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The purpose of this study is to show that corporations may resort to legal compliance instead of acting voluntarily towards abatement of environmental damages as a strategy for improving their reputation.

Based on the natural philosophy and postulate of business, theoretical models have been developed to justify the purpose of this paper. Financial impacts of Indian revenue law on environmental damage prevention by the polluting firms have been gauged mathematically.

Corporate environmental responsibilities have seemed to be more reputation-led than innovation-led or efficiency-led. Reputation-led environmental responsibilities can have ways to bypass innovations and some firms can simply comply with regulations at the society’s cost (may be to a sizeable extent). If penalty is imposed on companies in the form of taxation for damaging the environment, then companies get chances to pass the financial burden to the shareholders in the form of lower dividend pay-outs. Unless the capital market supports corporate green initiatives, there may be destruction of shareholder wealth.

Extensive empirical analysis have not been conducted as the paper concentrates on developing theoretical understanding of the models of “green cost”.

The exploration and outcomes of this paper can offer several directions to the government, business and social activists in articulating green economic policy for the benefits of all.

The civil society will understand better what the corporate environmental responsibility really means for them.

This paper has made a modest endeavour to develop theoretical models of both “green cost internalisation” and “green cost externalisation”. It has paved the path for further deliberations and research.

In this study, an optimal green product is selected from three newly developed ecological products and a non-environmentally friendly product. An analytic network process (ANP), used widely for multi-criteria decision making (MCDM), is applied to account for the tradeoff issues among the criteria (quality, cost and green issue) in the new green product selection processes. The paper aims to discuss these issues.

This paper focuses on current social and consumer requirements. New product selection processes consider three major perspectives, i.e., quality, cost and environment, as criteria. The following two main methods are applied to respond to this multi-disciplinary issue: the eight quality dimensions proposed by Garvin are used to manage the quality issue, and a life cycle costing (LCC) method is applied for consideration of the cost and green issue. Therefore, the dependency issue among the criteria is considered, using a suitably selected method, the ANP method, and all the methods are applied to a real business, which produces roof tiles, for the delivery of a new optimal green product.

An optimal environmentally friendly product does not overcome the existing toxic product of the focused company. The environmental performance is necessarily balanced by the quality and cost capabilities.

This paper focuses on the new product selection of roof tile products. The criteria or measuring indicators may be dissimilar, and cannot be applied to other products.

The proposed approach can be applied to other manufacturing companies or services to allow decision makers to make better determinations for a comprehensive dependency problem. The managers can apply the proposed model to benchmark the considered products as well as to find the weaknesses of products.

This method considers the relationship among quality, cost and environment for newly developed green products. The method produces better results than former MCDM studies which did not account for the dependency issue among the criteria.

The purpose of this paper is to develop a decision matrix for green project management processes (GPMPs) in commercial construction projects. GPMPs can assist in decoding all of the information required to make green-conscious decisions at various stages of a project.

Integrate the environmental factors into the traditional project management processes (PMPs) of major construction projects. The integrated product is worked into a process index, and the analytical hierarchy processes (AHP) method is used to prioritize the GPMPs according to pre-set criteria.

Research established the theoretical backing of green practices integration in the traditional PMPs, by creating an AHP weighted GPMP index that is linked to usable decision matrix.

Develops a fresh methodology to facilitate green decision-making in the project management of commercial construction projects.

The purpose of this paper is to propose a balanced scorecard (BSC)- and strategy map-based quantitative framework for assessing the lean and green performance of the supply chain (SC). As the SC competitiveness demands efficient and effective utilization of resources throughout the value chain, not only adoption of lean and green SC paradigms but simultaneously its performance evaluation is also vital.

The lean and green SC performance measures are classified into four categories of BSC. A fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology combined with analytical network process is proposed for examining the causal relationships between BSC perspectives and respective assessment criteria. The application of the proposed assessment framework is demonstrated for the case of Indian textile SC.

The research delivers a quantitative assessment framework for evaluating lean and green performance of the SC. The results obtained for a typical case of Indian textile SC revealed that “delivery performance,” “profitability” and “operational cost” are the most crucial performance measures. The perspective of “internal processes” is the most significant of all BSC perspectives while “learning and growth” perspective acts as the driving force to improve lean and green SC performance.

The paper makes two contributions in the domain of lean and green assessment of SC performance. First, it proposes an evaluation framework to investigate into the causal relationships among the BSC perspectives and related factors. Second, it undertakes an empirical investigation for Indian textile SC to develop key managerial insights and provide policy-related recommendations.

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.

The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.

The incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.

The designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.

The case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.

Inclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.

The objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.

This research aims to comprehensively analyse the Agri-food supply chain, by identifying the barriers, and considering effective pathways towards a green supply chain. To the best of our knowledge, in the research area of supply chain, the majority of the research is oriented towards the evaluation of barriers and pathways or drivers to the implementation of green supply chain management in the manufacturing industry. The field of Agri-food is among the sectors of concern due to the quantum and basic necessity of the industry.

The contribution of this paper is to develop and evaluate a general framework of the most relevant barriers and possible pathways towards the green Agri-food supply chain, with the help of a hybrid approach combining both the ANP and ELECTRE I methods, via a case study of the fish canning industry.

Furthermore, the study findings will help both academicians and practitioners in developing and evaluating green supply chain frameworks in this area of study.

The results of this study show that the cost of greening the supply in terms of implementing sustainability standard, or advanced technology are the most relevant barriers, and that the social and operational pathways family is among the best effectives pathways.

Although green logistics has become a new focus of cooperation between government and enterprises under environmental constraints, how local governments formulate subsidy policies to effectively guide the green transformation of regional logistics and how to facilitate the reasonable cost-sharing are rather critical. This paper will deeply explore the dynamic process of the tripartite participation (government, platform, and logistics enterprises) in the selection of regional green logistics strategy, and reveal the evolutionary game relationship of the three parties.

To explore the dynamics involving the government, platform and logistics enterprises for the green logistic transformation, and reveal the evolutionary gaming among the three parties, based on the bounded rationality premise, this study constructs the tripartite asymmetric evolutionary game models, uses the stability theorem of differential equation to explore the evolution and stability strategy of the system in different cases and explicates the paths of influence on the tripartite behaviors via simulations.

Results of this study indicate that there exist stable equilibrium strategies among the three parties regarding the regional green logistics, and they are affected by different factors. The government's subsidy, subsidy intensity and the platform's cost-sharing proportion can generate positive effects, but the latter two can also impact negatively beyond the effective ranges. The findings provide a theoretical basis for local governments, platforms and logistics enterprises to formulate justifiable subsidy intensity and determine reasonable sharing proportion.

Firstly, considering the significant relevance of local government, it is included in the evolution model, and the tripartite game (among government, platform and enterprises) is explored; Secondly, by comparing the equilibrium results under different game conditions, this paper analyzes the evolution of each party's game strategy to achieve the optimal return under bounded rationality and the important factors determining the strategic selection; Finally, the key factor of platform cost sharing is involved, and to what extent the change of platform cost sharing ratio will influence the systematic stability is explored.

Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

This study aims to investigate the hierarchical relationship between industry-specific attributes of supply chain (SC) strategies and information technology (IT) to improve the performance of firms in textile industry in Pakistan.

This study presents a mix of enablers through literature review and experts’ opinions. Next, the driving and dependence powers of enablers were identified, using the interpretive structural modeling (ISM) approach.

The ISM model suggests eight levels, with customer satisfaction at the top of the model. Process automation and TQM are placed at second and third level, respectively, whereas flexible sourcing and flexible capacity are positioned at fourth level. The key enablers of IT have high driving power, hence positioned at the bottom of ISM model.

This study has value for firms in garment manufacturing and exporting industry to invest into IT and sustainable SC design for competitive performance. The theoretical and managerial implications are provided.

The purpose of this paper is to identify and analyze the critical success factors (CSFs) behind the successful implementation of lean-green practices in Indian small- and medium-scale enterprises (SMEs).

The analysis employs two modeling approaches such as interpretive structural modeling (ISM) and interpretive ranking process (IRP) for examining the contextual relationships among the CSFs and ranks them with respect to key lean-green performance areas. A critical review of literature has led to the identification of total 25 CSFs for lean-green implementation. The list is reduced to 18 most relevant CSFs for the context of Indian SMEs based on experts’ (from industry and academia) opinions. The ISM is utilized to develop ten-level hierarchical model of CSFs. In order to gain greater insights into the nature of variables, the matrix of cross-impact multiplications applied to classification (MICMAC) analysis has been conducted.

The results show “Government support” as the most significant to the successful lean-green implementation in Indian SMEs and it is placed at the base of the ISM hierarchy. The CSF “Green disposal initiatives” is identified at the top level of the ISM hierarchy. Further, MICMAC analysis identifies five independent variables, eight linkages variables, four dependent variables and none autonomous variable. This may help SME managers to decide about resource priorities toward successful implementation of lean-green initiatives. Subsequently, the IRP has examined the dominance relationship and identifies “Organizational capabilities” as the most significant CSF.

This research intends to enable practitioners in prioritizing and managing strategic and tactical challenges involved in lean-green implementation in Indian SMEs.

This study makes an initial attempt in analyzing factors critical to successful implementation of integrated lean and green manufacturing practices in Indian manufacturing SMEs using ISM. The analysis is further enhanced by applying IRP to rank the CSFs by investigating the influence lean-green integration on various performance measures.