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Most marketing researchers use rating scales to understand consumer preferences. These have a range of problems, which can be greatly ameliorated by the use of a new technique, best‐worst scaling (BWS). The purpose of this paper is to demonstrate the BWS method by an empirical example, which demonstrates the steps to design and analyze a BW study.

A brief critique of ratings and rankings is presented. Then the basic concept of BWS is described, followed by how to use the BW method to explore how Australian and Israeli consumers choose wine in a retail store. The paper demonstrates the design of the questionnaire as well as the steps to analyze and present the results.

The BWS approach can be easily implemented for research in wine business especially for multicultural comparisons as it avoids scale confounds. After transformation of the best and worst scores of each respondent for each attribute, the data can be analyzed directly using various statistical methods and can be expressed as choice probabilities.

The advantage of BWS is its ability to compare attributes using B−W and B/W scores. The BW method provides a better discrimination of the attributes analyzed.

The simplicity of the analysis and graphical presentation makes a significant contribution to practitioners as the B−W counts and probabilities of attributes are easy to obtain and understand.

This paper presents BWS method in a form that researchers and practitioners can use and adopt for research and market surveys. The paper presents an empirical example using BWS method to determine the importance of wine cues while consumers are choosing wine in a retail store.

The purpose of this paper is to apply a very simple but powerful analysis of the variance‐covariance matrix of individual best‐worst scores to detect which attributes are determining utility components and drive distinct consumer segments.

First an analysis of variance and covariance is used to find attributes which are perceived to have different importance by different consumers and which jointly drive consumer segments. Then we model consumer heterogeneity with Latent Clustering and identify utility dimensions of on‐premise wine purchase behaviour with a principal component analysis.

Four consumer segments were found on the UK on‐premise market, which differ in the relative strength of five wine choice utility dimensions: ease of trial, new experience, restaurant advice, low risk food matching and cognitive choice. These segments are characterised by sociodemographics as well as wine and dine behaviour variables.

Attributes with high variance signal respondents’ disagreement on their importance and indicate the existence of distinctive consumer segments. Attributes jointly driving those segments can be identified by a high covariance. Principal component analysis condenses a small number of behavioural drivers which allow an effective interpretation and targeting of different consumer segments.

This paper's analysis opens new doors for marketing research to a more insightful interpretation of best‐worst data and attitude scales. This information gives marketing managers powerful advice on which attributes they have to focus in order to target different consumer segments.

This is the first study considering individual differences in BW scores to find post hoc segments based on revealed differences in attribute importance.

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.

DEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.

The proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.

The proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.

There is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.

Recent years have witnessed a significant rise in Indian healthcare establishments (HCEs) which indicate that there is a constant need to improve the healthcare quality services through the adoption and implementation of TQM enablers. The purpose of this paper is to identify such enablers and then propose a ranking model for TQM implementation in Indian HCEs for improved performance.

The study identifies 20 TQM enablers through comprehensive literature survey and expert’s opinion, and classifies them into five main categories. The prominence of these enablers is established using a recently developed novel multi-criteria decision making (MCDM) method, i.e. best-worst method (BWM). The importance of the various main category and sub-category enablers is decided on the basis of their weights which are determined by the BWM. In comparison to other MCDM methods, such as analytical hierarchy process, BWM requires relatively lesser comparison data and also provides consistent comparisons which results in both optimal and reliable weights of the enablers considered in this paper. Further, a sensitivity analysis is also carried out to ensure that the ranking (based on the optimal weights) of the various enablers is reliable and robust.

The results of this study reveal that out of five main category enablers, the “leadership-based enablers (E1)” and the “continuous improvement based enablers (E5)” are the most and the least important enablers, respectively. Similarly, among the 20 sub-category enablers, “quality leadership and role of physicians (E14)” and “performing regular survey of customer satisfaction and quality audit (E52)” are the most and the least dominating sub-category enablers, respectively.

This study does not explore the interrelationship between the various TQM enablers and also does not evaluate performance of the various HCEs based on the weights of the enablers.

The priority of the TQM enablers determined in this paper enables decision makers to understand their influence on successful implementation of the TQM principles and policies in HCEs leading to an overall improvement in the system’s performance.

This study identifies the various TQM enablers in HCEs and categorizes them into five main categories and ranks them using the BWM. The findings of this research are quite useful for management of the HCEs to properly understand the relative importance of these enablers so that managers can formulate an effective and efficient strategy for their easy and smooth implementation which is necessary for continuous improvement.

This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran.

To identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied.

First, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers.

The contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.

The number of studies on the use of choice cues in the purchase decision of a smartphone does not appear to be extensive, given the size and rate of growth of the market. Surprisingly, it appears that no study of this type in the Chinese context has been undertaken. Therefore, the purpose of this paper is to fill the existing gap in the marketing literature in this area.

Best–Worst (BW) scaling method was used in the study. It is suggested that the method overcomes some of the biases commonly found in surveys where Likert-type scales are used, and it has superior discriminating power, because respondents are asked to rank the most and the least important factor from a group, and are thereby forced to make tradeoffs between factors.

Among the 13 choice cues, connectivity, price and memory capacity are found to be the most important, whereas recommendation from others, ease of handling and availability of apps are found to be the least important. Findings due to gender, income and age difference were also analyzed and discussed for orderly decision-making purposes.

The ranking of factors showing what choice cues consumers consider most or least important in a particular market helps practitioners to develop appropriate adaptation strategies for the market. The comparison of findings for gender, income and age difference can further help practitioners to devise various alternative marketing strategies for different market segments and identify underserved segments, if any.

The BW scaling method, however, appropriate in ranking order of importance, had never been used in ranking choice cues of smartphone purchase. Moreover, there seems to be a dearth of studies about ranking of choice cues on smartphone purchases in the Chinese context.

Today, the high cost of e-learning systems’ implementation and the difficulty of managing the infrastructures motivate educational institutions toward application of cloud-based e-learning systems. This new system should be aligned with the academics’ aims and pedagogical principles to be beneficial for learners and instructors. Therefore, the vendor selection of learning systems is one of the most important processes to migrate toward cloud-based e-learning. The purpose of this paper is to develop a new framework to facilitate the vendor selection of cloud-based e-learning systems in the cloud market.

To identify the initial criteria as to the vendor selection of cloud-based e-learning services, a literature review is done. To enrich the initial criteria, a focus group of experts is investigated, and the framework developed; then, a survey analysis is conducted to validate the proposed framework. The extracted criteria and sub-criteria are weighted and prioritized using best-worst method (BWM).

The results indicate that the main dimensions of vendor selection framework as regards cloud-based e-learning systems are managerial, technological and pedagogical factors. The rank orders and weights of the mentioned aspects and their sub-criteria are calculated using the BWM.

The proposed framework helps managers to get a big picture of requirements as to cloud-based e-learning and more effectively to select appropriate vendors in this initiative. In the vendor selection process, managers must pay attention to technological issues as well as managerial and pedagogical considerations.

Cloud-based e-learning systems are getting increasingly essential to offer training courses more efficiently in educational institutions. Although the intersection between cloud computing and e-learning has increasingly grown in both practical and academic contexts, there are little studies on how educational institutions and organizations could be able to select appropriate cloud-based e-learning systems. This paper explores the ignored but critically important subject of cloud-based e-learning. The main contribution of this paper is to propose a novel and integrated framework containing the important aspects of vendor selection in cloud-based e-learning services. The proposed framework comprises managerial, technological and pedagogical aspects simultaneously as well as sub-criteria denoting each aspect.

This study focuses on the Critical Success Factors (CSF) for developing sustainable entrepreneurship in the Pakistani telecommunication industry. Despite the efforts made by governments and stakeholders to stimulate sustainable entrepreneurship initiatives, contributions in the telecommunications sector are lacking. Therefore, this study has the major objective of identifying a transformation path for these firms. This is done by providing a theoretical framework for sustainable entrepreneurship in the telecommunications industry, focusing on managerial and operational practices that should be modified according to a set of CSFs identified by experts in Pakistani firms.

This article proposes a novel Multiple Attribute Decision Making (MADM) approach based on Grey Systems Theory (GST) and Best-Worst Method (BWM) while unveiling endogenous relationships among current managerial/operational practices and the CSFs for sustainable entrepreneurship in the telecommunications industry.

CSFs for achieving sustainable entrepreneurship in the Pakistani telecommunications industry were found to rely on a tripod, based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing digital illiteracy, targeting poor communities, helping the young in structuring start-ups.

This article contributes to the MADM research stream by proposing a novel use of the BWM technique based on GST to promote sustainable entrepreneurship CSFs in Pakistani telecommunications firms.

The purpose of this paper is to investigate Spanish consumer preferences for several food-labelling schemes on semi-cured, pasteurised sheep milk cheese. In particular, the authors used three labels regulated by the European Union regulation (European organic logo, protected denomination of origin (PDO) and nutritional fat content), and the remaining four have been introduced to the European food market by private initiatives (local, carbon footprint, food miles and animal welfare).

A Best-Worst Discrete Choice approach was applied in Spain during Fall 2011 by administrating a survey to 549 consumers.

The results suggest that the most valued labels are the PDO, followed by the organic logo and the nutritional panel. The least valued are food-miles labelling and carbon foodprint labels, while local-origin labels and animal welfare are in the middle position.

This study is the first to value consumer preferences for cheese products bearing several public and private European food-labelling schemes since literature on consumer preferences for food labels has only dealt with a comparison of a few (two or at most three) food-labelling schemes. In addition, the added value of this paper is also the use of the BWC approach that has the advantage of providing the best way to discriminate the degree of importance given by respondents to each food labels by overcoming the problem of bias caused by differences in the use of rating scales.

City investment companies (CICs) in China, set up and funded by the government, are playing an important role in the construction of urban infrastructure in China. The purpose of this paper is to analyze the structural risk of diversified project financing of CICs and explore its key influencing factors.

The best worst method (BWM) is used in this study to empirically analyze and quantitatively study the optimization of the structural risk of diversified financing of CICs.

In this study, the structural risk of diversified financing of CICs has been clearly defined, and its key evaluation indexes, including the structure of projects, the structure of financing, asset-liability ratio, earnings before interest and tax margin, the rate of return on capital and the ratio of long-term debt and short-term debt, have been determined. What is more, a comprehensive evaluation system of the structural risk of diversified financing has been established.

This study has established a comprehensive evaluation system of the structural risk of diversified financing. Based on the validated systematic evaluation, comparison and ranking of the structural risk of diversified financing of CICs by using the BWM, the ranking results can help investors to select the CICs with small structural risk of diversified financing to invest.