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Multi-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research.

This study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights.

The findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas.

The data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases.

This study contributes to extant H&T literature by identifying the most prolific and influential countries, journals, publications and trends by applying MCDM techniques in H&T research, and elucidating the implications and characteristics of MCDM techniques in H&T research.

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.

The work on bridge resilience assessment includes quantitative and qualitative approaches to compare the multiple bridges based on their resilience. But still, the bridge resilience obtained by these assessment approaches is inefficient when prioritising multiple bridges to improve their resilience. Therefore, this study aims to develop a methodology for prioritising the bridges to improve their resilience.

The research methodology follows three sequential phases. In the first phase, criteria importance through intercriteria correlation (CRITIC) technique is used to compute the criteria weights. The criteria considered are age, area, design high flood level, finish road level FRL and resilience index of bridges. While 12 river-crossing bridges maintained by one bridge owner are considered as alternatives. Then, in the second phase, the prioritisation of each bridge is evaluated using five techniques, including technique for order of preference by similarity to ideal solution, VIKOR (in Serbian, Visekriterijumska Optimizacija I Kompromisno Resenje), additive ratio assessment, complex proportional assessment and multi-objective optimisation method by ratio analysis. Finally, in the third phase, the results of all five techniques are integrated using CRITIC and the weighted sum method.

The result of the study enables bridge owners to deal with the particular bridge that requires resilience improvement. The study concluded that it is not enough to consider only the bridge resilience index to improve its resilience. The prioritisation exercise should consider various other criteria that are not preferred during the bridge resilience assessment process.

The proposed methodology is a novel framework based on the existing multi-criteria decision-making (MCDM) techniques for contributing knowledge in the domain of bridge resilience management. It can efficiently overcome the pitfall of decision-making when two bridges have the same resilience index score.

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

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.

The purpose of this paper is to develop a systematic approach to extract users’ feelings and emotions about their experiences in hospitals from online reviews and rank the places using multi-criteria decision making (MCDM) techniques based on the aggregated sentiment score.

The proposed model used a linguistic approach to extract the sentiment words from the free text. It used term frequency-inverse document frequency values to represent features of various places in bag-of-words format. Sentiment dictionary is used to calculate senti-scores. It used different MCDM techniques like simple additive weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods for ranking hospitals based on their aggregated senti-score.

Statistical correlation analysis between the rankings of places reveals that the TOPSIS method is the most suitable ranking technique among other MCDM techniques. By improving the senti-score, one can bring their enterprise to the top position.

Data set is collected from different websites like Twitter, Facebook, etc., for various services/features. Moderate amount of reviews are collected for each place. But not all users give their views on the social media websites. It would be essential to collect responses from all the customers who avail different services at different places.

The sentiment analysis model proposed in this paper enables B2C and C2C commerce. Business may take suitable measures to overcome their issues/problems raised by the consumer. Consumers can share and educate other consumers about their experiences.

The development of internet has strong influence in all types of industries like healthcare. The availability of internet has changed the way of accessing the information and sharing their experience with others. This paper recognizes the use and impact of social media on the healthcare industry by analyzing the users’ feelings expressed in the form of free text. A suitable decision-making technique is applied to rank the places, which enables the users to plan their treatment place in a better way.

The paper develops a novel approach by applying the TOPSIS method to rank the different alternative places of the healthcare industry by using the senti-score derived from the users’ feelings, emotions and experiences expressed in the form of free text.

This study aims to focus on sustainable supplier selection in a construction company considering a new multi-criteria decision-making (MCDM) method based on dominance-based rough set analysis. The inclusion of sustainability concept in industrial supply chains has started gaining momentum due to increased environmental protection awareness and social obligations. The selection of sustainable suppliers marks the first step toward accomplishing this objective. The problem of selecting the right suppliers fulfilling the sustainable requirements is a major MCDM problem since various conflicting factors are underplay in the selection process. The decision-makers are often confronted with inconsistent situations forcing them to make imprecise and vague decisions.

This paper presents a new method based on dominance-based rough sets for the selection of right suppliers based on sustainable performance criteria relying on the triple bottom line approach. The method applied has its distinct advantages by providing more transparency in dealing with the preference information provided by the decision-makers and is thus found to be more intuitive and appealing as a performance measurement tool.

The technique is easy to apply using “jrank” software package and devises results in the form of decision rules and ranking that further assist the decision-makers in making an informed decision that increases credibility in the decision-making process.

The novelty of this study of its kind is that uses the dominance-based rough set approach for a sustainable supplier selection process.

The purpose of this study is to evaluate the performance of the Champions League teams using the entropy-integrated Multi Attribute Ideal-Real Comparative Analysis (MAIRCA) and super-slack-based data envelopment analysis for the 2012–2022 period.

This study consists of two sections. First, this study uses the entropy-integrated MAIRCA approach, which is a novel multi-criteria decision-making (MCDM) technique developed by Gigović, to measure the performance of Champions League clubs. Second, this study proceeds with the super-slack-based DEA to evaluate the efficiency of the Champions League clubs.

As per the empirical results, Real Madrid is found to be the best-performing club over the past 10 years in terms of financial and sportive performance. Over the analyzed period, teams from the five Major Leagues of Europe perform better.

To the best of the authors’ knowledge, performance measurement studies in football have focused on either DEA or MCDM. This study aims to present novelty for football literature by evaluating holistically both the sportive and financial dimensions. This paper also analyzes Champions League teams from the perspective of both MCDM and super-slack-based DEA methods.

Social media platform, like Twitter, has increasingly become the mode of reporting civic issues owing to their vast and fast reachability. A tremendous amount of information on urban issues is shared every moment out of which some tweets may need immediate attention to save lives or avoid future disasters. Existing approaches are only limited to the identification of complaint tweets; however, its prioritization based on urgency is still unexplored. This study aims to decide the ranking of complaints based on its criticality derived using multiple parameters, like type of complaint, season, day or night, gender, holiday or working day, etc.

The approach proposes an ensemble of multi-class classification (MCC) and “two-level” multi-criteria decision-making (MCDM) algorithms, like AHP and TOPSIS, to evaluate the accurate ranking score of the tweet based on the severity of the issue. Initially, the MCC is applied to tweets to categorize the tweets into three categories, i.e. moderate, urgent and immediate. Further, the first level of MCDM algorithm decides the ranking within each complaint type, and the second level evaluates the ranking across all types. Integration of MCC and MCDM methods further helps to increase the accuracy of the result.

The paper discusses various parameters and investigates how their combination plays a significant role in deciding the priority of complaints. It successfully demonstrates that MCDM techniques are helpful in generating the ranking score of tweets based on various criteria.

This paper fulfills an identified need to prioritize the complaint tweet which helps the local government to take time-bound actions and save a life.

Proposing a fuzzy multi-criteria decision making (MCDM) algorithm that is able to incorporate the heterogeneousness effect of DM group into the decision process, in order to determine the best remotely operated vehicle (ROV) design alternative to manufacture and developing a practical decision aid tool based on this algorithm. The paper aims to discuss these issues.

An algorithm utilizes fuzzy AHP Buckley’s approach for modeling heterogeneousness of the DM group, fuzzy AHP Chang’s extent analysis to calculate the priority values of criteria and Chen’s fuzzy TOPSIS for ranking the alternatives and finally group working technique for initiation issues is developed. MATLAB is used to implement the algorithm and generate a decision aid tool. Real life application and sensitivity analysis is performed by the help of generated tool. Literature and background explanations are also provided.

A MCDM algorithm that incorporates the heterogeneousness effect of the DM group into the decision process is introduced. Sensitivity analysis suggested the independence of the final result from DM group and criteria set. A practical decision aid tool is generated for ROV manufacturing companies.

A computerized MCDM aid tool that incorporates heterogeneousness of the DM group into the decision process is generated. Tool let ROV manufacturing companies to evaluate ROV design alternatives with respect to qualitative and quantitative criteria and determine proper choice.

Determination of the proper ROV design alternative to manufacture gap within the literature filled with an algorithm that provides more reliable results due to its incorporation the heterogeneousness of the DM group into the decision process characteristic. A practical decision aid tool is generated.