literature review techno stress

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Analyzing the evolution of technostress: A science mapping approach

Cristian salazar-concha, pilar ficapal-cusí, joan boada-grau, luis j camacho.

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Corresponding author. [email protected]

Received 2019 Jul 31; Revised 2020 Dec 2; Accepted 2021 Apr 1; Collection date 2021 Apr.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This paper analyzes the scientific map of technostress and the scientific production on this topic between 1982 and 2017, highlighting its structure, evolution, and trends in this field. A literature review based on bibliometric analysis of 246 records indexed in Scopus database was conducted. These publications were analyzed according to bibliometric indicators and through science maps with SciMAT. Co-occurrence of terms by grouping techniques was implemented. In addition, elaboration of maps of science and performance analysis for periods was executed. The main contribution of this work is to provide the first scientific map of technostress and a detailed understanding of the scientific production that predicts the directions of future research. The bibliometric analyses permit an overview of the growth, extent and distribution of the scientific literature related to the technostress and the study of the scientific production of an institution, country, author or research group.

Keywords: Technostress, Bibliometric analysis, Science mapping, Bibliometric indicators, SciMat

Technostress, bibliometric analysis, science mapping; bibliometric indicators; SciMat.

1. Introduction

Information and communication technologies (ICT) are fully integrated into our lives and jobs and will even more in the future. However, for many workers, ICT is surpassing the boundaries between labor and going into their personal experience. The use of ICT in different industries, the internet prevalence, and their ubiquitous nature, forces employees to deal with a considerable amount of information that grows along with the unprecedented development of new tools which demand employees be updated ( Shu et al., 2011 ). In many cases, employees are exposed to more information than they can efficiently manage ( Fisher and Wesolkowski, 1999 ).

The capabilities of a human being to deal with information is limited, although the development of new ICT is limitless. ITC's will be incorporated in our lives, and we will have fewer possibilities the be free of the technostress that they produce ( Shu et al., 2011 ). Technostress is a managerial problem that organizations are facing in a technologically dependent working environment ( Hung et al., 2015 ); in the organizational context, this reality can be attributed to ITC's constant presence and pace of change ( Ayyagari et al., 2011 ). Conceptualization of the technostress phenomenon is directly related to psychosocial effects associated with the use of ICT, and negative feelings related to the value of its use ( Burke, 2009 ; Carlotto et al., 2017 ).

Technostress is defined as the stress that people experience due to the use of information and communication systems and technologies ( Tarafdar et al., 2007 , 2019 ; Ragu-Nathan et al., 2008 ; Ayyagari et al., 2011 ; Chen and Muthitacharoen, 2016 ). It represents an emergent global phenomenon of academic research experienced by workers who transcends national and cultural boundaries ( Chen, 2015 ). For instance, at the global level, high levels of technostress have been reported among workers in some of the fastest growing economies, such as China ( Tu et al., 2005 ), India ( Sinkovics et al., 2002 ), Indonesia ( Suharti and Susanto, 2014 ) and the malaysian economy ( Ibrahim and Othman, 2014 ).

The purpose of the present research is, first, to explore the scientific production and evolution of technostress research, and second, provide the first technostress science map that shows the structure, evolution, and trends of this topic over time. We go further to investigate with several questions we considered relevant. First, who are the most prolific authors and most influential researches in technostress. Second, what are the journals with the highest number of publications related to technostress. Third, what are the main research topics in this topic. Fourth, what are the most used methods in leading publications about technostress. Fifth, what are the most critical themes in terms of production and impact. Finally, how have the themes evolved since 1982, and what topics have not yet been addressed or developed.

We have chosen a bibliometric research methodology allows to quantify and measure the performance, quality, and impact of generated maps and their components ( Cobo et al., 2012 ). A bibliographic analysis of the scientific production of technostress indexed from 1982 to 2017 in the Scopus database is carried out using a scientific mapping approach, analyzing its co-occurrence of terms through grouping techniques, making maps of science and performance analysis for to detect and visualize conceptual subdomains on technostress, as well as its thematic evolution. This study used a bibliometrics tool (SciMat v1.1.04) to build maps of science and strategic diagrams to analyze the temporal evolution of technostress main topics. The bibliometric analysis ( Pritchard, 1969 ) allows to quantify and measure the performance, quality, and impact of generated maps and their components ( Cobo et al., 2012 ) and provides objective criteria for evaluating scientific production ( Noyons et al., 1999 ).

The paper is structured as follows. In the next section, works of literature reviews of the selected articles related to technostress are highlighted. Afterwards, we explain the methodological approach, bibliometrics, and science mapping. Next, we analyze the findings. Finally, we propose some discussion and present conclusions regarding the limitations of the present research and a number of venues of future research.

2. Literature review

The phenomenon of technostress has been studied since the 1980s. First, it was associated with the automation of the workplace, and later it evolved to problems generated by employees use of ICT ( Polakoff, 1982 ; Shu et al., 2011 ). The term technostress was coined by the American psychotherapist Craig Brod as "a modern disease of adaptation caused by an inability to cope with the new computer technologies in a healthy manner” ( Brod, 1984 ) (p. 16). Years later, Weil and Rosen (1997) extended this definition because they did not agree that technostress was a disease. Technostress is "any negative impact on attitudes, thoughts, behaviors, or body psychology caused directly or indirectly by technology” ( Weil and Rosen, 1997 ) (p. 36). Despite the popularity of these first definitions, Connolly and Bhattacherjee (2011) pointed out that they did not have a theoretical or empirical basis.

From a transactional perspective, Caro and Sethi (1985) define technostress as "a perceived, dynamic adaptive state between the person and the environment, mediated by sociopsychological processes and influenced by the nature of the technological environment" ( Caro and Sethi, 1985 ) (p. 292). Therefore, technostress' experience depends on the users' individual characteristics, and their coping mechanisms or adaptive capabilities. In the organizational context, Tarafdar et al. (2007) indicated that technostress is caused by individual attempts and struggles to deal with constantly evolving ICTs and the changing physical, social, and cognitive requirements related to their use. They presented one of the most cited articles on the subject. The authors point out that technostress is a phenomenon that encapsulates a combination based on a condition of demand that causes stress. Technostress creators are defined as the factors that cause technostress for employees ( Krishnan, 2017 ) and the individual's response to it -adverse manifest results or tension. The work of reference ( Tarafdar et al., 2007 ) found that technostress was manifested behaviorally and psychologically in the following five dimensions: techno-overload, techno-invasion, techno-complexity, techno-insecurity, and techno-uncertainty ( Chen, 2015 ).

Although the above definitions are widely used in literature, Lei and Ngai (2014) stated these definitions assume that technostress is negative and do not conform to the nature of stress, which is neither positive or negative ( Webster et al., 2011 ). The authors define technostress as "the state of mental or physiological stimulation caused by the ICT usage for work purpose, which is usually attributed to increasing work overload, accelerated tempo, and erosion of personal time, among others" ( Lei and Ngai, 2014 ) (p. 2).

According to the transactional theory of stress ( Lei and Ngai, 2014 ), technostress can produce both negative and positive outcomes. In this regard, Tarafdar et al. (2019) indicated that stress embodies the condition of unbalance experienced by an individual between the demands of a situation and the ability to fulfill them.

Not all people react in the same way to certain internal or external alterations; hereof, two concepts arise, techno-eustress and techno-distress. Techno-eustress is positive stress that causes satisfaction, joy, increases vitality, does not cause imbalances and helps facilitate people's decision making ( Tarafdar et al., 2019 ). According this reference, it originates due to the emergence of new challenges and opportunities, allowing skill development. If adequate use of the technologies is given, these tools would facilitate the human being to reach new goals and challenges based on coexistence and interrelation with the new ICT, improving the performance and providing a faster use of new technologies.

Positive effects generated by technostress in people are to improve individual performance, greater efficiency, and innovation, and improve tasks made through ICT producing happiness and stability. Wajcman and Rose (2011) mentioned that first-line positions employees use information systems under positive or motivating pressures. The result of these positive pressures can increase efficiency (e.g., reducing time and effort, working faster, reducing errors) and effectiveness (e.g., improving service quality), resulting in better performance.

A risk that technostress can cause is that, in the long term, an individual could be overloaded and can, therefore, be stressed causing harm to his health. The worker will have a greater personal development thanks to the stress; however, it will be probably based on the detriment of his health; therefore, it is advisable not to exceed its use.

On the other hand, techno-distress is the negative effect generated by peoples use of ICT. It is originated due to the emergence of threats or obstacles ( Tarafdar et al., 2019 ). Since ICT goes beyond the competences of users, they see ICT's as a threat, not as a benefit. Ragu-Nathan et al. (2008) stated that individuals evaluate characteristics of information systems as threatening, with pressures that go beyond their own abilities. Moreover, they perceive negative consequences of not facing them.

In the beginning, researchers observed technostress as a disease; however, further researches consider it more as an inability of adopting changes in organization produced by ICT. Also, it is a natural reaction to technology where each employee must be prepared to adopt new technologies ( Jena, 2015 ) and organizations should be ready to support workers to reduce technostress ( Chen, 2015 ). Nimrod (2018) points out that technostress is a consequence of an individual's attempts and struggles to deal with evolving ICT regularly, as well as changes in cognitive and social needs related to their use.

First definitions of technostress were quite broad, and the authors often used the same concept to refer to different phenomena related to technostress such as Technophobia and Technoadiction ( Nimrod, 2018 ). Tarafdar et al. (2019) mention that technostress represents an emergent phenomenon of academic research. It is a process that includes the presence of technological environmental conditions, which are evaluated as demands or techno stressors, which bond the individual and require change. It is a physical and psychological discomfort condition caused by the interaction with the technology; however, these authors point out that technostress can be considered as positive or negative according to the personality of an individual and the reaction to the trigger situation of the fact.

In the last decade, three works of literature reviews related to technostress is highlighted. The first review conducted a search through Google Scholar. This Study analyzed 40 works with more than 4 quotations each ( Riedl, 2012 ). The second work reviewed relevant articles from different disciplines including the information systems, organizational behavior, psychological stress, and other disciplines where stress in workplaces had been studied. This study included articles published in 20 years (1995–2016). The Authors selected 27 articles for their analyses ( Tarafdar et al., 2019 ).

The third article analyzed 103 empirical studies. Specifically, they focused on the data and methods used in various researches and concluded that research in technostress constitutes a field conducive to multidisciplinary collaboration and the application of approaches that use multiple methods ( Fischer and Riedl, 2017 ).

3. Methodology

3.1. sources and data.

Cobo et al. (2011a) highlighted the concept of bibliometric analyses can be employed to carry out a performance analysis of the generated maps. This paper uses science mapping analysis, that is focused on monitoring a scientific field and defining the areas of research determining its cognitive and evolutionary structure, showing the structural and dynamic aspects of scientific research ( Noyons et al., 1999 ; Börner et al., 2003 ; Morris and Van der Veer Martens, 2008 ; Cobo et al., 2012 ). Two software tools have been used on the bibliometric analysis carried out in this study: a) The Scopus analysis tool allows conducting the performance bibliometric analysis and; b) The SciMAT software tool, which allows to carry out bibliometric analysis of content based on science maps. The publications were analyzed according to bibliometric indicators and through science maps with SciMat 1.1.04 version.

To provide a rigorous analysis, we followed the steps of a scientific mapping analysis ( Börner et al., 2003 ; Cobo et al., 2011a ): data recovery, data preprocessing, network extraction, network normalization, mapping, analysis and visualization. At the end of this process, we interpreted and obtained conclusions from the results.

In the data search stage, we use the Scopus database. It is a good choice among multidisciplinary databases ( Norris and Oppenheim, 2007 ). It offers a greater selection of journals in all different fields ( Goodman and Deis, 2007 ) and includes, in addition to articles, other document types such as books and conference proceedings ( Fingerman, 2006 ). In addition to the above, Scopus has a greater degree of singularity, containing a greater number of unique documents than other databases as WoS, which is of particular interest when making a selection of information sources ( Sánchez et al., 2017 ).

In order to create a representative corpus of documents for investigation all records containing one or more of the keywords “technostress” or “techno-stress” in the fields abstract, title and keywords were selected from the Scopus database. The tracking formula in Scopus was: TITLE-ABS-KEY (technostress OR "techno-stress") AND PUBYEAR >1981 AND PUBYEAR <2018.

A total of 246 publications were found, obtaining relevant data from each of them (title, authors, abstract, keywords, journal, volume, number, pages, year, direction and author affiliation) along with received appointments until August 17 of 2018. The sample is restricted to the period 1982–2017.

According to the combined trends in productivity, documents, citations and total citation, the period was divided into four discrete subperiods for evolutionary analysis. The time slice process is useful to divide the data into different time subperiods, or time slices, to analyze the evolution of the research field under study ( Cobo et al., 2011b ). Four discrete periods were established that identify the most relevant research topics, emerging topics, declining issues, and peripheral issues. Temporary segmentation has been established considering two criteria. The first of these periods, 1982–2003, refers to the main scientific milestones when the first publications on technostress are carried out and have served as theoretical frameworks in subsequent studies. In the periods 2004–2011 and 2012–2014 scientific groups from the United States and Europe appear that changed the orientation of this area of science due to the great technological leap that changed the usual way of work and lifestyle. Finally, 2015–2017 reflects current work and trends in the field of techno-stress science. On the other hand, it has been contemplated that the documentary volume of each period is representative enough to allow the detection of research lines. Scopus includes 51, 40, 55 and 99 documents respectively in each period.

3.2. Bibliometric analysis tools

With Scopus analysis tool, the main authors, universities, journals and other antecedents that characterize the scientific production on technostress will be analyzed preliminarily, for example, impact assessed by h-index ( Hirsch, 2005 ). To conduct the evolutionary evaluations, SciMat v1.1.04 was used. This tool carries out the publications' content analysis, allows constructing maps of the scientific production, which allow monitoring a scientific field, delimiting the areas of investigation to understand its intellectual, social and cognitive structure, as well as to analyze its structural evolution. To carry out the scientific mapping production associated with the technostress, the recommended stages were followed by ( Cobo et al., 2012 ). SciMAT allows building science maps based on the co-occurrences analysis that characterize each publication. Also, SciMAT helps to analyze the structural evolution to construct scientific maps and visualize the evolution of a scientific area ( Cobo et al., 2012 ). The bibliometric tools may produce a higher level of analysis of research trends, productivity in different fields or scientific connection patterns ( Ellegaard and Wallin, 2015 ). The analysis carried out by SciMat is based on the methodology of associated words or co-words analysis developed in the 1980s by the École des Mines de Paris with Leximappe software tool, which greatly promoted the analysis of Science and thematic maps ( Callon et al., 1983 , 1986 ). The advantages of using SciMAT compared to other bibliometric tools (e.g., Bibexcel, CiteSpace, CoPalRed, IN-SPIRE, VantajaPoint, VOsViewer) have been demonstrated ( Cobo et al., 2011a ).

In Addition, the thematic networks between keywords were established through this tool SciMAT allows identifying the importance of each thematic network by the construction of strategic diagrams through measures of analysis of thematic networks: centrality and density ( Callon et al., 1991 ). The centrality measures the topic's degree of strength of external links with other topics; this measure allows interpreting the importance of a topic in the overall development of a field of investigation. The density measures the internal cohesion of all links between the keywords that describe the topic and provides an idea of the level of development of that topic ( Cobo et al., 2011b ; Martínez et al., 2015 , 2018 ). Through centrality and density, a field of research can be represented in a strategic diagram.

SciMat allows to characterize the importance of each thematic network with a scientific field that can be represented as a set of subjects classified in four categories and positioned on a two-dimensional space called strategic diagram ( Figure 1 ):

Right Upper Quadrant: Represents those subjects that are well developed and essential for the construction of the scientific field, since they represent a strong centrality and a high density. They are also called as "Motor themes" because they are fundamental for building the research area.

Upper left Quadrant: Represents those that correspond subjects well developed internally, but isolated from the rest of the subjects and have marginal importance in the development of the scientific field. They are called "Highly Developed and isolated themes" because they have little relevance for the field and these are specialized peripheric topics of the area.

Right lower Quadrant: Represents those basic themes that are important to the scientific field but are not well developed. They are called "Basic and Transversal themes" because they show relevant issues but with little development.

Left Lower Quadrant: Represents those that correspond to very few developed and marginal subjects with a low density and centrality. They are also referred to as "emerging or vanishing topics" because they include lack development and relevance topics.

The strategic diagram. Source ( Cobo et al., 2011b ):

4.1. Analysis

The first publications on technostress emerged in the year 1982. The journal Occupational Health & Safety , in its July 1982 issue, published the first article that included the concept of Technostress: “Technostress: Old villain in new guise” ( Polakoff, 1982 ). The same year, in October, The Personnel Journal published the article: "Managing Technostress: Optimizing the use of computer technology" ( Brod, 1982 ). These are the first studies that consider technostress as a modern disease caused by the inability of workers to use new technologies. In addition, these studies were realized based on observations of people's health effects.

In 1984, Craig Brod published the book "Technostress: The human cost of the Computer revolution" ( Brod, 1984 ). Brod's works have been citated in many articles, and it is explained by being the two oldest articles in this field, and because has been considered one of the pioneers in studying and conceptualizing and defining technostress. The research development on technostress has progressed slowly and it has been consolidated from the year 2011, where different lines of research have been developed on this subject. Figure 2 shows the number of publications and citations received between 1982 and 2017, and Figure 3 shows the publications and citations cumulative frequency in the period studied.

Published items and appointments for each year.

Accumulated graph of publications and citations.

Since 2007, the number of citations and publications began to grow steadily due to the publication of three articles (Figures. 3 and 4 ). These three articles are the most cited in the study of this topic during the last ten years. In 2007, the first article "The impact of technical stress on stress and productivity of roles" ( Tarafdar et al., 2007 ) was published in the Journal of Management Information Systems , the first quartile journal in the Information Science & Library Science categories of Journal Citation Reports (JCR). In 2008, the second article "The consequences of technostress for end users in organizations: Conceptual development and validation" ( Ragu-Nathan et al., 2008 ) was published in Information Systems Research , journal of the second quartile in the JCR category. These two works built and validated a measuring scale on technostress creators called Technostress Questionnaire that it has been used in many numbers of subsequent publications (e.g., Shu et al., 2011 ; Srivastava et al., 2015 ; Alam, 2016 ; Krishnan, 2017 ) as shown in Figure 4 . Finally, in 2011, the article "Technostress: Technological Background and Implications" ( Ayyagari et al., 2011 ) was published in a first quartile journal in the JCR category ( MIS Quarterly ). Figure 5 depicts the cumulative number of quotations from the scientific production on technostress. It is observed that since the year 2007, citations on conference papers and other sources begin to appear.

Citations average value per published document per year.

Accumulated citations by types of scientific work.

According to the combined trends of productivity, documents, citations and total citation, the period was divided into four discrete sub periods to conduct evolutionary analyses. Figures  6 , 7 , 8 , and 9 shows the number of citation-free publications for each year of the periods 1982–2003, 2004–2011, 2012–2014 and 2015–2017. It can be observed that from 1982-2003 ( Figure 6 ), where the first studies on technostress are carried out, the publications have served as theoretical frameworks in later studies (a). In the period 2004–2011 (Figures  7 and 8 ) citations take time to appear (approximately two years since an article is published), instead of in the period 2015–2017 ( Figure 9 ) citations appear in the same year of publication; therefore, the delay decreases from an article was published and quoted.

Publication citation evolution in period 1982–2003.

Publication citation evolution in period 2004–2011.

Publication citation evolution in period 2012–2014.

Publication citation evolution in period 2015–2017.

Table 1 presents the main published topics. It is appreciated that in the period 1982–2003, the scientific production on technostress was more oriented to the area of medicine and health. Technological innovations were incorporated into companies, and individuals had to adapt to these innovations and learn new skills to use them. Therefore, it is understandable that the interest of scientists in this period was analyzing the connection between the effects of the human health with the use of new technologies.

Topics published in indexed scientific documents 1982–2017.

Periods 2004–2011 and 2012–2014 were characterized because technostress publications are no longer aimed at studying the effects of technology focused on human health. "Computer Science" and "Social Sciences" appear in the first places.

Scientific groups from the United States and Europe changed the orientation in these periods. At that time, the global population entered the moment when most people have integrated into their life and work different ICT technologies. The development of technologies compared to the past period took a big jump; internet, social networks, smartphones, office automation software, and new business information systems changed the usual way of working and lifestyle ( Stadin et al., 2016 ; Haddadi Harandi et al., 2018 ).

In the last period, 2015–2017, the subject "Computer Science" as well as the previous two periods appears in the first place. In Addition, it is appreciated that the topic "Business, Management and Accounting" appears in second place and covers 10% of all the publications. "Medicine" and "Psychology" together cover 15% of all publications during this period.

Globally, technostress-related scientific production focuses on 3 Regions: North America (mainly the United States with 28% of production), European Union with 29% (notably Germany with 9%), East Asia and South-East (mainly Japan and China with 12% and 9% respectively).

Table 2 shows the most relevant publications, with more than 100 citations, are related to "Computer Science", "Business Management & Accounting" and "Psychology". Regarding to the number of citations stand out of study about used the person-environment fit model as a theoretical foundation ( Ayyagari et al., 2011 ). In another study, the authors used the transaction-based stress model as a theoretical lines ( Ragu-Nathan et al., 2008 ). It is also worth noting that, according to Yin et al. (2014) the most of the modern technostress research is based on the technostress questionnaire developed by Ragu-Nathan et al. (2008) .

Publications with more than 100 citations in Scopus between 1982-2017 (August 17, 2018).

Psychology, as a topic related to technostress, has been growing as research development area. As an example, the research "The Dark side of smartphone usage: Psychological traits, compulsive behavior and technostress" ( Lee et al., 2014 ), published in the journal Computers in Human Behavior . Researchers used the view from personality theories to explain compulsive behavior.

Table 3 exhibits the most used keywords in the articles in the period 1982–2017. Three groups of words are identified. All terms that connect with stress add 230 repetitions in all publications analyzed (technostress/techno-stress, stress, mental-stress, stress-psychological). Another group of words focuses on the human being (human, adult, female, male, human) which add up to 146 repetitions. A third group is composed of words related to technology (information systems, technology, information-and-communication technology) which add up to 88.

Number of keyword occurrences greater than 15 repetitions (August 17, 2018).

Related to authoring tendencies, authors who contributed to more than ten documents in all periods were identified ( Table 4 ). Noteworthy that most of the scientific production on technostress is generated by groups of authors that change their position in each publication. The authors with more than ten documents published, therefore with higher productivity in this field, are: Monideepa Tarafdar, Professor of information systems, affiliated to Lancaster University, England; and Professor Nobuyo Kasuga, member of the Shibaura Institute of Technology, Japan.

Top researchers on technostress and its h-index generated through SciMat in period 1982–2017.

period = 1982–2017.

In the case of h-index, Professor Monideepa Tarafdar presents the major h-index (h = 23), followed by Emeritus Professor T.S. Ragu-Nathan, from the University of Toledo in the United States, that holds an h-index = 22. Both researchers co-authored several publications on technostress. In the third place, with an h-index = 21, the Professor Ofir Turel, who belongs to the Department of Information Systems and Decision Sciences of the California State University Fullerton, United States. Table 4 presents that despite Nobuyo Kasuga holds second place in published documents, his h-index is the lowest since each of his publications has between one and two citations.

Journals with the most significant number of research papers published on technostress are presented in Table 5 . The journal with the largest number of publications is Computers in Human Behavior , which highlights the work presented by Lee et al. (2014) . The journal with the greatest impact factor is the Information Systems Journal , which highlights the article "Technostress: negative effect on performance and possible mitigations" ( Tarafdar et al., 2015 ).

Journal with the largest number of publications related to technostress (August 17, 2018).

Table 6 exhibits articles with more than 50 and less than 100 citations in the period studied. Works with the highest number of citations are published in the Journal of Occupational and Environment Medicine ( Berg et al., 1992 ; Arnetz and Wiholm, 1997 ).

Top ten papers with more than 50 and less than 100 citations in the period studied.

Cit. = N° citations (1982–2017).

4.2. Thematic analysis on the scientific production of technostress using SciMat

The production of technostress thematic analysis, in the superposition map ( Figure 10 ), it can be seen the co-appearance continuity of the terms that make up the titles of scientific documents indicating the number of terms per period and how these are repeated in the following period. Each circle represents a period of scientific production. The central numbers show the total terms of the period, the numbers on the oblique arrow up indicate the terms that did not have co-occurrence in the following period; those on the down arrow indicate the new terms that co-appeared in the next period and those of the horizontal arrow show the total terms that continued to co-appear, expressed in proportion in the parentheses. As can be seen in Figure 10 , in those four periods there was a similar behavior, with an average level of thematic overlap.

Therm overlapping map in the scientific production of technostress, indexed in Scopus the period 1982–2017. Data were retrieved on August 17, 2018 and processed in SciMat V. 1.1.04.

4.3. Analysis of research topics and thematic evolution

To analyze the most relevant topics related to technostress scientific production, a strategic diagram is presented for each period ( Figure 11 ). The size and number within the sphere are proportional to the set of documents linked to the particular research topic.

Strategic diagram of the scientific production on technostress, indexed in Scopus, for periods 1982–2003, 2004–2011, 2012–2014 and 2015–2017 (The quadrants correspond to Figure 1 ).

First period: 1982–2003. During the first 22 years the field revolves around three subjects ( Figure 11 ). According to the topic's performance measures indicated for this period in Table 7 and Figure 11 , "Human" stands out, who gets the largest number of documents reaching 300 citations and corresponds to the theme of greater centrality and density, consolidating as a motor topic. The theme "Adrenaline" appears as a driving theme, presenting only one publication in the period, but with a high number of citations. The theme "technostress" is categorized as emergent, presenting three publications with 7.3 average citations.

Performance of topics for technostress in four analysis periods.

Second period: 2004–2011. During these eight years, the field consists mainly of two motive themes "Human" and "Stress" and a basic and transversal theme "Surveys". Unlike the previous period, documents related to technostress revolves around six topics. The theme "Human" is consolidated as a driving theme; however, it decreases its number of documents from 6 to 2 in comparison with the previous period, but its average number of citations increased. The subject "Surveys" appeared in eight documents which are highly cited. The theme "Stress" appears as the driving theme and is the second most cited theme of the period.

Third period: 2012–2014. During this two-year period, documents related to technostress revolves around eight themes. The theme "Information Technology" appears as the driving theme and is the most important according to performance indicators; however, the theme "Human" despite having only two publications presents a higher average of citations. The theme "Stress" which in the previous period appeared as the driving theme, now appears like a basic and transversal theme. The topic "Structural-Equation-Modeling" appears as a driving theme, possibly because in the previous period scales were developed to measure the technostress.

Fourth period: 2015–2017. The field revolves around nine subjects. The themes "Surveys" and "Stress" consolidated as basic and transversal themes; "ICT" also appears as a transversal theme. "Health-Care" and "Structural-Equation-Modeling" appear as motive issues. Also "Organizational-Commitment" appears with an interesting average of citations. In this period, technostress studies tend to analyze the effects of technological stress associated with health care and commitment to the organization.

Figure 12 presents the thematic evolution of the investigated periods. The first column of nodes depicts the period of articles that were published between 1982 and 2003, which represent 21% of all documents analyzed. In this period the term technostress was formulated, and science was focused on analyzing the effect of stress associated with technology on human health. Main researches of this period were carried out by researchers from Japan and the United States. The leading journal where these works were published was the Japanese Journal of Psychosomatic Medicine . The performance of each topic in the period can be seen in Table 7 .

Thematic evolution for periods of study.

In the second period, between 2004 and 2011, 16% of all works investigated were presented. Main topics were centered on the human being, stress, and the computer, which are connected with the subject related to the human being of the first period. The technostress theme of the first period evolved into research related mainly to the human being and stress and measuring instruments.

The third and fourth periods, comprised between 2012-2014 and 2015–2017, which represent approximately 22% and 40% respectively of all published works on the subject area, start to develop measurement instruments that connect stress with information technologies and information overload. Most of these works developed theoretical models that were validated empirically through the technique of structural equation models. The study of stress associated with technology has given rise to works that relate stress to role ambiguity and its effect on health care (fourth period).

It is observed that in the last period researches are focused on the application of measuring instruments that strongly connect with information technologies, smartphones, role ambiguity, and health care. Likewise, the study of stress has given rise to investigations about the effect of information overload on human health. In this period, studies focused on organizational commitment related to technological support and the use of information technologies appear. Likewise, studies related to human health begin to be relevant, since globalization has democratized technology. The use of technology has become more frequent in organizations and people and has started to be observed within organizations, people's adverse effects related to information overload and the use of ICT.

In Figure 13 it is possible to observe how all the themes associated with the technostress are connected. In Figures  12 and 13 it can be seen that the scientific production investigated focuses on analyzing different factors associated with ICT that generate technostress and psychosocial risks in workers. There are also investigations that perform sociodemographic studies to determine how various factors such as age, gender, level of education, among others, can be related to technostress.

Thematic network associated to the topic technostress.

In the last two periods, the use of methodologies such surveys and questionnaires have multiplied to analyze, through structural equations, how different variables are correlated with technostress, such as self-efficacy, work overload, technological overload, role ambiguity, work at home, privacy invasion, job insecurity, job satisfaction, individual performance and productivity, technological dependence, innovation, use of social networks, mobile devices, technostress inhibitors, labor exhaustion, work environment, among others.

5. Discussion and conclusions

After a systematic literature review on technostress, the results present that the most influential works in the field of research correspond to those developed in the period 2004–2011. These correspond to the work of Ragu-Nathan et al. (2008) and Ayyagari et al. (2011) . Both studies applied questionnaires to ICT professionals and end-users in the United States. These works developed and validated theoretical measures and constructs that have served as the basis for modern research.

Regarding the most prolific authors standing out with more than ten documents: Monideepa Tarafdar, Nobuyo Kasuga and Qiang Tu, from the United Kingdom, Japan, and the United States, respectively. Authors with higher h-index: Monideepa Tarafdar from Lancaster University, T.S. Ragu-Nathan of the University of Toledo and Ofir Turel of California State University.

Journals with the highest number of published works correspond to Q1 journals: Computers in Human Behavior (United Kingdom), Information Systems Journal (United Kingdom) and Telematics and Informatics (Netherlands).

Technostress is an emerging research field with little fragmentation. The results show that the research field is in evolution and has not yet reached a state of maturity. Fifteen fundamental thematic areas have been identified with little relation between them. Initially, the mutual connections were not very related; however, in the period 2015–2017 these connections have been more prevalent. The analysis has shown that “Computer Science”, “Business, Management and Accounting”, “Social Sciences” and “Medicine” are significant themes. “Medicine "was the most significant topic in the period 1982–2003, and in the last period is the fourth. Researchers' tendency has been marked by investigating the stress caused by the use of ICT which affect the health of the human being and that generate stress and psychosocial risks in workers.

In general, technostress research has been developed as new technologies appear and advance in their use, leading to the need to know its repercussions on people's health at work (e.g., Arnetz and Wiholm, 1997 ; Brod, 1984 ; Weil and Rosen, 1997 ), in working groups, in organizations and in society in general (e.g., Brillhart, 2004 ; Tarafdar et al., 2007 ; Ayyagari et al., 2011 ; Tarafdar et al., 2015 ; Fischer and Riedl, 2017 ). Literature analysis has reported that the effect of different factors and sociodemographic variables associated with ICT such as age, gender, level of education, among others, can be related to technostress and its consequences on job outcomes such as organizational commitment, information overload, role ambiguities, invasion of privacy, job insecurity, job satisfaction and exhaustion, individual performance and productivity, technological dependence, among others.

Most research on technostress has been carried out in organizational settings, studying employees in specific sectors. In this work the publications with more citations correspond to works that incorporate the Technostress Questionnaire developed by Tarafdar et al. (2007) (e.g., Ragu-Nathan et al., 2008 ; Tarafdar et al., 2011 , 2010 ).

Technostress research has been evolving and has spread to other domains, adopting measures and terminologies to the relevant contexts. The impact of new mobile technologies and social communication tools to produce technostress in people has not been explored in depth. For example, Tarafdar et al. (2011) developed and validated a scale to measure anxiety for the use of the mobile computer; Lee et al. (2014) examined technostress derived from the use of smartphones, exploring its association with various psychological traits and compulsive use, as well as the registry of differences between users of smartphones and traditional mobile phones; in this line, other authors also examined the consequences of technostress mobile (e.g., Hung et al., 2015 ; Yin et al., 2014 ; Yu et al., 2009 ).

Other studies have examined technostress based on social network use, exploring both techno-stressors such as the degree of use and the number of friends, as well as consequences such as social overload and exhaustion ( Maier et al., 2015b ); It has also been explored how the use of social networks affect the performance of school work and happiness ( Brooks, 2015 ), or how it affects the elderly specifically ( Nimrod, 2018 ). Also, the literature has extended in the realization of critical analyzes arguing that in contrast to the negative consequences, technostress can generate positive effects in the improvement of efficiency and innovation ( Tarafdar et al., 2019 ).

Regarding research methods and data analysis, scholars have mainly carried out cross-sectional studies. They have used self-administered surveys, the technique of structural equations to validate their models and test their working hypotheses. In particular, the use of this technique began to increase as of 2005 and more frequently from 2011 onwards.

The thematic evolution reflects that the studies related to this field of science have developed slowly. It is appreciated that since 2016, there has been an increase in publications and citations. The subjects with more citations correspond to those included in the first three periods: "Surveys", "Human", "Stress", "Information technology" and "Smartphones" methods ( Fischer and Riedl, 2017 ).

In almost 40 years of research on technostress, some issues have not been addressed yet or are poorly developed. Technostress is a promising field of science to conduct studies related to different business environments, different types of workers and professions (including disabled). Also, studies can be performed through different modalities such as face-to-face, flexible, remote work, and homework, and various technologies and social networks. Besides, it is a field that facilitates studies to all managerial levels and non-working population as students, with different labor and sociocultural contexts that involve countries outside the developed or developing economies.

As evidenced in the bibliometric analysis of this work psychosocial research in the field of the introduction and use of ICTs is growing. In developing a framework of ICT demands and supports, there are several important general models of work stress ( Day et al., 2012 ). The theoretical models used in the works aim to describe what happens during the stress process and are based on theories that study human behavior rooted in social psychology ( Sonentag and Frese, 2013 ; Maier et al., 2015a ), such as the Theory of Reasoned Action and its extension ( Effiyanti and Sagala, 2018 ), the Socio-Technical Theory and Role Theory ( Tarafdar et al., 2007 ), Social Cognitive Theory ( Koo and Wati, 2011 ; Shu et al., 2011 ), Person-Environment Fit Model ( Ayyagari et al., 2011 ; Yan et al., 2013 ; Saganuwan et al., 2015 ), Transaction-Based Model of Stress ( Ragu-Nathan et al., 2008 ; Hung et al., 2011 ; Fuglseth and Sorebo, 2014 ; Lei and Ngai, 2014 ; Chandra et al., 2015 ; Fischer and Riedl, 2017 ), Job Demands-Resources Model ( Salanova et al., 2014 ; Wu et al., 2017 ), Technology Acceptance Model ( Maier et al., 2013 , 2015b , 2015c ), among others. Despite this, there are studies that do not have an explicit theoretical basis, nor do they have a theoretical basis that belongs to the organizational level.

The researchers who have studied organizational behavior describe the technostress as a collection of interrelated psychosocial constructions that negatively impact employees. Mentioning, in addition, that this line of research focuses on the transactions of employees at work in a de-balance situation that affects the results of the organization ( Atanasoff and Venable, 2017 ). We consider it important that new studies on this phenomenon ben addressed from different theoretical and methodological approaches.

Attitudes play an important role in the adoption of new technologies. Individuals do not necessarily accept technology based on their traits, but in relation to perceived benefits. For this reason, we consider that future studies could addressed research on the Theory of Reasoned Action. This theory pretends predicting the human behavior by linking attitudes, social pressure, and behavior ( Ajzen and Fishbein, 1980 ).

In the area of ICT, the impacts of attitude and norm subjective differ depending on whether the use of technology is voluntary or not. This background can lead to new researches that addresses his research on the Theory of Planned Behavior (TPB). This theory relates behavior, intent, attitude, subjective norm, and perceived behavior control. This theory posits that the intention is determined by the attitude of the individual, the degree to which a person has a favorable or unfavorable assessment of the behavior in question, the subjective norm and the perceived social pressure to perform the conduct or not ( Ajzen, 1991 ). TPB includes a third predictor of intent called perceived behavior control, which reflects an individual's perception that there are personal and situational impairments to behavior performance ( Grandón and Ramirez-Correa, 2018 ). This theory intent is the best determinant of behavior, but attitude, subjective norm and perceived control are those that facilitate understanding of the factors that explain actions ( Rao and Troshani, 2007 ). The TPB also explains almost any human behavior and not just the use of technological innovations ( Ajzen, 1991 ).

Today, because of the innovation caused by telework, new researches could address Socio-Technical Theory and study how this change in the way they work impacts the social structure of workers and their families ( Trist and Bamforth, 1951 ). Likewise, measure the effect of new variables that allow to inhibit or decrease the effects of technostress in the work at home. In the same vein, studies based on Stress Theory and Coping could measure the effect of the continued use of videoconference platforms and collaborative work platforms and measure if active breaks in telework can inhibit the effect of technostress caused by this modality.

In general, we have detected empirical, cross-cutting, and self-reporting studies. We recommend the conduct of new longitudinal studies that measure the effect of the use of ICTs, over a prolonged period, incorporating different neuroscientific techniques to expand the methodological framework in the field of cognitive and behavioral neurosciences. There are few cross-national and cross-country studies. This field of research reflects interesting opportunities for research related to experiments and neuroscience.

As limitations indicate that only the SCOPUS database was used and the works up to December 2017 were analyzed, however, a formula for bibliographic search is presented and therefore this work can be repeated and updated. The fact that by using a single concept, it is possible that studies related to the topic analysed, but in which the concept of "technostress" was not specifically mentioned, have been left out of the analysis. Another limiting factor of this research is that the word co-occurrence method was used for the analyzes and probably with another methodology (for example of common references) other results could come out, but in any situation the main works and their effect on this theme. There are few cross-national and cross-country studies. This field of research reflects interesting opportunities for research related to experiments and neuroscience.

We analyzed classic works that are fundamental in the formation of this area of science. For future research they may focus on analyzes of works published in recent years and check our conclusions and main evolutionary steps in this area. Also, it is possible to implement works using quantitative indices to describe the contribution of certain countries to the overall development of the technostress scientific field ( López-Muñoz et al., 1996 , 2008 ).

Modern literature has been incorporating new concepts related to positive stress. The techno-eustrés cause satisfaction, joy, increase vitality, produce no imbalances and help facilitate people's decision-making. Techno-eustres it originates due to the emergence of new challenges and opportunities, allowing them to develop their skills. If technologies are properly used, they would be tools that facilitate and enable humans to balance and live with new ICTs by enabling them to achieve new goals and challenges, improving their performance and integrating faster into the use of new technologies. Contrary to the dominant belief that stressors are always harmful stress can help people improve their work, motivate them at work and keep them on alert.

A solution to technostress is the prevention of this through tools that allow to inhibit and/or reduce the effects of stress caused by the technologies. We recommend that organizations implement coping strategies through the theoretical concept of technostress inhibitors. The literature reports that inhibitors have the potential to decrease the stress levels created in workers by the use of ICTs, which will, likely, increase their job satisfaction by providing advantages to organizations.

Additionally, it is necessary to determine the position of this research topic in connection with other sciences and for that it is recommended to carry out an analysis of the common references of the works to find out with which sciences the field of technostress is connected.

Declarations

Author contribution statement.

Cristian Salazar-Concha: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Pilar Ficapal-Cusí: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.

Joan Boada-Grau, Luis J. Camacho: Analyzed and interpreted the data; Wrote the paper.

Funding statement

This work was partially funded by the Vicerrectoría de Investigación, Desarrollo y Creación Artística of the Universidad Austral de Chile, Chile.

Data availability statement

Data will be made available on request.

Declaration of interests statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

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Leadership and technostress: a systematic literature review

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• Tim Rademaker   ORCID: orcid.org/0000-0003-4709-0237 1 ,
• Ingo Klingenberg   ORCID: orcid.org/0000-0002-8693-4140 1 &
• Stefan Süß   ORCID: orcid.org/0000-0001-7454-4092 1  

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With the growing use of digital technologies at work, employees are facing new demands. Digital technologies are also changing how leaders and followers interact. Leadership must adapt to these changes and find ways to reduce the demands of digital work for their followers so they maintain their capacity for and motivation to work. Against this background, we analyze the impact leadership has on technostress by conducting a systematic literature review. An electronic search was based on 13 databases (ACM Digital, AIS eLibrary, APA PsychInfo, EBSCO, Emerald Insight, Jstor, Pubmed, SAGE, ScienceDirect, Scopus, Taylor & Francis Online, WISO, and Web of Science) and was carried out in October 2023. We identified 1725 articles—31 of which met the selection criteria. Thirteen more were identified in a backward search, leaving 44 articles for analysis. The conceptual analysis reveals that empowering and supportive leadership can decrease follower technostress. Leadership that emphasizes high availability expectations, task orientation and control can increase technostress and technostress-related outcomes. Furthermore, leadership’s impact on follower technostress is influenced by how ICTs are being used to convey leadership. We synthesize seven analytical themes of leadership among the technostress literature and derive them into the three aggregated dimensions which serve as the foundation of a conceptual model of leadership’s impact on follower technostress: technostress-increasing leadership, technostress-decreasing leadership, and technology-enabled leadership. Furthermore, we formulate avenues for future research.

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1 Introduction

Work is constantly changing, but there are some technological developments that have groundbreaking effects on work, like the steam engine or the assembly line. Information and communication technologies (ICTs) can join the ranks of these technologies when it comes to changing work (e.g., Kamarul Bahrin et al. 2016 ). Like the other technologies, the digital penetration of the workplace bears great potential for improvement of work, as the use of ICTs can enhance productivity and flexibility with an increasing number of tasks that had been done offline moving to the digital sphere (Schmidtner et al. 2021 ; Vargo et al. 2021 ). However, digitalization also poses risks for employees, including increased strain by blurring boundaries between the work sphere and private life or by overwhelming employees with the inherent complexity of digital technology (Ragu-Nathan et al. 2008 ). The mechanisms of strain triggered by digital technology—often termed technostress —can have a significant impact on employees’ health, as technostress is associated with emotional exhaustion (Brown et al. 2014 ; Kim et al. 2015 ; Turel and Gaudioso 2018 ), burnout (Leung 2011 ; Srivastava et al. 2015 ), and depression (Torales et al. 2022 ). Besides workers’ health, work-related factors like productivity (Tarafdar et al. 2007 , 2011 ), commitment and engagement (Ragu-Nathan et al. 2008 ; Srivastava et al. 2015 ), and job satisfaction (Ragu-Nathan et al. 2008 ; Suh and Lee 2017 ) can be negatively affected by technostress.

Researchers ascribe leadership—understood here as “a process whereby an individual influences a group of individuals to achieve a common goal” (Northouse 2019 )—an increasingly important role in the context of digitalization (Cortellazzo et al. 2019 ) and technostress (Fischer and Riedl 2017 ; Salazar-Concha et al. 2021 ). According to Cortellazzo et al. ( 2019 ), leaders take an active part in the digitalization by supporting and motivating followers, who face challenges like the ongoing requirement to learn how to use new technologies. Leadership itself is also affected by digital technologies. As teams become locally decentralized and increasing amounts of work are done outside the traditional office environment, ICTs influence the interactions between leaders and followers. Leaders should adapt to these changes to be able to lead their followers through the ongoing change process related to digitalization and maintain their capacity for and motivation to work (Cortellazzo et al. 2019 ). Not incidentally, in view of the potential impact of technostress on employees’ health, health management has also become an important part of successful leadership (Schwarzmüller et al. 2018 ).

Empirical studies (e.g., Felfe et al. 2014 ; Weiß and Süß 2016 ) and literature reviews and meta-analyses (Harms et al. 2017 ; Skakon et al. 2010 ) suggest a link between leadership and followers’ health and leadership and variables that affect health, such as followers’ self-efficacy (Perko et al. 2014 ), which can buffer technostress and technostress-related outcomes (e.g., Shu et al. 2011 ; Yener et al. 2021 ). Further, there are empirical studies that analyze the relationship between leadership and technostress (Çiçek and Kılınç 2021 ; Harris and Marett 2009 ). Still, previous reviews that address technostress do not focus on the impact of leadership (Agogo and Hess 2018 ; Borle et al. 2021a ; La Torre et al. 2019 ; Saganuwan et al. 2015 ; Sarabadani et al. 2018 ), or deal with it only in passing (Berg-Beckhoff et al. 2017 ; Gualano et al. 2023 ; Marsh et al. 2022 ; Pflügner 2022 ; Rohwer et al. 2022 ; Shirmohammadi et al. 2022 ). Similar blind spots in the systematization of the connection between leadership and technostress are evident in the leadership literature, as literature reviews and meta-analyses that deal with leadership and digitalization often miss considerations related to followers’ health (e. g. Jakubik and Berazhny 2017 ) or deal with the relationship between leadership and well-being or health without considering the role of digital technology (Harms et al. 2017 ; Inceoglu et al. 2018 ; Kuoppala et al. 2008 ; Montano et al. 2017 ; Skakon et al. 2010 ). Marsh et al. ( 2022 ) integrative review of the dark side of digital work is an exception, as they identify two studies that address the role of transformational leadership as a resource for coping with technostrain (Salanova et al. 2013 ) and the quality of leader-member exchange as a moderator of the relationship between technology overload and work-family conflict (Harris et al. 2013 ). Given these initial findings, the authors call for further research on the role of leadership “as potential dark side effects moderators” (Marsh et al. 2022 , p. 13).

Against this background, a systematic examination and elaboration of the relationship between leadership and technostress is necessary to systemize the link between leadership and technostress; thus, enriching technostress research by means of systematic insights into the effect of leadership on technostress and strengthening the technostress perspective in the leadership literature. Given the increasing prevalence of digital technology in the workplace, with the COVID-19 pandemic catalyzing this process (Amankwah-Amoah et al. 2021 ), and the associated risks of technostress, understanding the conditions that influence the occurrence of technostress and its consequences is of both scientific and practical value. Therefore, the aim of our study is to identify and analyze research regarding the influence of leadership on the emergence of technostress and its outcomes in the workplace. To achieve this goal, we conducted a systematic literature review. The well-structured method allows us to screen, collect, and analyze relevant studies systematically and reliably (Atkinson et al. 2015 ; Siddaway et al. 2019 ; Snyder 2019 ) and to provide avenues for future research in leadership and technostress based on an overview of the current literature.

Our review offers several contributions to research and practice. First, as most existing studies only provide insights into the effects of certain aspects of leadership in certain digital settings, a summary of these studies is a logical next step in establishing the status quo and connecting these fragmental insights to form a cohesive picture of how leadership affects followers’ health in a digitalized work environment. Hereby we answer the call of Sarabadani et al. ( 2018 ) to consider new inhibitors of technostress identified in the technostress literature by systematically collecting and analyzing studies on leadership’s influence on technostress. Second, we derive a conceptual framework of leadership’s impact on follower technostress. Third, the limitations and gaps in the current research identified in the review can be a foundation for future research on the adaption of leadership to the challenges of digitalization and can provide researchers easy access to existing knowledge in this research area (Siddaway et al. 2019 ). The remainder of the study is structured as follows: First, the conceptual background on technostress and leadership and derivations of the research questions that guide this review are provided in Sect.  2 . Section  3 presents the methodological approach applied in conducting the systematical literature review. Section  4 presents the results of the analysis. These serve as the basis for the discussion and the derivation of avenues for future research in Sect. 5 . The study concludes with limitations (Sect. 6 ) and a short conclusion (Sect. 7 ).

2 Conceptional background and research questions

2.1 technostress and the transaction-based model of stress.

As early as 1982, Brod identifies the risks entailed in digitalization by introducing the phenomenon of technostress as “the inability of an individual or organization to adapt to the introduction and operation of new technology” (Brod 1982 ). Brod offers this concept even before the wide use of personal computers or the commercial use of the internet. The digital penetration of the workplace has continued ever since, and stress induced by ICT has become increasingly relevant in research, as current reviews and bibliometric analyses of technostress point out (Fischer and Riedl 2017 ; Salazar-Concha et al. 2021 ). As new technology emerged, the definition of technostress also changed, with the most recent and widely accepted definition (La Torre et al. 2019 ) of technostress being “stress experienced by end users of information and communication technologies” (Ragu-Nathan et al. 2008 ). This definition is also applied in this work.

According to the transaction-based model of stress (Lazarus and Folkman 1984 ), stress is the result of a transaction between individual and environmental dispositions that occurs in two appraisal processes that precede coping (Lazarus 2012 ). Several central publications on technostress (e. g. Bondanini et al. 2020 ; Fuglseth and Sørebø 2014 ; Ragu-Nathan et al. 2008 ; Tarafdar et al. 2010 ) use the transaction-based model of stress as a theoretical framework. In the primary appraisal process, the individual assesses the extent of demands an environmental situation may present, and in the secondary appraisal process, the individual assesses its coping options in dealing with these demands (Lazarus 2012 ). Applied to the context of technostress, the focus of the primary appraisal is on the transaction between digital technology and the technology-user, evaluating whether digital technologies present a potential demand. The second appraisal process represents a consideration between the user’s options for coping and these digital demands. The transaction-based model of stress served in several central publications on technostress (e. g. Bondanini et al. 2020 ; Fuglseth and Sørebø 2014 ; Ragu-Nathan et al. 2008 ; Tarafdar et al. 2010 ) as a theoretical framework.

Digital technologies in the professional context can be perceived as demanding in many ways, but five typical stressors established by Ragu-Nathan et al. ( 2008 ), often referred to as technostressors , are well established in technostress research and provide the conceptual basis for many articles (Grummeck-Braamt et al. 2021 ): (1) techno-invasion, which describes digital technology’s potential to cross the boundary between work and personal life; (2) techno-overload, which refers to digital technology’s potential to accelerate work and increase workload; (3) techno-insecurity, which refers to digital technology’s potential to create feelings of insecurity about one’s own capabilities in dealing with technology and the fear of being replaced by technology or more qualified employees; (4) techno-uncertainty, which refers to the fast pace of digital technology, with its frequent updates and system changes that can overwhelm its users and (5) techno-complexity, which refers to the complexity inherent in ICT that can evoke feelings of inadequacy (Ragu-Nathan et al. 2008 ).

Following the transaction-based model of stress, even when technology is perceived as a stressor, strain does not necessarily result, as personal dispositions like individuals’ traits or states can influence their appraisal of technology or the resources they have to cope with these stressors. Previous studies identify individual factors like techno-affinity and techno-efficacy, age, gender, and resistance to IT-induced change (Koo and Wati 2011 ; Shu et al. 2011 ), as well as contextual factors like task complexity (Koo and Wati 2011 ), embeddedness in ICT-mediated communication networks, centralization of power, and corporate propensity to innovate (La Torre et al. 2019 ), literacy facilitation (Califf and Brooks 2020 ), and involvement and innovation support (Califf et al. 2015 ) as factors that can influence individuals’ appraisal of digital technology as a stressor and moderate the impacts it has.

2.2 Leadership and stress

The diverse history of leadership research is reflected in the multitude of definitions of leadership. According to Northouse’s ( 2019 ) definition of leadership, which is widely used in leadership research and comparatively inclusive, leadership can be understood as “a process whereby an individual influences a group of individuals to achieve a common goal”. Given this understanding, leadership is seen as a process that is not unilateral, as the leader’s behavior is also influenced by his or her followers (Gesang and Süß 2021 ; Northouse 2019 ) and can also take place in groups, so leadership can impact followers even if they are not directly affected. Harris et al. ( 2013 ) find empirical evidence that employees who hear rumors about their leaders’ directing abuse toward a third-party report higher levels of work frustration and lower levels of perceived organizational support. Leadership is also directed toward a common goal, so leaders seek to influence their followers to alter their attitudes, values, motivation, and behaviors (Northouse 2019 ). Leaders can employ a wide range of behaviors to exert influence, such as providing support and information and motivating and empowering followers (Bass 1999 ; Kotter 2001 ).

Former research on leadership categorizes leadership into task- and relation-oriented leadership behavior (Yukl et al. 2002 ). Task-oriented leadership behavior captures leadership that focuses on completing a task efficiently and reliably by planning and setting priorities, goals and rules, and monitoring followers (Yukl 2010 ). Leadership styles that fit into task-oriented leadership are for instance a transactional leadership style (DeRue et al. 2011 ) and an authoritarian leadership style. Relation-oriented leadership behavior focuses on the relationship between followers and leaders by means of such behaviors as supporting and encouraging followers, coaching, and consulting followers in decision-making (Yukl 2010 ). Yukl et al. ( 2002 ) expand this taxonomy by adding change-oriented leadership behavior, and DeRue et al. ( 2011 ) do so by adding passive leadership behavior. According to Yukl ( 2010 ), change-oriented behavior aims at implementing changes in organizations using transformational, inspirational, and charismatic leadership. DeRue et al. ( 2011 ) define passive leadership behavior as absent, inactive, or active only under certain circumstances, e. g. laissez-faire leadership. The taxonomy of leadership into task-oriented, relation-oriented, change-oriented, and passive leadership behavior covers leadership, as most other taxonomies of leadership can be mapped across these categories (DeRue et al. 2011 ).

Leadership research focuses primarily on the positive aspects of leadership. Thus, most taxonomies of leadership do not consider deviant and hostile forms of leadership, and DeRue and colleagues’ taxonomy is no exception. Therefore, destructive forms of leadership can be captured drawing on Schyns and Schilling’s ( 2013 ) definition of destructive leadership as “a process in which over a longer period of time the activities, experiences and/or relationships of an individual or the member of a group are repeatedly influenced by their supervisor in a way that is perceived as hostile and/or obstructive”.

Previous studies on leadership’s effect on stress show a connection between some leadership styles and behaviors with stress perceived by followers. Leadership can have a direct impact on a strain by being a stressor itself or an indirect impact by buffering or increasing the effects or outcomes of other stressors. For instance, task-oriented leadership behavior that is characterized by high levels of monitoring and low levels of autonomy for followers, as is typical of authoritarian leadership styles, can increase followers’ perceived work stress (Kang-Hwa and Hung-Yi 2018 ) and decrease their well-being and emotional regulation (Chu 2014 ). On the opposite, the total absence of control, as occurs with passive or laissez-faire leadership styles, can also cause stress, as this leadership style is often associated with role conflict, work fatigue (Barling and Frone 2017 ; Skogstad et al. 2007 , 2014 ; Vullinghs et al. 2020 ), and workplace bullying (Dussault and Frenette 2015 ; Skogstad et al. 2007 ). As for transformational leadership, that aims at initiating changes through inspiration, intellectual stimulation, individualized consideration and idealized influence (Avolio and Bass 2004 ; Bass 1999 ; Bass and Avolio 1994 ), results are less clear. Followers that were led by leaders with high levels of transformational leadership, reported fewer effort-reward imbalances on the one hand (Weiß and Süß 2016 ) but also reported increased job stress on the other hand (Parveen and Adeinat 2019 ).

Leadership behavior can have an indirect impact on how employees experience stressors and on their coping options. Supervisors who provide feedback can often ameliorate stress-related outcomes by helping employees improve their ability to withstand stressors (Demerouti et al. 2001 ). Feedback can also clarify role expectations, thereby reducing role conflict (Ashford and Tsui 1991 ), and can be experienced by employees as a form of esteem (Brooks et al. 2019 ) that can be a buffer against stress from demanding work (Lehr et al. 2009 ). However, feedback that is based on corrective criticism can increase emotional exhaustion and can be identified as a cause of chronic stress (Diebig et al. 2016 ). The interpersonal relationship and the degree of information exchange between leaders and followers are also identified as valuable resources for employees in coping with work demands, as employees who perceive high levels of social support from their supervisors report lower levels of work stress (McCalister et al. 2006 ) and burnout (Charoensukmongkol et al. 2016 ). Other sources of stress, such as work-family conflict, role conflict, and workplace bullying are also reduced by supervisor support (Hauge et al. 2011 ). A good leader-member exchange quality is also associated with lower levels of role stress in some studies (Jian and Dalisay 2018 ; Nelson et al. 1998 ) and with lower levels of stress and burnout (Harms et al. 2017 ). Previous studies highlighted that digital technologies do significantly change work on several levels which comes along with new demands for followers (see Sect.  2.1 ). As the effectiveness of leadership behavior does depend upon the situation in which it is applied (as theories of situational leadership as the contingency theory (Fiedler 1964 ) or the path-goal theory point out (House 1996 )), it remains to be seen whether these insights can be transferred to the technostress context.

2.3 Research questions

A systematical literature review requires clearly defined research questions that set the direction of the synthesis and serve as the foundation of the search strategy (Hiebl 2021 ). As structure is necessary to understand the mechanisms between leadership and technostress and to acquire a sound overview of the extant research and what it lacks, we conducted a literature review to organize the literature, synthesize leadership’s influence on technostress, and set new guidelines for future research.

To reach these objectives, we first identify the current status of technostress research that addresses leadership by describing the composition of the literature on leadership’s influence on technostress and providing an overview of the quantitative distribution of leadership studies in technostress research over time, and the methodological approaches used. Therefore, our first research question is formulated as follows:

How is leadership analyzed in the extant technostress research in terms of development over time, and methodologies being used?

While the first research question has a descriptive nature, the second research question deals with the synthesis of the underlying processes for how leadership can affect technostress. Findings in the work-design research emphasize the need to consider contextual factors like leadership in designing good work environments for employees, as the same technology can lead to different outcomes depending on how it is used and how it is integrated into existing work systems (Fischer and Herrmann 2011 ; Schuepbach 2007 ). The transaction-based model of stress and the current research on technostress suggest that technology use is not always experienced as a stressor and that, even when technology is perceived as a stressor, it does not always lead to strain or other stress-related outcomes, as both depend on the composition of external and individual factors (Sect.  2.1 ).

Previous studies indicate that leadership is both a resource for followers who are facing digital demands and a constraint on available coping options (Sect.  2.2 ), so an investigation of how leadership can affect technostress and its outcomes can expand theoretical knowledge on the mechanisms that underlie technostress. Therefore, the second research question focuses on the role of leadership along the emergence of technostress and technostress-related outcomes:

How is leadership related to followers’ technostress and its related health outcomes?

No systematic review of the relationship between leadership and technostress is extant, making it difficult to identify relevant research gaps. Systematic literature reviews are well suited to gather cross-study knowledge and to map the state of research based on the patterns in previous research questions. Identifying the gaps and limitations in current research that suggest avenues for future research can prevent duplication of studies, so the third research question asks:

What gaps in the current research on the relationship between technostress and leadership can be identified that offer avenues for future research?

A systematic literature review is an appropriate method to answer the three research questions, as it can identify relevant scientific studies while helping to ensure reliability in data collection and analysis (Snyder 2019 ). This section presents, explains, and visualizes the study design using a flow diagram (Fig.  1 ) to ensure the necessary transparency and replicability (Atkinson et al. 2015 ; Shamseer et al. 2015 ; Snyder 2019 ). We used an adapted version of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Moher et al. 2009 ) to perform a systematic review in five steps: (1) data extraction using a pilot search and a main search to identify relevant publications based on a specified search string, (2) identification and removal of duplicates, (3) primary screening of titles and abstracts using selection criteria formulated based on the research questions, (4) secondary screening of the remaining publications, and (5) a backward search using the publications that remain from the second screening. The five steps of this process are explained in more detail in the following and are visualized in a flow diagram in Fig.  1 .

Flow diagram of the systematic literature review process

The search string that we applied for the (1) data extraction was generated in an iterative process. In the first step, the authors identified two sets of keywords based on the current technostress and leadership literature and with regard to their respective expertise (Pittaway et al. 2004 ). One set of keywords included “technostress,” “digital stress,” and the aforementioned technostressors, as well as several ways of spelling. The other set of keywords, used to identify publications that deal with the subject of leadership, contained the keywords “leader,” “supervisor,” and—as our language skills could ensure accurate screening and analysis for only German and English articles—the German term for leadership “ Führung ,” combined with wildcards (*). The keywords for technostress and leadership were combined into a search string that was iteratively tested and optimized during an initial pilot search that took place between June and August 2021. The pilot search was limited to the databases PubMed, JSTOR, EBSCO Business Source Premier, Web of Science, and Scopus, which are multi-publisher databases that are used in other systematic reviews on technostress (Borle et al. 2021a , 2021b ; La Torre et al. 2019 ). We also choose EBSCO Business Source, as it is often used in the business sciences and PubMed because of its wide coverage of the biomedical literature. This first search generated exactly 400 publications. One of the objectives of this pilot search was to test the search strategy and optimize the search string and the inclusion criteria based on its result. As a result, we modified the search string by incorporating additional keywords related to "digital stress" and also included peer-reviewed conference papers in our inclusion criteria.

After testing our search string (see Appendix Table 1 ) and inclusion and exclusion criteria (see Appendix Table 2 ) we carried out the main search in the data-extraction process in October 2023. By using a search strategy based on electronic cross-journal databases, we expected wider coverage than would be likely with a search strategy based on selected journals (Hiebl 2021 ). Since technostress is an interdisciplinary phenomenon (Salazar-Concha et al. 2021 ; Tarafdar et al. 2019 ) researched across such disciplines as public health, sociology, business informatics, and economics, we searched in 13 cross-disciplinary and discipline-focused databases: ACM Digital, AIS eLibrary, APA PsychInfo, EBSCO, Emerald Insight, Jstor, Pubmed, SAGE, ScienceDirect, Scopus, Taylor & Francis Online, WISO, and Web of Science. No restrictions were applied concerning the publication date. In databases that had filter options for languages, we filtered for German and English articles; otherwise, we removed articles written in other languages in the primary screening. Based on the search string, we identified 1725 articles. Furthermore, we identified in the process of the secondary screening four relevant articles that the screened articles referred to and included them in our final sample, even if the origin articles were not of relevance. This leaves us with 1729 articles from which we removed 181 duplicates in the (2) selection of duplicates , leaving 1548 articles for primary screening.

In the (3) primary screening , two researchers screened the titles and abstracts of the remaining sample (n = 1548) according to a set of inclusion and exclusion criteria: Only quantitative and qualitative empirical field studies were included, so conceptual studies, lab experiments, and meta-studies were excluded. We considered only articles that were published in peer-reviewed journals or conference proceedings and relied on Beall’s List of predatory open-access publishers to exclude articles published in open-access journals with problematic peer-review processes. In addition, studies were included only if they deal with the effect of leadership on technostress experienced by followers, the perception of technostressors by followers, or followers’ technostress-related health outcomes, such as strain, burnout, and depression or other stressors like work-life conflicts. Studies that focused only on either technostress or leadership without considering the other were removed. Examples of such studies were studies that addressed the impact of leadership on the relationship between ICT and productivity or motivation without addressing technostress or technostress-related health outcomes. Studies were excluded if they focus only on either technostress and the technostress-related health outcomes or leadership, not both, such as when they deal with the impact leadership has on the relationship between ICTs and productivity or motivation. Based on the inclusion criteria (see Appendix Table 2 ), we assigned the articles to one of three categories: A = match, B = neither excludable nor includable based on the abstract and title, and C = no match (Pittaway et al. 2004 ). The articles categorized as A (n = 84) or B (n = 168) were then screened fully in the next screening step (Atkinson et al. 2015 ).

The (4) second screening was carried out by two researchers, who read the full texts of the remaining 252 articles and sorted out any contradicting classifications (inter-coder disagreements) in agreement (Atkinson et al. 2015 ; Frank and Hatak 2014 ; Snyder 2019 ). An example of such an inter-coder disagreement was Benlian ( 2020 ), who tested the effect of work-related technostressors on partnership satisfaction, mediated by positive or negative affect, and tested moderation by the variable “perceived organizational support in work-home boundary management” in the relationship between affect and partnership satisfaction. While leaders unarguably are an influential factor on followers’ perceptions of organizational support for work-home boundary management, the items that the study uses to measure this variable do not mention the impact of supervisors or leaders, so the article was finally excluded. In the first screening, 1296 articles were removed based on abstract and title, and in the second screening 221 papers based on a full-text screening. Thus, a sample of 31 articles remained.

Based on the remaining 31 articles, a (5) backward search was conducted by screening references based on the previously outlined selection criteria (see Appendix Table 2 ) (Atkinson et al. 2015 ). Screening of the studies identified in the backward search was carried out using the same two-step process, where the articles were first screened based on their titles and abstracts and then based on their full text. In the end, the backward search identified 13 articles that met our criteria for inclusion, so the results presented in the following section are based on a final sample of 44 papers. The flow diagram in Fig.  1 illustrates the systematical literature review process along its five steps.

We followed Webster and Watson ( 2002 ) as a methodological foundation and extracted relevant information (name, authors, date, journal, impact factor, key findings, sample, method) from the articles and inserted them into a concept matrix. This concept matrix served as the basis for answering research question 1 (“How is leadership analyzed in the extant technostress research in terms of development over time, and methodologies being used?”) and for our coding process to answer research question 2 (“How is leadership related to followers’ technostress and its related health outcomes? “). Following the methodology of Gioia et al. ( 2012 ), as previously done in the review of Nadkarni and Prügl (2021), we used an open coding process to synthesize underlying concepts along the literature (Fisch and Block 2018). In the first step, we identified descriptive codes (first-order constructs), which served as a foundation to derive analytic themes (second-order themes), which were then synthesized into higher-level dimensions (aggregated dimensions).

4.1 Descriptive overview of leadership in the technostress literature (RQ1)

To answer the first research question, we provide a descriptive overview of the literature on leadership and technostress in terms of a quantitative distribution of leadership studies in technostress research over time, the methodological approaches used, and the aspects of leadership that the studies analyze.

We identified 44 studies that deal with the impact of leadership on technostress and technostress-related outcomes. The quantitative development of the technostress literature that deals with leadership shows an increase in publication-volume over time with the oldest studies published in 2009 (Harris and Marett 2009 ; Lautsch et al. 2009 ) and a preliminary peak of eight articles published in 2021 (Fig.  2 ). The increase in publications can be attributed partially to the increase in technostress because of the COVID-19 pandemic, as we found substantive references to the COVID-19 pandemic in 60 percent of the studies published since 2020 (Azpíroz-Dorronsoro et al. 2023 ; Bartsch et al. 2021 ; Chambel et al. 2022 ; Chen and Wu 2023 ; Dicu et al. 2022 ; Dolce et al. 2020 ; Günther et al. 2022 ; Islam et al. 2022 ; Jämsen et al. 2022 ; Jin et al. 2020 ; Lanzl 2023 ; Olsen et al. 2023 ; Spagnoli et al. 2020 ; van Slyke et al. 2022 ; Vaziri et al. 2020 ). The identified articles were published in 32 peer-reviewed journals in the areas of, among others psychology, (e.g., Journal of Applied Psychology), management and leadership (e.g., Academy of Management Journal), and information technology (e.g., Computers in Human Behavior). The variety of journals that published studies on the topic underscores its multidisciplinary nature. The journals’ latest impact factors of the year 2022, which indicate the sample’s quality (Tranfield et al. 2003 ), ranked between 1.4 (Information Resources Management Journal; Discrete Dynamics in Nature and Society) and 10.6 (Journal of Service Management), with an average impact factor of 4.9 (see Appendix Table 3 ). Three of the identified articles were published in conference proceedings (Fieseler et al. 2014 ; Massa et al. 2023 ; Stana and Nicolajsen 2021 ) but remained in the sample because the proceedings were peer-reviewed.

Frequency of articles on leadership’s impact on technostress and its outcomes

Regarding the methods used , of the 44 articles, 37 were quantitative and five were qualitative (Cavazotte et al. 2014 ; Dicu et al. 2022 ; Jämsen et al. 2022 ; Obushenkova et al. 2018 ; Stana and Nicolajsen 2021 ), while two papers use a mixed-method design, one analyzes open-ended semi-structured interviews with cross-sectional survey data in two studies (Spreer and Rauschnabel 2016 ), and one analyzes both qualitative and quantitative data of the same sample (Lautsch et al. 2009 ). Both mixed-method articles rely on cross-sectional data. One of the qualitative studies, Dicu et al. ( 2022 ), is of longitudinal nature and relies on a mix of methods that includes interviews and diaries. 28 of the quantitative studies are of cross-sectional nature: (Azpíroz-Dorronsoro et al. 2023 ; Bartsch et al. 2021 ; Bauwens et al. 2021 ; Bentley et al. 2016 ; Bregenzer and Jimenez 2021 ; Chen and Wu 2023 ; Cheng et al. 2021 ; Chesley 2014 ; Çiçek and Kılınç 2021 ; Dolce et al. 2020 ; Fieseler et al. 2014 ; Ghislieri et al. 2017 ; Grant et al. 2019 ; Harris et al. 2012 , 2015 ; Harris and Marett 2009 ; Islam et al. 2022 ; Jin et al. 2020 ; Ma and Turel 2019 ; Massa et al. 2023 ; Molino et al. 2019 ; Park et al. 2020 ; Salanova et al. 2013 ; Spagnoli et al. 2020 ; Stich et al. 2019 ; Turel and Gaudioso 2018 ; van Slyke et al. 2022 ; Zaza et al. 2021 ). Six of the studies are of longitudinal nature: (Butts et al. 2015 ; Derks et al. 2015 ; Günther et al. 2022 ; Lanzl 2023 ; Olsen et al. 2023 ; Valle et al. 2021 ). One qualitative study, Dicu et al. ( 2022 ), and three quantitative studies, Chambel et al. ( 2022 ), Klebe et al. ( 2023 ), and Vaziri et al. ( 2020 ), rely on both cross-sectional and longitudinal data.

All of the studies in the sample deal with ICT use, but only 20 studies consider ICT use as a criterion for their samples by, for instance, focusing on followers whose work deals to a significant degree with ICTs (Fieseler et al. 2014 ; Salanova et al. 2013 ), computers (Harris et al. 2015 ; Valle et al. 2021 ), smartphones (Cavazotte et al. 2014 ; Derks et al. 2015 ), or instant messengers (Cheng et al. 2021 ) or who work remotely (Chambel et al. 2022 ; Chen and Wu 2023 ; Dicu et al. 2022 ; Dolce et al. 2020 ; Grant et al. 2019 ; Jämsen et al. 2022 ; Klebe et al. 2023 ; Lautsch et al. 2009 ; Massa et al. 2023 ; Spagnoli et al. 2020 ; van Slyke et al. 2022 ), or that work in a virtual work setting (Bartsch et al. 2021 ), or in IT (Zaza et al. 2021 ).

In gathering information about technostress, technostress-outcomes, and leadership behavior, all of the empirical studies in our sample rely on self-assessments and none use medical measurements for strain, such as cortisol levels, blood pressure, or heart rate. 40 of the empirical studies deal with employees in companies, three studies with employees of educational facilities like schools, universities, or childcare facilities (Bauwens et al. 2021 ; Jin et al. 2020 ; Spagnoli et al. 2020 ) and one in the public sector (Jämsen et al. 2022 ). With 40 articles relying on data related to followers, the followers’ perspective is clearly predominant in our sample (see Appendix Table 4 ). Four articles rely on a sample of followers and leaders (Cavazotte et al. 2014 ; Lautsch et al. 2009 ; Obushenkova et al. 2018 ; Stana and Nicolajsen 2021 ), but only two studies analyze leaders and followers as dyads (Cavazotte et al. 2014 ; Lautsch et al. 2009 ). None of the identified studies collects quantitative data from leaders. Table 5 gives an overview of the identified articles, it includes additional information regarding the analyzed articles (“author(s) and year of publication”, “study aim(s)”, “methodological approach”, “study design”, “sample”, “leadership”, “instruments to measure leadership”, “relevant outcome(s)”) (see Appendix Table 5 ).

4.2 Leadership’s impact on technostress (RQ2)

In this section we present the results of our analysis concerning research question 2 “How is leadership related to followers’ technostress and its related health outcomes?”. By relying on the Gioia methodology (2012) we synthesized first order constructs from the identified studies which we then grouped into theoretical themes. The first order themes were of descriptive nature and aimed at briefly summarizing leaderships impact on follower technostress (for example: “leadership support reduces distress” or “leadership technology support buffers perception of technostress”) which were then aggregated into broader descriptions of leadership as higher themes (for example: leadership support). We then checked for trends along the studies that were assigned to the themes and which led to the distinction into the aggregated dimensions of technostress-increasing leadership (see Sect.  4.2.1 ) and technostress-reducing leadership (see Sect.  4.2.2 ). The synthesized categorization, while useful for mapping leadership’s impact on follower technostress, does not cover a crucial aspect of the leader–follower dynamic in digital work. It fails to account for how leadership is evolving due to digital technology use and how this transformation influences its impact on follower technostress. To acknowledge the importance ICT has on how leadership is carried out, we included a third dimension “technology-enabled leadership” that maps how leadership carried out through digital technologies impacts followers.

4.2.1 Technostress-increasing leadership

Three second-order themes form the aggregated dimension “technostress-increasing leadership”. It covers leadership behavior that increases technostressors perceived by followers and/or amplifies strain related to digital work: destructive leadership, leaders-availability expectations, and task-oriented leadership.

Theme 1: Destructive leadership

”Destructive leadership” examines how destructive leadership, understood here as supervisor behavior towards followers that is “perceived as hostile and/or obstructive” (Schyns and Schilling 2013 ), contributes to increased technostress levels among followers. The theme covers first-order concepts that dealt with abusive leadership or destructive leadership and was found in five studies (Butts et al. 2015 ; Dolce et al. 2020 ; Molino et al. 2019 ; Stich et al. 2019 ; Valle et al. 2021 ). The impact of destructive leadership on followers’ technostress is two-sided: on the one hand, destructive leadership behavior itself represents a demand for followers and increases stressors on the job as well as job demands outside work (Butts et al. 2015 ; Dolce et al. 2020 ; Molino et al. 2019 ). Followers that worked in a digital work environment and were led by abusive leaders reported higher workloads (Molino et al. 2019 ), cognitive demands (Dolce et al. 2020 ), off-work hours technological assisted job demands (Dolce et al. 2020 ; Molino et al. 2019 ), tendencies of workaholism (Molino et al. 2019 ), and had to engage more in labor surface acting when interacting with their supervisors (Valle et al. 2021 ). On the other hand, destructive leadership affects followers’ resources and thus their ability to deal with those demands as followers led by abusive leaders had more difficulties in recovering from work demands (Dolce et al. 2020 ) and felt limited in their work-related autonomy (Dolce et al. 2020 ). This interplay between increased demands and decreased resources led to followers reporting higher emotional exhaustion (Dolce et al. 2020 ; Molino et al. 2019 ) as well as interference between the work and family domain (Butts et al. 2015 ; Valle et al. 2021 ) if they were led by destructive supervisors.

Theme 2: Leaders’ availability expectations

The analytical theme “leaders’ availability expectation” revolves around leadership behaviors related to leaders’ expectations and actions concerning their followers’ availability via ICT outside of working hours. The pervasive work-related use of ICT has raised concerns regarding its potential demands as it has been linked to a blurring of boundaries between work and private life as well as job demands and even burnout (Park et al. 2020 ). Leaders can significantly influence whether followers use ICT for work-related purposes outside working hours. On the one hand, leaders can exacerbate this phenomenon by proactively transcending the boundaries between work and private life as they communicate with followers via ICT beyond regular working hours (Cheng et al. 2021 ). On the other hand, leaders can inadvertently establish the perceived need for followers to be accessible outside their working hours through their own use of digital technology during those times, thereby unintentionally normalizing off-work availability (Stana and Nicolajsen 2021 ). This can create the perception that followers are also obligated to be available outside working hours (Stana and Nicolajsen 2021 ). Qualitative studies have also shown that the simple provision of smartphones can be perceived as a “deal” between followers and leaders that includes higher flexibility but also higher availability expectations as well as higher levels of supervisor control (Cavazotte et al. 2014 ; Obushenkova et al. 2018 ). High availability expectations by supervisors often resulted in increased conflicts or interferences between work and private life (Cavazotte et al. 2014 ; Cheng et al. 2021 ; Derks et al. 2015 ; Obushenkova et al. 2018 ), feelings of being controlled (Cavazotte et al. 2014 ) and strain (Obushenkova et al. 2018 ; Stana and Nicolajsen 2021 ). However, leaders that required a separation between work and private life reduce interferences and work-family conflicts for followers working remotely (Lautsch et al. 2009 ). The theme underscores the versatile influence leaders have in shaping how followers use ICT and highlights leaders’ impact on a normative level, such as, by setting rules or expectations or as a result of their own ICT use (Cavazotte et al. 2014 ; Derks et al. 2015 ; Obushenkova et al. 2018 ; Stana and Nicolajsen 2021 ). Especially in work environments without clear rules regarding ICT use outside working hours, leaders’ own ICT use can shape how technology is being used by their followers.

Theme 3: Task-oriented leadership

Leadership that focused primarily on completing tasks efficiently and reliably through planning, setting priorities, goals, and rules, and monitoring followers (Yukl 2010 ) was partially associated with an increase in technostress (Cheng et al. 2021 ; Fieseler et al. 2014 ; Spreer and Rauschnabel 2016 ). Related to the use and introduction of digital technology, followers whose supervisors require that they adapt certain digital technology may feel more resentful about the adoption of digital technology (Spreer and Rauschnabel 2016 ). Whereas leaders encouraging followers to use digital technologies does not have a significant effect on technostress or work exhaustion (Fieseler et al. 2014 ). Leaders that use instant messengers after working hours to assign tasks to followers do increase work-life conflicts for followers (Cheng et al. 2021 ). A study by Spagnoli et al. ( 2020 ) revealed a positive impact of authoritarian leadership on technostressors as well as a moderating impact of workaholism on technostressors for followers working remotely. These results suggest that followers whose leaders impose the use of digital technologies are less likely to adopt these ICTs, and that followers led by authoritarian leaders are more likely to perceive digital technologies as demanding.

4.2.2 Technostress-reducing leadership

Leadership behaviors that help followers to navigate through the demands of digital work and thus reduce the perceived technostressors or mitigate the technostressor-strain relationship and thus act as an inhibitor or moderator of technostress were grouped as technostress-reducing leadership behavior. Along the literature, we identified two themes of leadership behavior that had a decreasing impact on followers’ technostress: leadership support and change-oriented leadership.

Theme 4: Leadership support

The analytical theme “leadership support” revolves around leadership behaviors that provide support and assistance to followers in managing technostress and well-being in a digital work environment. It encompasses leaders providing technological and social support as well as leaders fostering segmentation between work-life and thus helping followers harmonize work and family. The theme “leadership support” covers five first-order concepts technological support, social support, family support, health-oriented leadership and leader-member exchange quality, representing different forms of support for followers, leaders can provide. While supervisors’ technological support had no significant impact on techno-overload (Harris and Marett 2009 ), followers who reported high levels of supervisor computer help in combination with the liking of computer work reported the lowest levels of techno-overload in a study by Harris and Marett ( 2009 ). Whereas a study by Harris et al. ( 2012 ) came to the results that supervisor computer help did not significantly impact work-family conflicts but increased the impact of overload on time-based work-family conflicts.

Family-supportive leadership and social support provided by leaders are important resources for followers dealing with technology-related demands on the job as they have a reducing impact on burnout of followers working in a digital work environment (Zaza et al. 2021 ), work-family conflicts (Chambel et al. 2022 ; Azpíroz-Dorronsoro et al. 2023 ), distress (Chesley 2014 ; Turel et al. 2018; Olsen et al. 2023 ), emotional exhaustion (Chambel et al. 2022 ; Azpíroz-Dorronsoro et al. 2023 ), psychological strain (Bentley et al. 2016 ) and burnout (Park et al. 2020 ). As well as off the job by buffering the impact of technology-assisted work-related demands outside work hours and thus maintaining work-life balance and followers’ well-being (Chambel et al. 2022 ; Park et. al 2020; Vaziri et al. 2020 ). Besides its buffering impact on the stressor-strain relationship, social support had been also shown to mitigate technostressors (Chesley 2014 ; Azpíroz-Dorronsoro et al. 2023 ). In contrast to the previously cited studies, Lanzl ( 2023 ) finds a positive, albeit small, relationship between the extent to which a supervisor cares about followers well-being and followers’ technostressors. The author suggests that the relationship between techno-invasion and social support may be explained by followers’ willingness to be contacted outside regular working hours if they have a close relationship with their supervisor, while the relationship with other technostressors requires further investigation.

In the context of remote work, which can come along with risks like social isolation (Bentley et al. 2016 ) and increased interference between work and private life, leadership support represents an important resource for followers, as it reduces social isolation, psychological strain (Bentley et al. 2016 ) and helps followers to deal with work-life conflicts (Chambel et al. 2022 ; Vaziri et al. 2020 ). Furthermore, teleworkers that were led by supportive supervisors reported an increase in teleworker’s perceived eustress, which represents stress that is beneficial to followers’ well-being (van Slyke et al. 2022 ). Health-oriented leadership had been shown to have a direct reducing impact on follower strain (Bregenzer and Jimenez 2021 ; Klebe et al. 2023 ) and an increasing impact on followers’ work-related resources (Bregenzer and Jimenez 2021 ). In the study of Chen and Wu ( 2023 ) supervisor’s health-oriented leadership was not significantly related to followers’ stress but indirectly mediated though followers’ self-care. Furthermore, Klebe et al. ( 2023 ) found a significant link between health-promoting employee leadership and follower stress but only for followers that experienced low levels of ICT hassles.

That followers who perceive support from their supervisors are better equipped to handle digital demands is also underscored by the identified studies dealing with the leader-member exchange quality’s impact on followers’ technostress (Harris et al. 2015 ; Jin et al. 2020 ). Followers that are part of the ingroup, which is characterized by higher levels of support and resources provided by supervisors, were better equipped to handle technostressors in a way that work-family conflicts are less likely to occur (Harris et al. 2015 ). On the other hand, a study by Jin et al. ( 2020 ) showed that the interaction between security-related technostress and leader-member exchange quality was not significant but leaders-member exchange quality had a reducing impact on burnout.

Theme 5: Change-oriented leadership

The theme “change-oriented leadership” that aims at implementing change using transformational, empowering, and enabling leadership (Yukl 2010 ) was mostly associated with lower technostress levels for followers. Followers that were led by transformational leaders were more open-minded towards adopting work-related ICT, the studies linking transformational leadership to a decrease in skepticism towards ICT in followers (Salanova et al. 2013 ) and techno-uncertainty (Çiçek and Kılınç 2021 ). Furthermore, followers that are led by transformational leaders report lower levels of technostressors (Çiçek and Kılınç 2021 ) and exhaustion when adopting ICT for work-related tasks (Fieseler et al. 2014 ).

The literature on empowering and enabling leadership is a bit more contradictory, as enabling leadership has a decreasing impact on teamwork tension for followers working in virtual teams (Bartsch et al. 2021 ). Empowering leadership had been shown to reduce the impact of techno-invasion on emotional exhaustion but to strengthen the impact of techno-overload on emotional exhaustion (Bauwens et al. 2021 ). Though the results of Bauwens and colleagues’ study (2021) suggest that autonomy and self-responsibility might be perceived by followers that already feel overloaded by ICT as an additional demand, the literature that deals with leadership styles that encourage followers’ autonomy, like transformational leadership and empowering leadership largely implies that autonomy and empowerment provided by leaders might be important resources for followers dealing with technostressors. This conclusion can be supported by the results of Grant et al. ( 2019 ) pointing out that followers led by leaders that provide them with high levels of autonomy and flexibility report higher levels of mental health (Grant et al. 2019 ).

4.2.3 Technology-enabled leadership

The preceding themes focus on the influence of leadership behaviors on follower technostress, yet they do not explicitly consider the specific role of digital technologies as a channel in the leader–follower interaction. As digital technologies continue to play an increasingly relevant role in work-related communication, they lead to significant changes in the environment in which leadership takes place, by shifting it further into the digital sphere. In order to investigate how digital developments influence the effect of leadership behaviors on technostress, we introduce a third aggregated dimension. The dimension “technology-enabled leadership” deals with how leaders use ICT to exercise leadership and assesses its impacts on follower technostress. Within this dimension, we identify two second-order themes: “technology-enabled technostress-increasing leadership” and “technology-enabled technostress-reducing leadership”. These themes show how digital technologies interact with leadership behavior and influence follower technostress.

Theme 6: Technology-enabled technostress-reducing leadership

As already discussed before, leadership can represent an important resource for followers working with digital technologies. With ICT taking on a more important role in leader–follower interactions, the analytical theme explores the impact of leadership that is exercised through these technologies on followers’ technostress. Especially for followers working remotely studies suggest the increased need of leadership support (Dicu et al. 2022 ; Jämsen et al. 2022 ) and that those followers might benefit from technology-enabled leadership support as it can reduce social isolation, strain (Bentley et al. 2016 ), work-family conflict (Chambel et al. 2022 ), and increases teleworkers’ perceived eustress (van Slyke et al. 2022 ). Hence, the focus lies on how leaders can support or encourage their followers through digital channels.

On the one hand, Chambel and colleagues’ (2022) results suggest, that family-supportive supervisor behavior’s impact on work-family conflict and exhaustion is not moderated by the levels of remote work. Besides, a quantitative study by Lautsch et al. ( 2009 ) showed that supervisor contact with telecommuters did not significantly affect followers work-to-family nor family-to-work conflicts. In the study by Islam et al. ( 2022 ), remote work did not serve as a significant moderator in the relationship between leader-member exchange and anxiety or depression. On the other hand, technostress literature suggests that it can be more challenging for followers to receive leadership support through digital channels, as they can feel reluctant to ask their supervisors for help through ICT or find the support received through digital channels as not sufficient (Dicu et al. 2022 ; Jämsen et al. 2022 ). The difficulties for followers in perceiving leadership support through digital channels are also underscored by the findings of Bregenzer and Jimenez ( 2021 ) and Klebe et al. ( 2023 ) emphasizing that health-oriented leadership loses its reducing impact on strain for followers with high levels of remote work (Bregenzer and Jimenez 2021 ) or ICT hassles (Klebe et al. 2023 ).

However, Lautsch's study took place in 2009 when telework was still a marginal phenomenon, practiced primarily by highly qualified employees with leading responsibility and experience with working remotely. Dicu et al. ( 2022 ) and Jämsen et al. ( 2022 ) collected their sample in turn of the mandatory remote work due to the COVID-19 pandemic. Concluding, it can be assumed that the different results of these studies could partially be attributed to the times in which the sampling of these studies took place. Thus, technostress literature indicates that with the increasing digitalization, the communication between leaders and followers also shifts towards digital channels and that important resources provided by supervisors might be more difficult to grasp by followers.

Theme 7: Technology-enabled technostress-increasing leadership

The analytical theme “technology-enabled technostress-increasing leadership” covers the first-order concepts: (1) contact outside work hours via ICT, and (2) ICT as a vessel for destructive leadership. The analytical theme deals with the role digital technologies do play in leadership’s impact on followers’ technostress. As already shown in theme 2 “leaders’ availability expectations”, ICTs enable leaders to cross borders between work and family life, and thus extend their impact on followers even outside work. This can result in conflicts between work and private life and decrease recovery times.

This dissolving of borders can be especially demanding for followers whose leaders use ICT to carry out destructive leadership behaviors. Digital technologies can exert the previously in theme 1 stated influence abusive leaders have on their followers, as they enable them to contact followers more frequently on the job and even outside work hours. Literature has shown that followers that are being led by destructive leaders report higher degrees of technology enabled-off work demands (Molino et al. 2019 ; Dolce et al. 2020 ). This either suggests that abusive leaders use ICT to contact followers outside work hours more frequently or that the behavior itself of contacting followers outside work hours is seen as destructive by followers. The latter would be strengthened by the research of Stich et al. ( 2019 ) that have drawn a link between the perceived extent of work-related emails and followers’ perception of social stressors like feeling intimidated by supervisors or constant critique by supervisors.

Furthermore, technology-enacted abusive supervision can trigger emotions like anger in followers (Butts et al. 2015 ), so they have to engage in emotional labor surface acting (Valle et al. 2021 ). Abusive leaders contacting followers outside work hours can also increase the time followers are exposed to job-related demands and thus limits their ability to distance themselves from work-related demands. This spillover to the family domain can result in reduced recovery from work (Dolce et al. 2020 ) as well as work-to-life conflicts (Valle et al. 2021 ). The interplay of increased demands, especially through the ubiquity of digital technologies that makes it harder for followers to gain distance from leaders, combined with limited resources and ability to recover, suggest that followers of abusive leaders may face particular problems dealing with technostress.

4.2.4 Conceptual model of leadership’s influence on technostress

Building upon the synthesized themes, we have developed a comprehensive conceptual model illustrating the intricate influence of leadership on follower technostress throughout the technostress process. The technostress process unfolds from the use of ICT to the appraisal of ICT as a stressor and finally to the experience of strain. This process is depicted in the lower section of Fig.  3 . Conversely, the upper section of Fig.  3 portrays the leadership component.

Conceptual model of leadership’s impact on followers’ technostress

These two sections are interconnected by three descending arrows, each representing a discrete pathway we synthesized to illustrate leadership’s nuanced influence on follower technostress. The first pathway illuminates the influence of leadership on followers’ appraisal of ICT use as stressors (Butts et al. 2015 ; Chesley 2014 ; Çiçek and Kılınç 2021 ; Derks et al. 2015 ; Dolce et al. 2020 ; Ma and Turel 2019 ; Molino et al. 2019 ). Conceptually, this pathway takes a forefront position in the technostress process within the context of primary appraisal in the transactional-based model of stress. There are several ways in which leaders can shape followers’ perception of ICT use as demanding: On the one hand, leaders significantly influence the extent and manner in which followers adopt ICT. This influence can occur at a normative level, such as through rule-setting or establishing expectations (Cavazotte et al. 2014 ; Derks et al. 2015 ; Obushenkova et al. 2018 ; Stana and Nicolajsen 2021 ). Furthermore, leaders can indirectly create expectations by modeling ICT use themselves and thus acting as role models. On the other hand, leadership’s impact on technostressors manifests both directly and as a moderator between ICT usage and technostressors. However, leadership can also affect the outcomes of technostress, either by moderating the stressor-strain relationship as demonstrated in the second pathway, or by directly influencing technostress-related strain as seen in the third pathway (Bentley et al. 2016 ; Chesley 2014 ; Fieseler et al. 2014 ; Vaziri et al. 2020 ; Zaza et al. 2021 ). These two pathways can conceptually be located along the secondary appraisal of the transaction-based model of stress.

Within the context of these pathways, leadership exerts a dual influence on followers’ technostress, manifesting both diminishing and amplifying effects on follower technostress. Thus, we have synthesized these impacts into two distinct dimensions: “technostress-increasing leadership” and “technostress-decreasing leadership”. Leadership behaviors that cultivate autonomy, empowerment, and support offer valuable resources to followers working in a digital environment (see Sect.  4.2.2 ). Therefore, we have grouped leadership behaviors that foster support and change-oriented behaviors under the aggregated dimension of “technostress-decreasing leadership”.

Conversely, leadership may also constrict available resources or emerge as a stressor itself, thereby increasing the perceived demands of digital work and technostress-related outcomes, as expounded in Sect.  4.2.1 . In contrast to leaders who provide support, destructive leadership has been correlated with higher demands for followers in the digital work environment. Furthermore, change-oriented leadership has demonstrated associations with reduced technostress and heightened openness among followers towards adopting digital technologies. Conversely, under leaders exhibiting task-oriented leadership, such as authoritarian leadership or dictation to use certain digital technologies, followers exhibited a reduced willingness to embrace digital technologies, coupled with heightened reports of technostressors. Therefore, we classified leadership behaviors that are characterized by destructive tendencies, task-oriented approaches, and those fostering expectations of availability outside work hours into the dimension of “technostress-increasing leadership”. This dichotomy between “technostress-increasing” and “technostress-decreasing” leadership is visualized in the upper segment of Fig.  3 .

In both cases—technostress-reducing and technostress-increasing leadership—leaders employ ICT as a channel for exercising leadership (visualized in the box labeled “ICT as a channel for leadership” in Fig.  3 ). It can be used to provide supportive and change-oriented leadership across geographical distances and to provide remote working followers with the necessary resources. However, it appears that technostress-reducing leadership may experience a diminishment of its effectiveness when exercised through digital technology.

Moreover, technology-enabled leadership carries potential drawbacks for followers, as it can amplify the impact of technostress-increasing leadership. This amplification can lead to interferences between work and private life, culminating in increased demands. The pervasive nature of ICT can make it difficult for followers to evade the influence of leaders both during work hours and off-work hours, potentially resulting in strain and impairing followers’ ability to recover from work-related demands. To visualize how ICT can shape leadership’s influence on follower technostress, we have placed it between leadership and followers’ technostress within our conceptual model.

It is worth noting that the conceptual model is not an isolated system, and it is important to consider the impact of leadership within a broader context rather than isolated from other individual or contextual factors. Leadership’s influence on technostress and technostress-related outcomes can also operate indirectly through interactions with contextual or individual factors. For instance, by altering individual resources like autonomy (Bartsch et al. 2021 ; Dolce et al. 2020 ), workaholism (Molino et al. 2019 ), and recovery (Dolce et al. 2020 ). Moreover, leadership has been shown to moderate the impact of individual factors like workaholism (Spagnoli et al. 2020 ) or the level of preference for computer work (Harris and Marett 2009 ) on technostress and technostress-related outcomes. Furthermore, the effect of leadership itself can depend on organizational and technological factors, such as the political work environment (Park et al. 2020 ) or mode of work (e.g., remote work, telecommuting) (Bregenzer and Jimenez 2021 ; Dicu et al. 2022 ; Jämsen et al. 2022 ; Lautsch et al. 2009 ; Spagnoli et al. 2020 ).

5 Discussion and avenues for future research (RQ3)

5.1 discussion.

With 44 articles, the literature on leadership makes up a small portion of technostress literature (La Torre et al. 2019 ). This is surprising given the increasing role of ICT in everyday work, and as health risks associated with work-related ICT use are attracting increasing interest in the scientific community (Charalampous et al. 2019 ). When it comes to analyzing the antecedents of technostress and the factors that influence technostress, leadership plays a comparably small role in technostress research. Nonetheless, the near-continuous growth of the technostress literature focused on leadership indicates a growing interest among researchers, which peaked in the Covid-19 pandemic (see Sect.  4.1 ). Given that systematic literature reviews have yet to extensively address the influence of leadership on technostress, our objective was to present an overview of the literature on this topic, and thus offering easier access to the rather fragmented and cross-disciplinary literature on technostress literature that deals with leadership.

Based on our analysis, we derived a conceptual model that incorporates the distinction of leadership into leadership that reduces and increases technostress of followers and locates leadership impact along the transactional process of technostress (see Sect.  4.2 ). These findings contribute to technostress research by extending existing classifications of technostress-antecedents and technostress-inhibitors (La Torre et al. 2019 ; Ragu-Nathan et al. 2008 ; Tarafdar et al. 2015 ) by the influence of leadership. We hereby respond to the call by Sarabadani et al. ( 2018 ) to introduce new inhibitors into technostress research.

The concept of technostress-inhibitors is predominantly understood as organizational or social factors that either mitigate the relationship between technostressors and strain or directly reduce strain (Ragu-Nathan et al. 2008 ). Technostress-antecedents are understood as factors that can influence the occurrence of technostressors (La Torre et al. 2019 ), but predominantly as factors that amplify stressors. Leadership had been shown to fit into both categories as it has an influence on whether followers perceive work-related ICT use as a stressor comparable to other technostress-antecedents. Furthermore, leadership can influence the relationship between stressor and strain. However, as we found both technostress-increasing and technostress-decreasing leadership as anteceding the perception of technostressors as well as moderators between stressors and strain, we conclude that the distinction of technostress-inhibitors and technostress-antecedents does not fully cover the influence of leadership. Since the two appraisal processes underlying the transaction-based stress model are circular in nature and influence each other, we consider the distinction between technostress-inhibitors and technostress-antecedents to be somewhat limited in mapping the effects of leadership on technostress. Especially as empirical studies have shown that the same leadership behavior has an impact on the evaluation of ICT use as a stressor as well on the stressor-strain relationship (e.g. Chesley 2014 ; Turel and Gaudioso 2018 ).

By analyzing how different types of leadership affect follower technostress, our findings represent a significant contribution to leadership research in the context of contingency theory. Our findings highlight that followers who engage with digital technologies experience distinct advantages from leadership support and empowering leadership. This underscores the benefits of leadership paradigms like transformational and servant leadership in preventing technostress, and strengthens the call of Scharzmüller et al. (2018) for leaders to provide followers with sufficient support and autonomy to handle the challenges of digital work. Moreover, the aggregated dimension of “technology-enabled leadership” shows that the effectiveness of these forms of leadership when preventing technostress outcomes depends on how digital technologies are being used by leaders. That the impact of technostress-inhibiting leadership behavior can lose parts of its impact when carried out through ICT, is in line with the results of Liu et al. ( 2020 ) who found similar results for the outcome variable productivity. We conclude that while digital technologies offer great opportunities for the rapid exchange and delivery of information, some leaders appear to face challenges in using ICT as a vessel for leadership. This underlines the relevance of specific leadership training for leading virtual teams. This is of greater importance as technology-enabled leadership can also bear risks for followers if carried out poorly or even used in a destructive way. The aggregated findings concerning the potentially detrimental influence of leaders’ ICT use—either by dissolving borders between work and private life and thus reducing recovery times for followers or as a vessel that can enable abusive leaders to extend their influence on followers—do underscore the importance that leaders themselves ethically use ICT and foster health-oriented use of digital technologies and that the use of mobile technologies is accompanied by norms that ensure recovery times off work.

These findings concerning leadership’s impact on followers’ technostress and technology-enabled leadership do also present a contribution to the growing body of digital leadership research (Tigre et al. 2023 ). While research on digital leadership deals with the relationship between leadership and ICT on outcomes such as team effectiveness, productivity, or the factors that facilitate ICT adoption (Avolio et al. 2014 ), leadership’s impact on technostress presents a perspective that had not yet been addressed in previous reviews or meta-studies of e-leadership or digital leadership (Avolio et al. 2014 ; Tigre et al. 2023 ). Though technostress is a significant predictor of productivity and ICT adoption (Avolio et al. 2014 ), we strongly believe that leaders’ impact on followers’ health needs to take a prominent place in the discourse about “effective leadership” in a digital work environment. Moreover, there are other discrepancies between the literature on digital leadership and the technostress literature on leadership. Technologies that were predicted to play an essential role in future e-leadership practices like embedded tracking systems, internet of things, artificial intelligence (Avolio et al. 2014 ; Tigre et al. 2023 ), play no role in the current technostress literature on leadership. Other than AI or robotic-assisted leadership (Avolio et al. 2014 ), e-mails (Butts et al. 2015 ; Stich et al. 2019 ) or instead messengers (Cheng et al. 2021 ), mobile devices like the smartphone (Cavazotte et al. 2014 ; Derks et al. 2015 ; Obushenkova et al. 2018 ; Park et al. 2020 ; Stana and Nicolajsen 2021 ), tablets (Spreer and Rauschnabel 2016 ) or computers/laptops (Harris et al. 2012 ; Harris and Marett 2009 ), as well as forms of remote work (Bentley et al. 2016 ; Chambel et al. 2022 ; Dicu et al. 2022 ; Grant et al. 2019 ; Günther et al. 2022 ; Jämsen et al. 2022 ; Lautsch et al. 2009 ; van Slyke et al. 2022 ), seem to play the predominant role in our sample. While it can be argued from our results that those widely used technologies can present stressors that can lead to harmful outcomes and therefore still need to be present in the discourse about digital work’s impact on followers’ health, current technostress literature on leadership does not seem to keep up with other research strands when it comes to technological process.

5.2 Avenues for future research

Based on our analysis we derive several avenues for future research. From a methodological point of view, we identified two limitations of the present technostress literature dealing with leadership. The current state of technostress literature dealing with leadership can be described as predominantly based on cross-sectional and self-reported data that is based on the follower’s perspective (see Sect.  4.1 ). As cross-sectional data provides only momentary insights and does not allow statements about the causal relationship between leadership and technostress (Carlson and Morrison 2009 ), we conclude that technostress research on the impact of leadership still lacks longitudinal or experimental studies. Especially studies whose sample collection took place during the pandemic are likely to find that the effect of leadership on followers who work remotely can be influenced by macro-developments like school closures and regulations regarded to personal contact. Against this background, the first recommended avenue for future research is longitudinal studies or experimental studies to gain more consistent and causal insights into the effect of leadership on technostress. This call for longitudinal studies is also raised by Dolce et al. ( 2020 ); Bartsch et al. ( 2021 ); Bregenzer and Jimenez ( 2021 ); Spagnoli et al. ( 2020 ); Chambel et al. ( 2022 ).

The majority of self-reported data of followers present the second methodological limitation of the existing technostress literature. Especially, as many studies deal with health-related behaviors, self-reported data should be treated with caution (Newell et al. 1999 ). By focusing predominately on followers’ perspectives, current technostress literature largely does not consider that leaders can also be subject to technostress. As leaders’ own experiences of stress (Harms et al. 2017 ) and technostress (Boyer-Davis 2018 ; Sandoval-Reyes et al. 2023 ) can influence their leadership behaviors and affect their followers, we believe that including leaders’ perspectives is necessary to get a full picture of the relationship between leadership and followers’ experiences of technostress in future research. Moreover, current leadership literature sees leadership as a dynamic interplay between leaders and followers (Gesang and Süß 2021 ; Northouse 2019 ). Thus, the conventional top-down approach to analyze leadership is not sufficient to represent the complex relationship between leaders and followers. We, therefore, suggest that future studies should involve leaders’ perspectives in technostress literature to get a more adequate picture of the relationship between leadership and followers’ experiences of technostress. Stana and Nicolajsen’s ( 2021 ) qualitative study underscores this argument by providing new insights into the unintended consequences of leaders’ use of ICT on followers’ perceived obligation to be accessible via ICT outside work hours.

The mixed findings regarding the effectiveness of leadership support through digital channels call for further research to investigate the factors that impact leadership support through digital channels. The effectiveness of providing sufficient support through ICT may depend on the abilities of the leaders to communicate and thus to lead via ICT—labeled as e-communication by Roman et al. ( 2019 ). But further research analyzing leaders’ digital competencies and how they utilize digital tools to provide support is needed to identify successful e-communication patterns in the context of technostress. An avenue for future research could be that qualitative studies examine how followers perceive technology-enabled leadership support, which could identify factors that influence the provision of leadership support through digital channels.

Another avenue for future research would be the identification of individual factors that might impact the relationship between leadership and technostress, as it is likely, that followers are impacted differently by leadership behavior, depending on their preferences, abilities, or personality traits (Matthews et al. 2021 ). Nearby, future research projects could consider followers’ segmentation preferences’ impact on how followers perceive leaders’ availability expectations or that followers with high levels of techno-literacy do benefit less from technology support provided by supervisors. Yet, there are only few studies (e.g., Spagnoli et al. 2021) that take those factors into account when analyzing the impact of leadership on followers’ technostress.

While a few of the identified studies imply that leadership’s impact on followers’ technostress might be mediated by individual or contextual factors, those studies are still rare. Against this background, future research should investigate the interplay between leadership and individual as well as contextual factors on different levels. Conceptually most studies took a dyadic approach by analyzing how leadership behaviors impacted followers’ health without factors on the team level. Research outside the technostress literature had linked destructive leadership behaviors to outcomes on the group level such as cooperation or good citizen behavior (Priesemuth et al. 2014 ). Future research should analyze mediating mechanisms on the team level that link specific leadership behaviors to technostress outcomes and thus provide a better understanding of the underlying mechanisms. For example, multi-level studies that analyze how destructive leadership may create a hostile work environment that hinders effective information flow thus impacting technostress among followers, or supportive leadership creating a supportive environment where followers are more likely to provide support for each other, could provide valuable insights.

6 Limitations

Like all studies, our study has limitations. The first limitation refers to the process of selecting and analyzing the body of literature, which is inherently influenced by the subjective evaluations of the researchers involved. We aimed to offset this limitation by proceeding systematically and transparently in our search process.

The second limitation, that the sample size (n = 44) is small, is mitigated by its similarity to the sample sizes of other literature reviews on technostress such as Borle et al. ( 2021a , b ) with n = 21, Sarabadani et al. ( 2018 ) with n = 23, or La Torre et al. ( 2019 ) with n = 105 and our sole focus on studies that deal with both leadership and technostress. We searched 13 databases, which is a high number compared to other literature reviews in the field of economics (Hiebl 2021 ), conducted a backward search, and applied a broad search string, so we adequately covered the technostress literature that deals with leadership. While this part of the technostress literature may be small, it can be assumed that several papers deal with leadership’s effect on stress triggered by digital work without referring to the terms “technostress” or “digital stress” (e.g., Bentley et al. 2016 ). We identified some of these studies while conducting the backward search, but future reviews could search for articles on the effect, other than technostress, that leadership has on the health of followers who work in a digital work environment that may be outside the technostress literature. The limited number of studies we identified underscores the need for further conceptual discussions of the technostress construct.

The third limitation refers to the themes, aggregated dimensions, and our conceptual model, which by nature only captures certain aspects of the relationship between leadership and technostress as they were driven by our research questions and represent a generalization and abstraction of the body of literature. This also applies to how leadership is represented in our analysis. Furthermore, our results only capture a small fraction of leadership behaviors compared to the complexity of leadership in leadership research.While some leadership behaviors such as support provided by leaders (Chesley 2014 ; Dicu et al. 2022 ; e.g. Harris and Marett 2009 ; Jämsen et al. 2022 ; van Slyke et al. 2022 ; Zaza et al. 2021 ), are present in technostress literature, research lacks insights on other forms of leadership. Especially passive forms of leadership—like the laissez-faire leadership—or the transactional leadership style were not found in the technostress literature and were therefore not considered in our analysis. This limitation is aggravated by the variety of understandings of leadership that are present in leadership research and the numerous studies that do not provide a clear definition of leadership or do not sufficiently delineate leadership from management.

The fourth limitation pertains to the challenges inherent in labeling or categorizing leadership behaviors. A critical reader might point out the situational nature of leadership. We consider this contingency and argue based on it for the need to analyze leadership in the context of digital work. Furthermore, we acknowledge that there are several unobserved situational factors that do impact how leadership is acted out and perceived beyond the digital context and that leadership itself is not always stable but also object of external influences. This is particularly evident in themes 6 and 7 that emphasize the influence of digital technologies on leaderships’ impact on follower technostress.

Furthermore, our results must be seen in the context in which the identified studies were conducted, as the data many of them analyze were collected during the COVID-19 pandemic. Because of the exceptional conditions in which work was carried out during that time, the results of these studies are to be used with caution, as they may not be representative of work done in other settings. These results may not even be generalizable to remote work during the height of the pandemic, as regulations differed between countries and were not consistent throughout the pandemic.

7 Conclusion

In the context of digitalization, employees are facing demands (Ragu-Nathan et al. 2008 ) that can entail stress-related risks for the health of employees who work with digital technologies (Brown et al. 2014 ; Kim et al. 2015 ; Leung 2011 ). As new digital technologies disrupt work processes, we must ask how leadership in digital work contexts should be structured to support followers in handling new digital demands. The need to rethink how leadership affects followers’ health is also growing, as mobile digital technology and remote work change the environments in which leadership is provided and increasingly move it into digital spheres. Leadership must adapt to digitalization and the challenges that accompany it.

Given these developments, we conducted a systematical literature review to determine the status quo of leadership research in the technostress literature. To answer our first research question, we undertook an examination of the evolution of the body of literature (n = 44) over time, alongside an assessment of the methodologies employed (RQ1), showing an increase in publications dealing with that topic. Furthermore, self-reports and cross-sectional studies are predominant in literature dealing with leadership’s impact on follower technostress. To explain how leadership is related to technostress and technostress-related outcomes (RQ2), we derived a comprehensive conceptual model to map leadership’s impact on follower technostress, showing the complex relationship between different leadership behaviors and follower technostress as well as technostress-related outcomes along the transactional-based model of stress. We located leadership along the primary as well as the secondary appraisal as it had been shown to influence whether follower perceive technostress and whether technostress-related consequences such as emotional exhaustion occur. Along this process leadership has a dual influence on follower technostress, as some leadership behavior can increase as well as decrease follower technostress.

The former dimension of leadership is characterized by destructive behaviors towards followers, accompanied by high expectations for availability outside work hours and a strong tasks-orientation. These leadership behaviors can limit available resources or even become stressors themselves, thereby increasing demands in a digital work environment and challenging followers' coping abilities. In contrast, leadership behaviors that fosters autonomy, empowerment, and support represents valuable resources for followers dealing with technostress. In light of our findings, we propose that conducting longitudinal studies and examining leadership from the perspective of leaders themselves are promising avenues for future research (RQ3).

Concluding, our paper contributes to the extant discussion by analyzing the existing technostress literature on leadership and providing a conceptual model of leadership’s impact on followers’ technostress. Hereby closing a gap in current literature, as technostress represents a topic that was up to now often missed in literature reviews and meta-analyses that deal with leadership and followers' well-being (Harms et al. 2017 ; Inceoglu et al. 2018 ; Kuoppala et al. 2008 ; Montano et al. 2017 ; Skakon et al. 2010 ). As part of this conceptual model we provided a first distinction of leadership behaviors that have a diminishing (“technostress-decreasing leadership”) and an amplifying (“technostress-increasing leadership”) impact on technostress and thereby extend existing distinctions of technostress-inhibitors and technostress-antecedents (La Torre et al. 2019 ). Based on identified limitations and contradicting findings of the current body of literature we highlighted avenues for future research and thereby hope to lay a foundation as well as direction for future research on the impact leadership has on follower’s technostress.

Availability of data and material

All relevant datasets generated or analyzed during this study are included in this manuscript and its appendix. Further datasets generated or analyzed during this study are available from the corresponding author on reasonable request.

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Conceptualization: T.R., I.K. and S.S.; Methodology: T.R.; Formal analysis: T.R. and I.K.; In-vestigation: T.R. and I.K.; Writing—original draft preparation: T.R.; Writing—review and editing: I.K. and S.S.; Visualization: T.R.; Supervision: S.S.; Project administration: S.S.; Funding acqui-sition: S.S. and N.D. All authors have read and agreed to the published version of the manuscript.

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Rademaker, T., Klingenberg, I. & Süß, S. Leadership and technostress: a systematic literature review. Manag Rev Q (2023). https://doi.org/10.1007/s11301-023-00385-x

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Received : 15 February 2023

Accepted : 20 November 2023

Published : 13 December 2023

DOI : https://doi.org/10.1007/s11301-023-00385-x

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