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This research uses social identity theory to propose that environmental social responsibility perceptions influence green commitment, and then influence pro-environmental behaviors, which are moderated by institutional pressure. Data were collected from 100 employees of technology firms in Taiwan, and the results support all hypotheses. This research chose technology firms as empirical data because Taiwan's technological level is known to the world, which can reduce sampling errors caused by the lack of environmental knowledge. Finally, this research not only advances the literature on sustainability issues in organizational management but also provides a paradigm to help firms implement pro-environmental behaviors to achieve competitive advantage and sustainable development goals. [ABSTRACT FROM AUTHOR]

Industry 4.0 has fostered innovation in industries around the world. Manufacturing industries in particular are advancing towards smart manufacturing by integrating and applying relevant technologies. The output value of machine tools in Taiwan is among the top of the world and the central region is a key area for this industry chain, which supplies manufacturers in Taiwan and their international downstream customers. To support innovation in this industry, the current study used the Six Sigma quality indices for smaller-the-better, larger-the-better, and nominal-the-best quality characteristics to construct a fuzzy decision-making model. Based on this model, we propose a process quality fuzzy analysis chart (PQFAC) for process quality improvement. Our use of fuzzy decision values to replace lower confidence limits decreases the probability of misjudgment made by sampling errors. The proposed fuzzy model also offers a more accurate assessment of process improvement requirements. We provide a real-world example to demonstrate the applicability of the proposed approach. Machine tool manufacturers can apply the platform and proposed model to evaluate their process capabilities for the vital parts suppliers and downstream customers, determine optimal machine parameter settings for processes with inadequate accuracy or precision, establish more suitable machine repair and maintenance systems, and combine the improvement experiences of customers to create an improvement knowledge base. This will enhance product value and industry competitiveness for the entire machine tool industry chain. [ABSTRACT FROM AUTHOR]

The annual output value of Taiwan’s wafer foundry and IC packaging test ranks first worldwide. The electronics industry has a complete industrial ecological chain in the supply chain system of global information and communication technology. In order to increase market competitiveness and increase the operational flexibility, manufacturing process outsourcing has become a trend in the business model of the electronics industry. The quality of the outsourcing affects the quality and function of the final product, the outsourcer selection is crucial to ensure the quality of the final product. This article takes the wire bonding process as an example, and proposes a fuzzy selection model of quality-based IC packaging process outsourcers. Then, this article selects the six standard deviation indicator that can fully reflect the process yield and quality level as the evaluation tool. Since the indicator contains unknown parameter, in order to improve the accuracy of estimation and overcome the uncertainty of measurement data, this paper applies mathematical programming to derive the confidence interval of six sigma quality index, and proposes a confidence-interval-based fuzzy testing meth as a green outsourcer selection tool to reduce the risk of misjudgment due to sampling errors and improve the accuracy of the selection. [ABSTRACT FROM AUTHOR]