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Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered. This paper compiles Multi-criteria decision-making (MCDM) studies related to automotive industry. We applied a Systematic Literature Review on MCDM studies published until 2015 to identify patterns on MCDM applications to design vehicles more fuel efficient in order to achieve full compliance with energy efficiency guidelines (e.g., Inovar-Auto). From 339 papers, 45 papers have been identified as describing some MCDM technique and correlation to automotive industry. We classified the most common MCDM technique and application in the automotive industry. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainties in the data was also observed. Despite the maturity in the use of MCDM in several areas of knowledge, and intensive use in the automotive industry, none of them are directly linked to car design for energy efficiency. Analytic Hierarchy Process was identified as the common technique applied in the automotive industry.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

In the recent dynamic market, supply chain disruptions are rapidly increasing with varied customer demand, technological changes, uncertain pandemic events etc. To overcome the unexpected disruptions, supply chain of each business should be resilient and pharmaceutical supply chain (PSC) is no exception. Motivated by the challenges and unexpected pandemic disruptions, this paper aims to examine the performance indicators (PIs) of the resilient PSC and to predict the resilience level for a certain time period in the context of Bangladesh.

The aim of this paper presents a structured framework based on the Delphi method, fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and system dynamics (SD). The proposed methodology was validated using expert's inputs from the relevant field in Bangladesh. This study reveals the influential relationships of indicators and resilience level using fuzzy DEMATEL and SD to improve the resiliency.

Findings revealed that “Supply chain risk orientation”, “Visibility”, “Flexibility”, “Agility in supply chain” and “Collaboration” are the top five influential performance indicators for resilient PSC. The cause and effect relationship found that “IT capability”, “Flexibility”, “Supply chain network design”, “Resource availability”, “Supply chain risk orientation” and “Velocity” were in cause category which play a vital role for establishing resilient supply chain. SD approach has developed a model for predicting the resilience level of the supply chain.

This work is one of the initial contributions in the literature that has targeted on the identification and analysis of the significant PIs and predicting the resilience level of the PSC.

The objective of this study is to investigate the barriers hindering the integration of lean manufacturing (LM) practices within the furniture industry of Bangladesh. The traditional operational paradigms in this sector have posed substantial challenges to the effective implementation of LM. In this study, the barriers of implementing LM in the furniture business are examined, aiming to provide a systematic understanding of the barriers that must be addressed for a successful transition.

The research reveals that “Fragmented Industry Structure,” “Resistance to Lean Practices” and “Inadequate Plant Layout and Maintenance”, emerged as the foremost barriers to LM implementation in the furniture industry. Additionally, “Insufficient Expert Management,” “Limited Technical Resources” and “Lack of Capital Investment” play significant roles.

The outcomes of this study provide valuable insights into the furniture industry, enabling the development of strategies for effective LM implementation. One notable challenge in lean implementation is the tendency to revert to established practices when confronted with barriers. Therefore, this transition necessitates informed guidance and leadership. In addition to addressing these internal challenges, the scope of lean implementation should be broadened.

This study represents one of the initial efforts to systematically identify and assess the barriers to LM implementation within the furniture industry of Bangladesh, contributing to the emerging body of knowledge in this area.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.