Social capital, information sharing and performance: Evidence from China

Abstract

Purpose

The purpose of this paper is to examine the effects of social resources on promoting information sharing practice and, thereby, improving firm performance. In particular, the authors are interested in addressing the following research questions. First, can the development of social capital (expressed in three dimensions: cognitive capital, structural capital, and relational capital) promote the content and quality of supply chain information sharing? Second, what are the relationships among the three social capital dimensions in the context of information sharing? Third, what are the effects of shared information (content and quality) on firm performance?

Design/methodology/approach

A theoretical model and several research hypotheses, well-grounded in the western literature, are developed. Data from 272 manufacturers in China were collected to test the model and the hypotheses. Structural equation modeling was used for statistical analysis.

Findings

The statistical results reveal that each social capital dimension has different effects on information sharing and performance. Namely, relational capital and cognitive capital have significant positive influences on information sharing. Structural capital has no direct positive impact on information sharing, but it displays indirect affects through the other two social capital dimensions. Furthermore, both the content and quality of the shared information improve manufacturing efficiency and responsiveness performance. Finally, the paper also recognizes possible reciprocal causality between relational capital and cognitive capital.

Research limitations/implications

First, considering the distinct role of social relations in China, future studies should examine the influence of social capital and the potential reciprocal relationship between trust and shared vision, using data from other countries. Second, data were collected solely from the Pearl River Delta, China. Studies based on samples drawn from other regions, such as the Yangtze River Delta, the Bohai Sea economic area, and southwest China, would provide a degree of geographic and economic diversity and extend the generalizability of the results.

Practical implications

Despite the touting of the value of information sharing, many companies struggle with the practice. The findings help us understand the process by which social capital accumulates and contributes to information sharing. Namely, firms must first engage in social interactions with supply chain partners in order to develop a trusting relationship and a shared vision for information sharing. The managers must also be aware of the possible reciprocal relationship between trust and shared vision. Both the volume and content of information sharing are critical to the performance.

Social implications

Manufacturers can use the concept of social capital to build relational rents for information sharing.

Originality/value

Responding to the call from the literature, this study extends the discussion of antecedents and consequences of supply chain information sharing, with a focus on the influences of relational resources. The paper proves that social capital provides a valid theoretical base from which to examine the role of social relations in promoting supply chain information sharing. Previous supply chain research in social capital often limited its consideration of social capital to relational capital. Understanding the effects of all three dimensions of social capital and their inter-relationships would contribute to the process by which social capital accumulates and promotes information sharing. Additionally, a study with the Chinese data should validate the theoretical model developed based on western literature, and offer valuable insights to researchers and practitioners from both economic and cultural perspectives.

Citation

Li, Y., Ye, F. and Sheu, C. (2014), "Social capital, information sharing and performance: Evidence from China", International Journal of Operations & Production Management, Vol. 34 No. 11, pp. 1440-1462. https://doi.org/10.1108/IJOPM-03-2013-0132