Manoj Govind Kharat

Modeling landfill site selection using an integrated fuzzy MCDM approach

Landfill site selection is a complex process, which requires the evaluation of multiple criteria. Decision-makers often face difficulties in taking the right decision in a multiple attribute environment. In this paper, an integrated fuzzy-analytical hierarchy process (AHP)–the technique for order preference by similarity to ideal solution (TOPSIS)-based methodology was applied to the municipal solid waste (MSW) landfill site selection problem. To demonstrate the approach taken, a real case of Mumbai city is taken. The model was developed to suit the socio-economic and regulatory set-up. The fuzzy-analytic hierarchy process was used to make pairwise comparisons of criteria to assign weights and rank them, while F-TOPSIS was employed to rank the alternatives. It was found that the fuzzy-AHP–TOPSIS-based methodology can be a powerful guiding tool for MSW management planners. With this modeling approach, the accuracy of landfill site selection procedure can be significantly enhanced as compared to the traditional methods, thereby reducing the cost and time required. The developed methodology helps in representing and analyzing the uncertainty and error in the decision making process of landfill site selection.

Decision support system framework for performance based evaluation and ranking system of carry and forward agents

Purpose – 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. Design/methodology/approach – 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. Findings – 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...

Identification and evaluation of landfill site selection criteria using a hybrid Fuzzy Delphi, Fuzzy AHP and DEMATEL based approach

Landfill site selection is a complex multi-criteria and time consuming process. The present study aims to identify, evaluate, and prioritize the landfill site selection criteria and finally study the relationship between them, and the degree to which they affect or are affected by one another. In the first stage, experts’ opinion was sought to select the relevant criteria and fuzzy Delphi Method (FDM) was employed to obtain the critical factors for selection of landfill sites. Next, the fuzzy Analytic Hierarchy Process (FAHP) was used to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria and to calculate their importance degree. Finally, by considering the interrelationships among the criteria, Decision-making Trial and Evaluation Laboratory (DEMATEL) technique was applied to deal with the importance and causal relationships among them, and to recognize the influential criteria of landfill site selection. Obtained results show that, the criteria of sensitive area and intra-municipality are revealed to be the top two significant influences in selecting landfill sites. By identifying the relevant criteria, the structures and interrelationships, this study can offer an insight for decision makers to understand cause-effect relationships and allow to select suitable sites.

The application of Delphi and AHP method in environmentally conscious solid waste treatment and disposal technology selection

Purpose – 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). Design/methodology/approach – 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. Findings – 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 alterna...

Critical Success Factors for Supplier Development and Buyer Supplier Relationship: Exploratory Factor Analysis

Development of supplier base is becoming mandatory for buyers, as it is not possible to manufacture all components in house, or to search new supplier every time. It is recommended that supplier base of buyer should be self-efficient and developed one to achieve competitive advantages. This development of supplier can be achieved by applying different supplier development practices and buyer supplier relationship practices as per the requirement. In this article, Exploratory Factor analysis (EFA) is applied for grouping the critical success factors with their items by using SPSS software. 6 factors viz., Drivers for Supplier Development Practices, Supplier Development Practices, Buyer supplier Relationship Practices, Buyer supplier Relationship Improvement, Competitive Advantages and Profitability were formed with their respective items. The multi-item scale shows strong evidence of reliability as well as convergent, discriminant validity in a sample. EFA and Reliability Analysis were applied on data for validation of instrument. Data from 87 respondents working in manufacturing sector were used for analysis.

A hybrid life cycle assessment based fuzzy multi-criteria decision making approach for evaluation and selection of an appropriate municipal wastewater treatment technology

Multiple-criteria decision-making (MCDM) has become a main area of research for dealing with complex environmental decision-making problems. In this paper, a hybrid life cycle assessment (LCA) based fuzzy MCDM methodology is developed for the evaluation and selection of appropriate municipal wastewater treatment (WTT) technology based on expert opinion and questionnaires. Further, the study also aims to identify the key evaluation criteria in the process of selecting WTT from a sustainability perspective. The use of fuzzy MCDM in wastewater management has the advantage of rendering subjective and implicit decision-making more objective and analytical, with its ability to accommodate both qualitative and quantitative data. This study provides a systematic approach towards WWT technology selection, in which four-phase procedure is proposed. First, the appropriate technology evaluation and selection criteria were derived from the literature, LCA and experts’ opinion. Next, in the second stage, the fuzzy Delphi method was used to evaluate and screen the critical factors for the evaluation of technology alternatives by interviewing the experts. Twelve criteria including sustainability and those derived from LCA and life cycle costing were obtained consisting of both qualitative and quantitative criteria. In the third stage, the weights of the selection criteria as the measurable indices of the WWT technologies were determined by fuzzy pairwise comparison matrices of analytic hierarchy process. Finally, the fuzzy the technique for order of preference by similarity to ideal solution technique was used for ranking the alternatives. The six most commonly used WWT technologies, viz. sequencing batch reactors (SBR), membrane bioreactor (MBR), moving bed bio-film reactor (MBBR), soil biotechnology, facultative aerated lagoon and activated sludge process were evaluated. The present study is the first study of its kind to develop a hybrid LCA-based fuzzy MCDM methodology for the selection of best WWT alternatives. Results illustrated that advanced technologies, MBR, SBR and MBBR are the preferred options with MBR the most preferred one followed by SBR and MBBR. The developed technology assessment framework enables decision makers to understand the complete evaluation and selection process better and provide a more accurate, effective, and systematic decision support framework. The framework is superior to existing methods since it has the capability of representing vague qualitative data and presenting all possible results with different degrees of membership. The framework developed and applied in this work will help identify appropriate WWT technologies for various decision-making situations faced while managing wastewaters.

Risk analysis in adoption of cloud computing in SMEs - a literature review

This paper presents a systematic literature review, to explore the current key issues related to cloud computing adoption in small medium enterprises SMEs. This is achieved by reviewing 55 articles published about cloud computing adoption in SMEs. Using the grounded review approach, articles are classified into four main categories: Cloud computing; adoption of cloud computing; adoption of cloud computing in SMEs; risk analysis in adoption of cloud computing in SMEs. Then, the four categories are divided into one focus abstract: risk analysis in adoption of cloud computing in SMEs, where the former affects the latter. The results of this review indicate that enterprises face serious problems after implementation of cloud computing with respect to risk. Based on the findings, the paper provides a future research agenda to explore the previously under-investigated areas regarding cloud computing adoption factors and processes. This paper calls for further theoretical, methodological, and empirical contributions to the research area of cloud computing adoption in SMEs. It provides a comprehensive view of insights gained in this area of research through the bibliography.

Structural Equation Modelling of Determinants of Buyer–Supplier Relationship Improvement Strategies: Case of Indian Manufacturing Firms

Recently, many organisations have recognised that development of supplier and buyer relationship improvement is becoming necessary to establish strong and mutually beneficial long-term relationships in improving performance across the supply chain, generating greater cost efficiency and enabling the business to grow and develop. The current study proposes a framework for buyer–supplier relationship improvement (BSRI) strategy and tests the same using structural equation modelling (SEM). Result indicates that BSRI can be improved under the condition of supplier development practices (SDP) and buyer–supplier relationship practices (BSRP). SDP are further driven by productive measure (PM) and competitive pressure (CP), whereas the impact of customer uncertainty (CU) turned out insignificant. The study results demonstrate that profitability (PR) can be improved by achieving competitive advantages (CA) through BSRI. CA includes operational effectiveness, innovation (INV), technology adaption (TAD) and risk minimisation (RIM). A survey response of 512 different manufacturing firms of India was used for data analysis. Initially, exploratory factor analysis (EFA) is performed for exploring the factor followed by confirmatory factor analysis (CFA), for confirmation and construct validity. Findings from the study revealed that linking of SDP with BSRI is necessary from buyer side along with consideration of supplier’s perspective to achieve CA, which will lead towards enhanced PR.

Sustainable evaluation and selection of potential third-party logistics (3PL) providers: An integrated MCDM approach

Purpose 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). Design/methodology/approach 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. Findings 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. Research limitations/implications This study does not investigate the relationships between environmental performances and differentiation advantage from the perspective of 3PLs. Also, sensitivity analysis is not performed. Practical implications 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. Originality/value 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.

A hybrid approach using data envelopment analysis and artificial neural network for optimising 3PL supplier selection

Today third party logistics (3PL) service providers are into almost all the businesses right from providing raw material to packaging. 3PLs are also getting involved in customers concerned with operations. At a suitable price and consideration of all affecting criteria, anything can be outsourced. Any exporter needs to find a smart balance of what to perform in-house and what to hire outside providers to do (i.e., increase verticals and reduce horizontal supply chain operations). Thus, the demand of 3PL provider has become an important issue for organisations seeking quality customer service and cost reduction. The current research presents an integrated data envelopment analysis (DEA) and artificial neural networks (ANN) methodology for the evaluation and selection of 3PL providers. DEA is employed to identify the maximally efficient 3PL and to eliminate the unsuitable ones; and, ANN to rank and make the final selection. The proposed method enables decision makers to better understand the complete evaluation and selection process of 3PL selection. Furthermore, this approach provides a more accurate, effective, and systematic decision support tool for 3PL selection. Finally, an actual industrial application is presented to demonstrate the proposed method.