Confirmation of a measurement model for green supply chain management practices implementation

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Abstract

This study aims to empirically investigate the construct of and the scale for evaluating green supply chain management (GSCM) practices implementation among manufacturers. With data collected from 341 Chinese manufacturers, two measurement models of GSCM practices implementation were tested and compared by confirmatory factor analysis. Our empirical findings suggest that both the first-order and the second-order models for GSCM implementation are reliable and valid. Our study contributes to the literature on empirical examination of the construct of GSCM practices implementation and to the practices of managers with a validated measurement scale to evaluate their strengths and weaknesses in different facets of implementing GSCM practices in their organizations.

Introduction

Environmentally sustainable (green) supply chain management (GSCM) has emerged as an important organizational philosophy to achieve corporate profit and market share objectives by reducing environmental risks and impacts while improving ecological efficiency of these organizations and their partners (van Hoek and Erasmus, 2000). As a synergistic joining of environmental and supply chain management, the competitive and global dimensions of these two topics cannot go unnoticed by organizations. For example, multinational enterprises have established global networks of suppliers to take advantage of country–industry-specific characteristics to build competitive advantage (Dunning, 1993). Simultaneously, due to stricter regulations and increased community and consumer pressures, manufacturers need to effectively integrate environmental concerns into their regular practices and onto their strategic planning agenda. As a result, integrating environmental concerns into supply chain management has become increasingly important for manufacturers to gain and maintain competitive advantage. Thus, the study of this topic is timely and necessary to better aid organizations in the GSCM principles.

To advance investigation and practice in GSCM, appropriate measurement scales are needed. In general, identification of appropriate measurement scales for emerging concepts and theories is necessary to complete robust research and to advance the body of knowledge in a field. Devellis (2003) states that measurement is a fundamental activity of science and that measurements and broader scientific questions interacting with each other within their boundaries are almost imperceptible. The field of GSCM is arguably in its early development phases, both academically and practically. Academically, to effectively and empirically advance theory within this field, some useful and testable multi-item measurement scales are needed. Thus, greater attention will need to be focused on employing multi-item latent constructs, assessing them for content validity and purifying them through field-based testing (Malhotra and Grover, 1998). Using literature in supply chain (operations) and environmental management, we introduce a number of scales that may be used to help evaluate practices in this area. Practically, organizations can also benefit from the development of reliable and valid scales to measure GSCM practices implementation. Practitioners can use these scales for benchmarking, continuous improvement, and project management activities when seeking to implement GSCM practices. One contribution of this study is to help manufacturers understand the different facets of GSCM practices implementation and identify the strengths and weaknesses of the implementation of their GSCM practices.

Given the academic (theoretical) and practical importance of developing a GSCM practices implementation measurement scale, we introduce a study based on an empirical survey of Chinese manufacturing organizations. Chinese manufacturers provide a microcosm of international markets. In some ways they are very advanced in practices and technology due to their relationships with international partners and community. In other ways, many Chinese organizations still lack the knowledge and economic resources of developed country institutions and function within a developing and emerging economy context. Thus, in one study, we can include situations where the GSCM practice concepts are relatively novel to some organizations but concurrently more mature and acceptable for more advanced organizations (see Zhu et al. (2005) for examples of the diffusion of these concepts). Thus, measurement scales that have general agreement in this diverse economic environment, and across numerous industries, provide an extra degree of robustness.

The objective of this study is to investigate the GSCM practices implementation construct and its defining measurement items emphasizing Chinese manufacturers with broader implications for application of these scales to other environments (e.g., research in other countries and further development of environmental and supply chain research). In this paper, we initially introduce literature reviews of measurement items for GSCM practices implementation in Section 2. The methodology used to develop and validate the GSCM practices implementation scale will be presented in Section 3. Section 4 will present results of this study, followed by discussions and implications of these results in Section 5. Section 6 concludes our discussion by summarizing our findings, implications, limitations, and potential topics for future research.

Section snippets

Literature review of GSCM practices implementation

GSCM has emerged as an effective management tool and philosophy for proactive and leading manufacturing organizations. The scope of GSCM practices implementation ranges from green purchasing (GP) to integrated life-cycle management supply chains flowing from supplier, through to manufacturer, customer, and closing the loop with reverse logistics. A number of definitions of GSCM exist (Zhu and Sarkis, 2004). Similar to the concept of supply chain management, the boundary of GSCM is dependent on

Methodology

Following Churchill's (1979) paradigm for construct development and measurement, we first conceptualize the construct of GSCM practices implementation and then operationalize the construct by developing a multi-item five-point Likert measurement scale to evaluate the different facets of GSCM practices implemented among Chinese manufacturers. To help support scale generalization, it is important to collect data from a broad variety of organizational and contextual characteristics. Even though we

Validity and reliability testing

We first tested the measurement properties of the GSCM practices implementation construct using reliability and item-to-total correlation analyses, followed by CFA (cf. Lai et al., 2002). CFA was used to assess how well the observed variables, i.e., measurement items, reflect unobserved or latent variables in the hypothesized structure. A strong a priori basis from our previous research warrants the use of CFA instead of EFA.

The reliability test and item-to-total correlation analysis results

Discussion

In this study, a construct for GSCM practices implementation, utilizing a survey instrument administered to Chinese manufacturers, is examined and a measurement scale for evaluating the different facets of GSCM practices implementation is tested for its validity and reliability. Utilizing exploratory results from our previous study (Zhu and Sarkis, 2004), the measurement items in the scale for evaluating GSCM practices implementation are classified into five a priori dimensions: IEM, GP, CC,

Conclusions and future research

This study presents practitioners with a 21-item measurement scale for evaluating the different facets of their GSCM practices implementation. The empirical results suggest that all 21 measurement items are critical attributes of the five underlying factors of GSCM practices implementation. Manufacturers wishing to improve their GSCM practices need to constantly monitor their implementation. The measurement scale validated in this paper can be used as a self-diagnostic tool to identify areas

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    Supported by the Ninth Huo-yingdong Young Faculty Foundation 91082, the National Natural Science Foundation of China Project (70202006), the Natural Science Foundation of Liaoning Province (20052180), and a research grant by The Hong Kong Polytechnic University (A630).

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