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Rural areas in southern China receive ample rainfall annually as well as over 1600 h of annual sunshine. Despite a generally severe urban–rural development imbalance, these rural areas feature well-developed basic infrastructure and diverse economic activities. Rural revitalization policies in these areas have emphasized the development of cultural and ecological tourism, which has spurred economic development and given rise to a trend of villa construction. Residential buildings sit on large areas where natural resources are abundant. These advantages are conducive to the development and use of sustainable resources. This study proposes an incentive policy encouraging rural residents to renovate their buildings to include rainwater conservation and solar power generation. The Delphi method, an analytic hierarchy process, and fuzzy logic theory were combined to establish an AI-MCDM model, with applications of artificial intelligence and multiple-criteria decision making. Using Conghua District, Guangdong Province as an example, the study suggested that the model is beneficial to increasing the willingness of rural residents to reconstruct and renovate their residences, promoting the development of a low-carbon ecological region, Wenquan Township. We conducted the Delphi process twice to assess and validate incentives for installing natural resource conservation structures in agricultural areas. Nine criteria were identified, which can be divided into three main dimensions of participation situation, generating capacity, and storage facilities. The proposed AI-MCDM model developed using the Delphi–Fuzzy Analytic Hierarchy Process Model has high objectivity and can support rural areas in developing low-carbon, sustainable characteristics. The findings can serve as a reference for governments formulating incentives to encourage the installation of rainwater conservation and solar energy generation structures by rural households.

While corporate social responsibility (CSR) is prevailing, the concept of creating sharedvalue (CSV) by coordinating business activities and social concerns brings a great opportunity totransforming the business model for sustainable development. To better understand the systemscomprising corporate shared value chains would be beneficial to economics, society, andsustainability. This study refers to the ecosystem as the theoretical lens in the exploration of the CSVcomponents and contexts, and takes Macy&rsquo, s as a focal case. In terms of academic contributions, thisstudy generalizes the CSV components, including markets, social innovations, social performances,new business models, corporate entrepreneurship, and social network support. The researchfindings contribute to conceptualize and systemize the concept of CSV. In terms of practicalcontributions, the contexts for the operation of CSV, as summarized by this study, can serve as atemplate for corporate planning of CSV activities and sustainable development.

Amid increased emphasis on sustainable development, understanding the sustainability initiative and practice of companies has attracted the attention of both academia and industry. Corporate sustainability combines triple values including environmental protection, social wellbeing, and economic benefit for companies. Drawing on institutional theory and employing an inductive case research method, we examine companies developing their green innovation and sustainability projects in a challenging context of China. Four representative case studies and in-depth interviews were conducted to examine how these firms overcome barriers in the less developed institutional environment. To better explain corporate sustainability with green innovations, a conceptual framework has been proposed to illustrate how firms operate in a network of relationship and cooperate with their external stakeholders. Firms&rsquo, strategies to dynamically achieve the aim of corporate sustainability were identified based on a co-evolutional mechanism in the interface between institutions and organizations.

The present study explores the impacts of corporate strategic orientation on innovation ecosystems through the perspective of systems thinking. Multiple-cases method was adopted to analyze three representative companies of different industries. In terms of academic contribution, the results of this study verify an innovation ecosystem model in a generalized manner, and find that market orientation, interaction orientation, and entrepreneurial orientation generate a positively reinforcing effect on the paths of the innovation ecosystem model in all phases, thus, diversifying the available literature of innovative ecosystems. In terms of practical contribution, this study presents a dynamic context of the development of new business, and describes the links between innovative activities and the market. Enterprises can refer to the proposed framework as well as strategic architecture in this study to effectively transform innovative activities into market performance.

National policies for science parks and innovation have been identified as one of the major driving forces for the innovation-driven economy, especially for publicly funded science parks. To investigate this collaborative ecosystem (government-academia-industry) for growth and sustainable development, this paper proposes a nation-wide economic impact analysis of science parks and innovation policy based on historical data drawn from one of the globally recognized high-technology industrial clusters in Taiwan. Systems thinking with causal loop analysis are adopted to improve our understanding of the collaborative ecosystem with science park policies. First, from a holistic viewpoint, the role of government in a science parks and innovation ecosystem is reviewed. A systems analysis of an innovation-driven economy with a science park policy is presented as a strategy map for policy implementers. Second, the added economic value and employment of the benchmarked science parks is evaluated from a long range perspective. Third, the concepts of government-academia-industry collaboration and policies to innovation ecosystem are introduced while addressing the measures and performance of innovation and applied R&D in the science parks. We conclude with a discussion of lessons learned and the policy implications of science park development and an innovation ecosystem.

The impacts of high technology industries have been growing increasingly to technological innovations and global economic developments, while the concerns in sustainability are calling for facilitating green materials and cleaner production in the industrial value chains. Today’s manufacturing companies are not striving for individual capacities but for the effective working with green supply chains. However, in addition to environmental and social objectives, cost and economic feasibility has become one of the most critical success factors for improving supply chain management with green component procurement collaboration, especially for the electronics OEM (original equipment manufacturing) companies whose procurement costs often make up a very high proportion of final product prices. This paper presents a case study from the systems perspective by using System Dynamics simulation analysis and statistical validations with empirical data. Empirical data were collected from Taiwanese manufacturing chains—among the world’s largest manufacturing clusters of high technology components and products—and their global green suppliers to examine the benefits of green component procurement collaborations in terms of shared costs and improved shipping time performance. Two different supply chain collaboration models, from multi-layer ceramic capacitor (MLCC) and universal serial bus 3.0 (USB 3.0) cable procurements, were benchmarked and statistically validated. The results suggest that the practices of collaborative planning for procurement quantity and accurate fulfillment by suppliers are significantly related to cost effectiveness and shipping time efficiency. Although the price negotiation of upstream raw materials for the collaborative suppliers has no statistically significant benefit to the shipping time efficiency, the shared cost reduction of component procurement is significantly positive for supply chain collaboration among green manufacturers. Managerial implications toward sustainable supply chain management were also discussed.

Building and construction sectors are significant contributors to the global economy, but their energy consumption necessitates greater commitment to sustainable developments. There is therefore a growing demand for green innovation in the form of cleaner production and policies to meet the modern requirements of sustainability. However, the nature in which public work is undertaken is in an environment of project-based market competition, whereby contractors routinely bid for contracts under specific project awarding systems, and variations are accompanied with the unique scope of individual projects before the final goods or services are delivered. A comprehensive understanding of the characteristics and contractors’ behavior in systems could help to identify the leverage points of policies. This paper proposes a system dynamics model, with quantitative analysis and simulations, to demonstrate the problems of a system with different project awarding systems and ineffective market performance. The framework of market efficiency and performance measures has been proposed to evaluate the project-based competition mechanism. Managerial policy implications for market efficiency and sustainable developments can thus be systematically discussed and compared through iterative computer simulations and scenario analysis.

The importance of research and development (R&D) for business sustainability have gained increasing interests, especially in the high-tech sector. However, the efforts of R&D might cause complex and mixed impacts on the financial results considering the associated expenses. Thus, this study aims to examine how R&D efforts may influence business to improve its financial performance considering the dual objectives: the gross and the net profitability. This research integrates a rough-set-based soft computing technique and multiple criteria decision-making (MCDM) methods to explore this complex and yet valuable issue. A group of public listed companies from Taiwan, all in the semiconductor sector, is analyzed as a case study. More than 30 variables are considered, and the adopted soft computing technique retrieves 14 core attributes—for the dual profitability objectives—to form the evaluation model. The importance of R&D for pursuing superior financial prospects is confirmed, and the empirical case demonstrates how to guide an individual company to plan for improvements to achieve its long-term sustainability by this hybrid approach.