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The main goal of any organization is to achieve the best quality of work through employees, and managers play a very important role in this field. Managers and leaders of organizations often face with paradoxes that make decision-making difficult. The purpose of this paper is to develop a competency model for human resource managers considering the importance of the role of paradoxes for organizations.

The research methodology is of a mixed type and with an approach based on paradox theory and using theme analysis and fuzzy Delphi, it seeks to provide a model of paradoxical managers’ competence. The statistical sample included 11 experts working in the information and communication technology industry, who were selected using the snowball and judgmental sampling method.

The results of this research show that the competency model of human resource managers has three managerial, organizational and individual levels and has 15 themes including strategic partner, organizational knowledge, awareness of the industry environment, awareness of the external environment, paradoxical thinking, managerial knowledge, relationship management, resource management , leadership, human resources analyzer, information technology (IT) knowledge, personality traits, development, multitasking and cognitive competence. The most important theme identified is paradoxical thinking and familiarity with IT knowledge, and it is suggested that human resource managers working in this field should preferably study technical and engineering fields at the undergraduate level and shift to human resource management fields at the graduate level.

The distinguishing feature of this paper is the presentation of a competency model based on paradox theory. Paradoxes are part of organizational life. Therefore, there should be a paradoxical view in all organizational analysis.

This study investigates the relationship between responsible leadership (RL) and employee sustainable performance (ESP), utilizing the CSR theory as a theoretical framework. Furthermore, this study aims to examine the role of ethical climate as a potential mediator in the relationship between RL and ESP.

A sample of 415 employees from the healthcare sector of India was collected through a questionnaire-based survey by using the convenience sampling technique. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) with the help of SmartPLS 4.

The study's findings demonstrated a significant, positive association between RL and ESP [employee well-being (EWB) and employee performance (EP)]. Additionally, the findings show that ethical climate partially mediates the link between RL and ESP (EWB and EP).

The generalizability of the study's data collection is limited because it is based on the responses of Indian healthcare sector employees to an online and offline survey. The authors propose that the healthcare industry implement an intensive leadership training program in light of the findings of this study, which will aid human resource (HR) managers in comprehending the significance of RL and fostering related behaviors, such as encouraging employees to maintain ethical behavior and positive attitudes.

To the authors' understanding, this study is among the earliest attempts to present an integrative model that examines the relationship between RL, ethical climate and ESP in the context of Indian healthcare employees, incorporating the theory of corporate social responsibility (CSR). Moreover, the novelty of this research study examines the relationship between RL and ESP, with an ethical climate serving as a mediator. The focus is specifically on employees working in the Indian healthcare sector.

This study investigates the impact of big data analytics capabilities on export performance. Moreover, it assesses the mediating effect of the supply chain innovation and moderating effect of supply chain agility.

This study is based on primary data that were collected from the manufacturing sector operating in Jordan. A total of 327 responses were used for the final data analysis. Data analysis was performed via a partial least square structural equation modeling (PLS-SEM) approach.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the export performance as well as a mediating effect of supply chain innovation. It was confirmed that supply chain agility moderated the relationship of supply chain innovation and export performance.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, export performance, supply chain innovation and supply chain agility. This study offers new theoretical and managerial contributions that add value to the supply chain management literature by testing the moderated-mediated model of these constructs in the manufacturing sector in Jordan.

This study explores the impact of intellectual capital on the adoption of supply chain analysis by manufacturing companies. The authors also examine the potential role of supply chain analytics in supply chain innovation and agility.

Data were gathered from 268 managers and directors of Jordanian companies. The hypotheses were tested using the Smart PLS software.

The results reveal that human, structural and social capital significantly impact supply chain analytics. Moreover, the findings show that supply chain analytics significantly affect supply chain innovation and agility. In other words, cultivating intellectual capital is crucial for utilizing supply chain analysis to enhance performance in terms of innovation and agility.

This study adds to the literature on the determinants of the adoption of supply chain analytics and its function in establishing the dynamic capabilities of businesses, including supply chain innovation and agility.