Exploring the implementation of green supply chain with cluster and discriminant analysis: Case study: Furniture industry at Central Java Semarang

Abstract

This study has two objectives. First, this study aims to categorize the level of the implementation of Green Supply Chain Management (GSCM) practice among Small and Medium Enterprises (SMEs) of wooden furniture in several clusters. Second, this study aims to find the linear combination of five dimensions of GSCM practices that will discriminate best between prior defined clusters. The study used primary data through questionnaires enclosed with the Likert scale 1–5 at 162 SMEs of wooden furniture located in Surakarta, Jepara, Semarang, and Kudus. The raw data level of implementation of five dimensions of GSCM practice is analyzed using K-Means cluster and discriminant analysis with the aid of the Statistical Package for the Social Sciences (SPSS) software. The result of K-Means cluster analysis indicated that a two-cluster is the optimal number of a group for separating the data of the level of implementation of GSSM practice among SMEs of wooden furniture and the two clusters founded in this research are labeled as early adopter and laggards. Then, the result of the discriminant analysis indicated that as high as 98.77% of the SMEs of wooden furniture was classified correctly. The result of discriminant analysis also revealed the discriminant function as Z= (0.238∗IeM) + (0.602∗GPU) + (1.161∗CCO) + (1.128∗ECO) + (1.126∗IRE) − 13.124 and the threshold for evaluating a discriminant score of implementation of GSCM practice is −0.276. The implementation of GSCM practices by new SMEs of wooden furniture with discriminant scores above −0.276 would be assigned to the Early Adoption (cluster 1); otherwise, they would be classified as Laggards (cluster 2).