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This study conceptualizes the digital transformation (DT) strategy in a supply chain context, identifies its drivers from intra- and inter-organizational perspectives and examines the effect of the DT strategy on the strategic agility and financial performance of Chinese manufacturing firms.

The authors constructed a theoretical model by synthesizing the diffusion of innovation and organizational information processing theory (OIPT) and provided a set of hypotheses. The authors empirically tested the arguments using partial least squares structural equation modeling using data from a sample of 200 manufacturing firms in China.

The findings indicate that while supply chain connectivity positively affects DT adoption and DT routinization, data analytics capability and organizational learning positively influence DT adoption but not DT routinization. The mediation analysis also shows that DT strategy has significant direct effects on financial performance and a stronger indirect influence on financial performance via improved strategic agility.

This study responds to repeated calls for a new understanding of supply chain DT strategy. In addition, the study offers important contributions to the literature by identifying the potential discord between the existing DT strategy and the supply chain context and proposes a new framework that provides essential theoretical underpinnings.

This study enriches the literature by conceptualizing and validating the dimensions, driving factors and performance implications of DT strategy in strategic supply chain management.

The purpose of this study is to conduct an empirical investigation into the impact of supply chain dependence (including customer dependence and supplier dependence) on credit risk through the lens of social network theory (SNT) by focusing on how to manage firm risk using supply chain relationships in the context of Chinese small and medium-sized enterprises (SMEs).

Using data from public databases, this study selects a unique sample from a Chinese SME board and uses an ordered logistic regression model to investigate the relationship between the dependence on major customers or suppliers and both credit risk and credit rating. It is found that the results are robust to the use of different empirical methods.

The main findings of this study are that a firm’s dependence on major customers is positively related to its credit risk but negatively related to its credit rating, while a firm’s dependence on major suppliers is positively related to its credit risk but negatively related to its credit rating.

To broaden the understanding of industrial marketing and purchasing, this study contributes to research on supply chain relationship management and risk management by focusing on SMEs’ dependence on major customers and suppliers and empirically examining the influence of this dependence on both credit risk and credit rating in an emerging market.

The necessity of geographical accessibility between service provider and the customer has been essential for face‐to‐face contact in many service industries. However, the emergence of electronic commerce (EC) and new technologies has altered the concept of location and geographical accessibility of service industries in a traditional economy. This study developed factors representing characteristics of product/service processes and verified that those factors are significantly related to customer needs of geographical accessibility in the transactions of EC. In addition, it investigated the relationships with the reasons for customer needs of geographical accessibility. Data for analyses were collected through customer surveys and statistically analyzed through exploratory factor analysis, multiple regression analysis, and canonical correlation analysis.

An issue devoted to the Second International Conference on Electronic Business, in December 2002, in Taiwan. Included are six papers, taken from a total of 205 papers that were originally submitted, accepted and included in the conference proceedings.