While many organizations have successfully leveraged big data analytics capabilities to improve their performance, our understanding is limited on whether and how big data analytics capabilities affect social innovation in organizations. Based on the organizational information processing theory and the organizational learning theory, this study aims to investigate how big data analytics capabilities support social innovation, and how knowledge ambidexterity mediates this relationship. A total of 354 high-tech companies in China, this study shows that big data analytics management, big data analytics technology, and big data analytics personnel capabilities all have positive effects on social innovation. In addition, both knowledge exploration and knowledge exploitation play a mediating role in this process. Furthermore, a polynomial regression and response surface analysis shows that social innovation increases when knowledge exploration and knowledge exploitation are highly consistent but declines when knowledge exploration and knowledge exploitation are inconsistent. This study not only provides new perspectives for understanding how big data analytics capabilities contribute to social innovation, complementing the existing literature on big data analytics capabilities and social innovation, but also provides important practical guidance on how organizations can develop big data analytics capabilities to improve social innovation and solve social problems in the digital age.

This study investigates how digital overload and perceived digital surveillance affect job performance in the Bangladeshi banking sector. It specifically focuses on technostress as a mediating variable and perceived organizational support (POS) as a moderating variable-two mechanisms central to understanding employees' responses to digital stressors. As digitalization reshapes the banking sector, employees face increasing pressures from these digital demands, that can significantly influence their job performance. By surveying 468 banking employees, the study employs the Job Demands-Resources (JD-R) model and the Transactional Theory of Stress to examine how digital stressors contribute to technostress, which subsequently impacts job performance. The findings reveal that digital overload and perceived surveillance significantly elevate technostress, which in turn positively influences job performance. Additionally, POS moderates this relationship by strengthening the positive effect of technostress on performance, suggesting that organizational support enables employees to harness technostress as a motivating force. This research makes a novel contribution to the literature by integrating technostress within the framework of digital transformation in the banking sector, a topic underexplored in the Bangladeshi context. The study not only advances theoretical understanding of digital work stressors but also offers practical insights for organizations aiming to maintain employee performance and well-being amid ongoing digital change. It underscores the importance of organizational support as a key enabler of effective digital transformation.

In order to cope with the multimodal changes led by the digital era, enterprises urgently need to promote the construction of new-quality productive forces (NQPFs) through digital transformation. NQPFs take digital technology empowerment as the core driving force and emphasize the dynamic matching and synergy between the new-quality elements (digital infrastructure, digital talents, data resources, and diversified ecology) and the new-quality capabilities (digital dynamic capabilities) so as to unleash the innovation potentials of different production modes. Based on resource orchestration theory, this study constructs a “resource-capability-value creation” framework for digital empowerment (D-RCV) and employs fuzzy set qualitative comparative analysis (fsQCA) to examine 205 enterprise samples. Results reveal that enhanced innovation performance stems from digital empowerment at both resource and capability levels, generating three configurational paths: collaborative symbiosis, resource optimization, and data-driven approaches. These paths emerge through the interaction of resources and capabilities under different conditions. This study contributes by proposing a digital empowerment framework and exploring multiple pathway choices for new-quality productivity development. The findings provide theoretical insights for enterprise innovation research and practical guidance for innovation management strategies.

Purpose: The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.Design/methodology/approach: This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.Findings: The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.Originality/value: This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

Purpose: Online brand communities (OBCs) are important platforms to obtain consumers' ideas. The purpose of this study is to examine how peer influence and consumer contribution behavior simulate innovative behaviors in OBCs to increase idea quality.Design/methodology/approach: Using a firm-hosted popular online brand community – Xiaomi Community (MIUI), the authors collected a set of data from 6567 consumers and then used structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to empirically test the impact of peer influence and consumer contribution behaviors on idea quality in OBCs.Findings: The results of this study show that both peer influence breadth and depth have a positive effect on idea adoption and peer recognition, wherein proactive contribution behavior positively mediates these relationships, and responsive contribution behavior negatively mediates the impact of peer influence breadth and peer influence depth on peer recognition. A more detailed analysis using the fsQCA method further identifies four types of antecedent configurations for better idea quality.Originality/value: Based on the attention-based view and the theory of learning by feedback, this study explores the factors that affect idea quality in the context of social networks and extends the research of peer influence in the digital age. The paper helps improve our understanding of how to promote customer idea quality in OBCs.

This study examines how environmental regulation (ER), green intellectual capital (GIC), green human resource management (GHRM), and green ambidextrous innovation (GAI) contribute to enhancing the sustainable performance (SP) of manufacturing firms. Using a quantitative approach, data from 472 managers of green garment manufacturing firms in Bangladesh were analyzed with SmartPLS4 software. The results indicate that GHRM and GIC positively impact SP, with GIC exerting a stronger influence on GAI—encompassing green exploitative innovation (EIGI) and green exploratory innovation (ERGI)—compared to GHRM. Additionally, GAI positively affects SP and serves as a partial mediator in the GIC-SP relationship but not in the GHRM-SP relationship. ER negatively moderates the GHRM-SP and GHRM-GAI links, while it positively moderates the GIC-GAI relationship, albeit weakly in the GIC-SP connection. This study highlights GAI’s mediating roles in the GHRM-SP (specifically, GHRM-EIGI-SP and GHRM-ERGI-SP) and GIC-SP (specifically, GIC-EIGI-SP and GIC-ERGI-SP) relationships within a regulatory context. By introducing fresh perspectives, this research advances green management studies, offering valuable insights for academics and industry professionals. It provides a strategic framework for firms to navigate regulations, foster innovation, optimize human and intangible resources, and enhance sustainable performance, thereby positioning themselves as leaders in the global market.