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Abstract
We conduct an evidence-based review using an integrative synthesis of published peer-reviewed literature on Human Resource analytics (HR Analytics). Our search of several publication databases identified 60 articles on this topic, however only 14 articles were in quality peer-reviewed journals. Our review of these articles addresses the following 5 questions: (1) What is HR Analytics (how has the concept definition evolved)? (2) How does HR Analytics work (what are the processes)? (3) Why does HR Analytics work (what theories explain cause-effect relationships, antecedents, and consequences)? (4) What does HR Analytics produce (what are the outcomes)? (5) What is required for HR Analytics to succeed (what are the moderators of the analytics-outcome relationships)? We conclude that despite evidence linking the adoption of HR Analytics to organizational performance that adoption of HR Analytics is very low and academic research, and therefore, evidence on this topic is sparse. We offer potential explanations for this paradox and suggest avenues for future research.
... However, a primary and repeated reason for the strategy implementation failure is the physical or psychological 'unavailability' of people to implement strategy (Bourgeois and Brodwin, 1984;Gallup, 2021;Kahn, 1990;Nienaber and McNeill, 2022;Pfeffer in Leavy, 2016). Furthermore, it is maintained that leaders do not know how people link to strategy (Hamilton and Sodeman, 2020;Marler and Boudreau, 2017). Hence, people are deployed in positions that do not utilize their competence (CIPD, 2018). ...
... We observed the direction of reputable scholars in conducting the empirical study (Daniel, 2012;Forza, 2016;Jann and Hinz, 2017;Jansen, 2010;Kelly et al., 2003;Lavrakas, 2008;O'Leary, 2021). The limited empirical evidence on the topic investigated (Hamilton and Sodeman, 2020;Marler and Boudreau, 2017) dictated an exploratory approach (Forza, 2016;Jann and Hinz, 2017;Jansen, 2010;Lavrakas, 2008). The study aimed to uncover insights early on to lay the foundation for future descriptive and explanatory research, instead of conclusive analyses and generalizations (Forza, 2016; Jann and Hinz, 2017; Jansen, 2010). ...
... Thus, leadership development metrics used by these respondents may not have been applied to their full advantage (i.e., identifying competence domains to be developed) to accomplish competitive advantage ensuring effective strategy execution (Hogan and Warrenfeltz, 2003;Levenson, 2018). Some answers imply that the respondents did not have a clear view of the link between the people metrics used and organizational goal achievement, creating a competitive advantage, and link with business performance (CIPD, 2018(CIPD, , 2022aHamilton and Sodeman, 2020;Levenson, 2018;Marler and Boudreau, 2017;Rothwell, Hohne and King, 2018). These responses suggest an ineffective integration of leadership development to effective strategy execution, but instead and possibly fads du jour. ...
Leaders are answerable. Organizational performance is attained by successful strategy execution. Consequently, organizations heavily spend on leadership development to hone leaders’ competence aimed at ensuring the organization’s competitive success. However, the success of such programs is questioned because of, amongst others, (a) frequently reported strategy implementation failure, allegedly owing to the absence of a competitive advantage and (b) observations that leadership as a mandatory source of competitive advantage has declined, despite leadership development initiatives. Thus, the question arises whether organizations systematically use leadership development foundational metrics (e.g., direction-setting capacity, trust, etc.) for effective strategy implementation. As part of a larger study, this report accounts for organizational use of leadership development metrics in strategy implementation. We followed the guidance of reputable scholars in conducting the empirical study. Limited information on the topic dictated an exploratory approach to gain insights to lay the foundation for future descriptive and explanatory studies. The considerable amount of data required to answer the question necessitated an exploratory survey. We collected data from a purposely selected population with an online questionnaire, based on a literature review and pre-tested with Human Resource professionals, complying with ethical principles. The findings include: The study met norms for exploratory surveys and trustworthiness criteria. More than half of the diverse respondents (concerning demographic variables, strategies applied, and ensuing organizational performance) reported the use of leadership development metrics in strategy implementation. However, few respondents linked the metrics used to competitive advantage. The implications include that the leadership development interventions may not have been optimal in ensuring effective strategy implementation based on competitive advantage. It can be concluded that the leadership metrics the respondents’ organizations have used may have been ineffective in ensuring competitive success. The value of this paper stems from its actionable insights based on proven theory and validated by an exploratory survey. However, the main limitation of the study is its cross-sectional nature. Hence, we recommend further descriptive and explanatory research to enable broader generalizations.
... HR data are generally stored and processed by the so called Human Resource Information Systems (HRIS) or electronic human Resources Management (eHRM) (Johnson et al., 2016). These systems are not new, as analytics in the field of HRM has a long tradition (Marler & Boudreau, 2017). By way of example, 'The Principles of Scientific Management' was published over a hundred years ago by Taylor in 1919 and can be seen as one of the first attempt to take advantage of people data to increase productivity. ...
... There are different approaches and definitions of HRA, some of which contains shared elements that shed light on the concept of HRA (Marler & Boudreau, 2017): (a) it goes beyond HR metrics and implies the application of analytical techniques of a certain statistical sophistication; (b) it goes beyond the HR function's own data to integrate data from other functions of the organization and sometimes external data into the analysis; (c) it uses large volumes of data and therefore requires the use of information technologies to access and manipulate said data; (d) the primary focus of HRA is facilitating workforce decisionmaking; and (e), the ultimate goal of HRA is to generate an impact on organizational effectiveness through improving HR decision-making. ...
... Scholars have used different theories in order to explain the process of HRA adoption by organizations. For example, Marler and Boudreau (2017) used the Diffusion of Innovation Theory to explore the definitional aspects of the discipline in a first approach to the What, Why and How of the HRA. They also pointed out to the suitability of Institutional Theory, which has been used as a reference framework to explain the legitimacy development process of HRA in organizations as well as those limitations and accelerating factors organizations may as they develop their HRA functions (e.g., Belizón & Kieran, 2022). ...
In recognition of the growing interest in human resource analytics (HRA), this chapter provides an examination of five questions: what added value HRA offers to organizations, why HRA is necessary for strategic Human Resource Management (HRM), how HRA is carried out in practice, what are the main challenges that organizations must overcome to adopt HRA as a management practice, and finally, what are the ethical controversies that this discipline must address in the near future. HRA facilitates both predictive and prescriptive processes that require careful design and supervision. This chapter reviews the variety of theories that have been used to study the process of HRA adoption including diffusion of innovation, the LAMP model, and the knowledge discovery process (KDP). From these perspectives the authors construct an integrative strategic framework comprised of five building blocks: problem identification, data collection, data analysis, interpretation and communication, and action as well as three enabling dimensions: enterprise, leadership, and technology. The chapter concludes with a close examination of how HRA is undertaken in practice and the associated ethical implications.
... Researchers and practitioners are increasingly interested in studying and utilising data, technology and advanced analytical tools to support various organisational activities Edwin Cheng et al., 2022). This is driven by the perception that technology and emerging analytical domains like HR analytics (Xu et al., 2016;Cao et al., 2019) and supply chain analytics (Dubey et al., 2021;Agrawal et al., 2022) can empower organisations to make decisions more rapidly and with greater precision (Marler and Boudreau, 2017;Chalutz Ben-Gal, 2019). These analytics-driven decision-making approaches predominantly focus on organisational outcomes, such as performance (Mikalef et al., 2019;Rialti et al., 2019;Mikalef et al., 2020b), business value (Grover et al., 2018;Mikalef et al., 2020a) and innovation (Duan et al., 2020;Akter et al., 2022). ...
... It involves the systematic identification and quantification of the peoplerelated factors that impact business outcomes and enable organisations to make informed and improved decisions (van den Heuvel and Bondarouk, 2017). In the context of the resourcebased view (RBV), HR analytics is recognised as a valuable resource that allows Mental wellbeing through HR analytics organisations to make data-driven decisions to address challenging problems among employees, ultimately leading to a competitive advantage (Marler and Boudreau, 2017;Minbaeva, 2018). ...
... Technology-based analytics is useful in that it can analyse and provide potential information about a larger number of employees than the human handling of such issues (Singh and El-Kassar, 2019). HR analytics has also been found to positively impact employee and organisational outcomes (Marler and Boudreau, 2017;Quddus Mohammed, 2019). In alignment with RBV, analytics or technology as a resource can facilitate individual employee outcomes, contributing to the organisation's competitive advantage (Khanra et al., 2022). ...
Purpose
Organisations are increasingly adopting and adapting to technological advancements to stay relevant in the era of intense competition. Simultaneously, employee mental well-being has become a prominent global concern affecting people across various demographics. With this in mind, the present study explores the influence of human resource (HR) analytics, mental health organisational evidence-based management (OEBM) and organisational mental health support on the mental well-being of employees. Additionally, the study examines the moderating effects of manager and peer support on the association between organisational mental health support and the mental well-being of employees.
Design/methodology/approach
Data were collected from 418 employees in India and structural equation modelling was performed to analyse the data.
Findings
The study found significant positive associations between HR analytics with mental health OEBM, organisational mental health support and mental well-being. Mental health OEBM was also found to be positively related to organisational mental health support and mental well-being. The moderating roles of manager and team support were also found to be significant in the associations between organisational mental health support and well-being.
Originality/value
The study showed that HR analytics is a valuable source of mental health data. This data can facilitate the development of evidence-based management (EBM) strategies to promote the mental well-being of employees.
... Boudreau and Cascio (2017) summarized the essential prerequisites for leveraging human capital analytics in organizations based on the Logic-Analytics-Measures-Process (LAMP) framework (Boudreau & Ramstad, 2007), which encompasses strategic considerations, data management, and effective storytelling. Marler and Boudreau (2017) suggested that three pivotal determinants (analytical skills, managerial support, and HR information technology [IT]) shape the relationship between the adoption of HR analytics and organizational outcomes. ...
... First, in conducting a systematic literature review of 89 HR analytics studies published up to 2022, we provide the most updated review of existing literature on HR analytics implementation. While previous studies have provided a broad overview of the field of HR analytics (Margherita, 2022;Marler & Boudreau, 2017;Tursunbayeva et al., 2018), our study also narrows down the research scope by specifically examining the implementation of HR analytics, and in doing so, addresses the mixed results of previous studies. Second, from the overview of studies on HR analytics implementation, we identify 18 determinants that influence HR analytics implementation and delineate the interrelationships among these determinants, thereby providing a better understanding of the dynamic nature of the implementation process. ...
... Given the inherently multidisciplinary nature of HR analytics, which encompasses technology (Margherita, 2022;Vrontis et al., 2021), we opted not to confine our search to any particular discipline to ensure inclusivity across relevant literature. To maintain rigor, we limited our review to peer-reviewed studies published in highranking academic journals, referencing the 66th edition of the Journal Quality List (Marler & Boudreau, 2017). Despite the ongoing debate surrounding journal rankings, they offer a useful set of criteria for authors when choosing research. ...
Human resources (HR) analytics implementation is a field that continues to evolve, keeping pace with the increasing speed of digital innovation. However, despite its practical significance, there is a lack of knowledge of effective HR analytics implementation. Therefore, in this study, by conducting an in-depth analysis of 89 peer-reviewed HR analytics studies published during the past twenty years, we present a comprehensive summary of determinants of successfully implementing HR analytics in organizations. Furthermore, using adaptive structuration theory, we propose a dynamic framework of HR analytics implementation, offering guidance to both HR practitioners and HR scholars. Finally, we provide a research agenda aimed at stimulating future research endeavors in HR analytics.
... The topic "Human Resources Analytics" (HR Analytics) seems to have relevant space within the field of Human Resource Management (HRM): either by the authors of the field of Human Resources (HR) who approach the topic (such as Levenson et al., 2021, Marler & Boudreau, 2017Angrave et al., 2016;Pape, 2016;Rasmussen & Ulrich, 2015;Dulebohn & Johnson, 2013;Aral et al., 2012;Davenport et al., 2010;Beatty et al., 2003), either by the ten-times increased evolution in publications from early 2010s to early 2020s, as shown in Graph 1. ...
... As for definitions of terms, Margherita (2021) (who makes no relevant distinction between "HR Analytics" and "People Analytics") provides 12 proposals for HR Analytics between 2007 and 2017. Although there does not seem to be a single definition for the term, both Margherita (2021) and Marler & Boudreau (2017) converge citing elements that seem common to most definitions: ...
... The analytics in HR research agenda has still a wide range of issues as notice since Angrave et al. (2016) to Margherita (2021). Focusing in the processes issue, since Angrave et al. (2016) and Marler & Boudreau (2017) to Gal et al. (2020) and Margherita (2021), the question "how" to make analytics in HR work is still under the spotlight. ...
Since the 2000s, the HR Analytics field has experienced a steady growth in published works, with a variety of focus, but aiming the value added to HR Management. Recently, the literature has been increasingly focused on factors to be considered in HR Analytics frameworks, suggesting the question of “how” HR Analytics should be put into practice and drove by objectives; unlike initial (but still abundant) approaches of “what” should be done. This paper aims to address gaps that could help setting management resources, researching if there are relevant nuances in HR Analytics objectives that may imply in distinct ways to manage the activity. Two main approaches were combined: (i) a quantitative and qualitative analysis of recent publications and (ii) an approach under the Systems Theory constructs. HR Analytics definitions, approaches, underlying themes, related areas of study and academic gaps were analyzed from 231 publications in the Scopus database until 2021. The analysis highlighted main features of interest, which were clustered and drove to the drawing of distinct (but related) objectives and ways of manage HR Analytics. Moreover, comparisons with knowledge creation of correlated activities led to the proposition of a taxonomy as a driver to objectives and a research agenda.
... It can offer observations regarding patterns in employee performance and pinpoint opportunities for enhancement. Furthermore, AI can enable ongoing feedback and growth by automating performance evaluations (Marler & Boudreau, 2017). ...
... Privacy Issues: The collection and analysis of employee data using AI systems give rise to worries about privacy and the security of data. It is essential to guarantee adherence to data protection regulations (Marler & Boudreau, 2017). ...
... -Making: AI offers data analytics functionalities that empower HR experts to make informed choices derived from extensive datasets. Employing this datacentric approach can result in improved workforce planning and talent management(Marler & Boudreau, 2017). Employee Experience: AI-powered HR technologies have the capacity to offer employees tailored experiences, spanning from the onboarding process to career advancement. ...
... To this end, this paper draws on the contextual strategic human resources framework of Paauwe and Farndale (2017) to classify the various contextual external and internal factors, their interplay and the role of key decision-makers in driving the adoption and institutionalization of workforce analytics, and ultimately organizational performance. Moreover, because workforce analytics is still considered an HR innovation (Marler & Boudreau, 2017;Peeters et al., 2020), learnings from the more experienced field of business analytics related to adoption and institutionalization are included. This cross-disciplinary approach is a key and unique contribution of this paper, bringing the broader organizational factors of business analytics diffusion to light. ...
... Various organizational disciplines have embraced data analytics, resulting in competence areas such as customer analytics (Davenport & Harris, 2017;Siegel, 2016), marketing analytics (Artun & Levin, 2015;Katsov, 2017), process optimization (Beheshti, 2016), and risk modeling (Hopkin, 2018;Naim & Condamin, 2019). However, the field of human resources management is lagging in data-driven decision-making and, more specifically, workforce analytics (Dahlbom, Siikanen, Sajasalo, & Jarvenpaa, 2020;Marler & Boudreau, 2017;Peeters, Paauwe, & Van de Voorde, 2020). This research defines workforce analytics, interchangeably used for HR or people analytics, as an organizational practice using advanced analytics to understand the impact of the workforce and workforce interventions on business outcomes, such as operational and financial performance, employee well-being, or societal well-being institutionalization consists of the implementation and internalization stages. ...
... However, because workforce analytics is still considered an HR innovation, this literature review also included papers from the broader field of analytics related to the diffusion process of analytics. A similar approach was applied in the literature reviews of Marler and Boudreau (2017) and Peeters et al. (2020). Specific competency areas such as marketing and risk analytics did not provide enough papers related to the diffusion of analytics. ...
Data analytics plays a crucial role in enhancing organizational decision-making. Various organizational disciplines have already embraced data analytics. However, human resources management is lagging in data-driven decision-making and, specifically, workforce analytics. Although an increasing number of studies explore the diffusion of workforce analytics, our understanding of why organizations decide to adopt workforce analytics and how organizations further institutionalize workforce analytics remains limited. Taking an HRM innovation and contextualized perspective, this systematic literature review aims to provide in-depth knowledge on factors driving workforce analytics adoption and institutionalization. The results, including relevant learnings from business analytics research, show the importance of competitive, institutional, heritage mechanisms, key decision-makers and actors, and HRM fit-related factors in the diffusion process. Based on the results of this review, various avenues for future research are presented. Additionally, insights from this literature review can help decision-makers allocate their scarce resources effectively and efficiently to cultivate workforce analytics as an organizational practice.
... Then, drawing on previous reviews (e.g. Marler and Boudreau, 2017), we included academic peer-reviewed publications published in high-quality journals, following the Journal Quality List, 69th Edition. Next, we analyzed the titles and abstracts of the articles and removed those studies that were not relevant to the issue of AIenabled HRM. ...
... An exploration into the dynamic interplay among AI algorithmic features, as advocated by Stein et al. (2020), within the context of AI-enabled HRM practices could shed light on their combined effects on employees' experiences and provide a more holistic understanding of the mechanisms underlying negative outcomes. From a methodological viewpoint, taking into account the nature of AI-enabled HRM and the limited empirical method, especially longitudinal and multilevel studies (Marler and Boudreau, 2017), there is a distinct need for more longitudinal multilevel research to track employee experiences and outcomes over extended periods in order to uncover evolving trends, potential adaptation mechanisms, and the persistence of negative effects. ...
Purpose
AI is an emerging tool in HRM practices that has drawn increasing attention from HRM researchers and HRM practitioners. While there is little doubt that AI-enabled HRM exerts positive effects, it also triggers negative influences. Gaining a better understanding of the dark side of AI-enabled HRM holds great significance for managerial implementation and for enriching related theoretical research.
Design/methodology/approach
In this study, the authors conducted a systematic review of the published literature in the field of AI-enabled HRM. The systematic literature review enabled the authors to critically analyze, synthesize and profile existing research on the covered topics using transparent and easily reproducible procedures.
Findings
In this study, the authors used AI algorithmic features (comprehensiveness, instantaneity and opacity) as the main focus to elaborate on the negative effects of AI-enabled HRM. Drawing from inconsistent literature, the authors distinguished between two concepts of AI algorithmic comprehensiveness: comprehensive analysis and comprehensive data collection. The authors also differentiated instantaneity into instantaneous intervention and instantaneous interaction. Opacity was also delineated: hard-to-understand and hard-to-observe. For each algorithmic feature, this study connected organizational behavior theory to AI-enabled HRM research and elaborated on the potential theoretical mechanism of AI-enabled HRM's negative effects on employees.
Originality/value
Building upon the identified secondary dimensions of AI algorithmic features, the authors elaborate on the potential theoretical mechanism behind the negative effects of AI-enabled HRM on employees. This elaboration establishes a robust theoretical foundation for advancing research in AI-enable HRM. Furthermore, the authors discuss future research directions.
... ESS systems are web-based platforms designed to enable employees to independently manage various HR tasks. These tasks encompass accessing pay information, updating personal details, applying for leave, and enrolling in benefits (Marler & Boudreau, 2017). ...
... While ESS systems offer substantial benefits, there are potential challenges. Concerns may arise regarding data security and privacy, necessitating robust safeguards (Marler & Boudreau, 2017). Furthermore, adequate training and support for employees are crucial to ensure effective utilization of the system, a factor KCM Smelter Co. Limited should carefully consider. ...
... Considering that AI-enabled HR analytics has become more widespread, scholars have been devoted to theorizing the role of AI-enabled HR analytics in optimizing various HR practices, including employee performance management, recruitment, retention, and training and development (Cavanagh et al., 2021;Giermindl et al., 2022). Much empirical research has confirmed that AI and HR analytics may provide many benefits for employees and organizations (Marler and Boudreau, 2017;Minbaeva, 2018), such as leading to better financial performance (Aral et al., 2012), improving business performance (Coco et al., 2011), and enhancing return on investment (Harris et al., 2011). These positive performance outcomes can be achieved because organizations access massive employee data and real-time information to gain comprehensive insights into their employees (Chatterjee et al., 2022). ...
... AI-enabled HR analytics is one of the technological advancements that can lead to superior organizational outcomes (Chalutz Ben-Gal, 2019; Marler and Boudreau, 2017), such as financial returns (Harris et al., 2011) and business performance (Coco et al., 2011). Nevertheless, scant attention has been devoted to the relationship between AI-enabled HR analytics and employee well-being outcomes. ...
Purpose
Based on the JD-R model and process-focused HRM perspective, this research paper aims to investigate the processes underlying the relationship between AI-enabled HR analytics and employee well-being outcomes (resilience) that received less attention in the AI-driven HRM literature. Specifically, this study aims to examine the indirect effect between AI-enabled HR analytics and employee resilience via job crafting, moderated by HRM system strength to highlight the contextual stimulus of AI-enabled HR analytics.
Design/methodology/approach
The authors adopted a time-lagged research design (one-month interval) to test the proposed hypotheses. The authors used two-wave surveys to collect data from 175 full-time hotel employees in China.
Findings
The findings indicated that employees' perceptions of AI-enabled HR analytics enhance their resilience. This study also found the mediation role of job crafting in the mentioned relationship. Moreover, the positive effects of AI-enabled HR analytics on employee resilience amplify in the presence of a strong HRM system.
Practical implications
Organizations that aim to utilize AI-enabled HR analytics to achieve organizational missions should also dedicate attention to its associated employee well-being outcomes.
Originality/value
This study enriched the literature with regard to AI-driven HRM in that it identifies the mediating role of job crafting and the moderating role of HRM system strength in the relationship between AI-enabled HR analytics and employee resilience.
... In particular, the data driven culture conveyed by Industry 4.0, applied to HR departments, helps through HR analytics to achieve operational and strategic objectives (Huselid, 2018). In more detail, Human Resource analytics is defined as "A HR practice enabled by information technology that uses descriptive, visual, and statistical analyses of data related to HR processes, human capital, organizational performance, and external economic benchmarks to establish business impact and enable data-driven decision-making" (Marler and Boudreau, 2017). In other words, HR analytics is a set of methods and technologies that allows addressing several different issues, such as the evaluation of the performance metrics (Boyd & Gessner, 2013), the consciousness of worker well-being (Greasly & Thomas, 2020) and the assessment of their attitudes, behavior, talents (Shah et al., 2017). ...
... In particular, the evaluation of performance and competences based on data is fundamental to both increase efficiency (Garcia-Arroyo & Osca, 2019) and taking fact-based insights reducing subjectivity (Anshu and Tanuja, 2017). There are multiple definitions that have been adopted in the last 15 years, which tried to define the boundaries of the topic: extensive use of data and predictive models to drive decisions (Davenport & Harris, 2007), logical analysis that uses business data for reasoning (Fitz-enz, 2010), evidence based approach for managing people (Bassi et al., 2012;Boudreau and Jesuthasan, 2011), descriptive and visual analysis (Marler and Boudreau, 2017) and scientific and systematic methods to gauge the impact of Human capital management practices (Kryscynski et al., 2018;Van den Heuvel and Bondarouk, 2017). To summarize, the purposes are many as well as the methods that could be applied for exploiting data. ...
In recent years, the manufacturing sector has been responsible for nearly 55 % of total energy consumption, inducing a major impact on the global ecosystem. Although technological advances are increasing its sustainability , zero-emission and fuel-efficient manufacturing is still considered a utopian target. Moreover, a primary feature of Industry 4.0 is the digitization of production processes, which offers the opportunity to optimize energy consumption. However, given the speed and often unpredictability with which innovation manifests itself , tools capable of measuring the impact that technology is having professions are still being designed. In light of the above, in this article we present the Worker Profiler, a software designed to map the skills currently possessed by workers, identifying misalignment with those they should ideally possess to meet the renewed demands that digital innovation and environmental preservation impose. In more detail, the authors inferred the key technologies and skills for the topic, isolating those with markedly increasing patent trends and identifying green and digital enabling skills and occupations. Thus, the software was designed and implemented at the user-interface level. The output of the self-assessment is the definition of the missing digital and green skills that enable the definition of a customized retraining strategy.
... Prominent use cases of PA are found in every stage of employees' life cycle in a company. These include the screening of CVs during the onboarding, the analysing of performance data and resulting personalised recommendations for future trainings, the prediction of unwanted fluctuation and retention, or suggestions of potential raises (Gal, Jensen and Stein, 2017;Marler and Boudreau, 2017;Tursunbayeva, Pagliari, Lauro and Antonelli, 2019;Giermindl et al., 2021). Another increasingly popular use case is employee-wellbeing. ...
... Empirical work is scarce. Multiple literature reviews on the topic have emerged in recent years (Marler and Boudreau, 2017;Tursunbayeva et al., 2018;Chalutz Ben-Gal, 2019;Giermindl et al., 2021;Margherita, 2022). Though, as Edwards and colleagues (2022) pointed out, the existing amount of reviews surpasses the amount of content to be reviewed. ...
As work becomes increasingly decentralised, employers and employees alike are searching for tools that support (self-) organising and leadership in dispersed teams. Therefore, people analytics, as a form of algorithmic management, is increasingly gaining popularity. However, besides the alleged potential held by people analytics, it also has an inherent potential to serve as surveillance software and to perpetuate existing biases and discrimination. Whilst vendors of people analytics software provide a positive narrative and researchers from different disciplines provide extensive literature reviews, empirical insights remain scarce. Falling back on privacy calculus theory, we develop a research model to explain employees' perception of people analytics deployment in their workplace. Leveraging insights from a scenario-based online survey, we find that employees overwhelmingly disagree with the concept of people analytics. Implementing people analytics causes privacy concerns and erodes employees’ trust in their organisation to a level where they are likely to consider leaving the company.
... It is not new for HR to play the effective role of being a strategic partner in the organization, as many studies have investigated the potential for HR practices to be strategically important [5]. Internationally, HR Analytics are still in their infancy [6][7][8][9] and there is still plenty of room for researchers to conduct research in this field, such as the need for quantitative empirical studies and developing frameworks for testable hypotheses [10][11][12]. Current studies on HR Analytics have generally been undertaken in the developed countries of the USA, Australia, Canada, and Western Europe [7]. ...
... These decisions maybe related to turnover rate among employees or to performance measures that might lead to a new specific training program for the staff. However, as Marler and Boudreau's [11] review of the HR Analytics literature reveals, this topic is still in its infancy; inviting researchers to investigate its many unexplored facts to develop adequate understanding of the topic and statistically test the findings that emanate from this understanding. ...
: In this paper, we explore the factors influencing the adoption of Human Resources (HR) Analytics by HR professionals in large Palestinian enterprises. A convenience sample of 151 HR professionals from the service and manufacturing sectors participated in a questionnaire-based survey. The study identified self-efficacy, performance expectancy, effort expectancy, resource availability, quantitative self-efficacy, data availability, and social influence as the most significant factors positively influencing individual acceptance and adoption of HR Analytics. Fear appeals, on the other hand, had no significant effect. The study proposes a conceptual framework to help policymakers in organizations understand how to adopt HR Analytics.
... The role of technology in performance management is magnified in the era of digital transformation. Automated performance tracking systems, data analytics for employee assessments, and real-time feedback platforms are examples of how technology enables more efficient and effective performance management (Marler & Boudreau, 2017). The influence of organizational culture on performance becomes intertwined with the digital culture fostered during transformation. ...
This research explores digital transformation strategies to enhance company performance, identifying four common types of strategies emerging through the utilization of technologies such as artificial intelligence, data analytics, cloud computing, and the Internet of Things. Mature digital transformation strategies are key to success, focusing on specific goals and aspects. Research results indicate that companies with clear and comprehensive digital strategies tend to be more mature and achieve better performance. Digital transformation also impacts customer experience, facilitates better decision- making through data and analytics, and aligns human resources with digital technology. In conclusion, digital transformation is not just about technology; it involves digitizing all aspects of business to provide the best possible customer experience.
... Released, peer-reviewed literature that explores the direct or causal effect on corporate performance of HR analytics is comparatively scarce (Rasmussen & Ulrich, 2014;Angrave et al., 2016;Marler & Boudreau, 2017). Further academic research is required to specifically analyze how an automated and well-defined HR analytics feature ultimately contributes to better outcomes for organizations, such as corporate performance. ...
Objective: This research aims to explore and highlight the growing importance of HR analytics in the corporate sector for data-driven decision-making and strategy execution. The primary objective is to present evidence of the increasing adoption and impact of HR analytics, both in academia and the actual corporate world. The study also intends to identify the requisite experience and competencies for HR analytics practices and to propose best practices and recommendations to enhance the effectiveness of HR analytics in organizations. Method: This research involves a comprehensive literature review, examining existing research and case studies on the utilization of HR analytics in the corporate sector. Various sources, including academic papers, industry reports, and real-world examples, were analyzed to gain insights into the current state and trends of HR analytics in practice. Results: The findings of the literature review demonstrate a significant surge in interest and implementation of HR analytics in the corporate world. The data-driven approach has shown considerable promise in aiding HR professionals in making informed decisions and aligning HR strategies with overall organizational goals. Evidence from both academic and practical sources supports the value of HR analytics as a crucial tool for optimizing HR processes and enhancing workforce productivity. Conclusion: Based on the research findings, it is evident that HR analytics has emerged as a pivotal component in the corporate sector, revolutionizing how HR professionals execute strategies and contribute to organizational success. The study substantiates the need for organizations to prioritize the development of HR analytics expertise and competencies among their HR teams. Moreover, the research highlights the importance of establishing best practices and guidelines for effective HR analytics implementation, ultimately leading to better talent management and organizational performance. As HR analytics continues to evolve, future research in this field should delve deeper into addressing competency requirements and refining the strategies for harnessing the full potential of HR analytics in the corporate landscape.
... However, despite the buzz around the topic of HR Analytics, the implementation of this technology in companies could be more agile than expected. The reasons for this are the lack of skills in the technical areas of artificial intelligence and social sciences in HR departments, little sponsorship and interest from managers, risks related to privacy and data security, and high investment in IT infrastructure and means in HR (Marler and Boudreau, 2016). ...
HR Analytics is the area of Human Resources Management (HRM) that uses the techniques of artificial Intelligence, social sciences, and innovation to extract, treat, and present data for decision-making. This has been a big trend in HR in recent years, with already business cases, academic studies, and industry applications, but it is still in an early stage of development. The commercial aviation industry has people at the heart of its strategy, as it is a people-to-people service. But there are no satisfied customers without satisfied employees. In addition, the topic of aviation safety is a central one, and the sector has extensive regulations on the subject. Aviation safety is also based on human-machine interaction and crew resource management (CRM). People must therefore be in the core strategy of aviation companies because, for the provision of their service, the human factor in the interaction with the machine, the team, and the customer is a critical success factor. An appropriate approach to HR Analytics is to start with the problems that the business faces and, from there, create indicators and models that can measure them. In this paper, a sectoral and problem-based HR analytics is discussed, which is one of its main contributions. HR analytics techniques are descriptive, predictive, and prescriptive. Starting from the nature of the air operation and its problems, HR analytics is an essential strategy to better know and act on the evidence of aviation service and operation. The purpose of this publication is to understand what academic studies exist on the applications of HR Analytics to the aviation industry. Through a literature review, it was concluded that the aviation sector has also few academic studies about HR analytics; however, there are already some indicators and models that can point in the right direction for the future. This is an area that can help measure performance indicators of HR policies and provide management with important data for decision-making in human resources management. The results of this research are presented, future research paths are suggested, and the limitations of this study are pointed out.
... Nevertheless, the scope and scale at which they both have been deployed since the beginning of 2020 certainly are. Recently, scholars have provided insights into aspects such as the concept of PA or the challenges caused by ethics and privacy risks in PA literature reviews (Marler and Boudreau, 2017;Tursunbayeva et al., 2018;Tursunbayeva, Pagliari, Di Lauro and Antonelli, 2022;Chalutz Ben-Gal, 2019;Fernandez and Gallardo-Gallardo, 2020;Köchling and Wehner, 2020;Giermindl et al., 2021;Margherita, 2022). However, none of these reviews provides insights into the intertwinement of the key trends of the (post-) pandemic workplace: Leadership, PA and remote work. ...
The sudden decentralisation of work caused by the COVID-19 pandemic challenges institutionalised
work practices, which some companies seek to counter by using people analytics. Narratives around
people analytics often portray it as an enabler of remote workers’ (self-)organisation. Simultaneously,
especially when deployed for performance management, people analytics is considered an enabler of
workplace surveillance. Further, algorithmic biases in the systems can perpetuate social injustice and
discrimination of marginalised groups, impacting established hierarchies and social structures in the
workplace. Our study 1) provides an overview of the status of emerging themes around people analytics,
remote working, and leadership, and 2) assesses the impact people analytics has on shifting structures
in organisations. We guide our analysis by deploying and extending the Structurational Model of
Technology. Our results suggest that people analytics poses vastly different challenges for employees
and leaders, and that it can potentially contradict current trends towards flat hierarchies.
... Advanced analytics techniques can be utilized with social media data to build models that predict employee's attrition. Therefore, it is crucial to develop a reliable and predictive model that estimates the likelihood that an employee would quit the organization by examining existing data and identifying trends using HR Analytics [17]. It is discovered that updates on professional advancement impact job search behaviour using the theories of social contagion on SNSs and social comparison theory [18]. ...
... To present the findings, the researchers created a narrative synthesis of qualitative, quantitative, case study, commentary, and methodological studies. The research methodology is supported by empirical evidence from previously published works by (Marler & Boudreau, 2017 ;Ushara and Chandrika (2021) and (Giermindl et al., 2021) . Since integrative reviews include studies based on a variety of information sources, they can help to improve understanding of complex concepts and the state of science on disability and supernaturalism (Oermann&Knafl, 2021). ...
Disability challenges and superstitious beliefs in the society
... On the other hand, theory about managerial discretion (Shen & Cho, 2005) suggests that, although higher autonomy could signal that managers have greater discretion over both outcomes and processes, in practice less discretion is given over objectives (outcomes) than over actions (processes) as objectives are linked to the needs of powerful stakeholders (e.g., shareholders; customers). In the case of HR practices, organizational stakeholders focus more on outcomes such as absence, performance, and employee satisfaction than they do the means with which they were achieved (e.g., as an explicit focus of people analytics; Marler & Boudreau, 2017), meaning that managers experience autonomy about how to achieve these outcomes but not the outcomes themselves. This is supported by evidence that individuals who have autonomy to pursue intrinsically interesting tasks at work do so to the detriment of performance on other important but uninteresting tasks (Shin & Grant, 2019), suggesting that they receive the signal that they can choose their own way of working. ...
Line managers are often responsible for implementing HR practices in organizations. Why do some line managers implement HR practices as intended while others do not? We draw on the concept of accountability focus to highlight that managers' HR implementation behavior is driven by what they feel accountable for, and we examine how accountability focus is shaped by characteristics of managers' role. We test our theoretical model across two field studies: a three‐wave survey with managers and a study with dyads of managers and employees. When managers experienced more autonomy in their HR role, they felt more accountable for outcomes and were less likely to implement HR practices, but this was mitigated when managers also felt competent in their HR responsibilities. More competent managers felt more accountable for processes and in turn were more likely to implement HR practices, which positively related to employees' discretionary effort. Our findings highlight boundaries to managerial autonomy, and theoretical insights about the motivational mechanisms, which drive HR implementation, with implications for employees. We contribute to theory on managerial accountability by elaborating the nomological net of accountability focus and, by developing a measurement scale through several pilot studies, provide opportunities for further research.
... This equips managers with more comprehensive information to assess employee performance in terms of both outcomes and behaviors (Sharma and Sharma, 2017). HR analytics, as an evidence-based approach, aims to enhance individual and organizational performance by facilitating better decisions pertaining to the human resources aspect of the business (Marler and Boudreau, 2017). ...
Talent management is of utmost significance in contemporary organizations striving to navigate the challenges of the current environment effectively. This research aims to explore the perspectives of talent management development practices in the Sultanate of Oman and assess the influence of digital skills, human centric culture, employee wellbeing, and HR analytics on shaping talent management in the region. Employing a quantitative approach, the study was conducted across various organizations in the Sultanate. The findings are based on data collected from a sample of 207 respondents comprising human resource managers from diverse sectors in the Sultanate of Oman, obtained through an online questionnaire using nonprobability sampling. The study substantiates that variables such as digital skills, employee wellbeing, human centric culture, and HR analytics exhibit a significant positive association with talent management, thereby bolstering the mechanisms of talent management within companies in the Sultanate of Oman. These results have immediate implications for talent management practices, ensuring efficient discovery, attraction, development, evaluation, and retention of talented personnel within organizations. As a recommendation, this study proposes that all organizations in the Sultanate of Oman devise a comprehensive list of processes and HR activities to address talent management challenges in the post-COVID era, ultimately enhancing work efficiency and adeptly responding to emerging trends.
... The words "workforce analytics," "talent analytics," "people analytics," "human capital analytics," and "human resource analytics," having the same meaning and are used interchangeably in place of HR Analytics. Though these are the most often used phrase in the literature but still viewed as a relatively new concept (Marler & Boudreau, 2017). Due to the growing strategic importance of HR analytics for organizations and the acceptance of digital technology, its meaning and methodology have drastically changed over time. ...
HR analytics is becoming increasingly important for organizations to manage their workforce effectively and make data-driven decisions. Several studies have explored the current state of HR analytics in organizations, their challenges, and the emerging trends in the field. In fact, 71% of companies see people analytics as a high priority in their organizations. In this chapter, initially, the authors will focus on the emergence of HR analytics and the current form of it. Then, the chapter will focus more on the challenges associated with the integration of analytics in the organisations This chapter can help Indian HR professionals and researchers stay up-to-date with the current state and latest trends in the field. Furthermore, this chapter can highlight the challenges associated in various forms and shapes and how they can handle these challenges. This can further improve their decision-making and drive business outcomes positively.
... The field of HRM discusses this development under the umbrella term HR analytics (e.g., Edwards, Charlwood, Guenole, & Marler, 2022;Tursunbayeva, Pagliari, Di Lauro, & Antonelli, 2021). The integration of data analytics into HRM represents a disruptive and consequential innovation in the field (Marler & Boudreau, 2017;Minbaeva, 2021) that potentially increases the strategic influence of HRM on organizations' top management decisions. Core of this innovation is the so-called "epistemic shift" in HRM departments characterized by a move from typically experiential and intangible knowledge bases for HRrelated decisions (e.g., gut feeling) towards more data-driven and quantitative managerial knowledge (Davenport, 2014;Ellmer & Reichel, 2021;Loscher & Bader, 2022;Ulrich & Dulebohn, 2015). ...
Although people analytics is a fast-emerging field with importance to HRD, HRD researchers still lack a comprehensive understanding of it. This study examines the current body of knowledge in people analytics through the lens of human resource (HR) development by performing an integrative literature review of 91 articles. This study identifies five categories of knowledge: (1) definitions and boundaries of terms, (2) building blocks of people analytics in organizations, (3) types of analytics, (4) ethical issues related to people analytics, and (5) applications of people analytics to the HRD field. This study makes theoretical and practical contributions to the field of HR development by exploring the current state of people analytics and people analytics’ application to HR development practice. It also enhances scholars’ understanding of people analytics within HR development boundaries and provides insights for future research. Finally, this study provides practical guidance for HR development practitioners seeking to leverage people analytics in their work.
The need for this study arises from the increasing emphasis on employee well-being, purpose-driven cultures, and social responsibility in sustainable organizations. By investigating the relationship between E-HRM advancements and commitment, the study seeks to provide insights into how technology contributes to the overall work experience and aligns with organizational values. The objectives of the study revolve around understanding the impact of E-HRM on employee engagement, identifying key factors for talent retention, and establishing practical recommendations for organizations. Through this exploration, the study aims to contribute valuable insights to the growing body of knowledge in the realms of technology, HRM, and sustainability. The study recognizes the nuanced nature of the relationship between E-HRM advancements and employee commitment. It highlights key elements such as access to information, employee self-service, efficiency in HR processes, personalization of HR services, predictive analytics, communication, remote work support, recognition, rewards, employee well-being initiatives, and alignment with organizational values. In conclusion, this study endeavors to provide a holistic understanding of how E-HRM advancements shape employee commitment in sustainable organizations. The findings aim to guide HR professionals, organizational leaders, and policymakers in leveraging technological innovations for talent retention and sustainable business practices, offering strategic insights for organizations striving to remain competitive, socially responsible, and environmentally conscious.
Research in the field of digital HR transformation has gained significant momentum due to the influence of business transformation driven by digital technology. However, despite its growing prominence, the research on this topic remains relatively scattered and dispersed. Therefore, the authors employed bibliometric analytic methodologies in this article to portray the intellectual structure of literature related to digital developments in HR. A comprehensive analysis of 184 articles from the Scopus database is conducted using bibliometric methods, including citations, co-citations, and keyword analysis. Using bibliometric analysis, this paper thoroughly evaluates advancements made possible by digitalization in HR management. Utilizing visualization software such as Biblioshiny and VOSviewer, the analysis reveals the incremental trend of publications, research studies, affiliated organizations, and research-driven nations over time. Notably, the examination of the co-citation network using VOSviewer yields significant findings. This study contributes to the evolving body of HR literature and expands our understanding of HR digitalization through the application of bibliometric analysis.
This study investigated the relationship between human resource analytics and organizational sustainability in the chemical and non-chemical sector of Rivers State. The study employed the purposive sampling method and used descriptive method to describe systematically the relationship between human resource analytics and organizational sustainability. The population of the study consists of 16 major chemical and non-metallic companies in Rivers State. The sample size is the same as the population of the study and the source of data used for this study is mainly the primary data source. The instrument that was used for data collection is mainly questionnaire. Of 156 copies of questionnaires that were administered to the respondents, 150 which represent 97% response rate was retrieved and considered useful for the study, while the hypotheses were tested using the Spearman rank order correlation technique. The analysis of data revealed that dimensions of human resource analytic such as human resource metrics, training and development and leadership effectiveness are positively related with organizational sustainability in terms of financial performance, environmental sustainability and employee wellbeing. Based on the results of the analysis, the study concluded that human resource analytic positively and significantly relates with organizational sustainability of chemical and non-metallic companies in Rivers State, and recommends amongst others that, Chemical and non-metallic companies in Rivers State should not overlook the relevance of training and development, leadership effectiveness and human resource metrics as these will lead to organizational sustainability.
Information technology (I/T) has become a daily part of our lives. Organizations have adopted I/T for its supposed benefits and transformed the way they conduct business. Human resource management (HRM) is not exempt from changes brought by the adoption of technology within organizations. The intersection between HRM and IT is often referred to as e-HRM, and is essential for organizations because of its encouraging effect on staff productivity. Organizations in South Africa have adopted e-HRM to better manage their HR processes and activities; however, not much is known about their capabilities once adopted and are in use. This chapter's objective is to discover and understand how a typical South African organization uses e-HRM as an enabler for HR to be a strategic partner. TOE framework underpins this study. Data was collected using open-ended, semi-structured interviews from HR personnel e-HRM has the capability to handle complex environments with differentiated contracts. The study concludes that the environment plays a huge role in what happens to the e-HRM in an organization.
This study provides a comprehensive examination of the current research landscape of People Analytics (PA) from Human Resource Development (HRD) perspectives. By leveraging the methodologies of bibliometrics and topic modeling, the paper aims to illuminate key trends and emerging themes. By conducting a comparative analysis of topics and grouped themes from topic modeling and clusters from bibliocoupling, the study reveals a convergence in research focuses. This convergence is particularly evident in areas such as workforce planning and management, data-informed decision-making, applying analytics to various HR functions, and emphasizing the ethical and societal implications of data analytics in HR. The paper also identifies gaps and future research needs for HRD research in the current PA landscape and discusses fertile grounds for future research.
This study aims to explore effective public management within the framework of the integration of human resources and technology. By utilizing current literature review approaches, this study focuses on sources published within the last decade. Employing keywords related to human resource and technology integration on platforms like Google Scholar, the research aims to extract relevant and significant information from a wide range of scholarly materials. The findings in this study confirm that the integration of human resources and technology in public management is an essential foundation for creating responsive, transparent , and high-quality public services. Managing public management and optimizing public services in accelerating technology includes using digital platforms; human adaptation to technology; transparency and participation of the technology community; and data security. Meanwhile, the integration of human resources and technology in innovation and development can be described in the use of technology and data analysis; collaboration, and improvement of human resources; as well as a survival strategy not to change. Finally, to see the management of change in public management in a technological framework from the aspects of technology adoption, changes in organizational culture, service efficiency and improvement, HR training and development, and monitoring and evaluation.
İnsanlık doğduğu günden bu yana sürekli bir veri akışı yaratmaktadır ve bu veriler yaşamın her alanına yönelik önemli bilgiler sunmaktadır. Özellikle 2000’li yılların başından itibaren teknolojide meydana gelen gelişmeler sayesinde geleneksel veri toplama ve analiz yöntemlerini bir kenara bırakan büyük veri analitiği konuşulmaya başlanmıştır (Lavalle vd., 2011, s. 22; Zang ve Ye, 2015, s. 41). Büyük veri kavramının kullanımı 1990’lı yıllara dayansa da 2010’dan itibaren yaygın olarak kullanılır hale geldiği söylenebilir (Narı̇n vd., 2017, s. 218). 2001 yılında Gartner analisti Douglas Laney'nin "3D veri yönetimi: Veri hacmini, hızını ve çeşitliliğini kontrol etme" başlıklı makalesi, büyük verileri iş dünyasının ve akademinin odağına taşımıştır. Laney'nin makalesi çok sayıda büyük veri çalışmasının temeli olarak görülmektedir (Scholz, 2017, s. 12). Büyük veri; geleneksel veri tabanı teknikleri kullanılarak işlenmesi mümkün olmayan heterojen veri (Gahi vd., 2016, s. 953) olarak tanımlanmaktadır.
Our Special Issue is focused on the healthcare sector relevant to the Asia Pacific region, including hospitals, aged care facilities, allied health, doctors, nurses, management and administration staff and all services associated with the healthcare industry. There are a range of issues that impact on healthcare including the growing use of health services during the pandemic, emergency situations, complex forms of technology, worker expectations, work intensification, and government reporting requirements. More research needs to be carried out in these issues as well as social policy, the delivery and quality of patient care, gender in the workplace, disability, and management innovation (Cooke and Bartram, 2015; Human Resource Management, 2015, 54, 711). There are high levels of stress due to staff being overworked and experiencing a lack of coping skills (Pariona‐Cabrera et al., 2023; Health Care Management Review, 2023, 48, 42), burnout manifestations through emotional exhaustion (Maslach, 2017; Consulting Psychology Journal: Practice and Research, 2017, 69, 143) which often result in intention to leave (Holland et al., 2019; Applied Nursing Research, 2019, 49, 70; Pariona‐Cabrera, Cavanagh and Bartram, 2020; Journal of Advanced Nursing, 2020, 76, 1581; Shao et al., 2023; Human Resource Management Journal, 2023, 33,187). In Australia, more than 70% of 366,000 nurses working in aged care facilities have reported at least one experience of workplace violence during the previous 12 months including physical and verbal violence from residents, relatives, and visitors (Schablon et al., 2018; International Journal of Environmental Research and Public Health, 2018, 15, 1274). There are too many managers who rely on underdeveloped HR processes and outdated management perceptions to make decisions about the well‐being of healthcare staff. Countries in the Asia‐Pacific region are actively seeking partnership projects and new ways to enhance the performance of healthcare staff and their organisations. We have touched on broad issues here and argue it is possible some of the answers can be found in the use of HR analytics and artificial intelligence (AI).
Purpose
The study explores the factors affecting the use of smart human resource management 4.0 (SHRM 4.0) practices and its effect on dynamic capabilities and, consequently, on organizational performance.
Design/methodology/approach
The authors used socio-technical and dynamic capabilities theory to propose the notable research model. The authors explored the factors driving the use of SHRM 4.0 practices and their contribution to organizational performance through the development of dynamic capabilities. The authors collected data from 383 senior HR managers using a structured questionnaire, and PLS-SEM was used to analyze the data.
Findings
The results show that socio-technical factors such as top management support, HR readiness, competitive pressure, technology readiness and perceived usefulness influence the use of SHRM 4.0 practices, whereas security and privacy concerns negatively influence them. Furthermore, the authors also found the use of SHRM 4.0 practices influencing the dynamic capacities (build (learning), integration and reconfiguration) and, subsequently, its impact on organizational performance.
Originality/value
Its novelty lies in developing a model using dynamic capabilities and socio-technical theory to explore how SHRM 4.0 practices influence organizational performance through dynamic capabilities. This study extends the literature on SHRM 4.0 practices, HR technology use, HR and dynamic capabilities by contributing to socio-technical theory and dynamic capabilities and expanding the scope of these theories in the area of HRM. It provides crucial insights into HR and top managers to benchmark SHRM 4.0 practices for improved organizational performance.
Existing scholarship offers a comprehensive understanding of the concept and purposes of human resource analytics (HRA). However, how HRA is carried out in practice in organisations is still under‐researched. We examine the practice of HRA through a systematic review across three disciplines, namely, human resource management, business analytics and management information systems while using a process lens: the knowledge discovery process (KDD) model. A hundred and three high‐end quality manuscripts were analysed. Our findings show that the scope of HRA is expanding both in the use of HR and business data and certain sophisticated statistical techniques. However, much needs to be done to uncover the measurable impact of HRA on HR and business outcomes.
Recently, education and teaching have been significantly impacted by information and communication technologies. New cohorts of students, COVID-19 pandemic and pressure in the labour market on the labour force to master the technology-related skills and competence serve as main drivers for universities to redesign the way of teaching. A radical transformation of education caused by technologies is related to several aspects, such as online teaching or using other technologies in both physical and online learning environments with the focus on student-centred learning. The existing literature suggests that educational innovation through technologies allows for the adoption of collaborative, inclusive and student-driven pedagogy. The paper aims at revealing educational innovation through information and communication technologies in one of the courses for master’s students, namely People Analytics. While disclosing the particular case of one course, the paper seeks to provide the argumentation (advantages and disadvantages) for choosing specific tools and how these tools are embedded. The use of tools such as Zoom, digital escape rooms, Mentimeter, and Padlet, is presented. The paper concludes that technologies may offer many wide-ranging benefits in education; however, the further study is needed for revealing the students’ acceptance of technologies and the impact of technologies on learning outcomes.
The digital transformation is the scenario of integral change that organizations have experienced in recent years, within Industry 4.0. Organizations carry out their own internal digital transformation that involves changing organizational culture, redesigning business models and strategy. The paradigm of the new digital economy requires the creation of new talent management models through human resource practices that drive the changes inherent in digital transformation. Innovation has become a permanent factor in generating competitive advantages for companies. New digital skills and talent management models based on technologies such as HR Analytics and Artificial Intelligence (AI) are required. Companies must adopt new strategies for attracting and retaining talent, given the growing talent shortage. On the other hand, technology allows companies to personalize the job and professional offer, generating new lines of relationship between talent and the organization.
This research paper delves into the intricate interplay between workplace automation and Human Resources (HR) practices within contemporary organizations. The advent of automation technologies, including artificial intelligence, robotics, and advanced data analytics, has profoundly reshaped the work landscape, necessitating HR departments to adapt and evolve their strategies. This paper explores the multifaceted impact of automation on various HR functions such as recruitment, training and development, employee engagement, and workforce planning. Through a comprehensive analysis of existing literature up to 2019, this paper provides insights into the challenges and opportunities that HR professionals encounter due to workplace automation. Moreover, it offers recommendations for organizations to effectively harness the benefits of automation while ensuring the well-being and growth of their workforce.
The ability to thoroughly investigate the literature pertaining to particular themes is made possible by bibliometric analysis. The goal of this study is to use bibliometric analysis to explain the literature review of research on the topics of green human resource management (GHMR) and environmental performance. GHRM stands for a human resource management strategy that emphasizes sustainability. Environmental performance is defined as how successfully firms carry out their operations while taking the environment into account. Performance analysis and scientific mapping bibliometric analysis techniques were applied in this research. The target literature is the Scopus database, which includes the concepts of GHRM and environmental performance. In the study, Open Access studies were included. According to the bibliometric analysis findings, forty-five publications and two thousand two hundred twenty-four citations were found between the years 2015-2023. It has been determined that eighteen countries are the most contributing countries in this field. The number of co-authorships of the countries was determined and it was observed that China and Pakistan co-authors mostly conducted research on these concepts. In addition, universities and databases that contributed the most to this field were determined. GHRM and environmental performance trends are explained by making inferences based on the findings. As a result of the research, the current situation was revealed and suggestions were presented for future research.
Evidence‐based management (EBM) is a useful framework to assist managers in making organizational decisions based on the best available evidence. EBM use is nevertheless marginal among managers, and little is known about the enablers that can facilitate and effectively increase its use. We use two experimental studies to examine the effect of cognitive reflection, learning goals, and social norms in predicting EBM usage. We also propose an objective assessment task to measure the collection and use of evidence in the context of EBM. Results from both studies provide support for the importance of cognitive reflection and social norms to enable EBM. Surprisingly, learning goals were not associated with EBM use. This research increases our understanding of EBM, provides indications of how to increase its usage, and presents a methodology to investigate evidence collection and use objectively.
Zusammenfassung
Dieser Beitrag in der Zeitschrift „Gruppe. Interaktion. Organisation. (GIO)“ gibt einen Überblick über die vielfältigen Digitalisierungs- und Automatisierungsmöglichkeiten, die aktuelle technologische Entwicklungen für die Weiterbildung in Organisationen eröffnen, und diskutiert Chancen und Risken ihres Einsatzes.
Um wettbewerbsfähig, effizient und produktiv zu bleiben, müssen Organisationen sicherstellen, dass ihre Beschäftigten sich fortwährend weiterbilden und entwickeln. Die Weiterbildung aller Beschäftigten in allen notwendigen Kompetenzbereichen durch entsprechende Maßnahmen beansprucht jedoch viele Ressourcen. Um diese Ressourcen optimal einsetzen zu können, muss der Kompetenzentwicklungsbedarf der Beschäftigten kontinuierlich und zutreffend ermittelt werden, damit dieser auch durch passende Weiterbildungsmaßnahmen gezielt und adäquat adressiert werden kann. Auch diese übergeordneten Prozesse der Weiterbildung sind ressourcenintensiv. Daher wurde bereits in der Vergangenheit eine Vielzahl von Technologien eingesetzt, um die organisationale Weiterbildung (bspw. durch digital zur Verfügung gestellte Materialien zum Selbststudium) und die damit zusammenhängenden Prozesse durch Digitalisierung effizienter gestalten und verwalten zu können. In diesem Beitrag betrachten wir vor allem die vielfältigen Digitalisierungs- und Automatisierungsmöglichkeiten, die aktuelle technologische Entwicklungen eröffnen, und führen diese – strukturiert am Prozess der Personalentwicklung – mit Beispielen aus Forschung und Praxis aus.
Purpose
The research paper aims to analyse the scholarly literature on advancing HR analytics as an intervention for attrition, a problem that lingers on organisational performance. This study aspires to provide an in-depth literature review and critically assess the knowledge gaps in HR analytics and attritions within organisational performance.
Design/methodology/approach
The review analyses the corpus of 196 research articles published in ostensible journals between 2011 and 2023. To identify research gaps and provide valuable insights, this study synthesises relevant studies using School of thought (S), Context (C), Methodology (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) (SCM-TBFO framework). This study employs the R programming language to conduct a systematic literature review in accordance with the “preferred reporting items for systematic reviews and meta-analysis” (PRISMA) guidelines.
Findings
The emerging discipline of HR analytics encompasses the potential to manage attrition and drive organisational performance enhancements effectively. The study of SCM-TBFO encompasses a multidimensional approach, incorporating diverse perspectives and analysing its complex aspects compared to various approaches. The School of thought includes the human capital theory, expectancy theory and resource-based view. The varied research contexts entail the USA, United Kingdom, China, France, Italy and India. Further, the methodologies adopted in the studies are artificial neural networking (ANN), regression, structure equation modelling (SEM) case studies and other theoretical studies. HR analytics and attrition triggers are data mining decision systems, forecasting for firm performance and employee satisfaction. The barriers include leadership styles, cultural adaptability and lack of analytic skills, data security and organisational orientation. The facilitators were categorised into data and technology-related facilitators, human resource policies and organisational growth and performance-related facilitators. The study's primary outcomes are technology adoption, effective HR policies, HR strategies, employee satisfaction, career and organisational expansion and growth.
Originality/value
The primary goal of the literature review is to provide a comprehensive overview of the current state of HR analytics and its impact on organisational performance, particularly in relation to attrition. Further, the study suggests that attrition, a critical organisational concern, can be effectively managed by strategically utilising HR analytics and empowering data-driven interventions that optimise performance and enhance overall organisational outcomes.
Human resource analytics (HRA) has the power to revolutionize how businesses find, develop, oversee, and manage their employees. It is imperative to pay attention to the idiosyncrasies and negative implications that HRA creates leading to commotion and failing to generate value for the organizations. The chapter discusses the challenges faced in the implementation of HRA in diverse businesses. For this analysis, the authors conducted an extant literature review and later interviewed HR professionals to derive factors contributing to the dark side of HRA. The interviews were transcribed, and five themes were derived representing the experiences of the respondents with HRA implementation. This chapter gives a comprehensive understanding of the challenges faced in the implementation of HR Analytics and suggests ways to overcome these challenges as well.
This chapter explores the impact of job insecurity on psychological well-being in the context of the COVID-19 pandemic. This chapter is based on empirical study measuring the six elements of job insecurity on psychological wellbeing, i.e., perceived threats to job features, role insecurity, role conflict, powerfulness, meaningfulness, and perceived threats to total job. Further, this chapter the role of HR analytics in ensuring psychological wellbeing and job security, with a focus on the lessons learned during the COVID-19 pandemic. highlights the importance of HR analytics in identifying and addressing employee needs related to psychological wellbeing and job security, and explores the ways in which HR analytics can be used to improve organizational decision-making and drive business outcomes. This chapter also briefly highlights the emerging practices, and the ways modern digital technologies can be harnessed for the betterment of the employees.
This study synthesizes the various studies on the construct of employee engagement and HR analytics. This is a theoretical and methodological study substantiating the factors identified from the literature causing employee engagement and its effect on organizational performance indicators. This chapter is descriptive at first as it defines the employee engagement and HR analytics construct. Secondly, this study has the feature of being diagnostic to identify the cause and effect of employee engagement. Lastly, the study has the characteristic of being a prescriptive study to suggest solutions based on data derived through HR analytics to enhance the engagement level of employees. Thus, this three-fold study (descriptive, diagnostic, and prescriptive) is a readymade solution kit for management to investigate the low level of employee engagement through the lens of HR Analytics.
The main emphasis of this chapter is to identify the effect of motivation on variables of employee job performance in people analytics, which is seen as one of the major initiatives in human resources. The secondary sources have been utilised to identify the sources of the thematic approach. Considering this, the study explains how to determine the moderating factors in people analytics. The chapter offers an introduction to problem identification and focuses on detailed literature that helps in finding factors relevant according to the theme that has been elaborated in a thematic approach. A part of the Prisma model has been used to explain the four stages of literature identification. The moderating factors have been better explained through the case studies, and one case study has been explained in the context of an Indian scenario. While explaining the moderating factors, thematic methods have been used using manual screening. The major highlights have been reviewed, discussed, and summarised.
The debate over eliminating performance ratings addresses many important theoretical and practical issues. However, the academic debate on the topic is disconnected from the concerns of practitioners. Knowledge gained from theory-driven research is not leading practice on the use of performance ratings, despite the large volume of potentially relevant research findings. Many organizations are charging ahead with performance management solutions that seem sensible to them. They may be interested in academic research, but they are not waiting for it. We will argue that academic researchers who hope to influence practice need to better understand the concerns of practitioners and the research opportunities that are presented by contemporary practice.
The HR world is abuzz with talk of big data and the transformative potential of HR analytics. This article takes issue with optimistic accounts, which hail HR analytics as a ‘must have’ capability that will ensure HR's future as a strategic management function while transforming organisational performance for the better. It argues that unless the HR profession wises up to both the potential and drawbacks of this emerging field and engages operationally and strategically to develop better methods and approaches, it is unlikely that existing practices of HR analytics will deliver transformational change. Indeed, it is possible that current trends will seal the exclusion of HR from strategic, board-level influence while doing little to benefit organisations and actively damaging the interests of employees.
The HR world is abuzz with talk of big data and the transformative potential of HR analytics. This article takes issue with optimistic accounts, which hail HR analytics as a ‘must have’ capability that will ensure HR's future as a strategic management function while transforming organisational performance for the better. It argues that unless the HR profession wises up to both the potential and drawbacks of this emerging field and engages operationally and strategically to develop better methods and approaches, it is unlikely that existing practices of HR analytics will deliver transformational change. Indeed, it is possible that current trends will seal the exclusion of HR from strategic, board-level influence while doing little to benefit organisations and actively damaging the interests of employees.
Human resource (HR) analytics is touted to have the potential to bring great value to general managers’ and HR leaders’ decision-making on human and organization capital by supplementing intuition and experience with evidence. Yet, it currently risks becoming another management fad, because HR analytics has too often taken an “inside-out,” HR-centric, and academic approach being governed by a Center-of-Expertise (CoE) distant from the business. A shift towards an “outside-in” approach with a focus on actionable, high-impact analytics is needed. This development is accelerated by technology, which is rapidly consolidating the analytics landscape. This shift enables HR analytics to be taken out of HR and become part of existing end-to-end business analytics, where human resources is just one element in the value chains analyzed. This leads to more business relevant findings and impactful interventions, as illustrated in two cases.
Research dealing with various aspects of* the theory of planned behavior (Ajzen, 1985,
1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is
found to be well supported by empirical evidence. Intentions to perform behaviors of different
kinds can be predicted with high accuracy from attitudes toward the behavior, subjective
norms, and perceived behavioral control; and these intentions, together with perceptions of
behavioral control, account for considerable variance in actual behavior. Attitudes, subjective
norms, and perceived behavioral control are shown to be related to appropriate sets of salient
behavioral, normative, and control beliefs about the behavior, but the exact nature of these
relations is still uncertain. Expectancy value formulations are found to be only partly
successful in dealing with these relations. Optimal rescaling of expectancy and value
measures is offered as a means of dealing with measurement limitations. Finally, inclusion of
past behavior in the prediction equation is shown to provide a means of testing the theory*s
sufficiency, another issue that remains unresolved. The limited available evidence concerning
this question shows that the theory is predicting behavior quite well in comparison to the
ceiling imposed by behavioral reliability.
This paper surveys the development of the American human resource management field from the late 19th century to the start of the 21st century. Important people, ideas and events are identified as are contributing fields of study and schools of thought. Interesting and sometimes revisionist insights emerge, partly because human resource management is defined broadly to include industrial relations and personnel economics. The historical analysis is also used to derive implications for improving the current-day HRM research program.
Drawing on the ability-motivation-opportunity model, this meta-analysis examined the effects of three dimensions of HR systems-skills-enhancing, motivation-enhancing, and opportunity-enhancing-on proximal organizational outcomes (human capital and motivation) and distal organizational outcomes (voluntary turnover, operational outcomes, and financial outcomes). The results indicate that skill-enhancing practices were more positively related to human capital and less positively related to employee motivation than motivation-enhancing practices and opportunity-enhancing practices. Moreover, the three dimensions of HR systems were related to financial outcomes both directly and indirectly by influencing human capital and employee motivation as well as voluntary turnover and operational outcomes in sequence.
In this theory development case study, we focus on the relations across recurrent waves in the amount and kind of language promoting and diffusing, and then demoting and rejecting, management techniques—techniques for transforming the input of organizational labor into organizational outputs. We suggest that rather than manifesting themselves as independent, transitory, and un-cumulative fads, the language of repeated waves cumulates into what we call management fashion trends. These trends are protracted and major transformations in what managers read, think, express, and enact that result from the accumulation of the language of these consecutive waves. For the language of five waves in employee-management techniques—management by objectives, job enrichment, quality circles, total quality management, and business process reengineering—we measure rational and normative language suggesting, respectively, that managers can induce labor financially or psychologically. The results reveal a gradual intensification in the ratio of rational to normative language over repeated waves, suggesting the existence of a management fashion trend across these techniques. Lexical shifts over time, however, serve to differentiate a fashion from its predecessor, creating a sense of novelty and progress from the earlier to the later fashions.
Strategic human resources management (HRM) remains one of the most popular and rapidly growing areas of HRM research. In this article, we undertake a selective review of the strategic HRM literature with a particular emphasis on research from the North American context. After outlining the research landscape and areas of consensus and disagreement, we discuss several emerging issues that effective HRM systems must contend with in the future, including technological fluidity, workforce demographic changes and shifting worker values. With an eye toward future research opportunities, we also discuss the broadening of performance outcomes in strategic HRM research and highlight the importance of effectively managing HRM systems for multiple employee groups.
The strategic management of human resources (HR) has been one of the most rapidly growing areas of research within human resources. In the last decade, there have been numerous empirical examinations and theoretical treatments of the link between HR and firm performance. In this paper, we review this empirical and conceptual literature and highlight areas of agreement and those that need further development. We then begin the process of building a conceptual framework based on this review and the extensive employment systems literature. Using our framework, we then discuss several methodological concerns that must be addressed for continued substantive research to proceed. We conclude with our suggestions for future empirical and conceptual work.
We describe why human resource management (HRM) decisions are likely to have an important and unique influence on organizational performance. Our hope is that this research forum will help advance research on the link between HRM and organizational performance. We identify key unresolved questions in need of future study and make several suggestions intended to help researchers studying these questions build a more cumulative body of knowledge that will have key implications for both theory and practice.
Examines research on the relation between attitude and behavior in light of the correspondence between attitudinal and behavioral entities. Such entities are defined by their target, action, context, and time elements. A review of available empirical research supports the contention that strong attitude–behavior relations are obtained only under high correspondence between at least the target and action elements of the attitudinal and behavioral entities. This conclusion is compared with the rather pessimistic assessment of the utility of the attitude concept found in much contemporary social psychological literature. (4½ p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Guided by a general manager's perspective of human resources management (HRM), this paper identifies key factor affecting the introduction of HRM innovations in organizations. Because the essence of market and technological leadership is the development of the organizational capacity to carry out inventive ideas, it is critical to understand the main forces influencing HRM innovation. Following a definition of HRM innovation, six propositions are discussed using current and historical examples. Since HRM innovation also involves change in the social system of the organization, the adoption and diffusion of these innovations can be attributed not only to external environmental forces but also to social processes.
Despite a significant degree of academic and practitioner interest the topic of talent management remains underdeveloped. A key limitation is the fact that talent management lacks a consistent definition and clear conceptual boundaries. The specific contribution of the current paper is in developing a clear and concise definition of strategic talent management. We also develop a theoretical model of strategic talent management. In so doing we draw insights from a number of discreet literature bases. Thus, the paper should aid future research in the area of talent management through (1) helping researchers to clarify the conceptual boundaries of talent management and (2) providing a theoretical framework that could help researchers in framing their research efforts in the area. Additionally, it aids managers in engaging with some of the issues they face with regard to talent management.
This chapter advocates the good scientific practice of systematic research syntheses in Management and Organizational Science (MOS). A research synthesis is the systematic accumulation, analysis and reflective interpretation of the full body of relevant empirical evidence related to a question. It is the critical first step in effective use of scientific evidence. Synthesis is not a conventional literature review. Literature reviews are often position papers, cherry-picking studies to advocate a point of view. Instead, syntheses systematically identify where research findings are clear (and where they aren't), a key first step to establishing the conclusions science supports. Syntheses are also important for identifying contested findings and productive lines for future research. Uses of MOS evidence, that is, the motives for undertaking a research synthesis include scientific discovery and explanation, improved management practice guidelines, and formulating public policy. We identify six criteria for establishing the evidentiary value of a body of primary studies in MOS. We then pinpoint the stumbling blocks currently keeping the field from making effective use of its ever-expanding base of empirical studies. Finally, this chapter outlines a) an approach to research synthesis suitable to the domain of MOS and b) supporting practices to make synthesis a collective MOS project.
This paper comprehensively examined the linkages between systems of High Performance Work Practices and firm performance. Results based on a national sample of nearly one thousand firms indicate that these practices have an economically and statistically significant impact on both intermediate outcomes (turnover and productivity) and short- and long-term measures of corporate financial performance. Support for the predictions that the impact of High Performance Work Practices is in part contingent on their interrelationships and links with competitive strategy was limited.
What makes organizations so similar? We contend that the engine of rationalization
and bureaucratization has moved from the competitive marketplace to the state and
the professions. Once a set of organizations emerges as a field, a paradox arises:
rational actors make their organizations increasingly similar as they try to
change them. We describe three isomorphic processes--coercive, mimetic, and
normative-leading to this outcome. We then specib hypotheses about the impact of
resource centralization and dependency, goal ambiguity and technical uncertainty,
and professionalization and structuration on isomorphic change. Finally, we suggest
implications for theories of organizations and social change.
Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empiri- cally compare the eight models and their exten- sions, (3) formulate a unified model that integrates elements across the eight models, and (4) empiri- cally validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models ex- plained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Tech- nology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted
The authors compare and contrast two theoretical approaches to explaining a firm’s choice of human resource management (HRM) practices—one from strategic human resource management (SHRM) and the other from economics. They present HRM frequency distributions depicting key empirical patterns that both theories must explain and then review and apply SHRM theory to explain these patterns. Since no economic model has thus far explicitly considered firms’ choice of HRM practices, the authors develop one based on standard microeconomic production theory. The model yields a new theoretical construct, the HRM demand curve, and a new empirical estimating tool, the HRM demand function. Together, these provide an alternative explanation of HRM frequency distributions, new insights on the limitations of SHRM theory, and the first alternative to the standard “Huselid-type” regression model. Using recent survey data on HRM practices at several hundred American firms, the authors estimate representative HRM demand functions to illustrate the empirical implementation of the model. They find that although both theoretical approaches have value, the economic model seems superior in terms of generality, logical coherence, predictive ability, and congruence with empirical data.
Do investments in your employees actually affect workforce performance? Who are your top performers? How can you empower and motivate other employees to excel? Leading-edge companies such as Google, Best Buy, Procter & Gamble, and Sysco use sophisticated data-collection technology and analysis to answer these questions, leveraging a range of analytics to improve the way they attract and retain talent, connect their employee data to business performance, differentiate themselves from competitors, and more. The authors present the six key ways in which companies track, analyze, and use data about their people-ranging from a simple baseline of metrics to monitor the organization's overall health to custom modeling for predicting future head count depending on various "what if" scenarios. They go on to show that companies competing on talent analytics manage data and technology at an enterprise level, support what analytical leaders do, choose realistic targets for analysis, and hire analysts with strong interpersonal skills as well as broad expertise.
In this paper the focus is on how organizations select, adapt and retain best practices in HRM. Based on recent developments in two streams of thyeoretical thinking, i.e., new institutionalism and strategic management (especialy co-evolution and absorptive capacity), this paper contrasts economic rationality with normative rationality in the selection, adaptation and retention process. In this way we are able to construct the life cycle of a HRM best practice, the way in which companies differ in their speeed of selection and adoption of best practices, and the consequences this has for whether or not being able to achieve a competitive advantage. After presenting and describing our framework for the adoption and life cycle of best practices in the field of HRM, a range of hypotheses is presented to be tested for in follow-up research.
This paper presents the results of the largest HR Analytics study to date in terms of Fortune 1000 companies. 220 distinct firms participated in the study. The purpose of the study was to explore the meaning of HR analytics by those who perform HR research and analytics work. Common HR research analytics practices conducted in organizations were identified. The study also examined the extent to which HR analytic projects inform HR strategy and workforce decisions. Lastly, the privacy and ethical implications of the HR analytics movement were discussed.
The popularity of business intelligence (BI) systems to support business analytics has tremendously increased in the last decade. The determination of data items that should be stored in the BI system is vital to ensure the success of an organisation's business analytic strategy. Expanding conventional BI systems often leads to high costs of internally generating, cleansing and maintaining new data items whilst the additional data storage costs are in many cases of minor concern – what is a conceptual difference to big data systems. Thus, potential additional insights resulting from a new data item in the BI system need to be balanced with the often high costs of data creation. While the literature acknowledges this decision problem, no model-based approach to inform this decision has hitherto been proposed. The present research describes a prescriptive framework to prioritise data items for business analytics and applies it to human resources. To achieve this goal, the proposed framework captures core business activities in a comprehensive process map and assesses their relative importance and possible data support with multi-criteria decision analysis.
The "mental models" used in organizations often reflect disciplines such as finance, marketing or engineering. Such models can overlook or misinterpret evidence related to human capital, producing poor human-resource (HR) and organizational decisions. Improved evidence-based HR decisions may result from "retooling" HR issues using logic from mental models in other management disciplines. HR researchers and practitioners can tap the power of these well-accepted logic frameworks to "retool" evidence about HR management.
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are heterogeneously distributed across firms and that these differences are stable over time, this article examines the link between firm resources and sustained competitive advantage. Four empirical indicators of the potential of firm resources to generate sustained competitive advantage-value, rareness, imitability, and substitutability are discussed. The model is applied by analyzing the potential of several firm resources for generating sustained competitive advantages. The article concludes by examining implications of this firm resource model of sustained competitive advantage for other business disciplines.
One stated purpose of electronic human resource management (e-HRM) is to make the HRM function more strategic. The goal of this paper is to examine the research on e-HRM to provide evidence-based guidance to researchers and practitioners on the relationship between e-HRM and strategic HRM. We review 40 studies published from 1999 to 2011 using integrative synthesis as our evidence-based methodology. Results reveal that theoretical and empirical research in this area is still at an early stage. We find no empirical evidence showing that e-HRM predicts strategic outcomes. There is evidence suggesting that strategic HRM predicts e-HRM outcomes and that the relationship appears context dependent, however, research designs are not sufficient to establish causal direction. Our review highlights the need for more empirical studies on e-HRM and strategic HRM outcomes at a macro level.
Purpose
– More and more, the leaders of business functions are turning for competitive insights to the massive data they can now capture. But to date, human resources departments have lagged behind the efforts of marketing, IT, CRM and other functions. The purpose of this article is to show how executives can start using data to measure and improve HR's contributions to business performance.
Design/methodology/approach
– The article identifies six analytical tools that HR can use to connect HR efforts to business performance. Survey results underscore the value of an analytical approach while revealing that many HR departments are heavily focused on internal measures rather than business outcomes. Each analytical tool is exemplified through case studies. A model is presented to suggest how executives can get started by focusing on five key areas.
Findings
– Leading companies are using six analytical tools to improve the connection between HR investments and business returns: employee databases; segmentation of talent; targeted investments; customization of the employee value proposition; long‐term workforce planning; and talent supply chains.
Originality/value
– As the case studies reveal, the tools identified here can help HR leaders actively shape their organization's future – managing talent and directing programs toward the long‐term needs of the business. Survey data shows that most companies increasingly seek to use analytics for long‐term advantage, and the model presented here can help HR executives take the first critical steps.
We review the literature on individual acceptance of technology to show how organizations can improve the effective use of human resource web-based technologies. Integrating and expanding several theoretical models of technology acceptance, we develop a perceptual model of employee self-service (ESS) acceptance and usage. Based on this model, we propose several key individual, technological, and organizational factors relevant to individual intentions to use ESS technology. We summarize these in several testable propositions and also discuss implications for organizational researchers and practitioners.
Implementation of employee self-service (ESS) technology presents a variety of challenges for organizations as they strive to maximize return on investment and change management. Using a research framework grounded in the theory of planned behavior, this study examines factors that enhance user acceptance of ESS technology both before and after implementation. Results suggest that employees are more likely to intend to use ESS technology when they have positive attitudes toward using it and when subjective norms in the organization support use of the technology. Perceived organizational support (POS) enhanced the effect of managerial pressure on perceptions of normative beliefs supporting use of the technology post-implementation. Implications of the research and future research directions are discussed.
We test for three-way complementarities among information technology (IT), performance pay, and human resource (HR) analytics practices. We develop a principal–agent model examining how these practices work together as an incentive system that produces a larger productivity premium when the practices are implemented in concert rather than separately. We assess our model by combining fine-grained data on human capital management (HCM) software adoption over 11 years with detailed survey data on incentive systems and HR analytics practices for 189 firms. We find that the adoption of HCM software is greatest in firms that have also adopted performance pay and HR analytics practices. Furthermore, HCM adoption is associated with a large productivity premium when it is implemented as a system of organizational incentives, but has less benefit when adopted in isolation. The system of three-way complements produces disproportionately greater benefits than pairwise interactions, highlighting the importance of including all three complements. Productivity increases significantly when the HCM systems “go live” but not when they are purchased, which can be years earlier. This helps rule out reverse causality as an explanation for our findings.
This paper was accepted by Sandra Slaughter, information systems.
One of the more fundamental aspects of the ongoing debate about the added value of HRM relates to ‘best’ practice versus ‘best-fit’. Best practice suggests the universal success of certain HR practices, while best-fit acknowledges the relevant impact of contextual factors. We argue that differences in embeddedness and in institutional settings between, for example, countries affect the nature of HRM. To understand this phenomenon, we are in need of additional theory. In this article we will use the theory of new institutionalism as a better way to understand the shaping of HR policies and practices in different settings. After a concise review of the latest debates in the area of strategic HRM, in which the resource-based view is the dominant perspective, we turn to an analysis of HRM in different institutional settings, which suggests the need for additional theory: ie new institutionalism. We offer propositions to explain the impact of different institutional mechanisms, including coercive, normative and mimetic ones, on the shaping of HR policies and practices in organisations. The remainder of the article then focuses on possible implications for practitioners, theoretical implications for future research, and challenges for strategic HRM.
Two paradigm shifts are discussed here: talentship and sustainability. First, the traditional service-oriented HR focus must be extended to a “decision science” that enhances decisions about human capital. We call this decision science talentship. It includes talent segmentation, or identifying pivotal talent pools where the quality and/or availability of human capital makes the biggest difference to strategic success. Second, HR and business leaders increasingly define organizational effectiveness beyond traditional financial outcomes to encompass sustainability—achieving success today without compromising the needs of the future. A common strategic human capital decision science can reveal pivotal talent under both traditional and sustainability-based definitions, and thus uncover important insights about the talent implications of the shifting definition of strategic success. © 2005 Wiley Periodicals, Inc.
Summary This article asserts that any theory or research on fads or fashions in science has to answer three questions clearly and unambiguously. What defines "science"? What defines a "scientific fad" or a "scientific fashion"? What might facilitate the occurrence of scientific fads or fashions so defined? To illustrate this argument, this article critically examines the answers to three questions suggested by Starbuck's article: [Starbuck, W. H. (2009). The constant causes of never-ending faddishness in the behavioral and social sciences. Scandinavian Journal of Management]. The article concludes by discussing the challenges that certain scholars can pose to other scholars who courageously raise the possibility that fads or fashions might hold sway in the behavioral or social sciences.
Researchers have had difficulty accommodating materiality in voluntaristic theories of organizing. Although materiality surely shapes how people use technologies, materiality’s role in organizational change remains under-theorized. We suggest that scholars have had difficulty grappling with materiality because they often conflate the distinction between the material and social with the distinction between determinism and voluntarism. We explain why such conflation is unnecessary and outline four challenges that researchers must address before they can reconcile the reality of materiality with the notion that outcomes of technological change are socially constructed.
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are heterogeneously distributed across firms and that these differences are stable overtime this article examines the link between firm resources and sustained competitive advantage. Four empirical indicators of the potential of firm resources to generate sustained competitive advantage—value, rareness, imitability, and substitutability—are discussed. The model is applied by analyzing the potential of several firm resources for generating sustained competitive advantages. The article concludes by examining implications of this firm resource model of sustained competitive advantage for other business disciplines.ABSTRACT FROM AUTHOR
We begin by juxtaposing the pervasive presence of technology in organizational work with its absence from the organization studies literature. Our analysis of four leading journals in the field confirms that over 95% of the articles published in top management research outlets do not take into account the role of technology in organizational life. We then examine the research that has been done on technology, and categorize this literature into two research streams according to their view of technology: discrete entities or mutually dependent ensembles. For each stream, we discuss three existing reviews spanning the last three decades of scholarship to highlight that while there have been many studies and approaches to studying organizational interactions and implications of technology, empirical research has produced mixed and often-conflicting results. Going forward, we suggest that further work is needed to theorize the fusion of technology and work in organizations, and that additional perspectives are needed to add to the palette of concepts in use. To this end, we identify a promising emerging genre of research that we refer to under the umbrella term: sociomateriality. Research framed according to the tenets of a sociomaterial approach challenges the deeply taken-for-granted assumption that technology, work, and organizations should be conceptualized separately, and advances the view that there is an inherent inseparability between the technical and the social. We discuss the intellectual motivation for proposing a sociomaterial research approach and point to some common themes evident in recent studies. We conclude by suggesting that a reconsideration of conventional views of technology may help us more effectively study and understand the multiple, emergent, and dynamic sociomaterial configurations that constitute contemporary organizational practices.