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This study aims to investigate how dynamic capabilities, i.e. sensing, learning, integrating and coordinating trigger sustainable innovation performance. It also examines the direct and moderating role of environmental turbulence towards the sustainable innovation performance of small and medium-sized enterprises (SMEs).

The data were collected through a cross-sectional survey of 169 SMEs in Oman and analysed through structural equation modelling using SmartPLS software.

Findings of this study reveal that the sustainable innovation performance of SMEs is greatly influenced by the synergy of learning, integrating and coordinating capabilities. Notably, among these capabilities, coordinating capability emerges as the most important capability for SMEs with a primary emphasis on fostering both human and organizational well-being. However, this research reveals that building dynamic capabilities alone might not be sufficient to address social, ecological and economic sustainability criteria, and SMEs may need to extend their view beyond internal processes and integrate various environmental contingencies into their approaches while focusing on sustainable innovation performance.

This research is useful for business managers while allocating resources in their business efficiently and effectively to achieve sustainable innovation performance. It also highlights that SMEs need to integrate various environmental contingencies into their approaches while focusing on sustainable innovation performance.

To the best of the authors’ knowledge, this study is one of the first to contribute to SME scholarship by mainly investigating the effect of specific four types of dynamic capabilities on sustainable innovation performance in a turbulent environment. This study is likely to contribute to the SMEs addressing sustainability innovation performance and develop capabilities to be sustainable in a turbulent environment.

This study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on digital transformation (DT) outcomes for small- and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.

The study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.

The findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity’s positive and significant moderating effect on these indirect relationships.

This research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants and outcomes of digitalisation.

Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

This study examines how intellectual capital (IC) drives firm performance via the lens of dynamic capabilities (DCs). Drawing on resource-based view (RBV) and dynamic capability view (DCV), the authors elaborate the mediating role of learning, integration and reconfiguration DC in the Indian banking context.

A sample of 358 top- and middle-level managers from the Indian banking sector was administered with structured questionnaires for data collection. Structural equation modeling (SEM) and Sobel test were used to analyze the data and test the hypothesized mediating effect.

The findings reveal that learning and integration DCs are key mediators in IC and banks' performance relationships in an emerging economy context. In contrast, the analysis revealed partial mediating role of reconfiguration DC. Furthermore, the learning DC has been identified as the primary mediating mechanism for transforming bank's IC into performance benefits.

This study provides an important implication for the IC and DC link by empirically developing and validating a model in the Indian banking sector and making a several contributions to the related literature. This sector needs to incorporate and strengthen their IC and DCs to attain enhanced performance in today's dynamic environment. Bank managers can use these findings to bring their knowledge-related activities to channelize specific DCs to transform banks' IC when seeking to improve overall performance. Theoretically, this study extends previous research by outlining a set of organizational elements that tend to influence firm performances with the help of IC, learning, integration and reconfigurations DCs.

Although several studies have investigated the links between IC, DC and firm performance, studies on emerging economies are scarce. This study is one of the most in-depth investigations of the relationship between IC, learning, integration and reconfiguration DCs and firm performance in an integrated framework, with a particular focus on the banking sector of an emerging economy.

Against the backdrop of the global reshaping of supply chains, supply chain ecosystems have emerged as a critical force in ensuring the high-quality development of enterprises and fostering stable economic growth. However, a systematic theoretical understanding of how to construct these supply chain ecosystems remains nascent. This study aims to explore the mechanism of the process of building supply chain ecosystems between digital innovation platform enterprises and digital trading platform enterprises from the perspective of dynamic capabilities.

An explanatory case study is conducted based on a theoretical framework grounded on dynamic capabilities view. Two preeminent digital platform enterprises in China (Haier and JD.com) are studied. The authors primarily conducted this research by collecting a large volume of these Chinese public materials.

First, the construction processes of supply chain ecosystems in both digital platform enterprises can be delineated into three stages: embryonic, development and maturity. Second, digital innovation platform enterprises’ construction process is primarily influenced by factors such as production and operational collaboration, consumer demand and research and development. This influence is exerted through interactions on digital platforms and within sub-ecosystems. Meanwhile, digital trading platform enterprises’ construction process is influenced by factors such as infrastructure development, consumer demand and financial support, driving dynamic capability formation through multi-party cooperation and ecological interactions based on conceptual identity.

In the establishment of supply chain ecosystems, digital platform enterprises should prioritize the cultivation of opportunity expansion, resource integration and symbiotic relationship capabilities. Furthermore, this study shows that digital platform enterprises need to actively adjust their interactive relationships with cooperating enterprises based on changes in the market, industry, policies and their own developmental stages.

This study addresses prior deficiencies in understanding the comprehensive construction of supply chain ecosystems and provides significant insights to enhance the theoretical foundation of supply chain ecosystem studies. Additionally, this paper uncovers the dynamic capability development behaviors and contextual features inherent in the construction process of supply chain ecosystems by digital platform enterprises.

Eco-innovations (EIs) are intended to benefit not only the environment but society and firms, but how the relationship is reconciled is unclear, particularly in emerging economies. The advancement of EI has resulted in both positive and negative relationships with sustainability, indicating that the association is more complex than a simple linear one.

Thus, the authors hypothesize that EI has a curvilinear relationship with sustainable business performance (SPB) and that market turbulence (MT) exerts stimulus that reinforces EIs. Accordingly, using the Stata software, the authors apply a moderated regression to a sample size data of 511 manufacturing firms to test the hypothesized assumptions.

Although the results attest to a positive relationship between EI and SBP, the results are synonymous with an inverted “U” shape that renders EIs unprofitable beyond a certain threshold (rebound effect). Additionally, the authors observe that the moderation stimulus of technology turbulence flattens the inverted U-shaped curve.

Built on the foundations of natural-resource-based view (NRBV) and contingency theory, the authors identify the rebound effect point of EI and SBP and the reinforcing stimulus of MT.

Digital transformation provides a new impetus for the development of declining firms. However, there is currently a lack of sufficient research on whether digital transformation is beneficial for the turnaround of declining firms. This paper aims to explore the relationship between digital transformation and the turnaround of declining firms.

Drawing on the theoretical foundations of the resource-based view and dynamic capabilities theory, this research uses a comprehensive dataset of Chinese A-share listed companies from 2010–2021 to explore the influence of digital transformation on the turnaround of declining firms.

The research findings show that digital transformation contributes to the turnaround of declining firms. Mechanism analyses demonstrate that digital transformation enhances dynamic capabilities and attracts more analysts, thereby facilitating the turnaround process. Moreover, the moderation analysis reveals that CEO equity incentives strengthen the positive correlation between digital transformation and the turnaround of declining firms. Heterogeneity analysis indicates that the association between digital transformation and the turnaround of declining firms is particularly significant for firms with low financing constraints and high-tech firms. Moreover, this research reveals that digital transformation can facilitate the turnaround of firms in deep and long-term decline.

This research contributes to the literature on the digital transformation of enterprises and provides important insights for the turnaround of declining firms.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

To meet environmental performance (EP) goals, this study aims to identify the complex interaction between green Industrial Internet of Things (GIIoT), circular economic practices (CEPs) and dynamic capabilities (DC). This study analyzes how technological, operational and cultural compatibilities enhance GIIoT adoption.

Data were collected from diverse Chinese manufacturing firms (n = 339) through a quantitative survey. The research model was proposed, and hypotheses were tested using structural equation modeling. Moreover, the robustness of the structural model is further tested using Fuzzy Set Qualitative Comparative Analysis and importance performance map analysis.

The empirical results indicate that higher organizational compatibilities boost GIIoT adoption and EP. DC was assessed as a higher-order construct to examine its mediation of GIIoT adoption and EP. DC positively mediates GIIoT adoption-EP. Similarly, CEP’s positive impact on EP, partially mediating the relationship between GIIoT adoption and EP, has also been proved.

This research bridges current understanding and contributes useful insights for fostering environmental sustainability inside manufacturing firms and advances the theoretical understanding of technology adoption, sustainable development and dynamic capacity theory. It illuminates the way forward to harmonize and successfully integrate technology, CEP and EP. This research advances the area and gives decision-makers practical advice for creating sustainable and technologically sophisticated organizations.

For start-ups or growing firms, to effectively navigate the unpredictable nature of digital development and achieve superior innovative performance, it is crucial to have a workforce comprised of creative and innovative employees. Drawing upon the principles of social information processing theory, this study aims to investigate whether specific combinations of organizational internal and external environments, as well as work characteristics in the digital age, can foster a high level of employee innovative behavior.

By collecting a multilevel and multisource data set comprising 693 employees and 88 CEOs from 88 start-ups or growing firms, this study used fuzzy-set qualitative comparative analysis to examine the distinctive configurations associated with achieving a high level of employee innovative behavior.

The study found that six solutions enabled employees to innovate more effectively, but six solutions led to the absence of employee innovative behavior.

The findings of this study offer important theoretical and practical implications to motivate employee innovative behavior in Chinese enterprises.

First, this study contributes to the literature on employee innovative behavior by addressing the need to explore the impact of the digital context on promoting innovation among employees. Second, this study adds to the existing literature on employee innovation and entrepreneurship by examining multiple organizational contexts and their influence on innovative behavior. Third, this study makes a significant contribution to the field of employee innovative behavior by examining the macroenvironment surrounding digital transformation within enterprises and integrating both internal and external organizational factors.