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This paper aims to analyze the interaction among the major variables of reverse logistics seen in automobile industries.

In this research, interpretive structural modeling (ISM) has been used to understand mutual influences among identified variables of reverse logistics. The advantage of the ISM methodology is that variables can be categorized depending upon their driving power and dependence.

Regulations make it mandatory for automobile companies to own responsibility of products manufactured throughout their life cycle by collecting and reusing products, reducing volume of waste generated, increasing the use of recycled materials, etc. For example, End-of-Life Vehicle Directive had directed manufacturers to take back their vehicles at the end of their usefulness and responsibly dispose them. In this research, regulation has appeared at bottom of the ISM model, indicating that it has high driving power to influence other variables. Also, financial limitations are a significant inhibitor faced by the top management for implementing reverse logistics programs.

The ISM methodology relies upon expert opinions for developing contextual relation among identified variables. Thus, an expert’s knowledge, his familiarity with industry and its operations may have affected the final results of the ISM model. One of research implications of this study is that variables identified in this ISM model are quite generic, and thus, with marginal adjustments, these can be used in the context of any other supply chain for increasing its productivity and performance.

The ISM model reveals that regulations affect a significant number of enabler variables of reverse logistics like support of policy entrepreneurs, green purchasing by companies, information and communication technologies that are seen at the upper level of ISM. This indicates that regulations force companies to be proactive towards product recovery actions that lead to initiation of reverse logistics programs by them.

This research has tried to analyze the interaction among the major variables of reverse logistics typically seen in automobile industries which could be useful to logistics managers for taking strategic-level decisions.

Re-use of products in the supply chain has become a significant consideration in the last decade. It has resulted in the development of several product recovery alternatives. Remanufacturing in the supply chain is one such product recovery option that yields social, economic and environmental benefits. This study aims is to identify and evaluate the key performance indicators (KPIs) of the remanufacturing supply chain (RSC).

The KPIs of RSC are classified along with the five primary management processes (plan, source, make, deliver and return) of the supply chain operations reference (SCOR) model. A grey decision-making trial and evaluation laboratory (DEMATEL) technique is applied to investigate the complex interrelationships amongst the identified KPIs and categorize them into cause and effect group. The applicability of the proposed framework is demonstrated through a case organization involved in remanufacturing business.

The KPIs are identified based on literature analysis and subsequent discussion with decision panel experts. The present research work results reveal that “consumer awareness program”, “technological compatibility” and skilled workforce' are the most influential indicators.

This research work provides a framework to evaluate the causal relationship between the RSC KPIs. The framework proposed in this study is empirically applied to a case organization. Based on the study findings some important recommendations are presented to the decision-makers/policy planners to help them develop an action plan. This would help the case organization reduce resource consumption, increase market share and enable sustainable development.

Reverse logistics has attracted many industries due to product recalls, enormous waste generation, competitive reasons, vast opportunity in the waste management market, and to get the maximum value out of waste recovery. Selection of the right implementation strategy is vital for reverse logistics to function efficiently. Therefore, this research aims to evaluate the criteria for selecting reverse logistics strategy and help to choose the preferred strategy for its implementation.

Three reverse logistics implementation strategies, namely, in-house, joint venture and outsourcing, are proposed. A novel hybrid fuzzy analytical hierarchy process (F-AHP) and fuzzy measurement of alternatives and ranking according to COmpromise Solution (F-MARCOS) based framework is developed to fulfil the research objective. A survey is performed on Indian manufacturing industry to demonstrate the applicability of the proposed framework.

The result shows that government policy and regulations, reverse logistics risks and reduced emission have prime importance for a manufacturing industry which needs to implement reverse logistics into its supply chain. Outsourcing is the preferred reverse logistics strategy followed by joint venture and in-house that a manufacturing firm in India can implement.

The research results are based on the responses of the survey received. This research considers various industry sectors to test the applicability of the framework. However, for actual implementation, this survey must first be limited to a particular industry as the results will apply to that industrial sector only.

This developed framework simplifies the procedure of selecting the strategy when the industry needs to implement reverse logistics. For industries working with a smaller set of criteria, this framework is a powerful and dynamic approach for reducing and choosing the most pertinent one that helps accomplish their objectives of reverse logistics implementation strategy selection.

Based on the literature and current applicability of reverse logistics, this research proposes three models to implement reverse logistics in Indian industries. A novel hybrid F-AHP and F-MARCOS based framework is developed to handle the selection of suitable reverse logistics strategy.

The aim of this analysis is to review the Indian manufacturing organizations practicing Lean Six Sigma (LSS) tools/techniques with an objective of monitoring the performance of an organization and to develop recommendation for strategies to benchmark organizational operational efficiency.

This study offers insights of the LSS performance measurement aspects of the Indian manufacturing organizations based on Data envelopment analysis (DEA) approach. The five inputs and two outputs are considered on the basis of literature review and discussed with the practitioners.

In this analysis, the relative efficiency score of 18 Indian manufacturing organizations has been determined in order to assist evaluation of the impact of monetary investment on the outputs. The present analysis not only investigates the optimum level of input variables but also lays down a significant observation that an organization having higher profit and inventory turnover ratio is not necessarily an efficient organization.

The results assist to determine the best practice units, potential source of inefficiency and deliver beneficial data for the consistent enhancement of the operational efficiency. The DEA results assist managers and decision makers to derive appropriate strategies to enhance their performance with reference to the efficient organization and to regard it as their role model.

This analysis renders a DEA based framework of LSS practicing Indian manufacturing organizations. The framework is unique in terms of its input-outputs variable selection and measurement procedure.

The purpose of this paper is to investigate capacity coordination in services supply chain (SSC). It provides discussion and application of various contracts in a two-stage single period SSC.

This paper considers a two-stage serial supply chain with demand uncertainty and price insensitivity. A model is developed to represent a global IT SSC incorporating services specific factors like over-capacity cost and higher degree of substitution resulting in flexibility to meet unplanned demand. At first, centralized and competitive solutions of the model are studied. Then, the paper studies coordination in this supply chain using some of widely used contract templates.

This paper finds several key insights for the researchers and practitioners in this area around adverse impact of over-capacity cost on demand, positive effect of delivery team’s exposure to market on contracting terms and better understanding of efficient frontiers for selected contracting mechanism.

This paper has limited its analysis to three key and most widely used contracts and made assumptions about risk-neutrality of the firms. Future research can study other contracting templates and/or relax for the model as laid out in this paper.

An automated software agent can be built leveraging the closed form equations developed here to help decide on optimal capacity investment and devise coordinating contracts.

This paper established that because of higher degree of substitution, perishability and non-trivial over-capacity cost, SSC behave bit differently than the physical goods supply chain and coordination of participating firms needs to be studied in a services specific context for improving system-wide performance.

India is in the process to achieve an important place in $2,000bn global food trade. In order to achieve this goal, there is a need to develop a food safety system which is well written down in line with international practices that are highly coordinated based on self-compliance to assure consumer protection. Accordingly, many organizations undergo assessment of their food safety system to verify compliance internally as well as externally. The purpose of this paper is to provide insight on the critical factors and benefits by evaluating the food safety assessment practices.

A questionnaire-based survey is conducted among 96 Indian food business operators and regulators involved in assessment practices to obtain critical factors for the assessment of food safety practices. The questionnaire captures indicators for motivations or challenges and benefits of food safety assessment to identify critical factors using exploratory factor analysis. Model for the food safety assessment practices was developed based on multiple regression analysis by determining the impact of factors on the benefits of food safety assessment.

This paper identifies four factors responsible for assessing food safety practices, namely, business-centric approach, legislative needs, technical practices and organization resentment as a combination of reasons and challenges along with two benefits risk: protection and organization reinforcement. The regression analysis indicates that the organization reinforcement gets positively impacted by business and technical practices and negatively by organization resentment. Risk protection has a significant relationship with legislative needs.

This is the first attempt to systematically explore the factors around the assessment of food safety practices in India. This study provides inputs for the practical application of managers and regulators.

Lean Six Sigma (LSS) is receiving a tremendous attention as a modern process of streaming to improve the organizational ability and customer satisfaction. A successful LSS implementation is influenced by various factors and the execution of all the influencing factors simultaneously is a very difficult task for any organization. From the perspective of limitation of resources, this paper aims to present a basic issue in an LSS implementation of clustering complex and impacting factors into groups to achieve them in a stepwise manner. This paper aims to present a fundamental issue of clustering the complex and impacting factors of an LSS implementation into groups to achieve them stepwise.

A total of 40 relevant influencing factors toward an LSS implementation have been identified from the extensive literature review and duly validated with experts’ opinions. Integrated fuzzy set theory and decision-making trial and evaluation laboratory (DEMATEL) approach are demonstrated to explore the causal relationships among influencing factors of the LSS implementation. An empirical case analysis of an Indian manufacturing organization is carried out to illustrate the utilization of the proposed model.

The proposed framework effectively finds out the significance of each influencing factor of an LSS implementation and clustered into cause–effect groups. As per the results of the empirical case analysis, ten critical success factors (CSFs) of the LSS implementation are evaluated for the successful LSS implementation. Top management pays more attention to achieve them and implement them in a phase-wise approach under the limitations of accessible resources.

The presented framework provides an effective, precise and systematic decision support tool for recognizing CSFs of the LSS implementation. The organization, decision-makers, industrial practitioners and academic researchers may be able to comprehend the cause–effect relationship of the influencing factors of the LSS implementation. The exploratory nature and the single case study are two major limitations of this analysis. The developed model is heavily dependent on the experts’ opinions; hence, any bias in judgment will influence the final result.

This analysis is the first of its kind of effort, according to the best of the authors’ knowledge, to classify the influencing factors of LSS implementation into the cause–effect cluster. The outcomes of this analysis make the complexity of a problem easier in handling and assisting the decision-making.

The purpose of this paper is to examine and introduce comprehensive insights into the field of Lean Six Sigma (LSS) by reviewing the existing literature and identifying the research gap. The state of LSS research is assessed by critically examining the field, along with a number of dimensions, including time horizon, year, journal and publisher, university, country, author, geographic analysis, research design, research affairs, research methods, tools/techniques used, focus industries, major research area, benefits gained by LSS, critical success factors and barriers of LSS implementation.

This paper is based on a systematic literature review of 190 articles containing the word LSS in their title, which are published in a well-known database, such as Elsevier ScienceDirect, Taylor and Francis, Emerald Full Text, Springer Link, Wiley InterScience and Inderscience from January 2000 to September 2016.

This analysis reveals 15 significant dimensions to identify the state of LSS research. Authors find a noticeable rise in the attention of LSS research in the available literature. Major findings show that, the empirical research holds greater credibility. Statistics prove that the case study method scores the highest among all the research methods used in the discipline. The largest number of studies have investigated research issues related to implementation and process of LSS. The LSS uses a wide range of tools/techniques/methodologies: the choice of tools is situation-specific. Manufacturing and health-care sectors have been the focus of LSS research, but LSS has also been adopted by other types of industries. The organizations following LSS have improved bottom-line results, improved company profitability and growth and enhanced customer satisfaction. In general the research is more interpretive in nature; there is still a lack of standard in the LSS implementation framework.

This study is limited to reviewing those articles which contain the word LSS appeared in the title.

This study will help understand the current state of research on LSS, various trends in the field, its applicability and future prospects of investigation in the field.

The purpose of this paper is to develop the balance score card (BSC) approach based Lean Six Sigma (LSS) performance measurement system and investigate the critical measures currently practiced by Indian manufacturing organizations.

This study offers insights of LSS performance measurement from manufacturing industry. Initially, the BSC-based framework is developed to recognize the adoption of LSS performance measures. Then, the framework is applied to nine Indian manufacturing organizations to assess the LSS performance measure practice.

The BSC-based framework of LSS performance evaluation for manufacturing industry is formulated. Then, adoption of these LSS performance measures is investigated with nine Indian manufacturing organizations. The result indicates significant variability in terms of practicing level of LSS measures. However, the majority of organizations are more sensitive to the customer perspectives.

This study reveals a background as to why the performance measurement is required for the success of LSS and for providing practical guidelines for designing performance metrics. The framework interrelates and captures various LSS perspectives and indicator measures, and furnishes a comprehensive outlook of the organization for strategic analysis. This study provides BSC-based template for performing the benchmarking study. This analysis may serve as a reference point for manufacturing organization to determine their system weaknesses, and assist them to concentrate on their most vital and suitable criteria and objectives. However, the analysis contributes to the knowledge on LSS performance measurement system and catches differences in theory and practice, paving the approach to newer research.

This study renders an industry-oriented LSS performance measurement practical approach and suggests the easily adopted vital performance measures for different manufacturing organizations.

The ever-widening competitive global markets demand food business to demonstrate safe food supplies across the world. The causes of food borne illness are complex to determine and require a careful evaluation of all stages of food supply chain and food safety practices. The purpose of this paper is to systematically investigate the factors responsible for the assessment of food supply chain and evaluation of food safety system in India.

The study utilizes a combination of qualitative and quantitative approach by exploring expert’s opinion systematically using a semi-structured interview followed by careful grouping of responses using the grounded theory approach to build the research theme. The prioritization of the critical factors is carried out using Pareto analysis. The methodological review was carried out to identify factors and categorize them based on their impact on hierarchical logical relationship using total interpretive structural modeling approach to determine the enablers.

This paper attempts to deliver an inimitable list of seven vital factors for the effective design of evaluation system for food safety practices. The study provides a careful insight on the issue pertaining to designing of assessment system including competence building for assessor and availability of well-defined technical protocol. The recommendation for developing a robust food safety inspection system by implementing stricter regulation, enhancing competence and design initiatives is provided.

The study provides a unique list of factors for the assessment of food safety practices and develops the relationship. Food safety assessment is an integral part of food safety study which is systematically explored and conceptualized in this paper. The study is carried out using the opinion of Indian experts.