Gaining Competitive Advantage through Strategic Green Supply Chain Management: From a Literature Review towards a Conceptual Model

The link between green supply chain practices (GSCPs) and competitive advantages (CAs) is a subject of growing interest amongst academics and practitioners. Despite the theoretical arguments that environmentally conscious practices would give competitive advantages for companies, there is no consensus in empirical research concerning the positive impact of GSCPs on CAs. Due to this lack of clarity in the literature, this study undertakes a comprehensive review to evaluate the circumstances necessary for GSCPs to achieve sustainable CAs. Subsequently, a conceptual model is proposed to elaborate on the causal relationship between GSCPs and CAs. Future research opportunities are recommended to expand on the proposed conceptual model and to address the shortcomings of the existing literature

細菌細胞膜に含まれるカルジオリピンの抗原性とその抗体の細菌に対する反応性

The ecological issues arising from manufacturing operations have led to the focus on environmental sustainability in manufacturing. This can be addressed adequately using a closed-loop supply chain (CLSC). To attain an effective and efficient CLSC, it is necessary to imbibe a holistic performance measurement approach. In order to achieve this, there is a need to adopt a specific approach for a particular product rather than being generic. Since sustainability has direct environmental footprints that involve organizational stakeholders, suppliers, customers and the society at large, complexities surrounding supply chain performance measurement have multiplied. In this study, a suitable approach has been proposed for CLSC performance measurement in the automotive industry, based on reviewed literature. It is believed that this approach will result in increased effectiveness and efficiency in CLSC performance measurement

Fuzzy logic evaluation of reverse logistics performance in the automotive industry

This study was aimed at evaluating the performance of the reverse logistics process in the automotive industry. Fuzzy logic was applied in assessing the performance of the reverse logistics process using a case study. Linguistic variables were used to represent the performance of the metrics, and the variables were converted into fuzzy numbers. Fuzzy operators were applied to these numbers to obtain the performance of the measures and the entire process. From the results obtained, it was found that the approach adopted is applicable in evaluating the reverse logistics performance of the automotive industry. Based on this study, managers can assess their reverse logistics processes with ease and identify areas which are deficient, thus improving the overall performance of their reverse logistics. This will in turn support environmental management through waste reduction. In essence, this paper contributes to knowledge in performance measurement at large, thus putting forth a measurement approach for reverse logistics operations in the automotive industry. It also gives guidelines for future research in reverse logistics management

Evaluation of green supply chain management practices in the Malaysian automotive industry

Becoming 'green' has become the latest challenge to automobile manufacturers. Greening the supply chain is viewed as an effective strategy towards environmental friendly products. This study used a set of measures and metrics to evaluate the green supply chain practices of the major automotive companies in Malaysia. The evaluation was conducted based on the various echelons involved in each company's supply chain. Ten major suppliers and 100 customers were selected for the evaluation of each company. The internal operations of the organisations were also assessed. The results were analysed and inferences were drawn based on the results. It was found that green supply chain management in Malaysia has not received adequate attention. The study culminated with recommendations for further studies

An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry

Closed-loop supply chain management has been identified as an efficient, effective and economical strategy towards environmental sustainable practices in manufacturing companies. Without a formidable closed-loop supply chain to complement green supply chain management, most of the goals will not be achieved. A performance evaluation system is crucial for achieving a successful closed-loop supply chain in the automotive industry. Hence, a suitable expert fuzzy rule-based system for evaluation was developed in this study using Visual Basic.Net. The fuzzy rules and arithmetic used were described. The resulting performance measurement system was evaluated using a case study company from the automotive industry. The study culminated with recommendations and proposal of directions for future studies

A study on the validation of green supply chain performance measures in the automotive industry

This study was aimed at establishing the validity of the measures and metrics for automobile green supply chain performance measurement. The study involved statistical tests using 16 measures and 72 corresponding metrics. These statistical tests include exploratory factor analysis to investigate the construct validity of the measures and their metrics, a confirmatory factor analysis to test the model fitness and a multiple regression analysis to test the criterion validity of the measures. From the results obtained, the validity of the measures and their corresponding metrics has been established. The paper culminated with recommendations for further studies

Validation of green supply chain perfomance measure in the automotive industry

This study was aimed at establishing the validity of the measures and metrics for automobile green supply chain performance measurement. The study involved statistical tests using 16 measures and 72 corresponding metrics. These statistical tests include exploratory factor analysis to investigate the construct validity of the measures and their metrics, a confirmatory factor analysis to test the model fitness and a multiple regression analysis to test the criterion validity of the measures. From the results obtained, the validity of the measures and their corresponding metrics has been established. The paper culminated with recommendations for further studies