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Background: This paper aims to investigate the relationship between big data capability (BDC) and supply chain performance (SCP), and to examine the mediating role of supply chain resilience (SCR) and the moderating role of environmental uncertainty (EU) on the relationship between BDC and SCP. Drawing on the dynamic capability view and contingency theory, the study developed and tested a conceptual model with empirical data, clarifying the effects of BDA on SCP, the mediating effects of SCR and the moderating effects of EU. Methods: The primary survey data of 232 responses were collected from supply chain managers of manufacturers in China. The data were analyzed by employing SPSS and AMOS, and hierarchical regression was used to test the hypothesis. Results: The study found that BDC and its three dimensions have a significant impact on SCP, with a partial mediating role for SCR. Additionally, environmental uncertainty significantly moderates the relationships between BDC and SCR and between SCR and SCP. Conclusions: The results indicate the growing role of big data in supply chain resilience and performance, especially for small and medium-sized firms. Manufacturing companies should accelerate the development of supply chain resilience management systems and enhance their ability to cope with environmental changes. Managers should also be alert to the risks of changes in the external environment and allocate appropriate resources to mitigate environmental uncertainty and adapt to environmental changes. Limitations and further research directions are also provided in the paper. [ABSTRACT FROM AUTHOR]

Digital transformation has emerged as a key driver of high-quality enterprise development and an essential tool in forging an innovation-driven paradigm.Existing studies fail to delve into the specific mechanisms of their impact on firms' innovation performance, and views on their impact are divergent. Some studies suggest that digital transformation can enhance innovation performance, while others point out that it may have negative impacts, and cannot clearly answer how big data capabilities and organisational agility play a role in the digital transformation process. Therefore, based on dynamic capability theory and systems engineering theory, this study adopts the logical framework of ''strategy-behaviour-performance'' to systematically explore the process of digital transformation that enhances firms' innovation performance through the enhancement of big data capability and organisational agility. By empirically analysing the survey data of 476 manufacturing enterprises in China, the study reveals the chain-mediated effects of big data capability and organisational agility, and confirms the key roles of both in the transformation process. The findings suggest that digital transformation significantly improves firms' innovation performance, and that the dual mediating effects of big data capability and organisational agility are important links in its influencing mechanism. These findings not only provide empirical support for the theoretical model of digital transformation, but also provide practical guidance for enterprises to formulate strategies and optimise resource allocation in the digital era. We suggest that enterprises should strengthen the cultivation of big data capabilities and organisational agility while promoting digital transformation to better adapt to and lead market changes.

The past decade has seen the rapid emergence of research on Big Data and its implications in our society, yet research on its impact on organizations' sustainability challenges is still at an early stage. Based on the organizational learning theory, we develop a framework to investigate the effects of Big Data capability (BDC) and further intellectual capital on a firm's sustainability‐oriented innovation performance (SIP). Using a multi‐source data collected from 358 Chinese firms, we tested our proposed hypotheses using the partial least squares‐structural equation modeling (PLS‐SEM) and the fuzzy‐set qualitative comparative analysis (fsQCA). The results show that BDC is positively related to SIP and economic innovation performance (EIP), mediated by intellectual capital. The fsQCA results further reveal that three configurative combinations, that is, "external capability‐internal resource promotion," "external capability and relationship building help," and "external relationship collaboration compensation," can lead to high SIP. This study provides new insights for firms to develop sustainability‐oriented innovation and to coordinate sustainability innovation and economic innovation practices in order to create balanced outcomes. [ABSTRACT FROM AUTHOR]

Based on dynamic capability theory and legitimacy theory, a theoretical model is constructed to examine how big data capability, through the mediation of knowledge dynamic capability, drive business model innovation under the moderation effect of innovation legitimacy. The analysis is conducted using regression analysis and fuzzy set qualitative comparative analysis (fsQCA) on survey data from 302 enterprises that have already implemented big data application practices. The study finds the following four conclusions. (1) Big data capability has a significant positive impact on business model innovation. (2) Dynamic knowledge capability partially mediates the relationship between big data capability and business model innovation. (3) Innovation legitimacy positively influences business model innovation and positively moderates the relationship between big data capability and business model innovation. (4) Through further qualitative comparative analysis, two causal paths that influence business model innovation are identified. [ABSTRACT FROM AUTHOR]

In an era of digital economy, big data capability becomes a new approach for organisational competitive advantage in market. Products are the concentrated reflection of commercial value in market. It is crucial to clarify when and how big data capability promotes product speed-to-market. Based on the perspective of knowledge integration, we propose a model to clarify the impact of big data capability on product speed-to-market in a competitive market. Using data from 405 enterprises in China, we test our research model. We find that big data capability has positive effect on market-oriented knowledge integration (MOKI) and product speed-to-market, respectively. MOKI partly mediates the relationship between big data capability and product speed-to-market. In addition, the findings also indicate that market competition moderates the indirect effect. The results of this paper provide specific managerial guidelines as to how to apply big data to improve speed-to-market. [ABSTRACT FROM AUTHOR]

After the rapid expansion of data variety, velocity and volume, human civilization experienced rapid changes in the period between the "IT" and "Data" ages. Researchers view big data and data capability as new sustainable competitive advantages that enhance the sustainability of organizational development. This paper aims to develop and empirically test a framework that will investigate how big data capability is achieved through exploitative, explorative and ambidextrous modes of innovation strategies, and will also explore how they can, in turn, build firms' sustainable competitive advantage. Using data from surveys of 229 respondents working in Chinese manufacturing firms, we test the framework using regression and bootstrapped mediation analyses. It also shows how big data capability will make firms more inclined to implement exploitative innovation strategy and construct sustainable competitive advantage, as opposed to explorative innovation strategy; when viewed from an ambidextrous perspective, combined dimension of ambidextrous innovation strategy is found to partially mediate between big data capability and sustainable competitive advantage while balanced dimension of ambidextrous innovation strategy does not. The conclusions are of great significance because they will help firms to deal with challenges that arise in big data applications and digital transformation. The findings offer new insight into the strategic choices of organizational innovations. [ABSTRACT FROM AUTHOR]

Digital transformation has emerged as a key driver of high-quality enterprise development and an essential tool in forging an innovation-driven paradigm.Existing studies fail to delve into the specific mechanisms of their impact on firms' innovation performance, and views on their impact are divergent. Some studies suggest that digital transformation can enhance innovation performance, while others point out that it may have negative impacts, and cannot clearly answer how big data capabilities and organisational agility play a role in the digital transformation process. Therefore, based on dynamic capability theory and systems engineering theory, this study adopts the logical framework of "strategy-behaviour-performance" to systematically explore the process of digital transformation that enhances firms' innovation performance through the enhancement of big data capability and organisational agility. By empirically analysing the survey data of 476 manufacturing enterprises in China, the study reveals the chain-mediated effects of big data capability and organisational agility, and confirms the key roles of both in the transformation process. The findings suggest that digital transformation significantly improves firms' innovation performance, and that the dual mediating effects of big data capability and organisational agility are important links in its influencing mechanism. These findings not only provide empirical support for the theoretical model of digital transformation, but also provide practical guidance for enterprises to formulate strategies and optimise resource allocation in the digital era. We suggest that enterprises should strengthen the cultivation of big data capabilities and organisational agility while promoting digital transformation to better adapt to and lead market changes., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

This study draws on the dynamic capabilities view and the firm's big data capability (BDC) in the new economic environment. It constructs an adjusted intermediary model to study the mechanism of BDC, strategic flexibility, and environmental dynamic affecting financial performance. We find that strategic flexibility plays an intermediary role in the "Converse-U" relationship between BDC and financial performance. Environmental dynamics adjust the relationship between BDC and financial performance positively and smooth the "Converse-U" relationship. The findings suggest building and managing BDC, combining BDC with the management process, and achieving continuous financial performance improvement in a dynamic environment. The paper also puts forward the nonlinear hypothesis, discusses the "Converse-U" relationship between BDC and enterprise financial performance in the Chinese context of digital economy explosion and growth, and considers the intermediary mechanism of strategic flexibility and the regulatory effect of environmental dynamics. [ABSTRACT FROM AUTHOR]

This study draws on the dynamic capabilities view and the firm’s big data capability (BDC) in the new economic environment. It constructs an adjusted intermediary model to study the mechanism of BDC, strategic flexibility, and environmental dynamic affecting financial performance. We find that strategic flexibility plays an intermediary role in the “Converse-U” relationship between BDC and financial performance. Environmental dynamics adjust the relationship between BDC and financial performance positively and smooth the “Converse-U” relationship. The findings suggest building and managing BDC, combining BDC with the management process, and achieving continuous financial performance improvement in a dynamic environment. The paper also puts forward the nonlinear hypothesis, discusses the “Converse-U” relationship between BDC and enterprise financial performance in the Chinese context of digital economy explosion and growth, and considers the intermediary mechanism of strategic flexibility and the regulatory effect of environmental dynamics.

This research takes manufacturing enterprises with big data capability as the research object, based on organizational decision-making theory and planned behavior theory, the mediation effect model of "capability-intention-behavior" is constructed. It uses econometric models to explore the impact and conduction process of big data capability on green process innovation. The results show that big data capability have an obvious direct effect on green process innovation. By examining the mediation effect test, we find that green innovation intention partially mediates the relationship between big data capability and green process innovation. Then a fuzzy set qualitative comparative analysis (fs QCA) is used in this paper to analyze the causal complexity between big data capability and green process innovation, and to identify six effective configuration paths. According to the results, the synergy of big data acquisition capability, big data analysis capability and big data insight capability is crucial for high green process innovation, where big data insight capability plays a central role and big data acquisition capability or analysis capability and green innovation intention play a marginal role. According to the heterogeneity test, it is found that big data capability has stronger roles in the eastern region in China; green innovation intention has a stronger impact in the central and western regions in China. As enterprise-scale increases, the impact of big data capability on green process innovation increases and then declines, while the impact of green innovation intention on green process innovation continues to decline. [Display omitted] • Dividing big data capability into acquisition, analysis and insight capabilities. • Big data capability affects green process innovation via green innovation intention. • Constructing the intermediary effect model of "capability-intention-behavior". • Fs QCA is used to analyze the causal complexity and identify the configuration paths. [ABSTRACT FROM AUTHOR]

Keywords: COVID-19 pandemic; big data capability; strategic flexibility; financial performance; environmental psychological dynamics EN COVID-19 pandemic big data capability strategic flexibility financial performance environmental psychological dynamics 1 1 1 05/12/22 20220510 NES 220510 In the original article the authors neglected to include a Funding statement. COVID-19 pandemic, financial performance, big data capability, environmental psychological dynamics, strategic flexibility. [Extracted from the article]