Eco-industrial parks promise to reduce environmental and social impacts and improve the economic performance of industrial parks. However, the transition from industrial parks to eco-industrial parks is still not well understood. This study contributes to developing valid hierarchical eco-industrial park transition attribute sets with qualitative information, as prior studies lack an exploration of the attributes in the transition of eco-industrial parks in Hungary. In nature, eco-industrial park transition attributes have causal and hierarchical interrelationships and are described with qualitative information. The assessment involves an analysis of the industrial symbiosis principles by using linguistic preferences. However, multiple attributes are involved in the assessment; therefore, this study proposes the Delphi method to develop a valid attribute set and applies fuzzy set theory to translate qualitative information into crisp values. The fuzzy decision-making trial evaluation laboratory method is used to visualize the attributes' causal interrelationships under uncertainties. The results indicate that the policy and regulatory framework leads to collaboration among firms in the eco-industrial park transition model. In practice, price reforms, management commitment, strategic planning, cognitive barriers and the integration of external information are the practical criteria for improvement. Theoretical and practical implications are also discussed.
This study contributes to develop a hierarchical framework for assessing the strategic effectiveness of waste management in the construction industry. This study identifies a valid set of strategic effectiveness attributes of sustainable waste management (SWM) in construction. Prior studies have neglected to develop a strategic effectiveness assessment framework for SWM to identify reduce, reuse, and recycle policy initiatives that ensure waste minimization and resource recovery programs. This study utilizes the fuzzy Delphi method to screen out nonessential attributes in qualitative information. This study initially proposes a set of 75 criteria; after two rounds of assessment, consensus regarding 28 criteria is achieved among experts, and the 28 criteria are validated. Fuzzy interpretive structural modeling divides the attributes into various elements. The modeling constructs a six-level model that depicts the interrelationships among the 28 validated criteria as a hierarchical framework, and it finds and ranks the optimal drivers for practical improvement. This study integrates the best-worst method to measure the weights of different criteria in the hierarchical strategic effectiveness framework. The findings reveal that waste management operational strategy, construction site waste management performance, and the mutual coordination level are the top aspects for assessing strategic effectiveness in the hierarchical framework. In practice, the waste reduction rate, the recycling rate, water and land usage, the reuse rate, and noise and air pollution levels are identified to assist policymakers in evaluation. The theoretical and managerial implications are discussed.
This study develops a set of measures to address the interrelationship among circular waste-based bioeconomy (CWBE) attributes, including those of government strategy, digital collaboration, supply chain integration, smart operations, and a green supply chain, to build a circular bioeconomy that feeds fish waste back into the economy. CWBE development is a potential solution to the problem of waste reuse in the fish supply chain; however, this potential remains untapped, and prior studies have failed to provide the criteria to guide its practices. Such an analytical framework requires qualitative assessment, which is subject to uncertainty due to the linguistic preferences of decision makers. Hence, this study adopts the fuzzy Delphi method to obtain a valid set of attributes. A fuzzy decision-making trial and evaluation was applied to address the attribute relationships and determine the driving criteria of CWBE development. The results showed that government strategies play a causal role in CWBE development and drive digital collaboration, smart operations, and supply chain integration. The findings also indicated that smart manufacturing technology, organizational policies, market enhancement, supply chain analytics, and operational innovation are drivers of waste integration from fisheries into the circular economy through waste-based bioeconomy processes.