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Based on the theory of basic human values, this study aims to examine the impact of CEO conservation (i.e. security, conformity and tradition) and openness to change (i.e. self-direction, stimulation and hedonism) values on one of the most conflictual decisions inside a firm: workforce downsizing.

The hypothesis testing was done in the context of all workforce downsizing decisions made by German companies (and their CEOs) listed on the German Prime-Index between 2005 and 2019. A software-based psycholinguistic assessment of various sources of CEO communications was conducted to tap into their underlying values.

Tobit regression analysis confirms that CEO conservation and openness-to-change values impact the severity of workforce downsizing. Namely, the higher the CEO conservation values, the lower the downsizing severity (i.e. employees dismissed in relation to overall workforce). In contrast, the higher the CEO openness to change values, the higher the downsizing severity.

Against prior research that has centered around political ideology as a proxy to understand the mechanisms through which values impact strategic decisions, the present study employs advanced measurement approaches to assess the general impact of CEO values on critical firm decisions. As such, the study contributes to upper echelons research by offering a new perspective on how CEO values impact critical firms' decisions.

This paper aims to represent an exploration of drivers of workforce agility under the lens of dynamic capabilities to advance the existing workforce literature on agility and strategic human resource management.

In-depth qualitative interviews with senior information technology professionals, managers, directors and leadership were conducted. Data coding and analysis followed the Gioia methodology to develop a theoretical framework.

The theoretical paradigm of workforce agility is seeing revisions. In the past it was solely connected to resource-based view theory, current literature superficially speaks of the link with dynamic capability but lacks comprehensive and strategic understanding. The research brings in the evolutionary change by viewing workforce agility directly under the lens of dynamic capability theory and recognizes workforce agility as a high-level strategy. Based on the analysis of the qualitative interviews this study has developed a conceptual heuristic of workforce agility drivers, interlinked with dynamic capabilities micro-foundations – “sensing”, “seizing”, and “continual renewal”. This paper conceptualizes workforce agility as a response to high pressures for the dynamic capability of the company, which requires reconfiguration and redeployment of external and internal human resources and an inherent need to bring some stability to the internal resources of the company.

There is a growing body of literature linking organizational agility with dynamic capabilities, which overlooks workforce agility. This study is theory-based research on workforce agility, which guides practitioners in making human resource processes more agile.

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to find the best ways to plan their workforce, and the workforce emangement (WFM) is one of the biggest challenges faced by managers. Relevant research on WFM in operations has been published in a several range of journals that vary in their scope and readership, and thus the academic contribution to the topic remains largely fragmented.

To address this gap, this review aims to map research on WFM in operations to understand where it comes from and where it is going and, therefore, provides opportunities for future work. This study combined two bibliometric approaches with manual document coding to examine the literature corpus of WFM in operations to draw a holistic picture of its different aspects.

Content and thematic analysis of the seminal studies resulted in the extraction of three key research themes: workforce cross-training, planning workforce mixed methods and individual workforce characteristics. The findings of this study further highlight the gaps in the WFM in operations literature and raise some research questions that warrant further academic investigation in the future.

Likewise, this study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of WFM in operations.

Federal agencies are relying increasingly on contractors to perform their missions. With hundreds of billions of tax dollars spent each year on goods and services, it is essential that federal acquisition be handled in an efficient, effective, and accountable manner. The Government Accountability Office (GAO), however--as well as other accountability organizations, inspectors general, and the agencies themselves--continue to identify systemic weaknesses in key areas of acquisition. In fact, the acquisition function at several agencies has been on GAO's high-risk list, which identifies areas in the federal government with greater vulnerability to fraud, waste, abuse, and mismanagement. In January 2005, we added interagency contracting to this list. Far too often, the result of poor acquisitions has been an inability to obtain quality goods and services on time and at a fair price. We can no longer afford such outcomes. Given current fiscal demands and the fiscal challenges we are likely to face in the 21st century, the federal government must improve its ability to acquire goods and services in a cost-effective manner. GAO developed this framework to enable high-level, qualitative assessments of the strengths and weaknesses of the acquisition function at federal agencies. Such assessments can help senior agency executives identify areas needing greater management attention, and enable accountability organizations (including GAO) to identify areas requiring more focused follow-up work. The framework consists of four interrelated cornerstones that our work has shown are essential to an efficient, effective, and accountable acquisition process: (1) organizational alignment and leadership, (2) policies and processes, (3) human capital, and (4) knowledge and information management. The framework supports an integrated evaluation approach, but each of these cornerstones can stand alone so users of this framework may tailor evaluations to an agency's specific needs.

Human resources are one of the most important and effective elements for companies. In other words, employees are a competitive advantage. This issue is more vital in the supply chains and production systems, because of high need for manpower in the different specification. Therefore, manpower planning is an important, essential and complex task. The purpose of this paper is to present a manpower planning model for production departments. The authors consider workforce with individual and hierarchical skills with skill substitution in the planning. Assuming workforce demand as a factor of uncertainty, a two-stage stochastic model is proposed.

To solve the proposed mixed-integer model in the real-world cases and large-scale problems, a Benders’ decomposition algorithm is introduced. Some test instances are solved, with scenarios generated by Monte Carlo method. For some test instances, to find the number of suitable scenarios, the authors use the sample average approximation method and to generate scenarios, the authors use Latin hypercube sampling method.

The results show a reasonable performance in terms of both quality and solution time. Finally, the paper concludes with some analysis of the results and suggestions for further research.

Researchers have attracted to other uncertainty factors such as costs and products demand in the literature, and have little attention to workforce demand as an uncertainty factor. Furthermore, most of the time, researchers assume that there is no difference between the education level and skill, while they are not necessarily equivalent. Hence, this paper enters these elements into decision making.

This paper aims to contribute to the literature on human resources (HR) digitalization, specifically on HR analytics, disentangling the concept of analytics applied to HR and explaining the factors that hinder companies from moving to analytics. Therefore, the central research questions addressed in this study are: what does HR analytics encompass? What impedes the adoption of analytics in HR within organizations?

The authors performed a comprehensive literature review on analytics as applied in HR. The authors relied on two of the major multidisciplinary publication databases (i.e. Scopus and WoS). A total of 64 manuscripts from 2010 to 2019 were content analyzed.

The results reveal that there is an ongoing confusion on HR analytics conceptualization. Yet, it seems that there is an emerging consensus on what HR analytics encompasses. The authors have identified 14 different barriers for HR analytics adoption grouped into four categories, namely, data and models, software and technology, people and management. Grounding on them the authors propose a set of 14 key factors to help to successfully adopt HR Analytics in companies.

This paper brings clarity over the conceptualization of HR analytics by offering a comprehensive definition. Additionally, it facilitates business and HR leaders in making informed decisions on adopting and implementing HR analytics. Moreover, it assists HR researchers in positioning their paper more explicitly in current debates and encouraging them to develop some future avenues of research departing from some questions posed.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

Despite the growth and adoption of human resource (HR) analytics, it remains unknown whether HR analytics can impact organizational performance. As such, this study aims to address this important issue by understanding why, how and when HR analytics leads to increased organizational performance and uncover the mechanisms through which this increased performance occurs.

Using data collected from 155 Irish organizations, structural equation modeling was performed to test the chain mediation model linking HR technology, HR analytics, evidence-based management (EBM) and organizational performance.

The study's findings support the proposed chain model, suggesting that access to HR technology enables HR analytics which facilitates EBM, which in turn enhances organizational performance.

This research contributes significantly to the HR analytics and EBM literature. First, the study extends our understanding of why and how HR analytics leads to higher organizational performance. Second, the authors identify that access to HR technology enables and is an antecedent of HR analytics. Finally, empirical evidence is offered to support EBM and its impact on organizational performance.

The purpose of this paper is to focus on how the HR function takes advantage of human resource analytics (HRA), including big data (BD), and discuss factors hindering HRA and data utilization. Moreover, the authors discuss the implications of the HRA-induced role transformation of the human resource (HR) function.

This is an explorative case study based on qualitative interviews in nine leading Finnish companies.

The results indicate that both technical and human obstacles, operating with very basic HR processes and traditional information systems and poor data quality, hinder adoption of advanced HRA. This, combined with lacking skills in analytics and business understanding, inability to go beyond reporting, misconceptions related to BD and traditional compliance-oriented HR culture pose further challenges for the data analytics capacity and business partner role of the HR function. Senior executives expect no significant advancements of HRA, while HR professionals saw potential value in BD, although skepticism was not uncommon. The results point toward a need for increased cooperation with data analysts and HR professionals in provision and understanding the HR-related data for business-related decision making. Furthermore, cultural change and organizational redesign may be called for, in addition to overcoming technological obstacles related to BD, for it to have an impact on HR practices. HRA utilization and role transition of the HR function seem closely related and this transformation can be mutually reinforcing.

This study provides and theorizes explorative data on HRA within a group of some of the largest Finnish companies, pointing toward an immature state of the art in BD and HRA utilization and there being a relationship between HRA and the role transition of the HR function in organizations.

Drawing on human capital theory and the human capital resources framework, this study explores the knowledge, skills, abilities and other characteristics (KSAOs) required by the emerging role of human resource (HR) analysts. This study aims to systematically identify the key KSAOs and develop a competency model for HR Analysts amid the growing digitalization of work.

Adopting best practices for competency modeling set out by Campion et al. (2011), this study first analyzes 110 HR analyst job advertisements collected from five countries: Australia, Canada, Ireland, the United Kingdom and the USA. Second a thematic analysis of 12 in-depth semistructured interviews with HR analytics professionals from Canada and Ireland is then conducted to develop a novel competency model for HR Analysts.

This study adds to the developing and fast-growing field of HR analytics literature by offering evidence supporting a set of six distinct competencies required by HR Analysts including: consulting, technical knowledge, data fluency and data analysis, HR and business acumen, research and discovery and storytelling and communication.

The research findings have several practical implications, specifically in recruitment and selection, HR development and HR system alignment.

This study contributes to the evolving HR analytics literature in two ways. First, the study links the role of HR Analysts to human capital theory and the human capital resource framework. Second, it offers a timely and empirically driven competency model for the emerging role of HR Analysts.