This study examines the role of dynamic capabilities (DCs) in the adoption of artificial intelligence (AI) systems in China’s telecommunications industry and their impact on firms’ operational performance. Drawing on DCs theory and the technology–organization–environment (TOE) framework, this study investigates how TOE factors influence DCs for AI system adoption, which subsequently impacts operational performance. It also examines the mediating role of DCs in the relationship between TOE factors and operational performance. Despite numerous studies on AI system adoption, the underlying mechanism of DCs requires further investigation. Survey data were collected from 205 senior executives of telecommunications firms in China. Analysis of the data reveals that TOE factors positively influence DCs for AI system adoption, which in turn have a positive effect on operational performance. Additionally, competitive pressure positively moderates the relationship between technological factors (i.e., technology compatibility and expected benefits) and operational performance. These findings provide managerial and theoretical insights into AI system adoption.

We systematically review the data-driven innovation (DDI) literature spanning 2009-2022, analyzing key studies, assessing the current state of DDI research in information systems and operations management, and highlighting the research gaps. A classification framework to organize the DDI research literature is proposed. Using Gregor's (2006) theory classification framework, we identify theory types in the DDI literature. By applying the structural view (level of analysis) of Smith et al. (2011), we also investigate the level of analysis in the DDI literature. Our systematic literature review and analysis provide a roadmap both to facilitate knowledge creation and accumulation and to guide future DDI research. This review, the first of its kind focusing on DDI, summarizes DDI development, and identifies opportunities for new research, concluding with directions for future exploration in the field.

In recent years, there has been a growing emphasis on the role of innovation in enhancing resilience within supply chains. Furthermore, an increased interest in innovation as a key driver of resilience can be observed in practice. Despite this increased interest, research investigating the effects of supply chain innovation (SCI) on supply chain resilience (SCR) remains limited. To address this gap, we conceptualized a theoretical framework, grounded in the dynamic capabilities view, for testing the effect of SCI on SCR. Our research model further tested whether and how environmental uncertainty (EU) and top management involvement (TMI) moderate the effect of SCI on SCR, using structural equation modelling and survey data from 212 senior managers of firms in the textile and clothing industry in China. The study's findings offer a nuanced understanding of SCR and implications regarding SCI, EU, and TMI. Implications and suggestions for further research are also provided.

Studies have shown that digital manufacturing is a key factor in sustained competitive advantage (SCA). However, few studies have investigated how SCA is affected by advanced manufacturing technology (AMT), analytics capability (AC), sensing capability (SC), and planning comprehensiveness (PC) in an uncertain environment. We developed a conceptual model based on dynamic capabilities theory and the resource-based view to empirically investigate the effects of AMT, AC, SC, and PC on SCA. In addition, our research model tested whether environmental uncertainty moderated the effects of these factors using data from 200 validated surveys completed by senior managers of firms in the clothing and textile industry in China. Our results revealed that all four factors positively influenced SCA, and that environmental uncertainty positively moderated their impact, supporting our research model. We discuss the theoretical and practical implications of these findings.

Studies indicate that organizational capability is a key factor in operational performance, and that both sensing and analytics capabilities have a significant influence on operational performance. This study develops a framework to examine the impact of organizational capability on operational performance, with a specific focus on the implementation of sensing and analytics capabilities. We combine strategic fit theory, the dynamic capability view, and the resource-based view to examine how micro, small, and medium enterprises (MSMEs) strategically integrate a data-driven culture (DDC) with their organizational capabilities to enhance operational performance. We carry out empirical research to investigate whether a DDC moderates the influence of organizational capability on operational performance. Structural equation modeling of survey data from 149 MSMEs reveals that both sensing and analytics capabilities have a positive impact on operational performance. The results also suggest that a DDC positively moderates the influence of organizational capability on operational performance. We discuss the theoretical and managerial implications of our findings, the limitations of the study, and opportunities for further research.

This paper examines the impact of data-driven innovation (DDI) on firm performance, based on an exploratory case study of a manufacturing firm in China’s textile and apparel industry. It explores the influence of various contextual variables on the firm’s DDI and suggests ways to enhance DDI and thereby firm performance. Extending the literature on DDI, the paper proposes and validates a theoretical framework that incorporates the influence of various contextual factors on firms’ DDI. The findings show that (1) individual context is associated with DDI; (2) organizational context is associated with DDI; and (3) DDI is associated with firm performance. This paper extends our understanding of how firm performance can be improved through DDI and shows that DDI should match a firm’s contextual environment.

A supply chain (SC) is seen as a source of competitive advantage, and SC innovation has become a critical research topic in business-to-business marketing and production. However, the main obstacle to empirical research on SC innovation is a lack of validated and well-developed scales to measure it. Therefore, developing a measurement scale for the SC innovation construct is necessary. This paper describes the development and validation of a third-order SC innovation scale based on the collection of primary quantitative and qualitative data. SC innovation was then operationalized as a multidimensional construct with three aspects, namely, marketing, technology development, and logistics-oriented innovation activities, resulting in 31 measurement items. The developed SC innovation scale applies to the textile and apparel industry primarily. Business-to-business marketers can apply this empirically validated scale to evaluate their SC innovation efforts and identify areas for improvement.

Business sustainability has received considerable attention in academia and industry. Accordingly, we use a multiple-case design to study the outcomes of business sustainability capability implementation. Using a two-phase data collection approach and resource-based view, we developed a conceptual model to illustrate the importance of business sustainability capability and business sustainability competence and their influence on firm performance. On the bases of the results from a case analysis of three Fortune 500 corporations in the fashion and textile industries, we show how three business sustainability capabilities (i.e., organizational, environmental, and economic competencies) affect business sustainability competence and consequently firm performance. Using in-depth case studies, we develop a set of propositions on how business sustainability competence associates with firm performance. This study was conducted over three years and demonstrates the importance of business sustainability capabilities by confirming the impact of economic competence in the context of market-driven competence and innovation, organizational competence in the context of managerial competence and social well-being, and environmental competence in the context of application of the five Rs (i. e., re-imagine, redesign, reuse, recycle, and reduce). This study thus provides valuable insights into how business sustainability capability and business sustainability competence enhance firm performance in the global fashion business.

This paper aims to systematically review the supply chain innovation literature over the last 18 years. It examines the development and current state of supply chain innovation research in management and identifies research gaps. A literature review is conducted to identify and analyze publications in peer-reviewed academic journals that include contributions from different strands of management research. This paper analyzes the theoretical contributions of the supply chain innovation literature using Gregor's (2006) framework of theory classification. It also evaluates the levels of analysis of the literature using the structural view model proposed by Skinner, Han, and Chang (2006). This research identified and analyzed various topics related to the supply chain innovation construct and showed that supply chain innovations can be studied at multiple analytical levels. It also revealed that the field has largely relied on manufacturing firm-based samples and U.S. samples, limiting the generalizability of the findings. The identification and analysis of relevant articles highlighted the need to conceptualize the supply chain innovation construct and develop measurement scales to operationalize it. This literature review is the first to focus on supply chain innovations, summarizing the development of the last 18 years and providing fruitful opportunities for future research. The results presented can be applied to the decision-making process of managers regarding supply chain innovations.