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The purpose of this paper is to examine the relationships between supplier development practices (SDPs) and supplier-buyer relationship practices from the supplier’s perspective (SBRSP), and seek to understand how specific SDPs may impact a buyer’s operational performance as well as supplier-buyer relationship practices.

The authors conducted a survey of 512 respondents from the different manufacturing firms in India and applied structural equation modelling to test a structural model that proposes the impacts of various efforts of SDPs on a buyer’s performance as well as SBRSP.

The study concludes that SDPs and SBRSP together improve the relationship between a buyer and supplier, and this improved relationship leads to competitive advantages (CAs) followed by profitability. Results indicate that supplier perspective of buyer-supplier relationship can be improved under the condition of SDPs and SBRSP together. SDPs are driven by productive measure and competitive pressure, whereas customer uncertainty is found to be statistically insignificant.

The study was carried out in North Maharashtra Industrial Zone of India, where the auto sector and machine/components manufacturing firms have been established for a considerable period of time. Results of the study are limited to manufacturing organizations predominantly focussing on the automobile sector and machine/components manufacturing firms.

This study provides significant insights into the specific impact of various SDPs and SBRSP for both academics and practitioners. SDPs along with SBRSP practices lead to improvement in the relationship leading to CAs. SBRSP suggests that trust, long-term commitments and the supplier’s perspective are important practices for relationship improvement.

The current study attempts to identify what are the success factors for the supplier-buyer relationship from the supplier’s perspective and SDPs and how the supplier-buyer relationship can be improved under the condition of SDPs and SBRSP. Hence, the aim is to develop a more thorough understanding of the outcomes of a supplier-buyer relationship improvement from both buyer’s and supplier’s perspective, under the conditions of supplier development to achieve CAs leading to profitability. Furthermore, the study analyses the effect of the improved supplier-buyer relationship for achieving CAs leading to profitability.

The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria.

An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach.

The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company.

Exclusion of qualitative criteria for 3PL vendor selection and the judgment of weights for TOPSIS can be considered as the limitations of the present work. The study has significant practical implications for organizations belonging to any sector or industry. It can help them in evaluating the existing 3PL vendors and selecting the most efficient among them.

This paper deals with a framework modeled for 3PL vendor selection. It is the first attempt to utilize an integrated approach, i.e. DETOLP model for evaluation and selection of 3PL. For assessment of the model, real data from an Indian company has been taken to analyze the result and compare it with the present scenario within the company.

Wastewater treatment plants (WWTPs) have long-time environmental impacts. The purpose of this paper is to assess the environmental footprint of two advanced wastewater treatment (WWT) technologies in a life cycle and sustainability perspective and identify the improvement alternatives.

In this study life cycle-based environmental assessment of two advanced WWT technologies (moving bed biofilm reactor (MBBR) and sequencing batch reactor (SBR)) has been carried out to compare different technological options. Life cycle impacts were computed using GaBi software employing the CML 2 (2010) methodology. Primary data were collected and analysed through surveys and on-site visits to WWTPs. The present study attempts to achieve significantly transparent results using life cycle assessment (LCA) in limited availability of data.

The results of both direct measurements in the studied wastewater systems and the LCA support the fact that advanced treatment has the best environmental performance. The results show that the operation phase contributes to nearly 99 per cent for the impacts of the plant. The study identified emissions associated with electricity production required to operate the WWTPs, chemical usage, emissions to water from treated effluent and heavy metal emissions from waste sludge applied to land are the major contributors for overall environmental impacts. SBR is found to be the best option for WWT as compared to MBBR in the urban context. In order to improve the overall environmental performance, the wastewater recovery, that is, reusable water should be improved. Further, sludge utilisation for energy recovery should be considered. The results of the study show that the avoided impacts of energy recovery can be even greater than direct impacts of greenhouse gas emissions from the wastewater system. Therefore, measures which combine reusing wastewater with energy generation should be preferred. The study highlights the major shortcoming, i.e., the lack of national life cycle inventories and databases in India limiting the wide application of LCA in the context of environmental decision making.

The results of this study express only the environmental impacts of the operation phase of WWT system and sludge management options. Therefore, it is recommended that further LCAs studies should be carried out to investigate construction and demolition phase and also there is need to reconsider the toxicological- and pathogen-related impact categories. The results obtained through this type of LCA studies can be used in the decision-making framework for selection of appropriate WWT technology by considering LCA results as one of the attributes.

The results of LCA modelling show that though the environmental impacts associated with advanced technologies are high, these technologies produce the good reusable quality of effluent. In areas where water is scarce, governments should promote reusing wastewater by providing additional treatment under safe conditions as much as possible with advanced WWT. The LCA model for WWT and management planning can be used for the environmental assessment of WWT technologies.

The current work provides a site-specific data on sustainable WWT and management. The study contributes to the development of the regional reference input data for LCA (inventory development) in the domain of wastewater management.

The purpose of this paper is to efficiently assist the decision makers in evaluating and selecting the most appropriate third-party logistics (3PL) provider from environmental sustainability perspective using a two-phase model based on data envelopment analysis (DEA) and analytic network process (ANP).

The study uses an integrated approach of DEA and ANP as an evaluation and selection methodology to select an efficient and requisite 3PL. The integrated model is a sound technique for 3PL evaluation and selection. DEA effectively screens the maximally efficient 3PLs, whereas ANP easily performs the cumbersome process of weighting diverse criteria and ranks various alternatives according to their performance on the basis of these criteria. This study lists the prominent evaluation and selection criteria taking into consideration the environmental sustainability. Finally, a real-life industrial application is presented to demonstrate the proposed method.

The current research work is devoted to the emerging research topic of environmental sustainability in logistics industry and supply chain management. The results of study indicate that eco-efficient transportation and 3PLs lead better transportation planning, better inventory and warehouse management, lower inventory cost and sustainable supply chain operations. Also, the applied approach enables the decision makers to better understand the complex relationships of the relevant criteria in the decision-making process.

This study does not investigate the relationships between environmental performances and differentiation advantage from the perspective of 3PLs. Also, sensitivity analysis is not performed.

The developed integrated model enables decision analysts to better understand the complete evaluation process of 3PL evaluation and selection considering environmental sustainability perspective. Furthermore, the developed approach provides a more flexible, simple, accurate, effective, and systematic decision support tool for 3PL evaluation and selection.

The current study is first of its kind to use the integrated approach in evaluation and selection of 3PLs from environmental sustainability perspective considering the inter-dependencies among the evaluation and selection criteria.

The purpose of this paper is to present a research model that explore strategic outsourcing practices for sustainable competitive advantages. In this paper, a decision support system (DSS) for sustainable performance measurement of carry and forward agents (CFAs) is proposed.

The importance of seven criteria as a means of selecting the best CFA for warehouses under the aspect of sustainable environment is analyzed. The criteria are compared and ranked using analytic hierarchy process (AHP) with the combined assistance of literature review and expert opinions. This study makes use of unstructured interviews of Regional Distribution Manager and senior strategic leaders of the firms.

This paper discusses how strategic outsourcing can help firm to achieve desired business outcomes. The selection of best CFA gives a direction to the company to move toward excellence and provides the key areas to work upon to achieve competitive advantage. The main contribution of this paper includes modeling the performance evaluation problem within the context of a sustainable supply chain based on triple bottom line (TBL) concept.

The identified selection criteria are bound with Indian transportation and logistics industry. Further, it is suggested to conduct a real-life application of this study to other companies from different countries, to obtain criteria based on globally acceptable norms. The results may yield the network-specific evaluation criteria and their evaluations.

The developed excel-based tool could be used to record the inspection data, compare the CFAs and determine the best CFAs on the basis of selected criteria. With the help of this tool, CFAs know their position and ranking among all the CFAs and the focus areas they need to work upon to perform well. The training module could be used to keep the CFA staff on the right track which is very essential in a typical manufacturing industry warehouse. The improved performance of CFAs will in turn help to improve the manufacturing process, thus maximizing the gains along with environmental benefits.

This paper provides a priority of sustainable issues for evaluating the performance of the best CFA. The paper presents a strategic outsourcing model, which suggest both theoretical and managerial implications showing how to implement successful outsourcing practices in the global market by analyzing the performance of outsourcing partners, i.e. CFAs.

The purpose of this paper is to describe an application of Multi-Criteria Decision Making (MCDM) technique for the selection of waste treatment and disposal technology for municipal solid waste (MSW).

The proposed approach is based on the integration of Delphi and Analytic Hierarchy Process (AHP) techniques. A model has been proposed to evaluate the best treatment and disposal technology. Expert opinions have been incorporated in the selection of criteria. AHP has been used to determine the weights of criteria, followed by ranking of the available technologies.

Delphi method was used to derive appropriate evaluation criteria to assess the potential alternative technologies. A set of identified holistic criteria was used, representing the environmental, social, and economic aspects, as compared to the sub-criteria concept generally found in existing literature. Quantitative weightings from the AHP model were calculated to identify the priorities of alternatives. The study provides a simple framework for technology selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time consumed in the decision-making process.

The model identifies the optimal technologies for the handling, treatment and disposal of MSW in a better economic and more environmentally sustainable way. The study provides a simple framework for selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time taken by the decision-making process.

The paper highlights a new insight into MCDM techniques to select an optimum treatment and disposal technology suitable for MSW management in India. The study identifies a minimal relevant set of evaluation criteria, and appropriate technologies for the handling, treatment, and disposal of MSW in a more economic and environmentally sustainable way.