مقاله انگلیسی رایگان در مورد نوآوری محیط زیست برای بهبود ویژگی های کسب و کار – امرالد ۲۰۱۷
مشخصات مقاله | |
انتشار | مقاله سال ۲۰۱۷ |
تعداد صفحات مقاله انگلیسی | ۲۶ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
منتشر شده در | نشریه امرالد |
نوع مقاله | ISI |
عنوان انگلیسی مقاله | Fuzzy approach to Eco-innovation for Enhancing Business Functions: A Case Study in China |
ترجمه عنوان مقاله | رویکرد فازی در نوآوری محیط زیست برای بهبود ویژگی های کسب و کار: یک بررسی در چین |
فرمت مقاله انگلیسی | |
رشته های مرتبط | مدیریت |
گرایش های مرتبط | مدیریت کسب و کار |
مجله | مدیریت صنعتی و سیستم های داده – Industrial Management & Data Systems |
دانشگاه | School of Business – Dalian University of Technology – Panjin – China |
کلمات کلیدی | نوآوری محیط زیست ؛ توابع کسب و کار؛ آزمایشگاه تصمیم گیری فازی و ارزیابی؛ مدلسازی ساختاری تفسیری |
کلمات کلیدی انگلیسی | Eco-innovation; Business functions; Fuzzy decision making trial and evaluation laboratory; Interpretive structural modelling |
کد محصول | E7138 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
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۱٫ INTRODUCTION
Since the 1980s, an awareness of the Ecological Footprint, which is arguably mainly produced by human beings, has been receiving increased attention. This is because the issue has introduced a series of problems, including shortage of resources and ecological degradation that has stretched the health of the Earth to a worrying limit. The situation is complicated by the growing population. These evolutions force governments to explore policies and programs that support sustainable development. For example, the 2015 United Nations Climate Change Conference that was held in Paris led to the famous agreement to limit the effect of global warming by capping the increase in temperature by 2 degrees Celsius (°C). One approach or school-of-thought that may contribute to this is eco-innovation, which has gradually become a focus of attention for government, academic and business. According to Rennings (2000), eco-innovation is the act of “developing new ideas, behaviours, products and processes that contribute to a reduction in environmental burdens or to ecologically specified sustainability targets”. Developing the appropriate indicator is the key to the evaluation of the eco-innovation ability (or performance) of a company. Generally, we can define environmental performance from a micro or a macro perspective. Micro-level ecoinnovation performance can be used to evaluate and compare a firm’s operations to the others (Lazaro et al., 2008). Macro-level eco-innovation performance takes micro-level performance indicators into account and considers economic performance (Boons & Wagner, 2009). Nevertheless, micro-level performance indicators alone are not sufficient at the company level. There is a need to integrate multi-indicators to measure eco-innovation performance. Zoboli (2006) suggested that R&D expenses, expenses on pollution control, production efficiency of natural materials, pollution intensity and reduction of pollutant emissions should be considered when measuring eco-innovation performance of a firm. Many studies have attempted to develop a system of multiple performance indicators on eco-innovation measures of the business practices in developed countries. However, the research in the developing countries is limited (Dong & Shi, 2010). Along with the economic development of those countries in recent years, the awareness of eco-innovation has been soaring (Ockwell et al., 2010). In order to better understand the eco-innovation status of developing countries in this study, a Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) method is employed to extract causal indicators for evaluating the eco-innovation performance of a company. Specifically, the method incorporates a variety of business functions, namely, Production, Marketing, Research & Development (R&D), Human Resource Management (HRM), and Finance. Then, Interpretive Structural Modelling (ISM) technique is utilised to divide the identified factors into layers of index. To further contribute to the knowledge in this domain, the method is applied to a case company in a developing country. |