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This study aims to propose and empirically examine the simultaneous complementary mediating role of bank branch collective human capital and justice climate between implemented high-performance work system (HPWS) and bank branch performance in the banking sector.

Data were collected at three different intervals of time between March 2022 to July 2022 from a final sample of 323 branch managers and 1,369 employees of commercial banks operating in Pakistan. Partial least square structural equation modeling was used to test the theoretical model proposed by this study.

Study results revealed that collective human capital and justice climate simultaneously mediate the relationship between implemented HPWS and branch performance.

The study contributes to the strategic HRM theory by proposing the complementary mediating roles of human capital and organizational justice to reap the benefits of implementing HPWS for improving branch-level performance. The managers should focus on developing and exploiting the knowledge, skills and experiences (human capital) of branch employees and improve their collective perceptions of justice to reap the benefits of HPWS for enhancing branch-level performance.

Drawing upon the resource-based view of the firm and organizational justice theory, this novel study examines the simultaneous and complementary mediating effects of collective human capital and justice climate between implemented HPWS and branch performance relationships at the branch-level analysis.

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

Previous literature has identified human resources as a key source of competitive advantage in organizations of all sizes. However, Small and Medium-sized Enterprises (SMEs) face difficulty in comprehensively implementing all recommended Human Resource Management (HRM) functions. In this study, we shed light on the field of HRM in SMEs by focusing on the context of Greek Small and Medium-sized Hotels (SMHs), which represent a dominant private sector employer across the country.

Using a fuzzy-set qualitative comparative analysis (fsQCA) and 34 in-depth interviews with SMHs' owners/managers, we explore the HRM conditions leading to high levels of performance, while taking into consideration the influence of internal key determinants.

We uncover three alternative successful HRM strategies that maximize business performance, namely the Compensation-based performers, the HRM developers and the HRM investors. Each strategy fits discreet organizational characteristics related to company size, ownership type and organizational structure.

To the best of the authors' knowledge this is among the first empirical studies that examine different and equifinal performance-enhancing configurations of HRM practices in SMHs.

HRM decentralization and devolution have been highlighted as key HRM processes in organizations’ quest for increased flexibility. Although they have been extensively studied in the MNC and International HRM literature, they have mainly been examined on a separate basis, and their definition and operationalization have often been confused. Thus, we first clarify the difference between the two concepts by refining the definitions by Hoogendoorn and Brewster (1992), and then empirically examine how they are related.

The relationship between HRM decentralization and devolution is examined by means of a survey in a large multi-country sample of multi-unit organizations.

Regarding our clarification objective, we contend that devolution has to do with who takes responsibilities for HRM (i.e. line managers or HRM professionals) while decentralization refers to where HRM responsibilities are allocated (i.e. headquarters or increasingly local units). Regarding the relationship between the two concepts, the results show that higher levels of HRM decentralization are related to higher levels of devolution, but this association is attenuated in organizations with more powerful HRM departments.

The study contributes to theory and practice by disentangling, at the conceptual, operational, empirical and practical levels, two different but related HRM decisions (how much to devolve and how much to decentralize HRM) that organizations must make to efficiently cope with the characteristics of their own structure and competitive environment. It highlights the role of the relative power of HRM departments in how HRM responsibilities are ultimately distributed across the organization.

The study aims to develop a hierarchical model for innovative work behaviour (IWB) that can capture the complex associations among the factors contributing to IWB within the information technology (IT) sector. To accomplish this, the authors rely on an abductive approach using a graph theoretic model, often called interpretive structural modelling (ISM).

After conducting an in-depth literature review and using the Delphi method, the authors identified 12 factors (11 enablers and IWB as an outcome). The authors collected data through the Delphi approach by sending the questionnaire to 11 experts from academia and the IT sector who have extensive experience and knowledge relevant to the study. The authors then used the ISM method to analyse the relationships among these factors and understand their driving forces.

Based on the ISM model and the Matrice d'Impacts Croisés Multiplication Appliquée à un Classement analysis, the authors have identified that inclusive leadership, proactive personality and knowledge creation ability are the variables with strong driving power but weak dependence. Conversely, IWB has strong dependence but weak driving power. These findings suggest that to foster IWB, the organisation should prioritise inclusive leadership, proactive personality and knowledge-creation ability to succeed in challenging times. The study’s findings contribute to the social exchange theory, which explains IWB in a dynamic setting. Additionally, the study helps address the significant concerns that most IT companies face during times of crisis.

The study provides valuable guidance for managers and policymakers who are grappling with the challenges of improving IWB in the IT sector. This study is particularly relevant as the industry is currently navigating an economic recession and facing intense competition from other tech companies launching new products and services.

This research holds great significance for top executives, line managers and policymakers in the IT industry. It sheds light on the relevance and importance of various factors facilitating millennials' IWB.

The purpose of this study is to explore the mechanism of digitalized transformation in organizations’ human resource management (HRM). This study summarizes three basic factors driving the digital transformation process in China: level of perception, level of application and speed of transformation.

This study analyzes the strategic transformation process of HRM in Haier, Hisense and Chambroad to explore the human resource digital transformation mechanism in Chinese enterprises.

The results of this study show that three HR value chain models can be constructed based on how well HRM deals with business: the efficiency-oriented HRM value chain, quasi-business-oriented HRM value chain and business-oriented HRM value chain. The basic factors – level of perception, level of application and speed of transformation – are observed in the entire HRM digital transformation process.

This study provides theoretical and empirical insights for enterprises to explore the value of digital technology in HRM and facilitate the digital transformation of HRM.

This study aims to examine whether companies adopt digital platforms for corporate whistleblowing systems (CWSs), as more substantive corporate social responsibility (CSR) initiatives, by following the existing practices of their industry peers (competitive pressure) and/or geographical location peers (legitimacy pressure).

This study identifies 446 focal companies in the European Economic Area that introduced new CWSs during 2017–2021. Then, the peers are defined as companies with existing CWS practices that are similar in size to each focal company. Using a quantitative approach, this study uses a logistic regression model.

This study finds that companies are more likely to adopt digital CWS if their country peers (not, industry peers) have done so, especially the ones operated in countries where governments build CSR partnerships with companies through cooperative consensus. However, the role of country peers is less prominent when companies have CSR committees.

This study shows the importance of country norms over competitive pressure in CSR. Nevertheless, the results offer additional insights for policy-makers by showing that country regulations mandating CWSs are not significant in promoting the adoption of digital CWS nor reducing the role of country peers.

Providing CWSs with digital platforms may show corporate commitment to better preventing social misconduct and improving social responsibility.

While most literature focuses on the role of industry peers and/or community peers in a single-country setting, this study examines the role of country peers specifically on digitalization regarding CSR and governance.

To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.

A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.

Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.

The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.

The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.