AI Article Synopsis
- The green supply chain trends are driven by environmental pressures and customer demands, requiring the construction industry to assess its competitive advantage through proper tools.
- The study introduces a comprehensive assessment model for contractors' green innovation, combining methodologies like system dynamics, AHP, utility theory, and fuzzy logic to evaluate intrinsic and extrinsic factors.
- This model aids government evaluations of green contractors in public projects and helps contractors gauge their competitiveness and foster further green innovations.
Article Abstract
The trends of the green supply chain are attributed to pressures from the environment and from customers. Green innovation is a practice for creating competitive advantage in sustainable development. To keep up with the changing business environment, the construction industry needs an appropriate assessment tool to examine the intrinsic and extrinsic effects regarding corporate competitive advantage. From the viewpoint of energy and environmental protection, this study combines four scientific methodologies to develop an assessment model for the green innovation of contractors. System dynamics can be used to estimate the future trends for the overall industrial structure and is useful in predicting competitive advantage in the industry. The analytic hierarchy process (AHP) and utility theory focus on the customer's attitude toward risk and are useful for comprehending changes in objective requirements in the environment. Fuzzy logic can simplify complicated intrinsic and extrinsic factors and express them with a number or ratio that is easy to understand. The proposed assessment model can be used as a reference to guide the government in examining the public constructions that qualified green contractors participate in. Additionally, the assessment model serves an indicator of relative competitiveness that can help the general contractor and subcontractor to evaluate themselves and further green innovations.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842057 | PMC |
| http://dx.doi.org/10.1155/2013/624340 | DOI Listing |
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