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Based on social exchange theory and social identification theory, I investigated how employee organizational identification affects the effectiveness of commitment-based human resource (HR) practices. I focused on employee attitudes (job satisfaction) and behaviors (proactive knowledge seeking) as HR practices’ outcomes.

Using a structural equation modeling analytical approach, I tested the hypotheses with data from a web-based cross-sectional survey of 208 specialists and engineers of manufacturing subsidiaries in Poland.

Results showed that the positive relationship between commitment-based-HR practices and job satisfaction is weakened for employees strongly identified with the organization. Simultaneously, the connection between seeking knowledge and job satisfaction is stronger and more important for people who identify moderately to strongly.

The study limitations regard mainly its cross-sectional design and single cultural and industrial context.

From the managerial perspective, the study suggests that to enhance proactive employee behavior, companies need to increase employee organizational identification and ensure that employees have a positive perception of the implemented HR practices.

The study contributes to the ongoing discussion on whether individual contingencies affect the effectiveness of commitment-based HR practices in the form of individual attitudinal and behavioral outcomes. The findings revealed that the contingent effect of organizational identification depends on the type of individual outcomes, suggesting that the strength of organizational identification affects how employees decide to reciprocate the organization’s attention and investment.

The COVID-19 pandemic showed that preestablished contingency plans and resilience practices were insufficient to cope with long-term and global disruptions. Companies thus struggled to develop capabilities that ensure their survivability during similar crises. Building on the adaptation-based view (ABV) of supply chain resilience, this study aims to offer an in-depth perspective on survivability in supply chains (SCs).

The paper empirically tests related relationships between adaptation capabilities and practices that ensure operational continuity. Responses from 252 organisations were collected and analysed using partial least squares structural equation modelling.

The results empirically support the ABV’s theoretical propositions and assess the possibilities of intertwining, digitalisation, a circular economy and maturity for the survivability of SCs.

The derived insights are attractive for managers and researchers to foster supply chain survivability and contribute to the increasing efforts of middle-range theorising in logistics and supply chain management research.

To the best of the authors’ knowledge, this study is one of the first studies to define factors enhancing the survivability of SCs through the lens of the ABV.

This study investigates how firms build strong dynamic marketing capability (DMC) from open innovation (OI) to enhance the performance of entrepreneurial firms. Moreover, this study unfolds DMC's mediating and moderating mechanisms underlying inbound and outbound OI and performance relationships, respectively.

To test the research model and hypotheses, this study drew a sample of 251 firms operating in Malaysia using the time-lagged survey method. Structural equation modelling was used in this study to investigate the model relationships.

The findings of this study reveal the positive interplay between inbound OI (knowledge acquisition) and DMC. The outbound OI (knowledge exploitation) in this study is found to mediate the relationship between inbound OI and firm performance. In addition, while the DMC has a mediating effect in the relationship between inbound OI and firm performance, such a capability reinforces the positive relationship between outbound OI and performance.

This study provides a noble insight into the complex interplay between OI and entrepreneurial firms' performance by developing and testing an integrated framework underpinned by a knowledge-based view and dynamic capability theory. The findings highlight the significance of taking an interdisciplinary and integrated approach to better understand the determinants of entrepreneurial firms' performance in an emerging country context.

The authors contribute to the literature on leadership by investigating how characteristics of principal investigators (PIs) affect innovation performance, and how collaborative and non-collaborative projects moderate this relationship within the context of inter-organisational research projects.

The authors analysed panel data from the National Science and Technology Information Service on 171 research projects within a biomedical and regenerative medicines programme overseen by the Korea Health Industry Development Institute. The authors used a hierarchical regression model, based on the ordinary least squares method, to examine the relationship between PI characteristics and performance, considering both quantity and quality.

The results show that the characteristics of PIs have diverse effects on the quantity and quality of innovation performance. Gender diversity within PIs negatively affects the quality of innovation performance, while the capacity of PIs positively influences it. Moreover, the degree of PI’s engagement is positively associated with the quantity of innovation performance but does not have a significant relationship with the quality of performance. In terms of moderating effects, collaborative projects with multiple leaders seem less reliant on PI capacity than non-collaborative projects led by a single leader, in terms of innovation performance.

The results contribute significantly to the literature on innovation management by examining the role of leadership in collaborative environments to enhance innovation performance, addressing the need for empirical evidence in this area. Analyses of PI characteristics in government R&D management can lead to improved team performance, more efficient processes and effective resource allocation, ultimately fostering innovation.