Measure what matters: descriptive and predictive metrics of HRM-pathway toward organizational performance

Pillai, Rajasshrie

doi:10.1108/ijppm-10-2020-0509

Cited by 18 publications

(42 citation statements)

References 43 publications

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“…I4.0 technology is automating the different functions of HR such as recruitment, training, performance management and saving the cost of HR operation functions as well as eliminating repetitive tasks of human resource management (HRM) (Ahmad et al , 2020; Hassan Onik et al , 2018; Rana and Sharma, 2019a; Ras et al , 2017; Wan and Roshidi, 2019). Using I4.0 technologies such as robots, chatbots, AI, IoT and cloud-based services enables better HR data outcomes and decision-making (Dwivedi et al , 2019; Imperatori et al , 2020; Nagy et al , 2018; Pillai and Sivathanu, 2021). The I4.0 technology used for HR management supports HR managers to be more analytical and responsive by getting real-time data of employees and enables HR to drive HR function strategically (Hecklau et al , 2016; Rana and Sharma, 2019a; Taslim Ahammad, 2017).…”

Section: Introductionmentioning

confidence: 99%

Use of 4.0 (I4.0) technology in HRM: a pathway toward SHRM 4.0 and HR performance

Pillai¹,

Yadav²,

Kaushik

et al. 2021

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Purpose This paper aims to investigate the use of Industry 4.0 (I4.0) technology and its barriers in human resourcemanagement (HRM) for Smart HR 4.0 and its impact on HR performance. Design/methodology/approach The research has been conducted using the grounded theory approach. Semi-structured interviews were conducted with 122 senior HR officers of national and multi-national companies in India after the extensive literature review. NVivo 8.0 software was used for the analysis of the interview data. Findings I4.0 technology is used for HRM functions by HR professionals. It is revealed that Smart HR 4.0 that emerged from the I4.0 technology has leveraged the HR performance. It is also found that usage barriers, traditional barriers and risk barriers affect the use of I4.0 technology in HRM. Originality/value A model is developed using the grounded theory approach for HR managers to understand the impact of I4.0 on HRM. This study reveals the barriers affecting the use of I4.0 technology in HRM. It also provides the model for HR performance that emerged through the use of I4.0 technology in HR and Smart HR 4.0. The research delivered key insights for the HR professionals, marketers of HR technology and technology developers.

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Section: Introductionmentioning

confidence: 99%

Use of 4.0 (I4.0) technology in HRM: a pathway toward SHRM 4.0 and HR performance

Pillai¹,

Yadav²,

Kaushik

et al. 2021

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“…VT leaders and HR managers can comprehend these barriers with the help of this research; hence they can overcome these barriers as well. It would also help them develop tailored metrics of VT performance (Pillai and Sivathanu, 2021). These measurements can be created by focusing on project completion rates rather than the number of hours worked and increasing the trust index, enhancing overall VT collaboration and performance, leading to HR performance in the new normal or the postpandemic era.…”

Section: Practical Implicationsmentioning

confidence: 99%

“…HR performance is described as enhanced productivity and HR return on investment (Herington et al. , 2013; Pillai and Sivathanu, 2021; Wright et al. , 2005).…”

Section: Literature Reviewmentioning

confidence: 99%

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A pathway to virtual team performance in the New Normal paradigm

Mahtta¹,

Pillai²,

Gunasekaran

et al. 2022

JOEPP

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PurposeIn the postpandemic era, organizations have planned a combination of on-site and virtual work to portray the “New Normal”. The authors aim to analyze the effect of virtual team (VT)-building strategies on virtual team performance and HR performance in the “New Normal” context. This study aims to explore the drivers and barriers to VT performance and its contribution to HR performance.Design/methodology/approachThe study utilized the grounded theory approach. Semistructured interviews with 114 VT leaders of national and multinational companies in India were conducted and NVivo 8.0 software was used to analyze data.FindingsVT-building strategies contribute to VT collaboration and subsequently to VT performance. It was found that VT-building strategies catalyze VT collaboration which is impacted by the drivers and barriers of VTs, affecting VT performance and HR performance.Practical implicationsThe primary contribution of this work is the development of a framework that delivers important insights to VT leaders, talent managers, HR professionals and academicians.Originality/valueThis study uniquely examines the VT-building strategies and VT performance through the “New Normal” paradigm lens. This study proposes a conceptual model for VT performance and HR performance. It also provides the team-building strategies, drivers and barriers for VT performance. This work offers the roadmap to achieve VT performance and HR performance. This research also contributes to the human resource management literature by discussing the VT performance and HR performance in the “New Normal” paradigm. It provides insights to VT leaders, talent managers, HR professionals and academicians.

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“…HR data play a crucial role in guiding the performance measure in the competitive business environment. This includes employee data, such as employee performance, employee behavioral patterns, attendance, compensation and other personal data (Pillai & Sivathanu, 2021). Researchers have noticed that data strongly influences strategy formulation because the increase in data and analytical capabilities is redefining innovation, competition and productivity (Nisar, et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Adoption Factors of Artificial intelligence in Human Resource Management

Tuffaha¹

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The world is witnessing new technological advancements, which significantly impacts organizations across different departments. Artificial intelligence (AI) is one of these advancements that is widely heralded as a revolutionary technology in Human Resource Management (HRM). Professionals and scholars have discussed the bright role of AI in HRM. However, deep analysis of this technology in the HR process is still scarce.Therefore, the main goal of this thesis is to investigate the status of AI in HRM and derive concrete implementation key factors. Through, first, building an academic framework for AI in HRM; second, analyzing the most commonly used AI applications in HR process; third, identifying the optimal ways to transfer the knowledge of AI implementation processes.The methodology used for the investigation combines a systematic literature review and a qualitative research technique. As a basis and preparatory measure to address the research questions, an extensive literature analysis in the AI-HRM field was carried out, with a particular focus on publications of AI in HRM, HR-Big data analysis, AI applications/solutions in HRM and AI implementation. Along similar lines, the author published papers in several conference proceedings to improve the maturity of research questions.Based on this work, the published studies illustrate the gap between the promise and reality of AI in HRM, taking into account the requirements of AI implementation as well as the applications and limitations. Subsequently, HR experts and AI consultants, who had already gained first-hand experience with HR processes in an AI environment, were interviewed to find out the truth of the dominant AI's application in HR process.The main findings of this thesis are the derivation of a complete definition of AI in HRM as well as the status of the adoption strategies of AI applications in HRM. As a further result, it explores the usefulness and limitations of chatbots in the recruitment processes in India. In addition, derived the key factors to transfer the knowledge of AI implementation process to HR managers and employees. Challenges associated with AI implementation in the HR process and the impact of COVID-19 on AI implementation were also concluded.

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Measure what matters: descriptive and predictive metrics of HRM-pathway toward organizational performance

Cited by 18 publications

References 43 publications

Use of 4.0 (I4.0) technology in HRM: a pathway toward SHRM 4.0 and HR performance

Use of 4.0 (I4.0) technology in HRM: a pathway toward SHRM 4.0 and HR performance

A pathway to virtual team performance in the New Normal paradigm

Adoption Factors of Artificial intelligence in Human Resource Management

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