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In recent years, the pulp and paper industry has changed a lot and products have been constructed in quite different methods using new technologies. It can be due to the emergence of challenges and constraints such as shortage of raw materials, energy consumption (fossil fuels, electric, etc.), management of the resulting pollutants, environmental issues, ongoing legal requirements and cleaner production strategies. In Iran, the pulp and paper industry's technological development is not keeping pace with global growth. Iran's pulp and paper mills supply a small fraction of domestic market. The reasons can be due to old technologies being used in factories, aging machinery, low productivity of production systems and lack of coordination with modern technologies. It leads to low-quality of paper products and willingness to buy local products. The aim of this study is to select the most appropriate technologies in the pulp section, due to high impact of pulp quality on the quality of final paper. Using a 2-filterd fuzzy decision-making, hierarchical structure of research is designed to assess technological alternatives according to the selected criteria. Findings show that after passing through two filters, Kraft method was chosen as the most appropriate method. The Kraft process has still many advantages like the high quality of the produced pulp and self-sufficiency in energy supply. This framework offers an appropriate procedure for identifying and selecting technologies that has not been used in past researches. Using this framework facilitates using a clear procedure for evaluating and selecting technology and prevents future losses for organizations. [ABSTRACT FROM AUTHOR]

LCA studies on waste management have been promoted as they can help policy makers choose the best environmental options. However, the increasing globalization of raw materials and waste makes the optimization of waste management strategies and policies quite challenging. Therefore, new approaches are needed in order to identify the consequences of markets on the waste management systems. This paper concentrates on the quantification of greenhouse gas (GHG) emissions of recycling processes. The aim is to generate a comprehensive assessment of GHG emissions as a consequence of increasing the amount of material collected for recycling. Consequential life cycle assessment (CLCA) is an effective methodological framework for addressing GHG quantifications within market, but to properly perform and assess all of the market links between raw materials and waste, it is necessary to determine the cause-effect chains made up of physical flows. Thus, we propose integrating the methodologies of material flow analysis (MFA) and CLCA. We applied these methodologies to the paper and cardboard recycling system in Spain. The GHG results varied between −36 kg CO 2 eq. and −317 kg CO 2 eq. per ton of waste paper collected, depending on the quantity of waste paper exported and the source of marginal pulp considered. The cumulative energy demand (CED) was also calculated as complementary indicator. Similar trends as for GHG emissions were obtained. The future GHG quantifications should be based on the flows described by MFA analysis and should be quantified using CLCA because methodologies that accurately account for GHG are necessary for decision-making. [ABSTRACT FROM AUTHOR]

Pumped storage technology plays a crucial role in achieving balance in power systems and enhancing the stability of energy systems. Scientific planning can help optimize the operation of power systems, promote the development of renewable energy, and conserve energy. This paper addresses the capacity planning problem of pumped storage stations in hybrid operation systems considering wind power uncertainty. A comprehensive decision-making method is proposed, based on the Delphi method, interval intuitionistic fuzzy theory, grey relational theory, entropy weight method, and prospect theory. This method comprehensively evaluates decision alternatives by considering various factors such as the uncertainty of qualitative indicators, the interrelationships between indicators, and the impacts of different risk environments. The test system in this paper is conducted on a hybrid wind-thermal-pump storage output model based on the IEEE 30-bus system. The optimal capacity planning scheme determined by the proposed method is 190 MW when decision-makers are risk-neutral or risk-averse, and 200 MW when they are risk-appetite. Subsequently, the case study verifies the impact of different load levels and proportions of wind power access on the optimal decision-making scheme, and compares it with decision-making method such as principal component analysis, technique for order preference by similarity to an ideal solution, and a combined method of Pythagorean fuzzy theory and cumulative prospect theory, validating feasibility and effectiveness. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

Environmental issues drive the manufacturer to strive for green technology innovation. The manufacturer cannot strictly control all the activities in the production process, which may cause yield uncertainty. However, the existing studies that consider uncertainty factors usually assume that yield is deterministic. This paper constructs a green supply chain considering yield uncertainty and corporate social responsibility by a manufacturer and a retailer under different market power structures. We examine that yield uncertainty negatively affects the optimal decision-making strategies under four different power structures, especially in the centralized model. The retailer who adopts corporate social responsibility can alleviate the negative effects of yield uncertainty to a certain extent. Meanwhile, it is interesting that the manufacturer is not maximizing profits in the market dominated by himself and is subject to interference from yield uncertainty and corporate social responsibility. When the yield uncertainty is relatively small, the manufacturer's profit is the largest in the retailer-dominated market structure. However, when the yield uncertainty is significant, the revenue for the manufacturer is the largest in the manufacturer-dominated market. Regardless of how the yield uncertainty changes, the retailer's profit is always the largest in the retailer-led model. To alleviate the manufacturer's green costs, the retailer will share part of their revenue with the manufacturer under the Nash model. The Nash-revenue-sharing contract always benefits the manufacturer but hurts the profits of the retailer with a higher sharing coefficient. Finally, this paper provides prominent implications for managers and governments. [ABSTRACT FROM AUTHOR]

Recently, Indian manufacturing industries have undergone a significant transformation emphasising customer-centric objectives to meet the dynamic market's demands. To achieve this, existing industries must upgrade their existing infrastructure to a smart environment driven by automatic data exchange, transparency, and interconnected digital systems. These are the key enabling elements of Industry 4.0. As a result, many Indian industries are developing various sophisticated implementation strategies for adopting it. However, few research works and strategies contribute to its effective and successful implementation. This paper proposes two types of implementation strategies for implementing Industry 4.0 enabling technologies based on the requirements and adaptability of India's commercial vehicle manufacturing industry. The first strategy identifies various aspects of implementing Industry 4.0 enabling framework elements and categorizes it for developing implementation strategies based on India's commercial vehicle manufacturing industry. The significance of each was determined using fuzzy-AHP analysis and ranked accordingly based on the linguistic responses of the industry experts. The most significant framework element is found to be 'Decision Making and Management Skills'. The second strategy emphasizes long-term sustainable implementation objectives. The framework elements are reconstructed and developed into a novel, customized sustainable framework based on six dimensions of sustainability. Using the Fuzzy-DEMATEL method, the causal relationships among these elements are investigated to determine a sustainable implementation strategy. 'Central Database Server' is determined to be the most significant sustainable framework element, while the maximum number of casual relationships is obtained from the group, 'Skill upgradation of the workforce'. This paper proposes a novel research direction for implementing Industry 4.0 technologies into the existing industry. The findings provide several insights and strategies for technological upgradation in other industries in this geographical region. The findings of the work enhance the implementation process of I4.0 technologies, transitioning it from a conventional approach to a futuristic sustainable implementation that is economical and effective. • Industry 4.0 enabling framework elements for Indian manufacturing industry were identified and categorised. • Significance of each framework element are determined using Fuzzy AHP. • A customised sustainable framework of I4.0 enabling elements is presented. • Fuzzy DEMATEL approach used to examine their causal relationships and significance based on long-term sustainability. • Sustainable implementation strategies and implications are discussed. [ABSTRACT FROM AUTHOR]

Since the use of LNG as an alternative fuel has drawn increasing attention from the marine industry, this paper aimed to evaluate three competitive LNG fuelled engine systems: ultra-steam turbine, four-stroke medium speed engine, and two-stroke low-speed engine systems. To achieve this goal, the paper developed an enhanced hybrid decision-making model which was applied to integrate the economic, environmental and technical performance of these systems. This model can be represented as a semi-quantitative multi-criteria decision making process in combination of several novel techniques, particularly 'life cycle cost assessment' for economic analysis, 'life cycle assessments' for environmental analysis, 'fuzzy order preference by similarity to ideal solution' for technical analysis and 'fuzzy analytic hierarchy process' for multi-criteria decision making. A case study with a 174 K LNG carrier has revealed that the two-stroke low-speed engine system is the most effective overall and suggested that this type of engine system will hold the lead over the other candidates in the large LNG carrier market. It has also demonstrated the effectiveness of the proposed model to improve the inherent subjectivity in existing qualitative multi-criteria decision-making processes by guiding the overall process in a more objective direction. Finally, this paper has revealed an underlying novelty of the proposed model to enhance the level of confidence level in the decision by expanding our short-term perspective to the holistic one. • The strengths and limits of three different marine LNG engine systems were investigated in various aspects. • The effectiveness of an enhanced hybrid MCDA model was demonstrated by evaluating an optimal marine LNG engine system. • It was ultimately suggested that the two-stroke engine systems would be the best option. • The impact of the proposed model is expected to extend to various studies related to proper decision-making. [ABSTRACT FROM AUTHOR]

Information has become an extremely important commodity nowadays. The privatization of corporate social responsibility cost information has a negative impact on the sustainable development of supply chain. Hence, it is important to set up a reasonable coordination mechanism to encourage the supply chain members to reveal the true corporate social responsibility cost information. This paper investigates corporate social responsibility-sensitive supply chain, where a contract supplier sells products through a brand retailer. The contract supplier can invest in corporate social responsibility activities, but its corporate social responsibility cost information is only privately known to him. According the corporate social responsibility cost information revealed by the supplier, the retailer will decide whether to cooperate with him for a long time. Stackelberg game is used to explore the impact of the cost information asymmetry on the decision of supply chain members. The paper compares the decision effects under information asymmetry and symmetry decision, and designs a coordination mechanism for promoting the supplier to reveal the true corporate social responsibility cost information and achieving the supply chain coordination. The results show that the decision-making effect under symmetric information is better than asymmetric information, and the supplier's profit under the designed mechanism is not lower than that under asymmetric information. Moreover, the designed mechanism can improve the supplier's commitment to corporate social responsibility and eliminate double marginal effect to a certain extend. This paper provides managerial and practical insights for the enterprise adopting sustainable business models. [ABSTRACT FROM AUTHOR]

Abstract This study analyzes the effect of multi-attribute decision making (MADM) on the efficiency of the end-of-life vehicle (ELV) reverse logistics industry in the context of the circular economy to improve resource utilization efficiency. In this paper, the DEA-TOPSIS method, based on a prediction model of Triple Exponential Smoothing (TES), is adopted for multi-attribute decision making with a view to improving industry efficiency, Data Envelopment Analysis (DEA) is used to calculate the input and output indicators' efficiency values and the slack movements of the indicators of input and output decision-making unit's (DMU's) base with TES as the decision-making basis. Meanwhile, the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is used to rank alternative decision-making schemes. Moreover, the ordering is also carried out using the Additive Weighting, Weighted Product and Elimination et Choice Translating Reality (ELECTRE) method. In this study, the DEA-TOPSIS method is used to make multi-attribute decisions about industry efficiency. Taking Shanghai's ELV industry as an example, this study utilizes 2017 data from seven member-enterprises of the Shanghai End-of-life Vehicle Professional Committee; it uses the DEA-TOPSIS method based on TES to conduct an empirical study on multi-attribute decision making to improve efficiency and analyze efficiency improvement through alternative decision-making schemes. The findings show that the DEA-TOPSIS method based on TES is effective for multi-attribute decision-making to improve the ELV reverse logistics industry's efficiency. The multi-attribute decision-making in this paper facilitates the management and investment decision making of the ELV recycling industry. It also provides an effective solution for managers and researchers in the ELV industry to improve its efficiency. Highlights • Researched MADM to improve the efficiency of the end-of-life vehicles reverse logistics industry. • Used DEA to measure technical efficiency and pure technical efficiency. • Developed a TOPSIS decision-making matrix with each indicator's slack movement as the attribute indicator. • The slack movements evaluated based on a prediction model of TES is proposed as the decision-making matrix. • The AW, WP and ELECTRE method are compared with the TOPSIS in terms of the ranking of decision-making alternatives. [ABSTRACT FROM AUTHOR]

Abstract During modern times of economic and political turmoil, we ask how we should be educating current and future business leaders to navigate periods of global turbulence. The paper suggests that firstly, undergraduates (future managers) and executive MBA students (current managers) need sustainability embedded in their management education because both groups believe that the global supply chain practices have contributed to global turbulence and that sustainable supply chain actions could help to reduce that turbulence. Secondly, that exposure to supply chain sustainability examples in management education increases global awareness and empathy in current and future managers. Thirdly, it is suggested that a gender balance is required for improved sustainability decision making. Lastly, it is found that direct facilitation by an instructor is not required for threshold learning and that it can occur exclusively through self-reflection. The overarching contribution of the paper is that rather than viewing economic, environmental, social and political turbulence as external factors that managers must simply navigate, supply chain sustainability education enables managers to connect how their global supply chain decisions can either intensify or reduce the turbulence. Highlights • Exposure to sustainability examples in management education increases global awareness. • Sustainable supply chain approaches can help to mitigate concerns of turbulence. • Globally aware managers act as agents of positive social change. • Undergraduates and Executive MBAs have a similar threshold knowledge of sustainability. • Sustainability in management education advances alternate approaches to managing turbulence. [ABSTRACT FROM AUTHOR]

Abstract Optimization allocation of agricultural water and land is a very complex system involves multiple objectives. Moreover, weights of each objective were signed by subjective judgement of decision makers is unreasonable. Furthermore, uncertainties are inevitable in the optimization allocation of irrigation water and land. In order to solve the above problems, this paper developed an improved multi-objective stochastic fuzzy programming method. The developed model was then applied to a case study in Wuwei City, Gansu Province, China. Maximum net benefit, maximum agricultural water productivity, and minimum irrigation area were regarded as planning objectives. A series of optimal irrigation and planting structure schemes were obtained under multiple uncertainties. From the results, water resources shortage in Wuwei city is very severely and it could not satisfy Wuwei's water demand even if the risk probability P i reaches 0.25. Moreover, water and irrigation area would vary in different crops. Such changes would mainly take place in potato, vegetable and cucurbit, which have the same characteristics with higher yield, lower cost or lower irrigation quota than other crops. Furthermore, the decision makers could make reasonable decisions on the optimal use of irrigation water and land resources under multiple objective and uncertainties based on the obtained results. Highlights • This paper developed an improved multi-objective stochastic fuzzy programming method. • It simultaneously optimizes irrigation water amount and irrigation areas. • AHP method was introduced to assign weight of each objective. • Optimal irrigation schemes were obtained under multiple uncertainties. • It could be helpful to make decision under multiple uncertainty and multiple objectives. [ABSTRACT FROM AUTHOR]

Abstract: In practice, carbon tax is an effective supplement to emissions trading system, and is also a key to achieving China's emission reduction targets. Although much research has been done to study the internal mechanism and macro impact of carbon tax, prior literature paid little attention on whether carbon tax affect the strategy and performance of low-carbon technology sharing among enterprise. A differential game model is developed in this paper, which assumed that enterprise low-carbon technology stock is jointly determined by both the efforts of the enterprise low-carbon technology innovation and the external enterprise low-carbon technology sharing. This paper constructs dynamic models under decentralized decision-making with cost-sharing, without cost-sharing, and centralized decision-making respectively, obtain enterprise optimal feedback equilibrium strategies, low-carbon technology stocks and the trajectory of optimal value function of benefits. The results demonstrate that carbon tax can promote enterprise low-carbon technology innovation and sharing to some extent. Meanwhile, this paper found that under the scenario of centralized decision-making, the more the efforts of enterprise low-carbon technology innovation or sharing, the higher the system emission reduction benefits than non-cooperation scenarios. Some factors, such as cost coefficient, cost sharing ratio, etc., will affect the enterprise's decision-making and emission reduction benefits. Finally, the validity of the model is verified through numerical simulation and the sensitivity of the relevant parameters in the scenario of cooperative innovation are analyzed. The results may provide important policy implications for promoting low-carbon technology sharing among enterprises, so as to faciliate the achievement of China's emission reduction targets. Highlights • We explore the effects of carbon tax on effort level on LCT innovation and sharing of enterprise. • We analysis the enterprise LCT stocks and the trajectory of optimal value function of benefits, under different scenarios. • Some relevant parameters of enterprise LCT stocks and reduction benefits under the centralized decision-making are discussed. [ABSTRACT FROM AUTHOR]

Abstract Material efficiency in lifecycles is a challenge that affects product innovators, producers and political stakeholders. The recycling and waste management is a direct consequence of this challenge, heavily compounded by data requirements. Especially third parties such as recyclers, remanufacturers or waste treatment sites face limited documentation and data on products. In addition, those actors face additional data management challenges due to their distinct upstream supply chains of dispersed suppliers and hence due to interrupted information flows. This study investigated various software tools to critically compare the tool's potential to improve data availability and data completeness, as well as the management of the reuse or recycling business processes using Enterprise Resource Planning software evaluation metrics for each waste-related sub-domain. The main objective of this paper is thus to provide a framework for comparison through key features, measured adherence to these features and to infer how this affects the software landscape. Software packages were sampled using public software listings and keyword filters to arrive at a final subset of publically accessible software packages, which were then critically analysed and compared by feature support. The main results of the comparison of these software packages in the discussed waste-related sub-domains revealed that data compatibility between packages and reporting requirements is the largest issue on a general level. On the level of sub-domains, the results showed that software offerings lack essential domain-specific features in order to support circular lifecycles of products and materials. Secondary results revealed a lack of database interoperability and various lesser concerns, such as incorrectly reported pricing or obsolescence information. The impact of these missing features reinforces the "silo" effect of packages, reduces the adoption rate in larger companies, and compounds the problem of smaller start-ups and companies using manual paper-based solutions and lacking reporting capabilities. Publically available databases and an increased rate of sharing of information between Original Equipment Manufacturers and recyclers would improve the decision-making through software solutions in waste-related processing. [ABSTRACT FROM AUTHOR]

Cyanobacterial bloom has posed a serious threat to the sustainable development of Taihu Basin. All basin stakeholders could not make an agreement on pollution solution. During decision-making, they insist on “gross domestic product (GDP) only” rather than a sustainable development preference. This paper establishes a new cost-risk decision-making system from the sustainable perspective. Contrary to the work carried out by others, water rather than money is taken as management cost here. With grey water footprint concept, pollution in water can be measured by converting into water. Due to emission reduction space limitation, some basin areas suffer the vicious circle of “management after pollution”. Management responsibility allocation alone cannot combat the pollution management due to the mismatch between responsibilities and reduction space, which should be optimized. Therefore, it is suggested that each agent, with the purpose of cost (water) saving, selects responsibility allocation schemes and cost allocation institutions through mutual negotiation. It is found that a grand coalition in any scheme or institution can achieve the minimum management cost, with approximately 24.05 billion m 3 water being saved. In the grand coalition, Changzhou has the largest discharge reduction space with small management responsibility, so the other five cities may transfer their responsibilities to it by inside compensation. However, to achieve fairness and stability inside the grand coalition, Nash-Harsanyi institution in the Emission Sharing is the most optimized scheme, which can ensure a sustainable full-cooperative pollution management in Taihu Basin. In short, this paper provides a new decision-making plan to pollution management in Taihu Basin. [ABSTRACT FROM AUTHOR]

Eco-efficiency is an important index to measure the degree of sustainable development, and is now attracting emerging attentions from both academia and industry. Based on previous data envelopment analysis (DEA) studies on environmental performance, this paper combines the big data environment, specific environmental issues in recent years, and related environmental policies. This study illustrates a more specific production process for pursuing higher environmental performance (it is not possible to further reduce undesired outputs by remodelling the process) and proposes a dynamic environmental performance evaluation model that considers the use of environmental inputs multiple times based on DEA. Our model can achieve dynamic and forward-looking evaluations of environmental performance in all stages based on real-time data that contains environmental protection inputs in sustainable cycles. Due to the dynamic and forward-looking results of the model evaluation, our model can also assist DMUs (decision-making units) in selecting schemes to enable them to have higher eco-efficiency from numerous schemes of environmental protection and achieve scientific decisions in the era of big data. This paper also demonstrates an illustration of real-world data of China's major coal-fired power plants. Besides quantitatively showing how the power plants to adjust their production plans and environment protection plans, the results imply that there exists a positive correlation between the redundant inputs and the scales as well. [ABSTRACT FROM AUTHOR]

By adopting the concept of modularity, this paper introduced an optimal framework which facilitates life cycle assessment and life cycle cost assessment, thereby supporting rapid and reliable decision-making in the marine industry. The benefits of the proposed framework were discussed through two case studies where the optimal configurations of marine propulsion systems were determined from the economic and environmental perspectives. First, the performance of a short-route ferry using the hybrid system was compared with those of equivalent ships using diesel-electric and diesel-mechanical propulsion systems respectively. Research findings revealed the excellence of the hybrid system in both economic and environmental aspects. Second, the same method was applied to an offshore tug vessel to determine an optimal engine configuration. Results of analysis emphasised that the selection of multiple small-sized engines is more effective than two medium-sized engines. Both studies have proven that the proposed framework would be useful and practical for accelerating the life cycle analysis which allows ship designers and owners to obtain the long-term view of economic and environmental impacts for particular products or systems without demanding process. The paper also opened up the possibility of extending the application of the proposed framework to the areas where proper decision-making is essential but under-used. [ABSTRACT FROM AUTHOR]

Industry 4.0 arrives with a multitude of technological advances which impact the different components of a product's value chain. Most existing research investigate the application of Industry 4.0 technologies in various parts of the manufacturing process. However, there is still a lack of comprehensive research on the impact of Industry 4.0 technologies on decision-making and how it must be adapted in order to truly benefit from the advantages brought by these technologies. This paper is thus intended to give more enlightenment on the subject, with evidence brought from the textile and clothing industry. Following this objective, a systematic literature review of research articles associated with decision-making in the Industry 4.0 era is performed with a focus on the textile and clothing industry. Articles were retrieved from the Scopus database, and the selection procedure resulted in 61 research papers. Moreover, a content analysis was performed using tables and graphs featuring quantitative results which are grounded on the proposed taxonomy. This study permits to identify some decision-making trends such as data-driven, real-time, decentralized, integrated, and sustainable decision-making. Following these decision-making trends and technologies brought by Industry 4.0, we discuss the keys for a competitive textile and clothing industry of the future. Finally, challenges facing the industry are presented following two aspects including digitalization and Industry 4.0 technologies implementation as well as environmental and social responsibility. [ABSTRACT FROM AUTHOR]

Modern agriculture involves the cooperation of stakeholders in multi-fields where their interaction significantly impacts the planning and operation of rural power systems. However, the traditional planning and operation for rural power systems assumes the power consumption as a given input without considering its unique feature caused by human factors. Particularly in China's rural areas, power consumption will rapidly increase and decrease due to the human-factor-based activity of farmer households' off-farm employment in urban and their home-returning during some important festivals. Therefore, this work proposes a multi-agent decision-making framework to realize the planning and operational optimization of power systems in a human-factor-based rural community. The framework integrates multiple agents' decision-making models including various stakeholders in modern agricultural systems and analyses their interaction. The meteorology-load and meteorology-generation models of power are materialized and embedded in the intensive agriculture and power system agent's decision-making models, which are used by the two agents to estimate the power consumption and photovoltaic (PV) generation, respectively. This work first quantizes the macro choice process of human-factor-based farm and off-farm employment and the numbers innovatively. Further, the farmer behavior for farm employment is simulated by the agent-based modeling system, and the power consumption of the farmer household group is estimated. Based on the overall agents' power consumption in the community, the planning and operation model of the power system is proposed to decide the optimal size and dispatch of the electrical devices. A multi-agent rural community is conducted for the case study to verify the effectiveness of the proposed decision-making framework. The results show that the farmer households who choose off-farm employment account for 66 % of the total households and their power consumption in most of the daytime on weekends is higher than on weekdays. The transportation system agent decides to purchase the electric truck with 5 tons of struck capacity for crop transportation. The power system agent decides to construct a hybrid system of PV, battery energy storage, and a transmission line of less transmission capacity, which can reduce its total system cost. Additionally, this paper finds that the solar radiation obtained by the greenhouse, which is considered the intensive agriculture agent, and its power consumption show opposite variation tendency, and the power consumption of the farmer household group in the Spring Festival is the largest. • A multi-agent decision-making framework of a rural community is proposed. • A meteorology-load and meteorology-generation models are materialized. • A macro choice process of human-factor-based farm/off-farm employment is quantized. • A bottom-up estimation method of power consumption is established by farmer behavior. [ABSTRACT FROM AUTHOR]

Global warming, as many other threats, requires more activity from the government, and people inquire about this, rightfully so. However, the public and private sectors nowadays have a joint responsibility with society. Global warming has come out of the scientific community and shows that climate change is an important social, economic, and political issue. Currently the carbon dioxide (CO 2 ) emissions by transportation sector are the main polluter of the planet. For this reason, in this paper we propose a reflection on transport, which is an important sector of the economy, responsible for the generation of many jobs and wealth but, at the same time, it has negative impacts on people, companies, and the environment. Recent investigations demonstrate that mobility problems affects the life quality of the people, business productivity and gross domestic product (GDP) performance. In the face of the changes that we are experiencing, it is important to find alternatives that assistance governments in the decision-making to solve the problem of traffic in large and medium-size cities and bring well-being to the population. The goal is to provide accurate tool to help take the best decisions in situations that most of the time has a lack of economic resources and transparency. Another motivation is to increase the productivity of companies and achieve sustainable development by reducing mobility problems and CO 2 emissions. As outcomes of the paper, an in-depth study is presented on the subject that indicates a gap in the literature with fuzzy logic applied to sustainability. We indicate a sustainable option for the transport sector using algorithms for decision-making, and broaden the discussion on climate change and solutions to reduce the impacts caused by humanity. When the models were applied through a conceptual study, it was possible to provide an instrument generated on the use of algorithms that can aid decision-making by getting qualitative data from a discussion with stakeholders on a topic. Finally, the document identifies the importance of the participation of stakeholder, reinforces legitimacy and transparency in decision-making processes and above all present a tool that can help governments to solve this problem. In short, this work proposes an original and valuable tool to be applied in the decision-making process for the sustainable transport sector based on the stakeholder engagement. [ABSTRACT FROM AUTHOR]

This paper explores the existing social life cycle assessment (SLCA) literature (theoretical and case studies) from decision making perspective. In order to tackle this, a critical review of 90 published work, including journal papers, conference proceedings and book chapters was undertaken. The selected articles were analyzed with a focus on methodological framework, boundary scoping, data inventories and practices. The analysis highlighted the inadequacies in the existing frameworks in terms of flexibility, conflicts in choosing and defining Area of Protection (AoP). Lack of consideration of social conditions of stakeholders in no-work and no-use phase, lack of inclusion of positive impacts, less attention to suppliers and consumers and choice of subjective indicators are highlighted as some weak portions within the boundary scoping. Less coverage of contextual and indirect indicators, and absence of documentation of a link between data collected (subjective indicators) and product activities are highlighted as a limitation within inventories, and finally within practices, lack of benchmarks is highlighted. This analysis highlighted an important differentiating factor between the actual definition of sustainability (maintenance of stocks for future generation) and the most common interpretation in literature as a summation of the three (social, environmental and economic) indices. [ABSTRACT FROM AUTHOR]

The procurement of high-quality aggregates is a global problem. In Chile, mining companies are in the process of developing massive underground projects that require the extensive use of Portland cement concrete (PCC), approximately 60%–75% of which is aggregate. Currently, mining projects transport all the required aggregate to the site from stockpiles that can be more than 100 km away, while mining excavations produce millions of cubic meters of waste rock (WR) that are disposed of in landfills. The use of WR in PCC seems to be a sustainable solution for the production of PCC, but decision-makers lack the tools to support a sustainable decision based on CO 2 emissions and operation costs. This paper proposes a methodology that uses stochastic simulation tools to evaluate CO 2 emissions and operation costs to decide when it is sustainable to use WR in PCC for underground mining projects. The main objective of this paper is to provide a methodology to quantify CO 2 emissions and the cost of transporting natural aggregate versus recycling WR for PCC production in tunneling operations. A sensitivity analysis is also presented, which considers scenarios that include natural aggregate transportation distances of 50, 60, 70, 80, 90, and 100 km, and 0%, 25%, 50%, 75%, and 100% replacement of natural aggregate with recycled WR in PCC. The results indicate that the use of WR leads to reductions in CO 2 emissions only for natural aggregate transportation distances of greater than 70 km owing to the emissions produced when recycling WR. In addition, 100% replacement of natural aggregate with recycled WR leads to a greater reduction in CO 2 emissions than that obtained in scenarios in which a percentage of the required natural aggregate is obtained from WR. In terms of costs, 100% replacement of natural aggregate with recycled WR is the most economical alternative for most scenarios; however, the cost reduction varies with the required transportation distance of natural aggregate. It is concluded that using 100% recycled WR in PCC leads to lower CO 2 emissions and costs as compared to the traditional approach in which the natural aggregate is procured from a site located at a distance of 70 km or more from the construction site, under model assumptions. [ABSTRACT FROM AUTHOR]

Water initiatives for business and in business have ballooned in the 2010's because of concerns over increased uncertainty surrounding water supplies as well as competing demands. The challenge is how to improve accounting given the lack of available granular data on which companies can base their business decisions about water scarcity, water surpluses and water management opportunities. Corporate Water Management Accounting is a recently proposed extension to Environmental Management Accounting designed to support corporate management decisions and improve both economic and environmental water-related business outcomes. The paper identifies relevant water accounting information for decision making is lacking in current literature and water initiatives, which focus on external water reporting. In the light of the finding strengths and weaknesses of water initiatives are assessed and a new framework developed for Water Management Accounting. Based on both the literature and gaps in current water initiatives, the paper concludes with a set of specific research issues in corporate water accounting settings along with ways in which water accounting researchers can contribute to the future management of water by businesses. [ABSTRACT FROM AUTHOR]

Given that a fixed national emission reduction target could be achieved by imposing emission quotas among multiple decision-making units under administration, a novel nonlinear programming approach is proposed in this paper to obtain an optimal emission quota allocation in a least-cost way. Marginal emission abatement cost curves are simulated based on the environmental performance and marginal emission abatement costs measured in a set of parametric directional output distance functions with multi-inputs and multi-outputs. Further, the proposed model is applied to empirically investigate the optimal carbon emission quota allocation for China’s building construction industry among thirty-three provinces in three different regions. The results indicate that the relatively developed eastern region in China has higher marginal emission abatement cost and can be imposed with more emission quotas, while the central and western regions can undertake more emission reduction. Approximately 74 million RMB can be saved by implementing the optimal emission allocation (proposed in this paper) as compared to a uniform emission quota allocation. The findings are of great theoretical, methodological, and practical significance for policymakers and social science researchers in terms of climate change mitigation. [ABSTRACT FROM AUTHOR]

Risk ranking is a widely used technique for selecting and prioritizing multiple risks facing an organization or decision maker. In industrial practice and in academic work, risk ranking methods are commonly based an implicit risk conceptualization, adopting a particular foundational perspective and accounting for selected factors. Nevertheless, different stakeholders may adhere to various risk conceptualizations, applying different foundational perspectives and accounting for different factors in the ranking process. Identifying a gap in the literature to coherently consider these different foundations, this paper presents an approach for reconciling different foundational perspectives and stakeholder views, accounting for uncertainties about these. The approach is presented based on three foundational perspectives (the expected value, uncertainty and moral perspective), and developed as a Bayesian Network – Influence Diagram. The main use of the model is to make possible controversies in risk prioritization explicit, facilitating stakeholder deliberation. The model can easily be extended with new perspectives on risk ranking, or adapted based on additional knowledge about other aspects, e.g. relating to risk perception. The graphical representation allows insights into the contribution of various aspects, facilitating the selection of appropriate risk management actions. The developed model is applied to an example, suggesting that the envisaged benefits of the proposed approach are plausible. It is concluded that the novel approach has a clear potential for reconciling different foundational perspectives and stakeholder views on risk ranking. Nevertheless, it is stressed that the conceptual contribution made in this paper should be more elaborately tested in practical settings, substantiating the findings further. [ABSTRACT FROM AUTHOR]

With the increasing conflicts among economic growth, environmental deterioration, and resource shortage, as an effective way to achieve the sustainable development and circular economy, the eco-industrial park gradually becomes a critical research issue in the field of recycling economy. In this paper, a hybrid framework for evaluating the comprehensive benefit of eco-industrial parks from the perspective of circular economy was proposed. Firstly, the evaluation index system for eco-industrial parks was constructed by employing the grey-Delphi method according to the opinions provided by experts from relevant fields, which includes economic benefit criteria, social benefit criteria, environmental benefit criteria, ecology industry construction criteria, and management level criteria, consisting of seventeen quantitative sub-criteria and nine qualitative sub-criteria. Secondly, in order to solve complicated, uncertain and ambiguous problems under the fuzzy background, a hybrid multi-criteria decision making (MCDM) approach was put forward on the basis of superiority linguistic ratings and entropy weight method for weight determination as well as fuzzy-VIKOR for ranking alternatives. Finally, the effectiveness and practicality of the proposed hybrid MCDM approach was demonstrated through a case analysis of six representative eco-industrial parks in China, and the comprehensive benefits of six eco-industrial parks were prioritized effectively. The hybrid MCDM approach in this paper presents a great potential in evaluating and ranking the comprehensive benefits of eco-industrial parks through solving complex and ambiguous problems in a fuzzy environment and varying MCDM tools. The evaluation findings by employing the proposed MCDM approach can provide references for the construction and management of eco-industrial parks and relevant policy formulation. [ABSTRACT FROM AUTHOR]

Low-carbon development patterns have gradually attracted more attention because of strong shocks to society and the economy from environmental problems. Developing a low-carbon economy is essential for every country to improve sustainable economic development, and doing so is at the forefront of low-carbon research. Policy and government intervention play a key role in the development of a low-carbon economy. Using game-based learning theory for reference, this paper builds an evolutionary model of low-carbon strategies based on the game between the government and enterprises in the context of a complex network. It then studies the effects of government incentives on enterprises regarding the diffusion of low-carbon policies and how enterprises compete and transform in the Newman-Watts small-world network. We introduce government policy encouragement as a factor in the decision-making process of companies' adoption of a low-carbon strategy, thus enriching the literature on the diffusion of low-carbon strategies. The model proposed in this paper can be used as a tool to evaluate the diffusion and application of low-carbon strategies among companies. The findings suggest that enterprises’ expectation of government incentives including subsidy and regulation determines whether low-carbon strategies can be diffused, and the diffusion speed. The more quick enterprises adjust their expectations in the government–enterprise game, the more enterprises will learn and follow to adopt effective low-carbon strategy. When enterprises attach great importance to the expected earnings from government incentives, the less effective low-carbon strategy adopted initially can be replaced by another more effective one. [ABSTRACT FROM AUTHOR]

In order to analyze the action mechanism of environmental pressures on the development of environmentally friendly technologies (EFTs), this paper constructs a neo-schumpeterian simulation model containing firms' production, pricing, pollution abatement investment, (environmental) R&D, entry & exit decision-making and consumer choice behavior. The objective of this paper is to investigate the influence of consumer demand preferences and environmental policies on firms’ environmental investment decision-making as well as the development of EFT. Results showed that consumers prefer product price, a market-based instrument (MBI) combined with an information-oriented instrument (IOI) can promote the development of EFT, while MBI applied alone will reduce environmental investment. Under scenarios that consumers prefer product quality, a command and control environmental policy (CAC) can promote the development of EFT to a greater extent, but it inhibits environmental investment and damages the average profit rate of profit of the industry. If consumers prefer environmental performance of firms, CAC or IOI is advantageous to the change of EFT. However, in such a case environmental investment and consumer utility are reduced. [ABSTRACT FROM AUTHOR]

The vast and growing array of concepts, methods and tools in the sustainability field imply a need for a structuring and coordinating framework, including a unifying and operational definition of sustainability. One attempt at such framework began over 25 years ago and is now widely known as the Framework for Strategic Sustainable Development. However, as with the larger sustainability field, the social dimension of this framework has been found to not be sufficiently science-based and operational and thus in need of further development. In this two-part series an attempt at a science-based, operational definition of social sustainability is presented. In part 1 a systems-based approach to the social system was presented, based on extensive literature studies as well as conceptual modelling sessions using the Framework for Strategic Sustainable Development as the guiding structure. The focus of that study was on the essential aspects of the social system that need to be sustained, namely trust , common meaning , diversity , capacity for learning and capacity for self-organization . The aim of this second paper is to identify and present overriding mechanisms by which these aspects of the social system can be degraded, thereby finding exclusion criteria for re-design for sustainability. Further literature studies, conceptual modelling sessions and initial testing of this prototype with partners in academia, business and NGOs were performed. Based on the understanding of the essential aspects of the social system and the identified overriding mechanisms of degradation of these, a hypothesis for a definition of social sustainability by basic principles is presented. The proposed principles are that in a socially sustainable society, people are not subject to structural obstacles to: (1) health, (2) influence, (3) competence, (4) impartiality and (5) meaning-making. Overall, the two papers aim to provide a hypothesis for a definition of social sustainability, which is general enough to be applied irrespective of spatial and temporal constraints, but concrete enough to guide decision-making and monitoring. It is also a further development of the social dimension of the FSSD, which practitioners and researchers have requested for some time and can act as a support towards better integration of social sustainability in many other fields, e.g., sustainable product innovation, sustainable supply chain management, sustainable transport system development, and others. [ABSTRACT FROM AUTHOR]

Several publications approach the subject of corporate sustainability performance, considering this background, the present research conducts a systematic literature review based on 261 papers towards a conceptual framework for integrating sustainability performance into business. Moreover, it aims at structuring the literature on corporate sustainability performance to highlight its main contributions and gaps. Data analysis initiates with a descriptive statistics of the sample, including yearly distribution, main journals, and most cited papers. It is followed by the delimitation of each sustainability performance approach of measurement, management and reporting and the cross analysis among them. Finally, a conceptual framework is proposed to address the integration of sustainability performance into business. This framework is composed by three levels. The first represents the principles for corporate sustainability to guide decision-making driven by collective values. The second level includes the core sustainable business elements, which are processes and practices, capabilities, offerings and contributions to sustainable development. At the third level, the context factors represent the internal and external aspects that affect the previous levels. [ABSTRACT FROM AUTHOR]

Process and Input–Output based methods are standard models used in attributional life cycle assessment (ALCA). These are linear models that, when used to estimate environmental consequences of a decision that involves changes, rely on linear extrapolation to approximate the changes. Behind this linearity are several assumptions such as fixed input/output relationships and unlimited supply of inputs. These assumptions expose the limitations of the attributional framework when used for consequential modeling. For example, if a product system faces supply constraints and an additional output would induce input substitution, a simple linear extrapolation from existing situations would fall short of estimating the environmental consequences of the additional output. These assumptions, however, can be relaxed to better reflect reality and the attributional framework can provide more relevant and accurate estimates for consequential modeling and decision making. Drawing insights from LCA studies on biofuels and the rich literature of Input–Output Analysis, this paper presents a two-step approach to consequential life cycle assessment (CLCA) based on the attributional framework. The first step compiles inventories and conducts attributional analysis to evaluate the status quo of the system under study, identify hotspots on which to focus on subsequently, and construct business-as-usual scenarios. The second step introduces the decision in question, evaluates possible changes to take place, builds scenarios representing associated environmental consequences, and modifies the original inventories accordingly. This paper demonstrates that the attributional framework can serve the purpose of addressing change-oriented questions when it is used properly and its assumptions and limitations are recognized. [ABSTRACT FROM AUTHOR]

Numerous methods can be used during the design stage to ensure that new products are developed to optimize performance with respect to economic, environmental, and societal objectives. When an optimally chosen design is launched, many uncertainties are likely to affect its performance over different lifecycle stages. Such uncertainties give rise to various risks that can potentially lead to deviations between the expected and actual economic, environmental, and societal implications of the product designed. Therefore, it is imperative that sustainable product design alternatives are also assessed to evaluate their robustness against such risks, should they occur, before design decisions are finalized. However, comprehensive quantitative methods for use during the product design stage to evaluate the influence of the likelihood of different risks on expected sustainability performance are lacking. The purpose of this paper is to address these gaps by developing a methodology for risk likelihood assessment. The sequence of risk identification, risk analysis, and risk evaluation for systematic risk assessment, recommended in the ISO 31000 Risk Management Guidelines, is followed to develop a methodology to quantify risks and their effects. For risk identification, a comprehensive taxonomy is used to identify risks that can influence total lifecycle product sustainability performance. For risk analysis, Bayesian Belief Network (BBN)-based approach is used to develop a method to assess the influence of risks on total lifecycle product performance through predictive and diagnostic inference. A new metric, the Operational Risk Index (ORI), is developed to better communicate influence of risk likelihoods. For risk evaluation, methods to evaluate risk mitigation strategies are presented. An industrial case study is used to demonstrate the application of the methods. The proposed BBN-based decision support tool enables assessing and visualizing the effect of risks on product design performance, identifying critical risks, and risk propagation paths. The tools can enable product designers to make risk-informed choices when identifying product designs that are more robust and ensure improved total lifecycle sustainability performance. The new ORI metric is helpful to compare multiple designs with respect to total lifecycle risk assessment. The methods proposed in this research present a comprehensive methodology for total lifecycle risk likelihood assessment in sustainable product design decision making. • Numerous risks affect the sustainability performance of product designs. • ISO 31000 risk assessment facilitates sustainable product design decision making. • Bayesian Belief Network (BBN) enables assessing product design performance risks. • Mitigation strategies for critically performing risks simplifies decision making. • Operation Risk Index helps compare alternate product designs performances. [ABSTRACT FROM AUTHOR]

Sustainability assessment provides essential information to facilitate informed decision-making, enabling the selecting of the best option among various projects. This research paper considers the decision-making problem in the context of marginalised and isolated communities, introducing a groupal model for evaluating the sustainability of small-scale power supply projects. The proposed model incorporates a comprehensive set of five indicators and 25 criteria. The analysis presented in this study prioritises these indicators and criteria, introducing new criteria based on several stakeholders' participation and offering guidance on measuring the identified criteria. Furthermore, the proposal provides fundamental thresholds for evaluating the projects' sustainability and proposes a model based on aggregated indicators to assess the available alternatives. It encompasses all stages of the decision-making process, employing multiple indicators to evaluate the sustainability of power supply projects. The effectiveness of the proposed model was validated in a real case study conducted in a marginalised community facing isolation challenges in La Guajira, Colombia. The evaluation showcased the model's contribution to decision-making processes regarding power supply projects in isolated communities. Finally, the results demonstrated the suitability of this strategy for immediate application, highlighting its potential impact on decision-making for sustainable development within marginalised areas. • The multi-criteria-based decision-making model maximises projects' sustainability. • The model evaluates the projects' sustainability, incorporating innovative criteria. • The model implementation in a study case confirms its efficacy for decision-making. • The study case findings suggest adopting cooperative or community-based governance. [ABSTRACT FROM AUTHOR]

The major objective of this paper is to introduce a novel multi-criteria decision making method (MCDM) called Root Assessment Method (RAM) which is easy to understand, straightforward to use and comparable with other well-known MCDM methods. RAM is motivated by the shortcomings of existing MCDM methods to obtain a reliable result in a decision problem and also the fact that decision maker (DM) should understand the whole decision making process to be able to avoid possible computational pitfalls. To do so, we define an aggregating function to rank the alternatives based on a radical expression which its radicand and index are the sums of benefit and cost criteria of each alternative, respectively. Accordingly, RAM allows a different compensation degree between beneficial and non-beneficial criteria which is rare in existing MCDM methods. As the advantages of RAM, the ranking result is not influenced by additional parameter, beneficial and non-beneficial criteria can be simultaneously considered without any transformation and pairwise comparisons are not used. On the other hand, it is observed that RAM can provide the advantage of preventing rank reversal in two case studies, whereas TOPSIS and VIKOR are subject to this problem in the same cases. As another contribution, a new heuristic procedure is suggested to compare the ranking results obtained by RAM with other methods. Ten numerical examples demonstrate that RAM results are consistent with its presumed function and are easily interpretable for a DM who may not be well acquainted with theoretical aspects of MCDM methods. Examples are positioned in the field of sustainability research as the area with wide application of MCDM methods. The results provided by RAM are encouraging and we hope this method contributes to enrich decision theory. [ABSTRACT FROM AUTHOR]

Reasonable water resources management is critical for promoting the sustainable development of social economy. In the real world, water managers often work in an uncertain environment, and this uncertainty comes from inaccurate information related to water resource data. Therefore, there is uncertainty about the value of criteria in multi-criteria decision making (MCDM) and evaluation of water resources management. In addition, the robustness of multi-criteria decision-making evaluation based on uncertain data is difficult to quantify, which poses challenges to the application of MCDM in water resources management. Therefore, this paper proposes a decision-making framework combining interval TOPSIS and a multi-sensitivity strategy. The framework is used for robust water resources management under uncertain conditions, revealing the optimal solution under the influence of uncertainty and sensitivity strategies, and identifying the ranking change mechanism by revealing the threshold of each criterion to identify alternatives as the optimal solution. The applicability of the proposed framework is verified in different cases (including water resources allocation and reservoir flood control operations). The outcomes indicate that: (1) the proposed framework expands the capabilities of current methods and provides a potential approach to deal with the robustness of options identified by decision makers engaged in water resources management under uncertainty; (2) among the proposed sensitivity strategies, the strategy of changing one or more criteria of a single scheme is more realistic in a changing environment; (3) in the case analysis, two cases show that changing from the lower position to the first position requires 80% and 45% of a set of criteria values. The findings of this study will provide a scientific basis for water resources managers to make robust scheme decisions. [ABSTRACT FROM AUTHOR]

Water, which is predicted to be one of the most critical resources for the near future, also plays a vital role in society's sustainable development. Wastewater treatment is a critical part of the circular water management system and offers various technological alternatives. Taking appropriate decision for the technology selection is, therefore, essential for a long-term perspective. A complex yet imperative process is the sustainable selection of the wastewater treatment process. This paper presents the use of multi-criteria decision-making (MCDM) in the sustainability assessment of wastewater treatment technologies that may be very relevant to the growing sector with many emerging options. A comparison of six wastewater treatment technologies based on four sustainability parameters using three MCDM techniques, namely FSWARA, FMOORA and FTOPSIS is presented in detail. FSWARA is used for weighting criteria and the other two for technology ranking. The detailed step-by-step comparison study is presented and the results were somewhat predictable for the study, and this confirms the reliability of the methodology. This paper's primary objective is to propose a well-defined increscent practice for making sustainable wastewater treatment decisions among state-of-the-art technologies. • Sustainability ranking of wastewater treatment technologies using multi-criteria decision making methods. • Combined Fuzzy SWARA-MOORA and fuzzy SWARA-TOPSIS methods. • While weighing the criteria, most significance is given to environmental factors. • Inclusion of both conventional and non-conventional technologies. [ABSTRACT FROM AUTHOR]

Environmental deterioration is becoming a topic of focus for researchers and practitioners around the world, as increasing consumer demand is further driving activities across all sectors of products and services. As such, governmental regulations are being enforced and countries around the globe are adopting means of promoting environmental policies in order to mitigate pollution by improving environmental performance and increasing efficiency. Such policies are applicable across all industries, including both the manufacturing and services industry. Specifically, the packaging industry has a very high environmental impact due to the significant level of pollution occurring from the use of hazardous packaging material. The implementation of environmental management concepts can help control the effect from the hazardous packaging of products. However, the implementation of Green Supply Chain Management is hardly an easy task for most industries. There are several factors that act as barriers to the implementation of Green Supply Chain Management (GSCM). The objective of the current paper is to identify the key barriers to the implementation of GSCM in the packaging industry by using Decision Making Trial and Evaluation Laboratory (DEMATEL). The results of the study aim to assist the packaging industry in better understanding the major barriers, as this is the first crucial step in overcoming them. Results demonstrate that lack of adequate training and progress monitoring as well as poor customer awareness and lack of pressure for widespread adoption of GSCM are among the most influential barriers. Important findings, limitations and managerial implications are also discussed in the current paper. [ABSTRACT FROM AUTHOR]

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations. [ABSTRACT FROM AUTHOR]

It is widely known that governance is central to the successful implementation of sustainable development policies and measures. Yet, there is a paucity of research which explore the links between governance and sustainability. This paper attempts to address this research need by providing an analysis of the role of governance in enabling – and to some extent – fostering a transition towards sustainable societies. A set of indicators for assessing the capacity for and willingness and commitment to transition to a more sustainable society is presented, enabling identification of direction of change. This paper presents the results of a study, in the context of which sustainability governance has been comparatively investigated in a sample of European countries with, by methodological purpose, very different economic, environmental, political and social conditions (Denmark, Finland, Germany, Latvia, Lithuania and Poland). Lessons learnt and examples of good practice – which may be replicable elsewhere-are outlined. For instance, it is discussed that limited knowledge about sustainable development amongst municipal development planners and decision-makers, deficiencies in policy integration, intersectoral cooperation, municipality and stakeholder cooperation and urban management practices are major reasons for weak governance practices in sustainable development. Furthermore, some recommendations on the role of sustainability governance are made, so as to allow the integration of the principles of governance into sustainability practice and hence provide a more general basis upon which a transition towards sustainable societies may become a reality in different types of European countries and societies. The scientific value of this paper lies in identifying opportunities for integrating principles of governance into sustainability practice, as well as outlining the basis for sustainability transitions, providing a general picture of required policy measures. The paper offers a unique comparative analysis of sustainability governance in the Baltic Sea countries, outlining some of the challenges in sustainability governance in the Baltic Sea region. [ABSTRACT FROM AUTHOR]

Regionalization can improve the accuracy of life cycle assessment (LCA) results and make it more relevant for decision makers. There has been a growing body of regionalized LCA research, and in particular many regionalized life cycle impact assessment (LCIA) models have been developed. However, insufficient attention has been paid to regionalized life cycle inventory (LCI), the study of the geographic location and quantity of environmental emissions that occur throughout the life cycle of a product. Previous studies have often used a simplistic approach based on regional output percentages (ROP) to regionalize an LCI, but with little justification for the use of the approach or discussion of its limitations. This paper first reviews the ROP approach, analyzes its strengths and weaknesses, and in so doing demonstrates the importance of interregional commodity flows in compiling regionalized LCIs. Next, this paper discusses ways in which LCIs can be more accurately regionalized. Incorporating the multiregional Input–Output (MRIO) models that are widely used in the Input–Output Analysis (IOA) literature, even when there are limited data on interregional commodity flows, can improve the accuracy of regionalized LCI results as derived by the ROP approach. Also discussed are circumstances in which the ROP approach can be used to compile a relatively accurate regionalized LCI. One important implication of this paper is for selecting a proper spatial scale for both regionalized LCI and LCIA analyses. [ABSTRACT FROM AUTHOR]

Research on behavioral motivation for green product consumption has greatly advanced in recent years, but many unknowns remain, particularly regarding consumers' willingness to pay premium prices for products with ecological appeal. In this context, this paper reports an experimental research that investigates the relationship between consumer perceived value for green products and price elasticity. The research was performed using an adaptation of the model proposed by Zeithaml (1988) and it was applied in the automotive and furniture sectors. It was found that perceived value of green products increases willingness to pay in the purchasing decision. It was also observed that demographical variables, such as gender, age and revenue positively impact perceived quality and the consequent purchase intention. Considering the population sampled, results indicate that the effect of ecological appeal is similar to a 10% price reduction. It means that, according to the declared preference, respondents were willing to pay, on average, a 10% premium for green products in the studied product categories. The main theoretical contribution of our paper lies in furthering the understanding of how key dimensions that constitute perceived value relate to each other and to demographic and personal influence variables, as well as its impact in willingness to pay premium prices for green products. [ABSTRACT FROM AUTHOR]

The paper, through a “regenerative” lens, has focused upon a new conceptual game system involving transaction costs (TCs) for creating a more accessible green buildings (GB) market. Individual stakeholders steadfastly guard their own interests in any investment decision, which seldom considers any positive gains to society. Green buildings, branded as partial public goods, involve rational and irrational factors, incurring extra transaction costs (TCs) and affecting the willingness of the stakeholders to take part. This paper examines how to reduce the TCs incurred during the game played in the decision-making process with the ultimate aim of promoting GB. In the game model, the developers and end-users negotiate and bargain over the TCs caused by GB in comparison with its conventional counterpart. The findings are that 1) TCs are the overriding barriers impeding the development of the GB market. Reducing TCs will facilitate supply and demand in the GB market; 2) the equilibrium payoffs for the developer and the end-user are proportional to their bargaining powers (the higher the bargaining power is, the more benefit it will gain from the GB transaction); 3) strengthening the bargaining power of the developer can increase the expected utility of developing GB; and 4) more fake GB products or less credible developers will result in higher TCs for the end-users and therefore lower payoffs will be expected. The findings stress that the choice between developers & end-users over investing in GB is a complex game problem, where TCs could be conceptualized and showed their important role. By minimizing the TCs incurred in the complex decision of GB, it will not only benefit themselves but also bring net regenerative outcomes to society. [ABSTRACT FROM AUTHOR]

The anthropogenic use of phosphorus has emerged as a one of the major drivers of global environmental change. The finite supply of the nutrient, geographical concentration of the remaining supply, and continuing occurrences of eutrophication and harmful algal blooms (caused, in part, by excessive phosphorus outflows into the environment) are causes for immediate concern. As a response, there is increasing recognition that phosphorus entering waste streams should be recovered as a resource rather than disposed of as a pollutant. While phosphorus recovery technology and strategies have been outlined in some detail in the existing literature, none have explicitly addressed the reasons for why these processes have not been implemented at scale. In addition, the potential for urban systems to play a role in creating a holistic management system for phosphorus has received little recognition. This paper addresses these knowledge gaps by offering a tool for analyzing the context, drivers, barriers, and implementation of phosphorus recovery technologies in urban areas. The framework tool consists of five guiding questions. The process of answering the questions presents an opportunity for researchers, decision makers, and community stakeholders to explicitly identify what and how changes to the current system can be made. This paper provides an approach for producing the knowledge necessary for facilitating the transition to an urban phosphorus recovery regime that is relevant for both practitioners and academics. The approach may also be adapted to understanding other resource cycles in the future, such as nitrogen, water, and energy. [ABSTRACT FROM AUTHOR]

Building Energy Efficiency Retrofit (BEER) is considered as a valuable way to improve energy efficiency of high-energy-consumption buildings. Sustainable BEER helps integrate sustainable development strategy into existing buildings and retrofit projects. To ensure BEER projects that can fulfill the sustainable development strategy, Energy Performance Contracting (EPC) is one possible market mechanism to deliver energy efficiency projects. Sustainable BEER under the EPC mechanism is a comprehensive system which involves the various demands of sustainable dimensions, performance criteria and groups of project success factors, making multi-criteria decisions become a challenging problem for decision makers. This paper aims to examine the interrelationships of sustainable BEER by focusing on an existing hotel building. EPC mechanism is applied in the case study and an effective Analytic Network Process (ANP) approach is also employed in the research. The result indicates that sustainable BEER in hotel buildings under the EPC mechanism is mainly determined by project control mechanism, available technology, organizing capacity of the team leader, trust, accurate Measurement and Verification (M&V), and team workers' technical skills. Decision makers should dedicate more attention to these aspects. From the research findings, several policy implications are proposed in this paper. [ABSTRACT FROM AUTHOR]

Remanufacturing facilitates multiple usages of products by providing several life cycles and contributes to more sustainable societies by the reduction of raw materials and energy consumption. Previous studies on sustainability assessment in remanufacturing focus predominantly on the life cycle design and the life cycle engineering approach. There is a research gap regarding the assessment of remanufacturing operational excellence as far as sustainability issues are concerned. The problem in the application of the principles of sustainable development in everyday business operations is the lack of clearly defined sustainability indicators, which might be used in the assessment of remanufacturing activities. In this paper authors present a set of indicators which are used as the criteria for sustainability assessment and to address company classification. Authors define three classes of companies, which respond to the different sustainability levels. The aim of this paper is to provide a new tool for decision making based on Grey Decisions Making. This tool helps in classifying the current state of remanufacturing operations, and then identifying and prioritizing operations in the company which need improvement actions. The authors present the numerical example in order to explain the decision making process and indicate how the application of Grey Decision Making (GDM) can contribute towards more sustainable societies. [ABSTRACT FROM AUTHOR]

In today's manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision-makers to prioritize green manufacturing. The Internet of Things paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from manufacturing processes can be collected easily, and then analyzed, to improve energy-aware decision-making. Relying on a comprehensive literature review and on experts' insight, this paper contributes to the understanding of energy-efficient production management practices that are enhanced and enabled by the Internet of Things technology. In addition, it discusses the benefits that can be obtained thanks to adopting such management practices. Eventually, a framework is presented to support the integration of gathered energy data into a company's information technology tools and platforms. This is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage on such data in order to improve energy efficiency, and therefore competitiveness, of manufacturing companies. With the outcomes of this paper, energy managers can approach the Internet of Things adoption in a benefit-driven manner, addressing those energy management practices that are more aligned with company maturity, measurable data and available information systems and tools. [ABSTRACT FROM AUTHOR]

The aim of this paper is to discuss the measurement of eco-efficiency in the Finnish forest industry from three perspectives. First, the paper introduces a way to measure eco-efficiency in the Finnish forest industry. Second, the paper evaluates the suitability of public data for calculating eco-efficiency in the Finnish forest industry. Third, the calculations of selected eco-efficiencies are presented. The main method used in this research is the Delphi panel, and eco-efficiency indicators are based on the experts' rating. The environmental and economic performance information of the three biggest Finnish forest industry companies are used here as examples. According to the experts of the Delphi panel, the economic performance of the eco-efficiency should be measured using the ‘value added’ indicator. In environmental performance, they preferred the environmental impact or emissions groups. Based on public data, the value added data can only be calculated at the company level, although the environmental impact and emissions groups could be presented in detail as site-level figures. Eco-efficiencies can be calculated only with selected environmental aspects and for a limited time frame. The eco-efficiency calculations show varying trends for the three companies: improvements, declines and fluctuations in eco-efficiencies. The current research raises questions regarding the usability of public data as a source of research material, suitability of the indicators suggested for decision making of the forest industry, the need for more detailed data to study the development of the eco-efficiency of the Finnish forest industry and the need to compare the eco-efficiency performance of the Finnish forest industry with that of its international counterparts. [ABSTRACT FROM AUTHOR]

The European Union energy label informs consumers at the point of sale about the energy efficiency and electricity consumption of various electric goods. The label should enable consumers to purchase energy-friendly products (i.e., products with low energy consumption), thereby making a significant contribution to the reduction of overall energy consumption. This paper offers a systematic analysis of consumers' interpretation of the energy label. The results of a set of experimental studies revealed that consumers tend to base their estimates of a product's energy consumption mainly on the energy efficiency class (e.g., A) communicated on the energy label and largely ignore information about annual electricity consumption (e.g., 120 kWh/year). Thereby, consumers potentially overestimate the energy friendliness of a product assigned a high energy efficiency rating. This also holds true when consumers directly compare two products in terms of energy friendliness. Thus, participants chose a higher-consuming product because it had a high energy efficiency rating. High energy efficiency ratings (e.g., A +++ ) can distort consumers' perceptions of product categories that consume excessively (e.g., freezers). Participants were seduced into thinking that a high energy efficiency rating (e.g., A ++ ) means the energy consumption of energy hogs is no longer problematic. This paper provides evidence that the energy label could have a contrary effect than the one intended due to people's susceptibility to an energy efficiency fallacy. This misinterpretation of the energy label could further explain why overall energy demand is increasing despite enhanced energy efficiency. Finally, implications for policy makers and further research for enhancement of the energy label are discussed. [ABSTRACT FROM AUTHOR]

The process of a regional industrial system in China can be separated into two internal stages: production stage and pollutant abatement stage. This paper aims to examine the efficiency of Chinese regional industrial systems by taking the operational performance of its two internal stages into consideration. Unlike traditional data envelopment analysis models that treat decision making units as “black box” when measuring their efficiencies with undesirable factors, this paper proposes a two-stage model based on slacks-based measure to evaluate the efficiency of Chinese regional industrial systems. By decomposing the efficiency into production efficiency and abatement efficiency, the proposed model can estimate the efficiencies of the whole regional industrial system, its production stage and abatement stage simultaneously. The model provides a way of improving performance of a regional industrial system through identifying its inefficient internal stages. This can help to find out the main sources of the inefficiency that arise from the internal stages within the system, which cannot be done by using conventional environmental data envelopment analysis models. Findings resulting from the model application show that there are great disparities in regional industrial systems' efficiencies, and the inefficiency of Chinese industrial system is largely driven by the abatement stage. [ABSTRACT FROM AUTHOR]

Industrial energy efficiency has raised to the top of European energy policy agenda, and particular efforts should be placed to tackle the barriers to energy efficiency of small and non-energy intensive industrial users. To enhance the adoption rate of a specific industrial energy efficiency measure, it is crucial to properly evaluate the barriers. Without a proper level of detail - considering both the measure's specificity and the evaluation's perspective - company managers are hampered when making investment decisions, and policymakers are prevented from developing the most effective policies. The paper aims at highlighting that the value of a given intervention-dependent barrier may differ when evaluating it at the company level, by technology area, or with respect to a specific measure. To achieve this objective, an exploratory investigation of Italian small and medium-sized enterprises into the metalworking sector has been performed with respect to selected cross-cutting technologies. Although general barriers appear as most relevant at the company level, large differences appear when considering intervention-dependent barriers by technology area as well as at the energy efficiency measure level. The research presents innovative results, as the literature and policymakers have not accounted so far for how the value of barriers can effectively vary with respect to a single measure, but have only considered barriers at company level. Additionally, the paper highlights that differences can be appreciated when evaluating the intervention-dependent barriers according to some firm characteristics (i.e. size, production complexity, and innovativeness). The study concludes with suggestions for policymakers as well as industrial decision-makers. [ABSTRACT FROM AUTHOR]

This paper presents a new methodology to determine the best layout of water quality monitoring stations for drinking water distribution systems (DWDSs) threatened by deliberate contamination events. Optimal design of monitoring stations in DWDSs usually involves maximizing the detection probability which is attainable by limited numbers of monitoring stations. This is a challenging task due to the existing uncertainties in intrusion location, intrusion time, the amount of contamination injection, and network behavior in different parts of a day. This problem would be more complex when the conflicting objectives are taken into account to minimize the impact of deliberate contamination events. The proposed methodology, the conflicting objectives of detection time, undetected pollution events, number of monitoring stations and population affected prior to detection are minimized. In order to determine the best non-dominated alternatives in presence of the mentioned conflicting objectives, a multi-objective optimization model (NSGA-II) and a simulation model (EPANET) are embedded. For determining the best layout of monitoring stations, in this paper, perhaps for the first time, the evidential reasoning (ER) approach is applied to rank the obtained non-dominated alternatives and the results are compared with those obtained from the traditional technique for order of preference by similarity to ideal solution (TOPSIS). The method provides decision-makers with the flexibility to choose an optimal layout of monitoring stations. To evaluate the efficiency and applicability of the proposed methodology, it is applied to a real-world DWDS threatened by Arsenic as a hazardous chemical contaminant in terrorist attacks. [ABSTRACT FROM AUTHOR]