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The chemical industry has sustained the development of global economies by providing an astonishing variety of products and services, while also consuming massive amounts of raw materials and energy. Chemical firms are currently under tremendous pressure to become lean enterprises capable of executing not only traditional lean manufacturing practices but also emerging competing strategies of digitalization and sustainability. All of these are core competencies required for chemical firms to compete and thrive in future markets. Unfortunately, reports of successful transformation are so rare among chemical firms that acquiring the details of these cases would seem an almost impossible mission. The severe lack of knowledge about these business transformations thus provided a strong motivation for this research. Using The Open Group Architecture Framework, we performed an in-depth study on a real business transformation occurring at a major international chemical corporation, extracting the architecture framework possibly adopted by this firm to become a lean enterprise. This comprehensive case study resulted in two major contributions to the field of sustainable business transformation: (1) a custom lean enterprise architecture framework applicable to common chemical firms making a similar transformation, and (2) a lean enterprise model developed to assist chemical firms in comprehending the intricate and complicated dynamics between lean manufacturing, digitalization, and sustainability.

This study develops a framework for effectively implementing service Six Sigma projects. The framework is composed of four phases: (1) initial project identification, which deploys candidate projects in accordance with a firm's strategic goals, (2) project value assessment, which evaluates project's value based on the financial return, cost, and its impact on employee behavior, (3) project complexity assessment, which examines scope, data availability, and risk associated with the project, and (4) project prioritization, which identifies Six Sigma projects and categorizes them into black belt and green belt categories. Two cases in banking and health care services are discussed to demonstrate the proposed framework

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Global warming has triggered waves of public awareness to surface very strongly worldwide, urging to eliminate all greenhouse gas emissions in a timely fashion. Among all feasible approaches to achieving this goal, using renewables to replace fossil fuels and electric vehicles (EVs) to replace conventional internal combustion engine vehicles is arguably a top-priority task. However, there is a severe lack of practical approaches to measuring a proper renewable mix for powering EVs in a large highway network while also considering renewables’ seasonal availability and the possible need to regulate the production and consumption of renewable energy with grid-scale battery arrays installed at certain locations. This urgent need motivates developing the mixed-integer programming model as presented in this paper. Furthermore, a comprehensive case study on Taiwan’s national highways covers such useful knowledge as the process to prepare key numeric data, especially local solar and wind energy and highway traffic, in-depth analysis on model solutions to reveal the overall availability of renewable energy across the highway network, and close measurements on the required investments. These findings support using renewable energy to power EVs on a national highway and reveal the importance of local business involvements. However, a relatively small country, such as Taiwan, can still display significant variations in renewable power availability. In a stand-alone setting for power usage, these variations would result in massive volumes of renewable energy not used by highway travel in some seasons. These details demonstrate the applicability and values of the proposed model in a real situation.