needed.

The most commonly reported physical issues are byproducts of increasing technological sophistication (increased work pace, noise, mental demands, repetitive movements), which can lead to musculoskeletal disorders (e.g., carpal tunnel syndrome, tendinitis, back injuries). According to the U.S. Department of Labor, approximately 1.8 million people report work-related musculoskeletal disorders. These disorders are costly and long term. According to the U.S. Department of Labor, musculoskeletal disorder costs total more than $50 billion a year and are the third most frequent reason for disability and early retirement. In addition, they can lead to job loss, depression, and family disruption.

In addition to physical problems associated with increased technology in workplaces, there are also psychological health concerns. These come from office noise, changing work demands, a lack of control on the job (e.g., technological equipment breakdowns that they do not know how to fix), isolation from others, and reductions in privacy (e.g., increased electronic monitoring by supervisors). Research has linked most of these technology-related variables to psychological stress, which can then lead to other negative outcomes (strains, negative attitudes, anxiety, depression, low job satisfaction, mood disturbances).

The Impact Of Technology On Career And Developmental Practices

Today employers note that finding, attracting, and developing quality workers has become a top priority as they try to combat labor shortages, meet changing worker expectations, upgrade their workforce, and build innovation and creativity into internationally competitive organizations. Employers and applicants are increasingly relying on the Internet as part of the job search process.

Individual Job Search Strategies

With the advent of the Internet and computer-assisted career systems, individuals have greater control over their own career search strategies and progress. According to applicants, the use of the Internet for job searching is seen as a less effective strategy than personal networking but far superior to using newspaper ads and cold-calling to find jobs. In fact, most new college graduates view the Internet as a major source for help in locating job opportunities. Popular career sites such as Monster.com , Headhunter.com , and Dice.com are busy not only at their peak times on Monday and Tuesday afternoons but also during off hours (between 1 and 2 a.m.). College students, in particular, are known for pulling all-nighters to hunt for jobs online. Individuals often use these sites to view job listings and apply for jobs.

Despite the popularity of the Internet, there are some reported problems associated with using it to search for jobs. These include less personal contact, less accuracy with regard to the job’s description, difficulties finding companies’ Web pages or navigating through them, problems submitting resumes according to specific Web specifications and receiving an acknowledgment or follow-up call from company representatives once a resume is submitted.

Employers’ Use of the Internet to Hire Employees

Employers are increasingly relying on career and job Web sites to recruit and select employees. In fact, the job of the recruiter has changed such that candidates can be identified, screened, and recruited all online. Given the intense competition among employers for qualified employees, many recruiters are working late at night to look for potential resumes. Nocturnal Web surfing is now common practice among recruiters. Determined headhunters snap up hot resumes before dawn, contacting candidates by e-mail and sometimes even by phone. Many recruiters stay up past 2 a.m. examining job sites, surfing chat rooms, digging out fresh resumes on personal Web pages, posting help-wanted ads and sending e-mails. This is particularly true when recruiters are trying to hire overseas workers due to the time differences. Candidates with technical skills that are in high demand find themselves bombarded with calls and e-mail within minutes of posting a resume online. Thus from an employer’s perspective, online recruiting has tremendous potential benefits for corporations. These include reducing the time needed to hire someone, less costs relative to using headhunters and external search firms, reduced costs on mailings, brochures, and on-site interviews, and the ability to reach a more diverse applicant pool.

The Impact Of Technology On Employee Learning And Development

Due to the dynamic quality of work and work organizations, people will likely engage in seven or more jobs in their work lives. They will also have to frequently be retrained in order to remain competitive and manage their own career development. Some workers may become “world workers,” moving among nations in pursuit of suitable work. Thus there is a shift from developing “career maturity” and toward “career adaptability” (that is, being able to change to fit new or changed circumstances).

The corporation of the future will have accumulated knowledge and innovative potential of its workers as its single greatest asset. Thus training and continual learning is in demand as employees need greater skills to move more rapidly across jobs. Employees also need technical training and must learn how to operate with discretion in an open information environment. Retraining is increasingly important due to obsolescence of knowledge and skills among technical and professional workers. That is, as a result of the fast pace of technological advances, many workers lack the up-to-date knowledge and skills needed to maintain effective performance in their current or future work roles. This problem may intensify with an increasingly aging workforce. Thus retraining the expanding older techni­cal workforce is a major challenge facing the country. In addition, as firms downsize or restructure their workforce, they will need to retrain current employees to do other jobs or provide outplacement counseling so that those employees can find jobs in other organizations. For retraining efforts to be successful, it is important that there is top management support for retraining programs and that retraining is voluntary. It is also helpful if specific jobs are assigned to the employee prior to retraining so he or she can see the relevance of learning new skills.

Technology has not only impacted the importance of retraining or continual learning, but it has also influenced the type of training that can be used with employees. The methodologies used to train employees have changed due to advances in computer-based training and online methods. E-learning is gaining in popularity, since it allows individuals to continue their learning in a self-paced fashion. Thus it is immediately available to them and is not limited by travel time or costs (to attend training sessions). Likewise, distance learning programs are in great demand in firms. Some organizations (e.g., Federal Express) have implemented a corporate-wide computer system that handles most of the human resource functions of the firm (e.g., recording training completed for employees, posting job descriptions for hirings) as well as online training programs to help employees develop on their jobs.

Web-Based Or E-Mentoring

Advances in technology have created new opportunities for how the mentoring of individuals is conducted. Traditionally, mentors and proteges rely on face-to-face meetings to discuss issues and build a relationship. E-mentoring refers to the process of using electronic means as the primary channel of communication between mentors and proteges. The key distinction between electronic mentoring and traditional mentoring is reflected in the face-time between mentors and proteges. E-mentoring takes advantage of technology to broaden the definition of mentoring relationships by relaxing the constraints of geographical location and time. Thus individuals with alternative work schedules (telecommuters, flextime workers) may still access mentors without altering their work arrangements. In addition, those who have traditionally had less access to mentoring relationships (e.g., women, minorities) may have greater opportunities to get mentored with e-mentoring.

The Impact Of Technology On The Role And Services Provided By Career Counselors

History of technology and career counseling.

Vocational psychology faces a number of challenges in the next century from the globalization of economies to the changing nature of work and the workforce. Many of the changes come from the explo­sion of communication technologies in the last 20 years. The increased use of computers and the Internet in vocational psychology has been a major development for practitioners. It has led to the availability of more systems and approaches to career guidance and has essentially changed the job and role of the career counselor. In particular, with the larger number of jobs that people are expected to have over their lifetime due to advanced technology and longer life spans, counselors will be in more demand to provide career assistance. Vocational counselors will need to be prepared to deal with the changing needs and demands of both individuals and employers. For example, with the aging of the baby boomers, counselors will need to assist them in changing careers and updating skills.

The use of technology to assist individuals with career planning had its genesis in the late sixties, when early developers first used the computer to assist with career planning. The early systems that were used stored a personal record for each user in order to monitor a person’s progress through the career planning process. The results from the assessment were then linked to occupational options for the user. Some of the early sys­tems were precursors of later systems such as SIGI PLUS and DISCOVER, which are described below and are still prominent in schools and other settings today.

In the 1970s, career information systems were developed due to the National Occupational Information Coordinating Committee. These systems were comprised of search strategies through databases of occupations, schools, financial aid, and military programs. From the early seventies until 1999, there was a steady growth of customized versions of commercial career information systems in the states. With the advent of common access to the Internet in the early 1990s, career planning changed dramatically.

Several of the computer-based career information systems moved from stand-alone delivery to delivery via the Internet. Web sites devoted to career information or planning began to proliferate at an astounding rate and with a wide range of quality.

Today, individuals can take a more active role in their own career progress, since the Internet provides a rich source of career and job information that is accessible to almost anyone. This means that the counselor’s role/job has changed. Today, often the counselor’s primary role is to help clients access information on the Internet and other computer-assisted programs in an efficient and helpful manner. Of course, it is still impor­tant for counselors to meet with clients and provide career guidance. The best combination is using computers for assessment and then offering counseling with a vocational practitioner. Interestingly, cybercounseling has emerged, that is, the provision of face-to-face counseling via the Internet.

As noted, a number of different tools are used by career counselors today. These include computer-assisted career guidance systems (e.g., DISCOVER, SIGI (or the System of Interactive and Guidance Information), CHOICES, CDSS (or Career Decisions Software Solutions) and online information systems (Internet).

Computer-Assisted Career Guidance Systems

Computer-assisted career guidance (CACG) systems are often designed to help high school or college students make informed and educated decisions about their future. For example, CHOICES offers information about vocational technical schools, education and training, state and local information, and financial aid. Most computer-assisted career guidance systems offer occupational information, information about postsecondary institutions and technical/specialized schools, financial aid information, interest inventories, and decision-making skills. They might also include ability measures, value inventories, job search strategies, information on job interviewing, and local job information files. O*NET, or the Occupational Information Network, was recently developed as a replacement for the Dictionary of Occupational Titles. It is a comprehensive system that describes occupations based on at least 60 years of research and knowledge on the nature of jobs and work.

Two commonly used CACG systems are DISCOVER and SIGI PLUS. Both systems provide multiple online assessment devices to assist users in establishing links between their interests, values, abilities, and skills and the occupations that should best meet their needs. Counselors should do the following when using computer-assisted career guidance systems:

• Assess needs—assess the client’s needs to determine which parts of the career program to use.
• Orient the client—explain the purpose and goals of the program and the mechanics of the system.
• Offer assistance—provide individualized help when the client’s needs are determined.
• Provide online assistance—provide help when different stages are explored during the process.
• Follow up—encourage, motivate, set goals, and interpret outcomes to the client.
• Evaluate—monitor the effectiveness of the computer-assisted system.

As noted by Nadene Peterson and Roberto C. Gonzalez, computers provide a number of benefits to career counselors as noted below:

• A more efficient use of time for practitioners
• Immediate access to assessment results
• Greater accuracy of administration and scoring
• More opportunities for research
• Popularity with clients, especially self-motivated clients

There are, however, some potential problems such as the following:

• Loss of client/practitioner interactions
• Assumption of a certain level of client cognitive functioning and self-motivation
• Potential loss of privacy

Regardless of which computer system is used, it is important for counselors to know the client’s needs and tailor the technology to his or her needs. It is also desired that counseling assistance be provided in addi­tion to using the computer system, since most computer systems were not designed to be stand-alone. Furthermore, it is critical that career counselors receive additional training to keep pace with changes in technology as well as changes in the needs of a more diverse client population.

Career Guidance and the Internet

Today, the fastest growing source of information about careers, jobs, and related areas is on the Internet. The Internet is an international linkage of computers, telecommunications, graphics, and knowledge bases from sites around the world, making comprehensive information accessible to persons in any setting or geographic location. Some of the major sources of information about careers and jobs include the Web sites for

• Department of Labor ( http://www.dol.gov/ )
• Career Counseling Resources ( http://www.careers.org/counseling/ )
• Career Counselors Consortium ( http://www.careercc.org/ )

The Internet will continue to play an important role providing career services, because not everyone has the time or money to seek face-to-face assistance from career counselors. The primary ways in which the Internet assists individuals is by (a) administering career assessments, (b) providing information on a variety of career planning topics (e.g., occupational descriptions, job databases), (c) serving as a conduit for cybercounseling (where the client and counselor can see each other on computers to conduct their meeting), (d) serving as a forum for group communication or networking between clients and school alumni or employers or support group members, (e) enabling the creation of virtual career centers (Web sites that integrate skills or interest assessments with training required for various jobs and job openings), and (f) facilitating individual participation in virtual reality technology so that clients can explore potential work activities.

Some of the benefits of using the Internet for career services include the following:

• Service can be available to adults 24 hours a day 7 days a week, wherever they have access to the Internet.
• Multiple users can connect (alumni, employers, clients).
• Career services might be more accessible and affordable for some populations.

While online services can provide valuable information to individuals, there are a number of concerns, including the following:

• The accuracy, relevance, and timeliness of information
• The usefulness of the information
• Adequate preparation for the user to know how to process the information, since in some cases the information is disjointed or not integrated
• Opportunity for follow-up to correct or confirm the information
• Confidentiality and privacy
• Potential for violation of copyright law
• Ethical exchange of information between sites and users
• Lack of training of counselors with the technology
• Addressing issues of informed consent, trust, and protecting the identity of participants when conduct­ing research

Technology has had a dramatic impact on the nature of work itself, individual applicants and employees, employers, and career counselors. It has changed the nature of work and the types of jobs that people do today. It has altered the knowledge and skills individuals need to be effective workers. It has transformed how employers recruit, select, and train applicants and employees. It has also changed how individuals gather occupational information and how career counselors work with their clients. As a result, individuals, employers, and career counselors will need to keep pace with advancing technology and be adaptable and responsive to change in order to continue to be successful to meet the challenges of the 21st century.

• Career counseling
• Careers and health
• Internet career assessment
• Stress at work
• Telecommuting

References:

• Coovert, M. D. and Thompson, L. F. 2003. “Technology and Workplace Health.” Pp. 221-241 in Handbook of Occupational Health Psychology, edited by J. C. Quick and L. E. Tetrick. Washington, DC: American Psychological Association.
• Feldman, D. C. and Klaas, B. S. 2002. “Internet Job Hunting: A Field Study of Applicant Experiences with On-line Recruiting.” Human Resource Management 41(2):175-192.
• GartnerGroup. 2000. “Telecommuting Trends.” The Gartner Report. Retrieved from ( http://www.businesswire.com/ ).
• Harris-Bowlsbey, J. 2002. “Career Planning and Technology in the 21st Century.” Pp. 157-165 in Adult Career Development, 3d ed., edited by S. G. Niles. Columbus, OH: National Career Development Association.
• National Research Council. 1999. The Changing Nature of Work: Implications for Occupational Analysis. Washington, DC: National Academy Press.
• Niles, S. G., Herr, E. L. and Hartung, P. J. 2002. “Adult Career Concerns in Contemporary Society.” Pp. 2-18 in Adult Career Development, 3d ed., edited by S. G. Niles.
• Columbus, OH: National Career Development Association. Oliver, L. and Chartrand, J. M., eds. 2000. “Special Issues: Career Assessment and the Internet.” Journal of Career Assessment 8(1):1-104.
• Peterson, N. and Gonzalez, R. C. 2000. The Role of Work in People’s Lives: Applied Career Counseling and Vocational Psychology. Belmont, CA: Wadsworth/Thomson Learning.
• Russell, J. E. A. 2003. “Introduction: Technology and Careers.” Journal of Vocational Behavior 63(2):153-158.
• Swanson, J. L. and O’Brien, K. M. 2002. “Training Career Counselors: Meeting the Challenges of Clients in the 21 st Century.” Pp. 354-369 in Adult Career Development,3d ed., edited by S. G. Niles. Columbus, OH: National Career Development Association.
• Toffler, A. 1970. Future Shock. New York: Bantam. Zunker, V. 1994. Career Counseling: Applied Concepts of Life Planning. 4th ed. Pacific Grove, CA: Brooks/Cole.

Top 400 Information Technology Research Topics – Full Guide!

The field of IT is progressive and ever-changing due to the rapid development of hardware, software, and networking technologies. The demand for innovative research in IT has also continued to rise as businesses and organizations embrace digital systems and data-driven solutions. 

Understanding the salient areas of study in IT will help professionals keep up with changes that arise and enable organizations to leverage emerging technologies effectively. 

Cybersecurity, artificial intelligence, cloud computing , and big data analytics have emerged through IT research. These fundamental factors shape the modern technology landscape, giving rise to immense possibilities for boosting productivity, raising efficiency, and improving competitiveness across sectors. 

However, companies wanting to navigate the complexities of today’s digital age and exploit new technological advances must examine some of the latest IT research topics.

Understanding Information Technology Research

Table of Contents

In the world of technology, research is a compass that helps us navigate its convoluted evolutions. For instance, Information Technology (IT) research has been conducted in computer science, software engineering, data analytics, and cybersecurity.

IT research involves systematic inquiry to advance knowledge, problem-solving, and innovation. This includes conducting rigorous experiments and analyzing results to unveil new theories or approaches that improve technologies or bring breakthroughs.

Therefore, interdisciplinarity is at the core of IT research, with collaboration cutting across various disciplines. Whether using AI to reinforce cyber security or big data analytics in healthcare, collaboration leads to solutions to complex problems.

This is because IT research is changing rapidly due to technological advances. Thus, researchers need to be up-to-date to make meaningful contributions.

Ethics are involved so that technology can be responsibly deployed. The researchers grapple with privacy, security, bias, and equity issues to ensure technology benefits society.

As a result of this publication and conferences, which enable dissemination of findings, leading to further innovations, collaboration has supported progress, hence speeding it up.

Understanding IT research is vital for leveraging technology to address societal challenges and foster positive change.

Recommended Readings: “ Top 109+ Media Bias Research Topics | Full Guide! “.

Picking the Right Topic to Research: The Key to Finding New Things 

In the always-changing world of information technology, choosing the proper topic to research is like starting a smart path. It’s a big decision that sets where your hard work will go and how much your findings could mean.

Fitting with Industry Moves and Issues

Finding a research topic that fits current industry moves and big issues is important. By staying informed on the latest happenings and problems in the technology field, you can ensure your research stays useful and helps solve real-world troubles.

Growing Fresh Ideas and Practical Uses

Choosing a research topic that generates fresh ideas and practical applications is crucial. Your findings should not just add to school talks but also lead to real solutions that can be used in real situations, pushing technology forward and making work smoother.

Sparking Mind Curiosity and Excitement

Selecting a research topic that sparks your curiosity and excitement is essential. When you dive into an area that truly fascinates you, the research journey becomes more engaging, and your drive to uncover big insights is stronger.

Finding Gaps and Unexplored Areas

Finding gaps in existing knowledge or unexplored areas in the technology landscape can lead to big discoveries. Entering uncharted spaces can uncover fresh insights and meaningfully advance the field.

Considering Potential Wide Effect and Growth

Considering your research topic’s potential wide effect and growth is crucial. Will your findings have far-reaching effects across industries? Can your solutions grow and shift to address changing challenges? Evaluating these things can help you prioritize research areas with the greatest potential for big impact.

By carefully choosing the right research topic, you can open the door to discoveries, push technology forward, and contribute to the constant evolution of the technology information landscape.

Top 400 Information Technology Research Topics

The list of the top 400 information technology research topics is organized into different categories. Let’s examine it. 

Artificial Intelligence (AI) and Machine Learning (ML)

• Easy AI: Explaining and Using
• Group Learning: Getting Better Together
• AI in Health: Diagnosing and Helping
• Robots Learning on Their Own
• Being Fair with Computers
• Talking to Computers in Normal Language
• AI Fighting Bad Guys on the Internet
• AI Driving Cars: How Safe Is It?
• Sharing What We’ve Learned with Other Machines
• AI in Schools: Computers Learning About You

Cybersecurity and Encryption

• Trusting Computers: How to Stay Safe
• Keeping Secrets Safe with Fancy Math
• Secret Codes Computers Use: Safe or Not?
• Spy Games: Watching Out for Bad Stuff
• Keeping Secrets, Even from Friends
• Your Body as Your Password: Is It Safe?
• Fighting Against Computer Ransomers
• Keeping Your Secrets Secret, Even When Sharing
• Making Sure Your Smart Stuff Isn’t Spying on You
• Insuring Against Computer Bad Luck

Data Science and Big Data

• Sharing Secrets: How to Be Safe
• Watching the World in Real-Time
• Big Data: Big Computers Handling Big Jobs
• Making Data Pretty to Look At
• Cleaning Up Messy Data
• Predicting the Future with Numbers
• Finding Patterns in Connected Dots
• Keeping Your Secrets Safe in Big Data
• Sharing Our Secrets Without Telling Anyone
• Helping the Planet with Numbers

Cloud Computing

• Computers Without a Home: Where Do They Live?
• Keeping Computers Close to Home
• Moving Our Stuff to New Homes
• Juggling Many Clouds at Once
• Making Computers That Live in the Cloud
• Keeping Clouds Safe from Bad Guys
• Keeping Clouds Safe from Sneaky Spies
• Making Sure Clouds Do What They’re Supposed To
• Computers Need Energy Too!
• Making the Internet of Things Even Smarter

Internet of Things (IoT)

• Smart Stuff Everywhere: How Does It Work?
• Watching Out for Bad Stuff in Smart Things
• Smart Stuff: Is It Safe?
• Taking Care of Smart Toys
• Making Smart Things That Don’t Need Batteries
• Making Smart Factories Even Smarter
• Smart Cities: Making Cities Better Places to Live
• Your Clothes Can Be Smart, Too!
• Helping Farmers with Smart Farming
• Keeping Secrets Safe in Smart Stuff

Human-Computer Interaction (HCI)

• Magic Glasses: How Do They Work?
• Making Computers Easy to Use
• Making Computers for Everyone
• Talking to Computers with Your Hands
• Making Sure Computers Are Nice to People
• Talking to Computers with Your Voice
• Playing with Computers, You Can Touch
• Trusting Computers to Drive for Us
• Computers That Understand Different People
• Making Computers That Read Our Minds

Software Engineering

• Making Computers Work Together Smoothly
• Building Computers from Tiny Pieces
• Playing Games to Make Computers Better
• Making Sure Computers Work Right
• Making Old Computers New Again
• Making Computers Like to Exercise
• Making Computers Easier to Understand
• Building Computers with Blueprints
• Making Sure Computers Don’t Get Sick
• Sharing Computer Secrets with Everyone

Mobile Computing

• Keeping Phones Safe from Bad Guys
• Making Apps for Every Kind of Phone
• Keeping Phones Safe in the Cloud
• Finding Your Way with Your Phone
• Paying with Your Phone: Safe or Not?
• Checking Your Health with Your Phone
• Seeing the World Through Your Phone
• Wearing Your Phone on Your Wrist
• Learning on the Go with Your Phone
• Making Phones Even Smarter with Clouds

Networking and Communications

• Making Sure Computers Can Talk to Each Other
• Making Computers Work Together Without Wires
• Making the Internet Faster for Everyone
• Getting More Internet Addresses for More Computers
• Cutting the Internet into Pieces
• Making the Internet Even More Invisible
• Talking to Computers with Light
• Making Sure Tiny Computers Talk to Each Other
• Sending Messages Even When It’s Hard
• Making the Radio Smarter for Computers

Bioinformatics and Computational Biology

• Reading Your DNA with Computers
• Making Medicine Just for You
• Meeting the Microscopic World with Computers
• Building Computer Models of Living Things
• Finding New Medicine with Computers
• Building Computer Models of Tiny Machines
• Making Family Trees for Living Things
• Counting Germs with Computers
• Making Big Lists of Living Things
• Making Computers Think Like Brains

Quantum Computing

• Making Computers Better at Some Math Problems
• Keeping Computers Safe from Small Mistakes
• Making Computers Even Harder to Spy On
• Making Computers Learn Faster with Quantum Tricks
• Making Fake Worlds for Computers to Explore
• Building Computers from Super-Cold Stuff
• Making Computers Cold to Think Better
• Making Computers Think Like Chemists
• Making the Internet Even Safer with Computers
• Showing Off What Computers Can Do Best

Green Computing

• Saving Energy with Computers
• Using Wind and Sun to Power Computers
• Making Phones Last Longer Without Plugging In
• Making Computers Kinder to the Planet
• Recycling Old Computers to Save the Earth
• Computers That Care About Their Trash
• Saving Energy in Big Rooms Full of Computers
• Making Computers Save Energy and Work Faster
• Counting the Trash from Computers
• Making Computers Kinder to the Planet’s Air

Information Systems

• Making Computers Work Together in Big Companies
• Making Computers Remember Their Friends
• Making Computers Share What They Know
• Making Computers Smart About Money
• Making Computers Send Presents to Their Friends
• Helping Computers Make Big Decisions
• Making Government Computers Talk to Each Other
• Making Computers Count Likes and Shares
• Assisting computers to Find What You Asked For
• Assisting companies to Keep Their Friends Happy

Semantic Web and Linked Data

• Making Computers Understand Each Other Better
• Making Computers Talk About Themselves
• Making the Internet More Friendly for Computers
• Helping Computers Find What They Need
• Making Computers Smarter by Talking to Each Other
• Making Computers Friends with Different Languages
• Making Computers Understand Different Ideas
• Making Computers Think Like Us
• Making Computers Smarter About Old Stuff
• Making Computers Share Their Secrets Safely

Social Computing and Online Communities

• Making Friends on the Internet
• Getting Good Suggestions from the Internet
• Making Computers Work Together to Solve Problems
• Learning from Your Friends on the Internet
• Stopping Fake News on the Internet
• Knowing How People Feel on the Internet
• Helping Each Other on the Internet During Emergencies
• Making Sure Computers Are Nice to Everyone
• Keeping Secrets on the Internet
• Making the Internet a Better Place for Everyone

Game Development and Virtual Worlds

• Making Games That Play Fair
• Letting Computers Make Their Fun
• Making Fake Worlds for Fun
• Learning with Games
• Making the Rules for Fun
• Watching How People Play Together
• Seeing Things That Aren’t There
• Letting Lots of People Play Together
• Making the Engines for Fun
• Playing Games to Learn

E-Learning and Educational Technology

• Making Learning Easy for Everyone
• Taking Classes on the Internet
• Learning from Your Computer’s Teacher
• Learning from What Computers Know
• Learning Anywhere with Your Computer
• Making Learning Fun with Games
• Learning Without a Real Lab
• Learning with Free Stuff on the Internet
• Mixing School with Your Computer
• Making School More Fun with Your Computer

Digital Forensics and Incident Response

• Solving Computer Mysteries
• Looking for Clues in Computers
• Finding Bad Guys on the Internet
• Looking for Clues on Phones and Tablets
• Hiding Clues on Computers
• Helping When Computers Get Sick
• Solving Mysteries While the Computer Is On
• Finding Clues on Your Smart Watch
• Finding Tools for Finding Clues
• Following the Rules When Solving Mysteries

Wearable Technology and Smart Devices

• Keeping Healthy with Smart Watches
• Making Clothes That Talk to Computers
• Listening to the Earth with Your Shirt
• Wearing Glasses That Show Cool Stuff
• Making Your Home Smarter with Your Phone
• Using Your Body to Unlock Your Phone
• Helping People Move with Special Shoes
• Assisting people to See with Special Glasses
• Making Your Clothes Do More Than Keep You Warm
• Keeping Secrets Safe on Your Smart Stuff

Robotics and Automation

• Making Friends with Robots
• Letting Robots Do the Hard Work
• Robots That Work Together Like Ants
• Learning Tricks from People
• Robots That Feel Like Jelly
• Helping Doctors and Nurses with Robots
• Robots That Help Farmers Grow Food
• Making Cars Without People
• Teaching Robots to Recognize Things
• Robots That Learn from Animals

Health Informatics

• Computers That Help Doctors Keep Track of Patients
• Sharing Secrets About Your Health with Other Computers
• Seeing the Doctor on Your Computer
• Keeping Track of Your Health with Your Phone
• Making Medicine Better with Computers
• Keeping Your Health Secrets Safe with Computers
• Learning About Health with Computers
• Keeping Health Secrets Safe on the Internet
• Watching Out for Germs with Computers
• Making Sure the Doctor’s Computer Plays Nice

Geographic Information Systems (GIS)

• Watching the World Change with Computers
• Making Maps on the Internet
• Seeing the World from Very Far Away
• Finding Hidden Patterns with Computers
• Making Cities Better with Computers
• Keeping Track of the Earth with Computers
• Keeping Track of Wild Animals with Computers
• Making Maps with Everyone’s Help
• Seeing the World in 3D
• Finding Things on the Map with Your Phone

Knowledge Management

• Helping Computers Remember Things
• Making Computers Talk About What They Know
• Finding Secrets in Big Piles of Data
• Helping Companies Remember What They Know
• Sharing Secrets with Computers at Work
• Making Computers Learn from Each Other
• Making Computers Talk About Their Friends
• Making Companies Remember Their Secrets
• Keeping Track of What Companies Know

Computational Linguistics and Natural Language Processing (NLP)

• Finding Out How People Feel on the Internet
• Finding Names and Places in Stories
• Making Computers Talk to Each Other
• Making Computers Answer Questions
• Making Summaries for Busy People
• Making Computers Understand Stories
• Making Computers Understand Pictures and Sounds
• Making Computers Learn New Words
• Making Computers Remember What They Read
• Making Sure Computers Aren’t Mean to Anyone

Information Retrieval and Search Engines

• Finding Stuff on the Internet
• Getting Suggestions from the Internet
• Finding Stuff at Work
• Helping Computers Find Stuff Faster
• Making Computers Understand What You Want
• Finding Stuff on Your Phone
• Finding Stuff When You’re Moving
• Finding Stuff Near Where You Are
• Making Sure Computers Look Everywhere for What You Want

Computer Vision

• Finding Stuff in Pictures
• Cutting Up Pictures
• Watching Videos for Fun
• Learning from Lots of Pictures
• Making Pictures with Computers
• Finding Stuff That Looks Like Other Stuff
• Finding Secrets in Medical Pictures
• Finding Out If Pictures Are Real
• Looking at People’s Faces to Know Them

Quantum Information Science

• Making Computers Learn Faster with Tricks

Social Robotics

• Robots That Help People Who Have Trouble Talking
• Robots That Teach People New Things
• Making Robots Work with People
• Helping Kids Learn with Robots
• Making Sure Robots Aren’t Mean to Anyone
• Making Robots Understand How People Feel
• Making Friends with Robots from Different Places
• Making Sure Robots Respect Different Cultures
• Helping Robots Learn How to Be Nice

Cloud Robotics

• Making Robots Work Together from Far Away
• Making Robots Share Their Toys
• Making Robots Do Hard Jobs in Different Places
• Making Robots Save Energy
• Making Robots Play Together Nicely
• Making Robots Practice Being Together
• Making Sure Robots Play Fair
• Making Robots Follow the Rules

Cyber-Physical Systems (CPS)

• Making Robots Work Together with Other Things
• Keeping Robots Safe from Small Mistakes
• Keeping Factories Safe from Bad Guys
• Making Sure Robots Respect Different People
• Making Sure Robots Work Well with People
• Keeping Robots Safe from Bad Guys
• Making Sure Robots Follow the Rules

Biomedical Imaging

• Taking Pictures of Inside You with Computers
• Seeing Inside You with Computers
• Cutting Up Pictures of Inside You
• Finding Problems Inside You with Computers
• Cutting Up Pictures and Putting Them Together
• Counting Inside You with Pictures
• Making Pictures to Help Doctors
• Making Lists from Pictures Inside You
• Making Sure Pictures of You Are Safe

Remote Sensing

• Watching Earth from Far Away with Computers
• Making Pictures of Earth Change
• Taking Pictures from Very High Up
• Watching Crops Grow with Computers
• Watching Cities Grow with Computers
• Watching Earth Change with Computers
• Watching Earth from Far Away During Emergencies
• Making Computers Work Together to See Earth
• Putting Pictures of Earth Together
• Making Sure Pictures of Earth Are Safe

Cloud Gaming

• Playing Games from Far Away
• Making Games Work Faster from Far Away
• Keeping Games Safe from Bad Guys
• Making Sure Everyone Can Play Together
• Making Games Faster from Far Away
• Watching People Play Games from Far Away
• Making Sure Games Look Good from Far Away
• Watching Games Get More Popular

Augmented Reality (AR)

• Making Glasses That Show Cool Stuff
• Making Cool Stuff for Glasses to Show
• Watching Glasses Follow You
• Watching Phones Show Cool Stuff
• Making Cool Stuff to Show with Phones
• Making Places Even Better with Phones
• Making Factories Even Better with Glasses
• Making Places Even Better with Glasses
• Making Sure Glasses Don’t Scare Anyone

Virtual Reality (VR)

• Making Glasses That Show Different Worlds
• Making Glasses That Follow Your Hands
• Making Therapy Fun with Glasses
• Making Learning Fun with Glasses
• Making Glasses That Make Jobs Safer
• Making Glasses That Show Your Friends
• Making Sure Glasses Are Friendly
• Making Glasses That Make Buildings Better
• Making Sure Glasses Aren’t Scary

Digital Twins

• Making Computers That Copy the Real World
• Making People Better with Computers
• Making Flying Safer with Computers
• Making Cars Safer with Computers
• Making Energy Better with Computers
• Making Buildings Better with Computers
• Making Cities Safer with Computers
• Making Sure Computers Copy the Real World Safely
• Making Computers Follow the Rules

Edge Computing

• Making Computers Work Faster Near You
• Keeping Computers Safe Near You
• Making Computers Work with Far-Away Computers
• Making Computers Work Fast with You
• Making Computers Work Together Near You
• Making Phones Work Faster Near You
• Making Computers Work Near You
• Making Computers Work in Busy Places

Explainable AI (XAI)

• Making Computers Explain What They Do
• Making Medicine Safer with Computers
• Making Money Safer with Computers
• Making Computers Safe to Drive Cars
• Making Computers Fair to Everyone
• Making Computers Explain What They Think
• Making Computers Easy to Understand

Blockchain and Distributed Ledger Technology (DLT)

• Making Secret Codes Computers Use
• Making Contracts Computers Can Understand
• Making Computers Share Secrets Safely
• Making Money Safe with Computers
• Making Computers Work Together Nicely
• Making Computers Keep Secrets Safe
• Making Computers Work Together Fairly
• Making Stuff Move Safely with Computers

Quantum Communication

• Making Computers Talk to Each Other Safely
• Making Computers Talk to Each Other from Far Away
• Making Computers Talk to Each Other in Secret
• Making Money Move Safely with Computers

This list covers a broad spectrum of topics within Information Technology, ranging from foundational concepts to cutting-edge research areas. Feel free to choose any topic that aligns with your interests and expertise for further exploration and study!

Emerging Trends in Information Technology Research

In the rapidly changing world of Computer Studies, keeping up with the latest trends is indispensable. Technology keeps changing, and so does research in computer studies. From awesome things like clever robots to how we can safeguard our online information, computer studies research is always discovering new ways to improve our lives. Therefore, let us delve into some of the most exciting new trends shaping computer studies’ future.

• Smart Computers:

Right now, smart computers are a hot item. They can learn from experience, recognize patterns, and even understand language like humans do. This helps in many areas, such as healthcare or finance. So researchers are working on making smart computers smarter yet so that they can make decisions alone and be fair to everyone.

• Fast Computing:

As more devices connect to the Internet, we need ways to process information quickly. Fast computing helps bring processing power closer to where the information comes from, making things quicker and more efficient. Thus, researchers have been figuring out how to improve fast computing, especially for analyzing real-time data.

• Keeping Things Safe:

With all the cool tech around, keeping our information safe from bad guys is important. We must develop methods to safeguard our data and networks from cyber attackers. In addition, they have also been considering how to ensure the privacy of our personal information so that only authorized individuals can access it.

• Fancy Computers:

The next big thing in computing is quantum computers. They can do calculations at a high speed that ordinary ones cannot. Researchers are working hard to achieve quantum computing because it could be useful in cracking codes and creating new drugs.

• New Ways of Doing Things Together:

Blockchain is an exciting technology that allows us to collaborate without a central authority. Its use in cryptocurrencies is quite popular but it has other applications too. Blockchain can be applied for purposes such as helping us discover where products come from, proving who we are on the internet, and making contracts that cannot be changed later on.

• Virtual Reality Adventures:

Entering a completely different world is what Virtual Reality (VR) and Augmented Reality (AR) do. The feeling of being in reality is what these two technologies create, which is not real. These researchers are working hard on making VRs and ARs better so that they can be used for learning, training, and amusement in more innovative ways.

In summary, computer studies research keeps changing with new trends such as smart computers, rapid computing, cybersecurity issues, high-end computers, collaboration platforms and immersive games or virtual reality escapades. 

By exploring these trends and developing new ideas, researchers ensure that technology keeps improving and making our lives easier and more exciting.

How can I brainstorm research topics in information technology?

Start by identifying your areas of interest and exploring recent advancements in the field. Consider consulting with mentors or peers for suggestions and feedback.

What are some ethical considerations in AI research?

Ethical considerations in AI research include fairness, transparency, accountability, and privacy. Researchers should ensure their algorithms and models do not perpetuate bias or harm individuals.

How can I stay updated on emerging trends in IT research?

Follow reputable journals, conferences, and online forums dedicated to information technology. Engage with the academic community through discussions and networking events.

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Environmental Science: Water Research & Technology

Harnessing exoelectrogens in a novel microbial desalination cell: a study on the impact of salinity on sago effluent treatment and power generation.

* Corresponding authors

a Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu, India E-mail: [email protected]

Microbial desalination cell (MDC) provides integral solutions for addressing water scarcity and environmental challenges. This research paper investigates a novel MDC with two distinct exoelectrogens, Shewanella putrefaciens MTCC 8104 (MDC – 1) and mixed culture (MDC – 2) at three different NaCl concentrations (10 g L −1 , 20 g L −1 and 30 g L −1 ) and brackish water in the desalination chamber utilizing sago effluent as an anolyte. The maximum chemical oxygen demand (COD) removal and desalination efficiency of 95.1 ± 2% and 13.2 ± 2% were observed for 30 g L −1 NaCl for MDC – 1. Furthermore, the power density obtained at 30 g L −1 NaCl concentration for MDC – 1 was 60.22 ± 0.2 mW m −2 and 43.09 ± 0.2 mW m −2 for MDC – 2. The internal resistance of the Shewanella putrefaciens inoculated MDC – 1 was very low compared to MDC – 2. However, the dynamics changed in brackish water treatment, where MDC – 1 faced challenges due to the diffusion of ions other than Na+ and Cl − , leading to increased internal resistance and reduced power output. In contrast, the mixed culture in MDC – 2 adapted well to the brackish water ions, showcasing higher oxidation–reduction potential, increased power, and low internal resistance. These findings underscore the superior performance of Shewanella putrefaciens in NaCl desalination, while a mixed culture proves more adaptable and effective in real-time brackish water treatment. As conductivity increases, internal resistance diminishes, suggesting the potential future application of MDC in treating real seawater and brackish water by optimizing volume ratios, biofilm performance and preventing membrane fouling.

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S. Prakash, S. Naina Mohamed and K. Ponnusamy, Environ. Sci.: Water Res. Technol. , 2024, Advance Article , DOI: 10.1039/D4EW00081A

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Guest Essay

A Simple Act of Defiance Can Improve Science for Women

By Toby Kiers

Dr. Kiers is a professor of evolutionary biology at Vrije Universiteit in Amsterdam and the executive director of SPUN, a research organization that advocates the protection of mycorrhizal fungal communities.

They don’t tell you beforehand that it will be a choice between having a career in science or starting a family. But that’s the message I heard loud and clear 17 years ago, in my first job after completing my Ph.D. in evolutionary biology. During a routine departmental meeting, a senior academic announced that pregnant women were a financial drain on the department. I was sitting visibly pregnant in the front row. No one said anything.

I took a leave of absence when that child, my daughter, was born. Two years later, I had a son. That second pregnancy was a surprise, and I worried that taking another leave would sink my career. So I pressed on. When my son was barely 3 weeks old, I flew nine hours to a conference with him strapped to my chest. Before delivering my talk, I made a lame joke that the audience should forgive any “brain fog.” Afterward, an older woman pulled me aside and told me that being self-deprecating in public was a disservice to women scientists.

It felt like an impossible choice: to be a bad scientist or a bad mother.

The data suggests I wasn’t alone in feeling those pressures. A study published in 2019 found that more than 40 percent of female scientists in the United States leave full-time work in science after their first child. In 2016, men held about 70 percent of all research positions in science worldwide. Especially for field researchers like me, who collect data in remote and sometimes perilous locations, motherhood can feel at odds with a scientific career.

How have I addressed the problem? Through an act of academic defiance: I bring my kids with me on my scientific expeditions. It’s a form of rebellion that is available to mothers not just in the sciences but also in other disciplines that require site visits and field work, such as architecture and journalism. Bringing your kids to work with you doesn’t have to be something you do only once a year .

It started for me as a simple necessity. When my son was just under 2 and my daughter not yet 4, I took them on an expedition to the base of Mount Kenya in Africa, to study how fungi help trees defend themselves against the elephants and giraffes who feed on them. My son was still nursing, and I didn’t want to stop working. My husband, a poet, came along to stay with them at base camp.

As time went on, I began to embrace the decision to bring my kids with me on my expeditions, not as an exigency of parenting but as a kind of feminist act. When meeting other scientists in the field, the reaction was typically the same: They assumed my husband was leading the expedition. Once the facts were established, researchers were supportive and even willing to lend a hand.

Looking back at those expeditions now — after more than a dozen, in far-flung areas around the globe — I understand that bringing them into the field was more than a rebellion: Their presence on those trips also changed the way I do science, and for the better.

I started tasting soils in the field — a technique I now use to notice subtle differences across ecosystems — only after seeing my kids eat dirt. Children have an uncanny ability to make local friends quickly; many of those new friends have led me to obscure terrain and hidden fungal oases that I otherwise would never have come across. And my kids’ naïve minds routinely force me to rethink old assumptions by asking questions that are simultaneously absurd and profound. Can you taste clouds? Do fungi dream? How loud are our footsteps underground?

What can feel like an inconvenience is often a blessing in disguise. Children force the patience that scientific discovery demands. Last year, my kids and I traveled to Lesotho , in southern Africa. Collecting fungi in such a rugged landscape required horses, guides and months of precise planning. But my daughter caught the flu. Rather than mapping underground fungal life, we spent the week in a hut in a highland village with no running water or electricity, eating fermented sorghum. As the days ticked by, I began to panic, thinking of the fungi that would remain unsampled.

But one morning, as my daughter’s health improved, we were invited to cross a small mountain pass on horses. The local herder allowed me to collect dark soil among the agricultural ruins of his ancestral village. It was a type of soil I had never seen — with fungi that would have remained undescribed had we stayed on track. Thank you, chaos; thank you, kids.

Bringing my kids with me continues to challenge expectations, and not only among fellow scientists. In the summer of 2022, my kids and I embarked on an expedition in Italy to study fungi exposed to extreme heat and wildfire. Hiking across mountains with kids was hard and made even more arduous because a documentary film crew followed us. As we wrangled fungi in burn sites, the cameraman strategically positioned me for shots without my kids, presumably so the footage would look more “professional.”

Female scientists are right to fear being seen as unprofessional. How we talk, how we dress, is constantly under scrutiny — and so many of us mirror our male colleagues. Any deviation from that standard is often considered suspect. The primatologist Jane Goodall famously placed her young son in a cage so that he could safely join her in the field, and it is still a point of controversy, decades later.

At its core, feminism is about having the power to choose. For female scientists, this means having the ability to bring children into the field — or the full support to leave them at home. The pressure is acute because, as research shows, women on scientific teams are significantly less likely than men to be credited with authorship. So for me, it is crucial to keep collecting data with my own hands.

What do my kids make of all this? They both love and hate our expeditions. Frustrated by a grueling day of field work recently, my teenage daughter screamed at me, “You love science more than you love me!” In that moment, she — like so much of the scientific world — believed that the decision was binary: science or family. But by taking her with me into the field, I am relentlessly affirming that I won’t make that choice. My kids won’t make that choice either: They recently helped start a youth climate group to help protect soil fungi, including by organizing protests.

We are taught that good science requires detachment. But what if being a mother — with all the attachments that entails — allows you to explore different but equally fruitful scientific narratives? Last year, an article by the editor who oversees the Science journals argued that scientists should not be “afraid to acknowledge their humanity.” We should take that sound advice a step further and challenge the ideal of detachment. Perhaps by exposing our vulnerabilities — such as the children we are raising — we can change the system.

Toby Kiers ( @KiersToby ) is a professor of evolutionary biology at Vrije Universiteit in Amsterdam and the executive director of SPUN , a research organization that advocates for the protection of mycorrhizal fungal communities.

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How to Thrive as You Age

Got tinnitus a device that tickles the tongue helps this musician find relief.

Allison Aubrey

After using the Lenire device for an hour each day for 12 weeks, Victoria Banks says her tinnitus is "barely noticeable." David Petrelli/Victoria Banks hide caption

After using the Lenire device for an hour each day for 12 weeks, Victoria Banks says her tinnitus is "barely noticeable."

Imagine if every moment is filled with a high-pitched buzz or ring that you can't turn off.

More than 25 million adults in the U.S., have a condition called tinnitus, according to the American Tinnitus Association. It can be stressful, even panic-inducing and difficult to manage. Dozens of factors can contribute to the onset of tinnitus, including hearing loss, exposure to loud noise or a viral illness.

There's no cure, but there are a range of strategies to reduce the symptoms and make it less bothersome, including hearing aids, mindfulness therapy , and one newer option – a device approved by the FDA to treat tinnitus using electrical stimulation of the tongue.

The device has helped Victoria Banks, a singer and songwriter in Nashville, Tenn., who developed tinnitus about three years ago.

"The noise in my head felt like a bunch of cicadas," Banks says. "It was terrifying." The buzz made it difficult for her to sing and listen to music. "It can be absolutely debilitating," she says.

Shots - Health News

Tinnitus bothers millions of americans. here's how to turn down the noise.

Banks tried taking dietary supplements , but those didn't help. She also stepped up exercise, but that didn't bring relief either. Then she read about a device called Lenire, which was approved by the FDA in March 2023. It includes a plastic mouthpiece with stainless steel electrodes that electrically stimulate the tongue. It is the first device of its kind to be approved for tinnitus.

"This had worked for other people, and I thought I'm willing to try anything at this point," Banks recalls.

She sought out audiologist Brian Fligor, who treats severe cases of tinnitus in the Boston area. Fligor was impressed by the results of a clinical trial that found 84% of participants who tried Lenire experienced a significant reduction in symptoms. He became one of the first providers in the U.S. to use the device with his patients. Fligor also served on an advisory panel assembled by the company who developed it.

"A good candidate for this device is somebody who's had tinnitus for at least three months," Fligor says, emphasizing that people should be evaluated first to make sure there's not an underlying medical issue.

Tinnitus often accompanies hearing loss, but Victoria Banks' hearing was fine and she had no other medical issue, so she was a good candidate.

Banks used the device for an hour each day for 12 weeks. During the hour-long sessions, the electrical stimulation "tickles" the tongue, she says. In addition, the device includes a set of headphones that play a series of tones and ocean-wave sounds.

The device works, in part, by shifting the brain's attention away from the buzz. We're wired to focus on important information coming into our brains, Fligor says. Think of it as a spotlight at a show pointed at the most important thing on the stage. "When you have tinnitus and you're frustrated or angry or scared by it, that spotlight gets really strong and focused on the tinnitus," Fligor says.

"It's the combination of what you're feeling through the nerves in your tongue and what you're hearing through your ears happening in synchrony that causes the spotlight in your brain to not be so stuck on the tinnitus," Fligor explains.

A clinical trial found 84% of people who used the device experienced a significant reduction in symptoms. Brian Fligor hide caption

A clinical trial found 84% of people who used the device experienced a significant reduction in symptoms.

"It unsticks your spotlight" and helps desensitize people to the perceived noise that their tinnitus creates, he says.

Banks says the ringing in her ears did not completely disappear, but now it's barely noticeable on most days.

"It's kind of like if I lived near a waterfall and the waterfall was constantly going," she says. Over time, the waterfall sound fades out of consciousness.

"My brain is now focusing on other things," and the buzz is no longer so distracting. She's back to listening to music, writing music, and performing music." I'm doing all of those things," she says.

When the buzz comes back into focus, Banks says a refresher session with the device helps.

A clinical trial found that 84% of people who tried Lenire , saw significant improvements in their condition. To measure changes, the participants took a questionnaire that asked them to rate how much tinnitus was impacting their sleep, sense of control, feelings of well-being and quality of life. After 12 weeks of using the device, participants improved by an average of 14 points.

"Where this device fits into the big picture, is that it's not a cure-all, but it's quickly become my go-to," for people who do not respond to other ways of managing tinnitus, Fligor says.

One down-side is the cost. Banks paid about $4,000 for the Lenire device, and insurance doesn't cover it. She put the expense on her credit card and paid it off gradually.

Fligor hopes that as the evidence of its effectiveness accumulates, insurers will begin to cover it. Despite the cost, more than 80% of participants in the clinical trial said they would recommend the device to a friend with tinnitus.

But, it's unclear how long the benefits last. Clinical trials have only evaluated Lenire over a 1-year period. "How durable are the effects? We don't really know yet," says audiologist Marc Fagelson, the scientific advisory committee chair of the American Tinnitus Association. He says research is promising but there's still more to learn.

Fagelson says the first step he takes with his patients is an evaluation for hearing loss. Research shows that hearing aids can be an effective treatment for tinnitus among people who have both tinnitus and hearing loss, which is much more common among older adults. An estimated one-third of adults 65 years of age and older who have hearing loss, also have tinnitus.

"We do see a lot of patients, even with very mild loss, who benefit from hearing aids," Fagelson says, but in his experience it's about 50-50 in terms of improving tinnitus. Often, he says people with tinnitus need to explore options beyond hearing aids.

Bruce Freeman , a scientist at the University of Pittsburgh Medical Center, says he's benefitted from both hearing aids and Lenire. He was fitted for the device in Ireland where it was developed, before it was available in the U.S.

Freeman agrees that the ringing never truly disappears, but the device has helped him manage the condition. He describes the sounds that play through the device headphones as very calming and "almost hypnotic" and combined with the tongue vibration, it's helped desensitize him to the ring.

Freeman – who is a research scientist – says he's impressed with the results of research, including a study published in Nature, Scientific Reports that points to significant improvements among clinical trial participants with tinnitus.

Freeman experienced a return of his symptoms when he stopped using the device. "Without it the tinnitus got worse," he says. Then, when he resumed use, it improved.

Freeman believes his long-term exposure to noisy instruments in his research laboratory may have played a role in his condition, and also a neck injury from a bicycle accident that fractured his vertebra. "All of those things converged," he says.

Freeman has developed several habits that help keep the high-pitched ring out of his consciousness and maintain good health. "One thing that does wonders is swimming," he says, pointing to the swooshing sound of water in his ears. "That's a form of mindfulness," he explains.

When it comes to the ring of tinnitus, "it comes and goes," Freeman says. For now, it has subsided into the background, he told me with a sense of relief. "The last two years have been great," he says – a combination of the device, hearing aids and the mindfulness that comes from a swim.

This story was edited by Jane Greenhalgh

• ringing in ears
• hearing loss