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The present situation of COVID-19 pandemic has put the health-care systems under tremendous stress and stringent tests for their ability to offer expected quality of health-care services, as it decides the sustainability and growth of health-care service providers. This study aims to deliver a quantitative framework for service quality assessment in the health-care industry by classifying the health-care service quality parameters into four balanced scorecard (BSC) perspectives.

To determine the service quality for the Indian health-care system, decision-making trial and evaluation laboratory and analytical network process are integrated in a fuzzy environment to contemplate the interaction among BSC perspectives and respective performance measures.

The results indicate “internal processes” perspective assumes the key role within BSC perspectives, while performance measures “nursing staff turnover” and “staff training” play the key roles. The results also signify that “patient satisfaction” is the most vital issue and can be strongly influenced by measures belonging to the “learning and growth” perspective. In “learning and growth” perspective, “staff training” is the most decisive criteria, very highly influencing “patient satisfaction”, highly influencing “profitability,” “change of cost per patient (both in and out patients)” and “outpatient waiting time” while moderately influencing “staff satisfaction,” “bed occupancy” and “nursing staff turnover”. Moreover, “staff training” criteria have a positive influence on “nursing staff turnover.”

The contributions of this study are in two folds in the domain of quantification of service quality for the health-care system. First, it delivers an assessment framework for Indian health-care service quality. Second, it demonstrates an application of the framework for a case situation and validates the proposed framework.

The Indian manufacturing sector currently contributes 16–17% to gross domestic product (GDP) and gives employment to around 12% (2014) of the country's workforce. Among the various initiatives planned under Atma Nirbhar Bharat and “Make in India”, the Indian government aims to increase the share of the manufacturing sector to country's GDP to 25% by 2025. To ensure sustainable growth of the Indian manufacturing industries in global market, successful and implementation of strategies such as lean manufacturing, green manufacturing along with six sigma are crucial. This research aims at identification and analysis of barriers to successful implementation of integrated Lean Green Six Sigma (LG&SS) strategies.

Based on an evaluative literature review and expert's opinion, this research identifies 18 barriers to lean, green and six sigma implementation in the manufacturing industry in India. The inter-relationships among the barriers is identified using an integrated approach of ISM (interpretive structural modelling) and Fuzzy Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC).

ISM helps to derive key managerial insights and implementation plan based on the identified inter-relationships among the barriers. Fuzzy MICMAC analysis classifies the barriers into four categories, namely, autonomous, driver, dependent and linkage to understand their relative impact on the implementation of LG&SS practices in the Indian manufacturing industry. “Lack of cooperation and mutual trust between management and employees”, “The scarcity of time and work pressure”, “lack of continuous improvement work culture” and “lack of cooperation from suppliers” that forms the top most level of the model. “Weak legislation” is a highly significant barrier to LG&SS implementation in the Indian manufacturing industries.

It is expected that the findings of this research will help the Indian manufacturing industry to derive a sustainable competitive advantage through an effective implementation of LG&SS practices.

This study can be seen as the first attempt in investigating barriers to successful implementation of lean, green and six sigma strategies in the Indian manufacturing industries using ISM and fuzzy MICMAC analysis.

Risk management in defence aircraft industry has considerable interest among academics and practitioners. The purpose of this paper is to develop interactions among risk factors dimensions (RFDs) and inspect the importance relationship among the performance measures in Indian aircraft industry and, finally, understand the effect of involvements provided by the managerial team on risk reduction process.

An extensive literature review was carried out to identify 26 risk parameters and 13 performance measure indices relevant for an aircraft industry. Survey method was used to obtain the importance of these parameters and measures. Further, these factors are grouped into five risk dimensions based on the brain storming session by the project managers. Initially, Risk factors for defense aircraft industry (RFDs) analyzed by Interpretative structural model (ISM) to know the contextual relationship among the RFDs and then applied Interpretive ranking process (IRP) to inspect the pre-eminence relationship among them. Finally, SD is applied to understand the effect of involvements provided by the managerial team on risk reduction process.

Government policy and legal RFDs has emerged as the key driving RFDs. In IRP modelling, technology RFD has emerged as more influential RFD which is the more relevant factor with respect to performance measure indices and this result is supported by detailed sensitivity analysis of system dynamic model.

The outcomes of this research can help project management team to identify the high severity risk factors which need immediate risk reduction/mitigation action.

Improved performance in operational (lean) and environmental (green) dimensions has been extremely critical to the global competitiveness of organizations. As the performance of small- and medium-sized enterprises (SMEs) is influenced by various external and internal factors, the purpose of this paper is to analyze the lean–green performance of Indian manufacturing SMEs by investigating the influential relationships of various factors along with the set of lean and green practices adopted by the firms.

The study employs a holistic approach by integrating multiple case study and data envelopment analysis (DEA) in eight manufacturing SMEs to verify a set of five propositions relating issues such as organizational factors, quality and environmental management certifications, implementation of lean and green practices with operational and environmental performance in Indian SMEs. Within-case analysis and cross-case analysis are used for a qualitative investigation of cases while DEA with four input variables, two desirable output variables and one undesirable output variable, is used for quantitative investigation with returns to scale (RTS) and damages to scale (DTS) analysis.

The RTS/DTS results suggest that Indian SMEs exhibit decreasing RTS and increasing DTS, implying that they need to decrease their operational sizes in order to improve the operational and environmental performance. The possible alternative and more practical strategy could be to introduce new technology innovation and holistic adoption of manufacturing excellence initiatives such as lean and green.

The research findings provide insights into the lean and green performance enhancement approach in the context of SMEs. The study extends key managerial implications and policy-related guidelines.

The purpose of this paper is to apply a multi-criteria decision-making (MCDM) framework to evaluate distribution strategies for an e-tailer. An application of MCDM method, the hybrid DANP–VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model, is used for e-tailers’ distribution strategy evaluation. The choice of distribution strategies under various dimensions is evaluated.

The authors used a hybrid MCDM model to solve the decision-making framework, which combines Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based analytic network process and VIKOR method. Data were collected from the experts (e-tail manager, logistics manager, operations manager and distribution center (DC) manager) using two questionnaires, first for the influential relationship among the criteria and dimensions and second for a performance rating of each alternative (distribution strategies) against each criterion.

DANP with VIKOR method prioritizes the distribution strategies in the following order: DC shipment, drop shipment, click and collect, store shipment and click and reserve. Performance gap was calculated based on the VIKOR method to provide distribution strategies to an e-tailer under different situations. The authors infer that in developing country, product characteristics and transportation have a major influence on deciding the distribution strategy.

Decision-making framework will provide e-tail mangers a knowledge-based understanding to select the distribution strategy under the different situations related to the performance, product, e-tailer and external characteristics for smooth order fulfillment process. The insights developed by this research provide a framework for rational decision making in distribution strategy selection in e-business.

This is the first kind of a study which offers a decision framework for e-tail managers on how to choose distribution strategies under different situations which are related to the performance, product, e-tailer and external characteristics.

There is limited literature linking e-fulfillment and product type with postpurchase consumer behavior measures like loyalty, even though there has been a rapid increase in e-tailing. E-fulfillment is defined in literature as a sequence of processes. Each process in this sequence is expected to have a different impact on consumer loyalty across product type. Thus relative importance of e-fulfillment processes leading to consumer loyalty. The purpose of this study is to investigate the impact of e-fulfillment on consumer loyalty across two product types: “standard, regular” and “physical product” (e.g. book, clothing, etc.) and “standard, nonregular” and “physical product” (e.g. computer, refrigerator, etc.) using the peak-end rule theory for an e-tailer.

To know the consumer loyalty for e-fulfillment across the two product types, the partial least square-structural equation modeling approach aided by the SmartPLS 3 tool was used for data analysis as it avoids biases in the parameter estimation in regression analysis. A total of 603 consumer responses through an online and physically administered questionnaire were obtained and were used for the empirical analysis.

Results indicate that for standard, nonregular and physical products, all the e-fulfillment components (customization strategy, website quality, distribution strategy, last mile delivery and return management) positively impact consumer loyalty. Except for the customization strategy, for standard regular and physical product types, all other e-fulfillment components positively impact consumer loyalty.

This study will be helpful to e-tail managers to configure the e-fulfillment components according to product types, thereby increasing consumer loyalty.

While some e-fulfillment components have been linked to consumer loyalty in literature, there is no study establishing linkages between e-fulfillment as a construct and consumer loyalty across product types. This has implications for decision makers in e-tail as the study provides e-fulfillment strategy customization across product types for achieving consumer loyalty in e-tail, a key marketing metric.

The purpose of this paper is to identify the key performance factors that can lead toward sustainability in the Industry 4.0 supply chains of manufacturing industries.

Questionnaire is used to collect the data from manufacturing sector to prioritize the factors, which integrates both Industry 4.0 and sustainability. For this, stepwise weight assessment ratio analysis (SWARA) method is used to obtain the weights for criteria and sub-criteria to prioritize the factors.

The present study brings the findings about five key performance factors. Social factor needs much attention among all the criteria, followed by ecological, economic, information technology and dynamic capability theory. Further, change management, third-party audits and novel business models are key sub-factors to improve performance of sustainability in Industry 4.0 supply chains.

This study prioritized the performance factors of Industry 4.0 and sustainable supply chain in Indian manufacturing sector. These prioritized factors help to improve performance of organizations, which are practicing the Industry 4.0 and sustainability practices. Managers in manufacturing industries can use the SWARA for assessment of weights for the criteria and sub-criteria factors to take appropriate decisions to improve the organizations’ performance.

Managers in manufacturing industry can use these prioritized factors to improve the performance of their supply chains.

The food supply chain is exposed to severe environmental and social issues with serious economic consequences. The identification and assessment of risk involved in the food supply chain can help to overcome these challenges. In response, the purpose of this paper is to develop a risk assessment framework for a typical food supply chain.

An integrated methodology of grey analytical hierarchy process and grey technique for order preference by similarity to the ideal solution is proposed for developing a comprehensive risk index. The opinion of the experts is used to illustrate an application of the proposed methodology for the risk assessment of the food supply chain in India.

Valuable insights and recommendations are drawn from the results, which are helpful to the practitioners working at strategic and tactical levels in the food supply chain for minimising the supply chain disruptions.

The risk quantification for the case organisation is primarily based on inputs collected from the experts working for Indian food supply chain, and so the generalisation of the results is limited to the context of developing countries. However, the generalisability of the proposed risk quantification methodology and key insights developed in the food supply chain will assist practitioners in policy making.

The risk priorities established by this research would enable an implementation of systematic risk mitigation strategies and deployment of necessary resources for leveraging the efficiency of food supply chain.

Specifically, this research has delivered a risk quantification framework and strengthened the inquiry of risk management for the food supply chain.

The purpose of this paper is to apply the Six Sigma DMAIC methodology in order to reduce the rejections experienced in the manufacturing of the doors belonging to a telecommunication cabinet.

The process involved joining of sheet metal and hinge using welding operations with the help of a fixture. The methodology used is the structured DMAIC method in order to identify the root cause for the rejections and solve it.

The paper provides insights about the identification of the root cause for the defects and the solution to overcome it, and also the benefits that were obtained as a result of the application of the solution.

This methodology has been applied to the variation observed in the dimensions of a particular component to be welded with a main part. This approach can be used to find such dimensional variations.

This study has been successfully carried out in a medium-scale industry which has total quality management in practice.

Six Sigma DMAIC was necessary for the identification and reduction of the defects which arose in the sheet metal and welding operations, and had to be resolved in order to increase the bottom-line.

The purpose of this paper is to investigate into the improvement strategies for lead time reduction of military aircraft major overhaul (enhance the overhaul task from present seven to nine-plus aircrafts as agreed to customer) for ABC Company.

This research has been conducted based on the available knowledge and extensive experience gained while working in the overhaul unit of the case organization for a long period of time. The research employs an integrated approach of multi-criteria decision method (in specific analytic hierarchy process (AHP)), theory of constraint (TOC) and simulation for M/M/1/K queuing environment for investigating the improvement strategies for lead time reduction in major overhaul of military aircraft. This has mainly included: Step 1: analysis of existing activity network using actual overhaul data; Step 2: ranking of constraint activities that most affects the lead time using AHP; Step 3: revised flow activity network using time buffers (TBs) concept of TOC; Step 4: mathematical model formulation for effective utilization of TB using single server finite queuing approach (M/M/1/K queuing environment); Step 5: discrete event simulation representing present overhaul conditions and revised overhaul conditions with different scenarios; and Step 6: sensitivity analysis and interpretation of results. The proposed methodology has been tested on an industrial case study dealing with an aircraft overhaul in India (namely ABC Company).

The proposed overhaul lead-time reduction plan points out the augmentation of resources in order to achieve more than 50 per cent reduction in lead time and waiting time under two scenarios – with overtime and without overtime.

An integrated approach proposed has so far been applicable to the specific aircrafts (Jaguar/Mirage/Kiran) of the ABC Company overhaul division. However, the particular methodology can be proved potentially useful and highly practical when applying to other aircraft types.

The results indicate several problems with the current overhaul strategies that need focused process improvements and a need for capacity augmentation for achieving the enhanced overhaul task of nine+ aircrafts per year with reduced overhaul lead time. The proposed approach also provides the maintenance planners with a platform for decision analysis and support often ignored the capacity augmentation.