Guest editors’ overview essay:Exploring the dark side of electronic-human resource management: towards a new PROMPT model

Citation

Behl, A., Pereira, V., Varma, A. and Tarba, S. (2022), "Guest editors’ overview essay:Exploring the dark side of electronic-human resource management: towards a new PROMPT model", International Journal of Manpower, Vol. 43 No. 1, pp. 1-11. https://doi.org/10.1108/IJM-04-2022-560

1. Introduction

As has been with other management fields, human resource management (HRM) practices have undergone a profound digital disruption, especially in large firms. The transition of HRM to electronic human resource management (e-HRM) has helped several firms gain a competitive advantage and gain more insights about their employees and applicants applying for jobs (Marler and Boudreau, 2017). The introduction of analytics in HRM has offered unique insights about employees, which has helped firms find answers to important and pertinent questions such as (1) What is the percent and pockets of employee turnover annually?, (2) What intangible skills does an employee gain in his/her tenure of work with an organization? and (3) What do employees gain and transfer in terms of “knowledge” in teamwork and within team members, over time?. Over time, organizations' implementation of HR analytics has increased rapidly, driven mainly to enhance workflow and business operations. Firms have further invested in developing learning and training modules and started to build advanced recruitment models, which are easily accessible to managers and recruiters (Sapegina and Weibel, 2017). Additionally, a new wave of analytical investment has also been in the sector of automation in HRM, which are extensively using chatbots, augmented and virtual reality and automatic processes for hiring, retaining and firing employees, which has helped firms to keep their employees engaged and on their toes (Baesens et al., 2017).

While the above discussion portrays the positive aspects of using technology for HR, there is also a significant contribution within the literature on the “dark side,” which analytics and automation have brought to HRM. Thus, studies increasingly focus on capturing the employee experience, including “IT use-induced stresses” or “technostress” for several reasons. These include circumstances like handy and disposable real-time information; remote work and flexitime with their style and instrument of working and workstations and dynamic and shorter technology cycles and rapid changing learning environment force them to learn and unlearn interfaces constantly (see, for example, Bondarouk and Brewster, 2016; Baruch and Vardi, 2016). At the institutional level, there are three categories of pressures to invest in new technologies frequently, which also involve investment in upskilling the employee workforce (Spagnoli et al., 2019). These are categorized as mimetic, coercive and normative (Boddy and Taplin, 2016). Recent studies have also discussed issues when it comes to understanding cross-technical, functional roles and learning by HR managers, most of whom do not have formal training and exposure to information technology-enabled tools, systems, knowledge, skills or abilities (Holland and Bardoel, 2016; Mariappanadar and Aust, 2017). Another aspect of the dark side of IT is the threat of employees misusing organizational IT resources and triggering “attacks” of different kinds. Unsanctioned and naive user behaviors make up the vast majority of IT misuses. The flip or dark side of the use of advanced analytics in HRM has impacted employees and the customers of companies (Son et al., 2020; Southey, 2016). Issues also included exposure reports of customer database internal management systems that involved threats by inappropriate handling of employees, which led to defaming the brand and losing reputation in the market (Van den Heuvel and Bondarouk, 2017). There are also reports that HR professionals unethically and at times illegally scan for and use such information from social media about existing and potential employees to undermine and harm their careers (see Davison et al., 2011; Gibbs et al., 2015).

The special issue thus aims at attracting manuscripts from scholars working in the interface of HRM, information systems, business analytics, ethics and related disciplines. While most of the firms are busy adopting and adapting to the changing business dynamics for inclusion of complex applications of IT and analytics, this SI would draw significant attention to understand how the dark side of the promising tech-driven functions in a company's work is affected or exploited. We thus expect this particular section to explore, analyze, reflect and research the dark side of e-HRM within the discourse for the greater good of all stakeholders, especially employees, HR managers and technology developers.

We plan this editorial piece under two sections. Section 2 discussed a brief overview of the dark side of electronic, human resource management. This section presented a thematic review of the dark side of e-HRM and showed a projective scope of pursuing research in each of the themes. Section 3 discussed and presented an overview of the accepted papers in the special issue. This section briefly discussed each accepted paper and linked them to one or more themes identified and discussed in Section 2. We concluded the editorial by offering insights and critical research questions, which are future avenues for research.

2. Scoping review of the dark side of HRM

The term HRM is now established and researched in the literature regarding its role and scope in organizations. Most of the HR functions and studies have discussed how various HRM aspects have helped firms improve their efficiency by positively affecting the employees and teams. With an increasing reliance on technology, HR functions have also been automated. While, on the one hand, it has promised automation-driven HR processes, it has also reduced the control and autonomy of the HR professionals (Chavan et al., 2021). Thus, technology has acted as both a boon and a bane (Behl et al., 2021). Along similar lines, analytics has also played a similar role. While on the one hand, it has contributed to drawing critical insights about employees and their work patterns and has helped firms predict performance and attrition. On the flipside, analytics has also empowered HR professionals to judge employees based on algorithms and models. Recent studies have also reported personal space intrusion, highlighting employees' weaknesses and taking undue advantage of employees and workplace bullying.

We systematically analyzed published works on one or more aspects of the dark side of HRM by performing a scoping review. Unlike the traditional systematic review of the literature (SLR) that understands the past's trajectory, scoping review helps in peeping for the future. According to Grant and Booth (2009, p. 93), scoping reviews are a “preliminary assessment of potential size and scope of available literature and aim to identify nature and extent of research evidence (usually including ongoing research)” A scoping review is a relatively new approach to evidence synthesis, and there is little guidance regarding the choice between a systematic or scoping review approach when synthesizing evidence. We followed the guidelines of PRISMA to identify the relevant literature for the review between the years 2010–2022. The rationale for selecting papers until 2020 was to understand the critical gaps and potential areas of research that received significantly less attention than others. We then mapped the gaps with the papers published as part of our special issue and discussed the “how” and “what” research gaps, partially addressed by the special issue papers.

We classify the scoping review results into six themes, i.e. political; regulatory; organizational; management; psychological and technological (PROMPT).

2.1 Political dark side of HRM

In conclusion, although the role of politics in executive appraisals is not “public,” it is nevertheless accessible, especially if executives are open to talking about it (and, as it turns out, executives are surprisingly willing to open up when they are disadvantaged by political actions) (Holland et al., 2022; Mariappanadar and Aust, 2017). In organizational life, politics is often associated with many particular events, but the political nature of these events is either too elusive or too cleverly concealed to be easily discerned (Holland et al., 2022). While executive appraisals are politically motivated, it is easier to detect since it is possible to be openly revealed in conversations concerning performance.

Most organizations either ignore the existence of politics in the appraisal process or assume that its impact can be minimized by refining their appraisal instruments (contrary to our expectations, most organizations use some form of appraisal, even for executives) (Holland et al., 2022; Mariappanadar and Aust, 2017). Companies with politically connected directors build “board political capital,” providing them with preferential access to benefits. Still, it may also facilitate corrupt behavior, resulting in regulatory enforcement (Jensen and Van De Voorde, 2016).

Nevertheless, it is not yet clear which attributes of board political capital may expose firms to such negative results. In this regard, recent research highlights a dark side to board political capital, which could adversely affect firms by exposing them to regulatory actions by the authorities (Jensen and Van De Voorde, 2016). Furthermore, the impact of board political capital on firm performance may not always be positive, stable or homogeneous (Sun et al., 2011). Specifically, past research has shown political connections may have a diminishing positive or even a negative effect on firm performance (Sun et al., 2011) and firm value (Sun et al., 2015) as well as the quality of financial reporting, board independence and corporate disclosure, which may contribute to higher costs of capital (Sun et al., 2015).

2.2 Regulatory dark side of HRM

Laws and regulations have a strong influence on organizations. Edelman and Suchman (1997) observe that modern organizations see themselves immersed in a sea of law. A company is born through the legal act of incorporation and dies through the legal act of bankruptcy. In between, the organization witnesses and experiences the appointment of employees following labor and antidiscrimination laws and conducting production in compliance with environmental and health and safety laws (Edelman and Suchman, 1997). The vast body of literature (including Edelman and Suchman, 1997) suggests that governments in all countries, although to varying degrees, are key actors in shaping HRM policies and practices (Holland et al., 2022; Mariappanadar and Aust, 2017).

When deciding whether to obey or evade the law, organizations in countries where the law is viewed more than as a system of incentives and penalties may not respond to it in a straightforward cost benefit analysis (Edelman and Suchman, 1997). Organizations in these situations may consider the law a moral principle that guides their actions. Hence, they adopt the law not to evade sanctions but because they consider it a responsible and proper course of action (Durst and Henschel, 2020).

2.3 Organizational dark side of HRM

Organizations increasingly use digital tools to gain insights into job applicants and previous employees (Marler and Boudreau, 2017). Additionally, HR analytics provide an automated hiring process, retention and roadmap for terminating employees (Jensen and Van De Voorde, 2016; Marler and Boudreau, 2017). It is also important to note that despite such positive contributions of HR analytics applications in organizations, there are some downsides that HR analytics has brought to the management of organizations' human resources. For various reasons, HR managers face technostress when implementing HR analytics. HR managers and other organization employees must continually learn and unlearn interfaces due to shorter, dynamic technology cycles, handy and disposable real-time information and a rapidly changing learning environment (Mariappanadar and Aust, 2017; Sun et al., 2011, 2015).

Organizations use HR analytics as a data-driven approach to managing their employees. HR analytics consists of a combination of analysis and statistics. Its applications provide employers with information about their employees. Organizations maintain several HR-related data, including employee productivity, performance, engagement, training hours and other factors (Mariappanadar and Aust, 2017; Sun et al., 2011, 2015).

2.4 Management dark side of HRM

A dark side of HRM is the negative impact of HR practice on employees. This may lead to adverse effects on the employee, such as depression, burnout or work–family conflicts. Organizations use various innovative and advanced technologies to make their human resource management systems (HRMSs) more efficient and effective (Al-Harazneh and Sila, 2021). As a result of using information technology to manage human resources within organizations, performance, employee satisfaction and competitive advantage are enhanced (Al-Harazneh and Sila, 2021; Marler and Boudreau, 2017). Therefore, we witness significant changes in the management of human resources.

With the interaction of HRM and information technology, a new method of managing human resources has emerged, known as e-HRM (Al-Harazneh and Sila, 2021; Marler and Boudreau, 2017). e-HRM refers to the implementation of HR policies through information technology (Durst and Henschel, 2020; Jensen and Van De Voorde, 2016). Organizations are using online platforms to conduct a variety of HRM activities, including talent management (Johnson et al., 2021), performance appraisal (Gardas et al., 2019) and compensation management (Durst and Henschel, 2020; Jensen and Van De Voorde, 2016).

2.5 Psychological dark side of HRM

Psychology refers to the level of employee satisfaction with their jobs and their lives, the level of commitment they have to their organization and the level of commitment to their jobs. Psychological dimensions include self-respect, satisfaction and capability (Van De Voorde et al., 2012). To be satisfied, employees' self-esteem and self-respect must be high enough, and they must also have the opportunity to improve themselves and their abilities (Van De Voorde et al., 2012).

The various articles published on the psychological aspect did describe the different types of commitment or employee satisfaction, but none of the articles investigated a decrease in employee commitment or satisfaction (Holland et al., 2022; Mariappanadar and Aust, 2017; Van De Voorde et al., 2012). Researchers investigated how to strengthen or mediate these aspects, but not how to reduce them from an employee's perspective (Holland et al., 2022; Mariappanadar and Aust, 2017; Van De Voorde et al., 2012). Thus, we decided to include articles in the data where we expected to find a dark side effect. The research question, hypothesis or theory had to explain how they investigated a negative effect (for example, researching a loss of affective commitment rather than affective commitment itself). We excluded articles expecting a positive effect but found that the effect was negative. The inability to find data in that core dimension can also be explained by the fact that when there is a loss of commitment to the organization, for example, this does not necessarily result in a negative outcome for the employee personally. This hurts the organization, but it does not mean that it has the same negative effect on the employee personally (Holland et al., 2022; Mariappanadar and Aust, 2017; Van De Voorde et al., 2012).

2.6 Technological dark side of HRM

Technology advancements and the prevalence of social networking sites (SNSs) worldwide have increased the potential for extensive misuse and abuse of these platforms (Holland et al., 2022; Marler and Boudreau, 2017). Because of the adoption of e-HRM, research and practice have typically focused on the positive aspects of social networking websites. However, less is known about the dark side of e-HRM, such as the disadvantages associated with using social networking platforms in an organization (Holland et al., 2022).

It is tempting to think of HRM as becoming increasingly “humane” over the years. However, we should not jump to conclusions so quickly. Indeed, the terms themselves reflect a shift in attitudes over time. The term “human resource management” carries a positive connotation, but not so long ago there were terms such as “personnel management,” “human capital” and “human assets” in use (Holland et al., 2022; Marler and Boudreau, 2017). In annual reports, the regular de rigueur expression that “our greatest asset is our employee” does not always reconcile with how employees are treated in some organizations in practice (Van De Voorde et al., 2012). The quantity of information accessible to individuals and organizations has dramatically shifted connected smart technologies. Such data collection might result in massive volumes of information – or misinformation – as well as cross-moral and ethical lines (Al-Harazneh and Sila, 2021; Van De Voorde et al., 2012). This is especially important in the recruitment and selection process and reputation management for both the organization and the individual. Additionally, it has become a more prominent issue, not least for HRM specialists to manage, especially since, as with other issues discussed in this paper, technological advances tend to lead the legal, ethical and managerial frameworks within which they operate (Al-Harazneh and Sila, 2021; Van De Voorde et al., 2012).

The resulting PROMPT framework calls for immediate and definitive action from respective stakeholders to mitigate risks in HRM. The following section maps the accepted papers with the six themes and posts exciting questions for future researchers to extend the six dimensions of the dark side of HRM. Figure 1 demonstrates the PROMPT framework.

3. Thematic mapping of accepted papers with PROMPT framework

The special issue on the dark side of HRM received multiple submissions that predominantly proposed one or more proposed themes. Moreover, we witness that most of the accepted papers used a major and a minor theme. We now briefly discuss a directional movement of these themes. We accepted ten papers for our special issue.

The first paper titled “Decoding the dark shades of electronic human resource management” tries to demystify the dark side of e-HRM by examining banking institutions in India, which are believed to have undergone several transformations in recent years. The current study responds to the recent calls (Bondarouk et al., 2017) to pay more attention to e-HRM by enhancing our knowledge of the dark side of technology adoption in HRM practices and its implications for both theory and practice. The study answers a critical research question – “What are perceptions and attitudes of employees towards e-HRM in public sector banks in India?” The current study examined the adoption and usage of e-HRM systems and processes by banking professionals using the transtheoretical model of change.

The second study, “Sustainable electronic human resource management systems and firm performance: an empirical study,” investigates whether ability of e-HRM practices, opportunity enhancing e-HRM practices and motivation enhancing e-HRM can lead to the development of sustainable e-HRM systems. The study addresses two key research questions: first, “What are the association between ability-enhancing e-HRM practices, opportunity-enhancing e-HRM practices, and motivation enhancing e-HRM practices with sustainable e− HRM systems?” and second, “What is the association between sustainable e-HRM systems and firm performance?”. The study uses the dynamic capability view as an overarching theory to develop the hypotheses and uses PLS-SEM to test them. The present work shares a valid connection between sustainable e-HRM systems and firm performance while considering the importance of dynamic capabilities. The results of the tested model have not supported the association between opportunity enhancing e-HRM practices and sustainable e-HRM systems, which magnifies the future research directions in this context.

The third study is “Examining the dark side of human resource analytics: an empirical investigation using privacy calculus approach.” The extant literature appears to have investigated the contributions of HR analytics in matters concerning the automated hiring process, retention process, a roadmap for the future employees and so on (Southey, 2016; Son et al., 2020). However, research on how HR analytics could cause negative consequences, especially in the aforementioned context, has remained underexplored. The study aims to identify how HR analytics can benefit organizations and increase the privacy and security vulnerabilities of employees' data. It also aims to investigate the moderating impacts of leadership support and regulation in the usage of HR analytics applications. The study draws the theoretical model based on the technology acceptance and resource-based view theories. The study measures the effect of HR analytics application on the usage of HR analytical tools using the mediating effect of perceived benefits and perceived risk. The results confirm that HR analytics is suitable for real-time decision-making and employees.

Additionally, it shows that HR analytics has a dark side, like tracking, privacy concern and data security impact perceived risk. Results agree upon the following finding – the study adds security and privacy issues regarding information sharing to the technology acceptance literature. The present study has taken a holistic attempt to explore the existing literature to understand the nexus between HRM and analytics. This study has tried to realize how the applications of HR analytics in organizations sometimes raise privacy issues of employees' data.

The fourth study is “Artificial intelligence and human workers interaction at the team level: a conceptual assessment of the challenges and potential HRM strategies.” This paper specifically aims to focus on the challenges that HRM leaders and departments in contemporary organizations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers, especially at the team level. It further discusses essential potential strategies, which can be helpful to overcome these challenges based on a conceptual review of extant research. The current paper undertakes a conceptual work that integrates multiple streams of literature to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organizations. We highlight that interaction and collaboration between human workers and robots are visible in various industries and organizational functions, working as team members.

This gives rise to unique challenges for HRM function in contemporary organizations. They need to address workers' fear of working with AI, especially about future job loss and complex dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfillment expectations with their AI-enabled robot colleagues communicate and manage HRM staff carefully to maintain the collaborative spirit and future performance evaluations of employees. The authors found that organizational support mechanisms, such as facilitating environment, training opportunities and ensuring a viable technological competence level before organizing human workers in teams with robots, are essential. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. There is the development of performance evaluation models to analyze human and AI interactions while keeping the context and limitations of both in view. We referred to the lack of existing frameworks to guide HRM managers in this concern. We stressed the possibility of taking insights from the computer gaming literature.

The fifth study is “The dark-side of E-HRM: a qualitative exploration of social networking and deviant workplace behavior in an emerging country context.” Drawing on 26 in-depth interviews of HR practitioners and analyzing their narratives surrounding employees' use of social networking (both enterprise social networks (ESNs) and SNSs), this study illuminates the dark or the adverse side of EHRM. Specifically, it focuses on the link between employees' deviant workplace behavior and their usage of SNs platforms in organizations (i.e. SNs influencing employees' unethical behavior at work). The empirical findings reveal employees' subtle intentional and unintentional indulgence via SNs in various types of deviant behaviors, such as sharing confidential information, bullying, harassment, breaching colleagues' privacy, etc., at the workplace in the emerging market context of India. Utilizing the social networking perspective and the 4Ps of deviant theory, this article describes deviant behaviors in detail. It explains the accidental complexities of leveraging SNs as an e-HRM tool at the workplace. These insights then provide a starting point for discussing the theoretical and managerial implications of the research findings.

The sixth study is “A dark side of e-HRM: the mediating role of HR service delivery and HR socialization on HR effectiveness.” The primary aim of this paper is to study a dark side of e-HRM concerning its parallel effect on HR socialization and HR service delivery and the consequent impact of perceived HR effectiveness. The current study started with an in-depth review of the extant literature in the field of e-HRM to derive a set of constructs. Based on the theoretical foundation of the identified constructs, the current study went on to derive a set of hypotheses, subsequently validated using the uses the quantitative technique of PLS-SEM. They use a primary survey, in the form of a structured questionnaire, as the source for data collection on a sample size of 276 from the Indian industrial domain. They pay careful attention to eliminate the common method bias in the study.

The seventh study titled “Does LMX always promote employee voice? A dark side of migrant working in Saudi Arabia” investigates the shady side of migrants working in Saudi Arabia. They drew on the self-consistency theory and tested a model where employees' supervisor-based self-esteem (SBSE) is positively related to their promotive and prohibitive voice and mediates the positive relationship between leader–member exchange social comparison (LMXSC) of an employee's promotive and prohibitive voice, but only for local rather than migrant workers. As predicted, there is a positive relationship between employees' SBSE and their promotive and prohibitive voice. It mediates a positive relationship between their LMXSC and their promotive and prohibitive voice, but only for local workers. Our findings support the self-consistency theory perspective on LMX and provide new insight into the “dark side” of migrant working – a lack of voice.

The eighth study is titled “Human resources developments with a touch of artificial intelligence: a scale development study.” AI can help human resources gain strategic value, thanks to its current and developing applications. AI can determine the employees' skills and support them in creating a roadmap in their career choices within the organization. However, employees can misunderstand this support sometimes. Therefore, the study develops a new scale to reveal how employees with the rise of AI in HR processes have perceived this new situation. Observations numbering 821 were analyzed out of the samples from the HR managers and employees of Turkey's largest organizations in terms of capital by applying all scientific steps of the scale development process. Using appropriate statistical criteria, the scale showed to be valid and reliable. They demonstrated general conditions in the HR departments of large companies in Turkey because of these tests.

The ninth study is titled “Explaining resistance intention towards mobile HRM application: The dark side of technology adoption.” The mobile human resource management application (mHRM app) has recently been seen as an innovative cloud-based solution to manage the organization's HRM. Despite its great potential, organizations have shown resistance towards using the mHRM app. This study investigates the dark side of e-HRM by examining factors affecting HR professionals' resistance to the mHRM app using status quo bias (SQB) theory. This study also examines the moderating effect of personal innovativeness. Responses were collected from 239 HR professionals using an online survey. Structural equation modeling (SEM) and PROCESS macro were used to examine the hypotheses. The results indicated that regret avoidance, inertia, switching costs and perceived threat significantly affect HR professionals' resistance towards mHRM app adoption. Results also indicated that high personal innovativeness negatively moderates the association between inhibitors and resistance to adopting the mHRM app.

The tenth study is “A multi-stakeholder ethical framework for AI-augmented HRM.” This narrative review presents a multi-stakeholder ethical framework for AI-augmented HRM, based on extant research in the domains of ethical HRM and ethical AI. More specifically, we identify critical ethical issues about AI-augmented HRM functions and suggest ethical principles to address these issues by identifying the relevant stakeholders based on the responsibility ethics approach. This paper follows a narrative review approach by first identifying various ethical/codes/issues/dilemmas discussed in HRM and AI. We next discuss ethical issues concerning AI-augmented HRM, drawing from the recent literature. Finally, we propose ethical principles for AI-augmented HRM and stakeholders responsible for managing those issues.

4. Conclusion

Having developed a model PROMPT as a framework for the dark side of HRM and discussed each of the ten papers in this special issue on the topic, we now classify and categorize each contribution to the elements of the model and briefly identify future research directions.

We classify the first study, “Decoding the dark shades of electronic human resource ,anagement,” under the dual categories of organizational and psychological (O & P) dark side of HRM. Based on this study, it is proposed that future studies should examine the adoption and usage of e-HRM systems and processes by other similar professionals (such as the banking professionals studied here) by using the trans-theoretical model of change.

We classify the second study, “Sustainable electronic human resource management systems and firm performance: an empirical study,” under the heads of organizational and technological (O & T) dark side of HRM. Based on this study, it is proposed that future researchers can also explore how firms can enable ethical e-HRM systems in hiring and exiting an employee.

We classify the third study, “Examining the dark side of human resource analytics: An empirical investigation using privacy calculus approach,” under the heads of organizational and management (O & M) dark side of HRM. Based on this study, it is proposed that future studies can use longitudinal data to test causality and collect data from different countries. Also, the model's explanatory power can be further improved by including data from different sectors.

We classify the fourth study, “Artificial intelligence and human workers interaction at the team level: a conceptual assessment of the challenges and potential HRM strategies,” under the heads of technological regulatory and organizational (T, O & R) dark side of HRM. Based on this study, it is proposed that future studies need to examine the type of leadership styles conducive to utilizing emerging technologies in the workplace. Future studies need to explore the psychological issues related to emerging technologies and how various HR practices could mitigate employees' psychological problems associated with emerging technologies would provide useful insights.

We classify the fifth study, “Exploring the dark-side of E-HRM: a study of social networking sites and deviant workplace behaviour,” under the heads of regulatory, technological, and management (R, T &M) dark side of HRM. Future research could validate the research model for other knowledge and intensive Internet industries. It is also worth testing whether these forms of SNs usage can explain the gravity of deviant behavior as the gravity of deviance is also an essential part of deviance behavior classifications.

We classify the sixth study, “A dark side of e-HRM: mediating role of HR service delivery and HR socialization on HR effectiveness,” under the heads of organizational, psychological and regulatory (O, P & R) dark side of HRM. Future research must focus on several contextual factors that may reduce or reinforce the hypothesized mediation relationships, like organizational technology culture, leadership, organizational citizenship behavior of employees and LMX, among others. It is also essential to investigate the mediation effect of transformational consequences of e-HRM, like HR strategic orientation, employee learning and growth, knowledge sharing and absorptive capacity.

We classify the seventh study, “Does LMX always promote employee voice? A dark side of migrant working in Saudi Arabia” under the heads of political and organizational (P & O) dark side of HRM. The study proposes to respond to calls for more research exploring the roles of macroenvironmental factors on employees' voices in the future.

We classify the eighth study, “Human resources developments with the touch of artificial intelligence: a scale development study,” under the heads of technological and organizational (T & O) dark side of HRM. The future study seeks researchers to use the scale to measure and test the linkages of HRM and AI together in similar contexts. It also calls for scale validation in different geographical contexts as well.

We classify the ninth study, “Explaining resistance intention towards mobile HRM application: the dark side of technology adoption,” under heads of psychological and technological (P & T) dark side of HRM. Future studies may use the dual-factor model (the combination of models measuring both acceptance and resistance intention) to measure digital innovation's bright and dark sides. Future studies may use other variables, such as involvement, technology readiness, perceived privacy and security concerns, to understand the phenomenon better.

We classify the tenth study, “A multi-stakeholder ethical framework for AI-augmented HRM,” under the heads of technological and psychological (T & P) dark side of HRM. Future studies are recommended on ethical principles in less-researched AI-augmented HRM functions and find issues and challenges related to those functions' ethical dimensions to hone this framework further. Adequate policies, regulations and ethical guidance based on this framework can help prevent the misuse of AI in different HRM functions.

Thus, the special issue contributes to all the six dimensions of the dark side of HRM, and the PROMPT model can be tested and applied in future studies.

Figures

Figure 1

PROMPT framework