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1 – 10 of over 20000Rajasshrie Pillai and Brijesh Sivathanu
To understand human resource (HR) practices outcomes on HR decision making, strategic human resource management (HRM) and organizational performance by exploring the HR data…
Abstract
Purpose
To understand human resource (HR) practices outcomes on HR decision making, strategic human resource management (HRM) and organizational performance by exploring the HR data quality along with descriptive and predictive financial and non-financial metrics.
Design/methodology/approach
This work utilizes the grounded theory method. After the literature was reviewed, 113 HR managers of multinational and national companies in India were interviewed with a semi-structured questionnaire. The collected interview data was analyzed with NVivo 8.0 software.
Findings
It is interesting to uncover the descriptive and predictive non-financial and financial metrics of HR practices and their influence on organizational performance. It was found that HR data quality moderates the relationship between the HR practices outcome and HR metrics. This study found that HR metrics help in HR decision-making for strategic HRM and subsequently affect organizational performance.
Originality/value
This study has uniquely provided the descriptive and predictive non-financial and financial metrics of HR practices and their impact on HR decision making, strategic HRM and organizational performance. This study highlights the importance of data quality. This research offers insights to the HR managers, HR analysts, chief HR officers and HR practitioners to achieve organizational performance considering the various metrics of HRM. It provides key insights to the top management to understand the HR metrics' effect on strategic HRM and organizational performance.
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Jos Benders, Roel Schouteten and Mohamed Aoulad el Kadi
The purpose of this paper is to gain insights into the effects of an enterprise resource planning (ERP)‐implementation on job content.
Abstract
Purpose
The purpose of this paper is to gain insights into the effects of an enterprise resource planning (ERP)‐implementation on job content.
Design/methodology/approach
Data are collected using a qualitative expert instrument (WEBA) and a questionnaire (NOVA‐WEBA) among HR‐assistants in a case study in the Dutch hospitality industry.
Findings
Contrary to what one might expect, the introduction of an ERP‐system does not automatically result in a more centralized organization: in granting local authorizations user/employee job decision latitude is affected c.q. realized. However, even when a decentralization policy is pursued as is the case in our study, job decision latitude is not necessarily enhanced. This is partly caused by ERP‐related changes such as increasing standardization of operational procedures and data entry requirements, and partly by organization‐specific developments in how tasks get assigned to jobs.
Research limitations/implications
The configuration of ERP‐systems varies by organization, and is largely a matter of organizational choice. The case is unique, as is indeed any case.
Practical implications
Insights into ERP's effects can help organizations achieve better designed jobs. Pre‐implementation simulations of effects can help steering towards desired outcomes.
Originality/value
The paper provides useful insights into the effects of an ERP‐implementation on job content through a case study of HR‐assistants.
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Charles Cayrat and Peter Boxall
This paper aims to respond to questions being raised about the challenges, risks and impacts of Human Resource Analytics (HRA). Based on a study of 40 companies, it discusses the…
Abstract
Purpose
This paper aims to respond to questions being raised about the challenges, risks and impacts of Human Resource Analytics (HRA). Based on a study of 40 companies, it discusses the implications of HRA for practitioners, praxis and practices in HRM and adds to this a concern with whether HRA is enhancing mutuality in employment relationships.
Design/methodology/approach
Using an abductive approach, the authors analyzed data from semistructured interviews with an HRA leader or specialist in 40 large organizations.
Findings
While wrestling with the challenge of data quality and integration, the practice of descriptive analytics is widely adopted in these companies and the majority can demonstrate improvement in the efficiency and effectiveness of HR activities through predictive analytics. The analytical competence of HR specialists is an ongoing issue. While much more research is needed, the companies in the authors’ sample demonstrated some valuable examples of mutual gains from HRA.
Practical implications
Education in HRA must not only help to raise quantitative competencies among HR specialists but should also help them to ask critical questions about the theoretical propositions and subjective data points being built into HRA. Boundary spanning is important to enable effective HRA and processes for employee voice to be improved. Arguably, the time has come for a more formalized data analytics' strategy in large organizations.
Originality/value
This paper provides evidence on how HRA is being implemented in large companies, including how HRA leaders are managing its challenges and risks and the impacts it is having on business and employee outcomes.
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The purpose of this conceptual paper is twofold. The first objective is to introduce a multi-stakeholder power perspective to the discourse on repatriate retention, which has, to…
Abstract
Purpose
The purpose of this conceptual paper is twofold. The first objective is to introduce a multi-stakeholder power perspective to the discourse on repatriate retention, which has, to date, treated issues of career agency without considering whether other stakeholders might be capable of responding constructively. The second objective of the paper is more prescriptive, conjecturing that social media, which has also been completely overlooked by the repatriation literature, has the potential to empower repatriation stakeholders.
Design/methodology/approach
Following a review of the literature on repatriate turnover, this paper uses Hardy and Leiba-O’Sullivan's (1998) framework on empowerment to examine the nature and significance of powerlessness on the part of key stakeholders in the repatriation process – repatriates, HQ managers, and HQ HR professionals. It uses the same framework to investigate how social media might help to empower these stakeholders.
Findings
The analysis finds that social media has the potential to empower repatriation stakeholders in four key ways: first, by triggering expatriates’ awareness of the need to proactively manage different aspects of their own impending repatriation; second, by providing access to supportive mentoring resources; third, by strengthening access to key HR and managerial decision-making arenas; and fourth, by enabling HQ managers and HR representatives to more judiciously direct potentially scarce organizational resources (including their own time) toward key repatriation supports.
Research limitations/implications
Although this conceptual paper has no empirical data, it offers considerable value to the repatriation literature by introducing the topics of power and social media and explaining their relevance to repatriation (and indeed, to the field of international HRM).
Practical implications
Repatriate turnover is problematic, both for repatriates who would have liked to remain with the organization that sent them on assignment, and for the organizations that would like to have retained (and utilized) repatriates’ global competencies. Thus, the main practical implication of this paper is that it offers an innovative contemporary solution (e.g. the use of social media) to this problem of repatriate turnover.
Originality/value
The paper demonstrates that the topic of power has been completely neglected by the repatriation literature. Similarly, the topic of social media, has also been completely overlooked by the repatriation literature. This paper introduces these two topics to the repatriation literature, and, in so doing, broadens the understanding of constraints on repatriate agency as a means of repatriate retention, and offers innovative contemporary solutions (e.g. social media).
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Stefan Strohmeier, Julian Collet and Rüdiger Kabst
Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions…
Abstract
Purpose
Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality.
Design/methodology/approach
Theoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success.
Findings
The authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success.
Research limitations/implications
Major limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task.
Originality/value
The authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.
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Rita Bissola and Barbara Imperatori
The purpose of this paper is to examine whether the organizational redesign opportunities currently offered by web-based technological innovations contribute to rebuilding and…
Abstract
Purpose
The purpose of this paper is to examine whether the organizational redesign opportunities currently offered by web-based technological innovations contribute to rebuilding and strengthening the employee-HR department relationship, rendering personnel management policy criteria more transparent, increasing perceived fairness and thus helping to instil trust in the HR department, albeit in a diverse virtual context.
Design/methodology/approach
The authors designed a survey involving 526 Gen Y employees and tested the hypotheses using structural equation modelling analyses.
Findings
The results confirm a positive relationship between relational e-HRM system adoption, procedural justice and trust in the HR department.
Research limitations/implications
The results provide evidence that technology can support the development of institutional trust in virtual environments and thus contribute to the growing e-HRM literature, to the more consolidated strategic HRM research domain and to the debate on trust in technology-mediated relationships.
Practical implications
The paper provides valuable and at times unexpected results on the new potential role of the HR department in the current fluid and insecure labour market, thereby forming the basis for defining some useful guidelines to design and implement the e-HRM architecture.
Originality/value
The paper focuses on understanding how relational e-HRM could impact on the direct employee-HR department relationship, from the Gen Y employees perspective, that is almost neglected in the growing literature. Moreover it suggests some unexpected insights on the role of technology innovativeness in moderating the impact of e-HRM on trust in the HR department.
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Yusra Qamar, Rakesh Kumar Agrawal, Taab Ahmad Samad and Charbel Jose Chiappetta Jabbour
An original systematic review of the academic literature on applications of artificial intelligence (AI) in the human resource management (HRM) domain is carried out to capture…
Abstract
Purpose
An original systematic review of the academic literature on applications of artificial intelligence (AI) in the human resource management (HRM) domain is carried out to capture the current state-of-the-art and prepare an original research agenda for future studies.
Design/methodology/approach
Fifty-nine journal articles are selected based on a holistic search and quality evaluation criteria. By using content analysis and structural concept analysis, this study elucidates the extent and impact of AI application in HRM functions, which is followed by synthesizing a concept map that illustrates how the usage of various AI techniques aids HRM decision-making.
Findings
A comprehensive review of the AI-HRM domain’s existing literature is presented. A concept map is synthesized to present a taxonomical overview of the AI applications in HRM.
Research implications/limitations
An original research agenda comprising relevant research questions is put forward to assist further developments in the AI-HRM domain. An indicative preliminary framework to help transition toward ethical AI is also presented.
Originality/value
This study contributes to the literature through a holistic discussion on the current state of the domain, the extent of AI application in HRM, and its current and perceived future impact on HRM functions. A preliminary ethical framework and an extensive future research agenda are developed to open new research avenues.
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Nivedita Jha, Renato Pereira and Siddharth Misra
The purpose of this study is to provide human resource (HR) practitioners of multinational companies aspiring to invest in these two countries with guidelines for attaining…
Abstract
Purpose
The purpose of this study is to provide human resource (HR) practitioners of multinational companies aspiring to invest in these two countries with guidelines for attaining organizational effectiveness through people.
Design/methodology/approach
This study develops and tests a multiple criteria decision-making model with data collected in the banking sectors of India and Mozambique. It compares the job engagement, team building and innovation strategy preferences of Indian personnel with those of Mozambican employees.
Findings
The findings of the study reveal the differences in the perceptions of the respondents of both countries regarding the importance of the strategies for organizational effectiveness.
Research limitations/implications
Despite several contributions, the study has certain limitations too. Although utmost care was taken to avoid the issue of common method variance, the cross-sectional self-reported design of the study might be adversely affected by common method bias (MacKenzie and Podsakoff, 2012). Hence, future research might be conducted using different designs, such as diary studies or longitudinal studies. Future research might also be conducted making use of organizational productivity case studies to demonstrate the practicability of customizing the HR strategies using the multi-attribute decision-making approach.
Practical implications
This body of work is an addition to the existing literature on cross-national studies in the field of HR management (HRM) and adds to the limited literature on HRM in the least developed countries. The study is designed to provide guidelines for the HR practitioners of multi-national companies in these two countries to help them achieve enhanced organizational effectiveness. This should be of particular interest to the HR managers of the Indian companies aspiring to invest in Mozambique.
Originality/value
Research in the area of HRM is mainly limited to the developed and developing nations, with very few studies centering on emerging economies. While most cross-national studies on organizational effectiveness are also largely focused on developed and developing nations, this study is unusual, in that its focus is on a fast-developing nation (India) and an emerging economy (Mozambique).
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Lalita Mohan Mohapatra, A. V. S. Kamesh and Jayashree Roul
Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices…
Abstract
Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.
Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.
Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.
Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.
Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.
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Muhammad Ashraf Fauzi, Zetty Ain Kamaruzzaman and Hamirahanim Abdul Rahman
This study aims to provide an in-depth understanding of big data analytics (BDA) in human resource management (HRM). The emergence of digital technology and the availability of…
Abstract
Purpose
This study aims to provide an in-depth understanding of big data analytics (BDA) in human resource management (HRM). The emergence of digital technology and the availability of large volume, high velocity and a great variety of data has forced the HRM to adopt the BDA in managing the workforce.
Design/methodology/approach
This paper evaluates the past, present and future trends of HRM through the bibliometric analysis of citation, co-citation and co-word analysis.
Findings
Findings from the analysis present significant research clusters that imply the knowledge structure and mapping of research streams in HRM. Challenges in BDA application and firm performances appear in all three bibliometric analyses, indicating this subject’s past, current and future trends in HRM.
Practical implications
Implications on the HRM landscape include fostering a data-driven culture in the workplace to reap the potential benefits of BDA. Firms must strategically adapt BDA as a change management initiative to transform the traditional way of managing the workforce toward adapting BDA as analytical tool in HRM decision-making.
Originality/value
This study presents past, present and future trends in BDA knowledge structure in human resources management.
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