Multiattribute Models Research Articles

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

This paper reflects the results of research analyzing models of multi-attribute decision-making based on fuzzy preference relations. Questions of constructing the corresponding multi-attribute models to deal with quantitative information concomitantly with qualitative information based on experts’ knowledge are considered. Human preferences may be represented within the fuzzy preference relations and by applying diverse other preference formats. Considering this, so-called transformation functions reduce any preference format to fuzzy preference relations. This paper’s results can be applied independently or as part of a general approach to solving a wide class of problems with fuzzy coefficients, as well as within the framework of a general scheme of multi-criteria decision-making under conditions of uncertainty. The considered techniques for fuzzy preference modeling are directed at assessing, comparing, choosing, prioritizing, and/or ordering alternatives. These techniques have served to develop a computing system for multi-attribute decision-making. It has been implemented in the C# programming language, utilizing the “.NET” framework. The computing system allows one to represent decision-makers’ preferences in one of five preference formats. These formats and quantitative estimates are reduced to nonreciprocal fuzzy preference relations, providing homogeneous preference information for decision procedures. This paper’s results have a general character and were applied to analyze power engineering problems.

A simulation approach to investigate factors influencing the cost of omitted objectives in multiattribute models

AbstractEmpirical evidence suggests that decision‐makers are ill‐equipped to identify all relevant objectives in a decision problem. We examine the effect of an incomplete set of objectives using a Monte Carlo simulation to compare a baseline model to a reduced model incorporating only a subset of objectives. We assess the performance of reduced models varying in the number of objectives, the number of alternatives, the correlations among objectives, and attribute weights. Results suggest that missing objectives will most impact multiattribute models with negative correlations between objectives; similarly, models with equally weighted objectives suffer more than models with unequal weights. Decision problems with more objectives tend to be less impacted by missing objectives, given the same proportion of missing objectives. In contrast, decision problems with more alternatives are more impacted for some performance measures but less on others. However, the variation in model performance due to the number of objectives and alternatives is relatively minor compared to the variation due to the nature of the correlation between objectives.

The dynamics in asymmetric effects of multi-attributes on customer satisfaction: evidence from COVID-19

Purpose This study aims to explore how the “new normal” induces the dynamics in the asymmetric relationship between service quality attributes and customer satisfaction. Design/methodology/approach This study analyzes online reviews for hotels in New York City. The authors use multi-attribute models to examine how a situational factor – the COVID-19 outbreak – creates dynamics in the asymmetric effect of service quality attributes on customer satisfaction. Then, the authors examine the change in these dynamics over time after adjusting to the “new normal.” Findings The COVID-19 pandemic has introduced dynamics into the asymmetrical relationship between hotel service attribute performances and customer satisfaction. The pandemic magnified the asymmetric influences of particular attributes on satisfaction in the hospitality industry. In addition, the findings indicate the changes in such dynamics over time. Practical implications The findings emphasize that hotel managers should consider situational factors when understanding customer satisfaction. Particularly, this study suggests developing tailored strategies for responses during the COVID-19 pandemic. Hotel managers need to address changing customer expectations of service attributes to overcome unprecedented difficulties because of the limitations and new needs imposed during the pandemic. Originality/value This study contributes to the hospitality literature with an understanding of the significance of situational factors in asymmetric analysis.

Switzerland? The Best Choice for Accommodation in Europe for Skiing in the 2023 Season

The study investigates the connections between tourists‘ hotel preferences and distance from resort expressed in meters, distance from ski lift expressed in meters, booking score, number of reviews, room type, feature of free cancellation, price expressed in Euro, type (private host/hotel), destination (ski-to-door access/travel sustainable property) from 10 highly appreciated European ski locations offered in from February 2023 by Booking, using a sustainable, electronic instrument for collecting and analyzing a large amount of data, Octoparse 8 and a multi-attribute decision model. Previous studies concerning tourist preferences and online behavior used traditional methods, such as questionnaires and surveys, being limited to a certain number of questions and respondents; thus, this study covers a research gap in the literature with regard to the use of a large amount of data, electronic instruments and multi-attribute models to rank the hotel locations, which derives from the difficulty in obtaining the necessary data to carry out an in-depth analysis. The results show that when selecting a hotel location from an exclusive ski resort, the tourists are interested in the number of reviews, the price and the distances from the resorts to the ski slopes, while the booking score is less important. This is translated into practical implications for marketers and hotel managers, presented at the end of the paper.

코로나19 팬데믹 시대의 복지태도 변화

This study aims to confirm the changing in the welfare attitude of generations in the COVID-19 pandemic era. This study set 8 factors as explanatory variables based on the tri-component attitude model and multi-attribute models and then estimated latent classes by generation. Data from the ‘National Survey of Tax and Benefits’in 2019 and 2020 were used in this study. The latent classes derived were (1)double-attitude, (2)welfare expansion-opposing, (3)welfare-actively supporting, (4)public welfare expansion-supporting, and (5)public welfare expansion-actively supporting. A new type of double-attitude problem was identified in the latent class. It was found that there was a clue to firmly maintain a welfare-actively supporting latent class. It was also found that there was a driving force to support the welfare state in the baby boomers, Generation X, and Generation MZ. However, the welfare attitude toward the welfare state has somewhat retreated in the era of the COVID-19 pandemic. This suggests the need for reconsideration of welfare expansion.

BAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimization

Multi-attribute decision analysis is an approach to decision support in which decision alternatives are evaluated by multi-criteria models. An advanced feature of decision support models is the possibility to search for new alternatives that satisfy certain conditions. This task is important for practical decision support; however, the related work on generating alternatives for qualitative multi-attribute decision models is quite scarce. In this paper, we introduce Bayesian Alternative Generator for Decision Support Models (BAG-DSM), a method to address the problem of generating alternatives. More specifically, given a multi-attribute hierarchical model and an alternative representing the initial state, the goal is to generate alternatives that demand the least change in the provided alternative to obtain a desirable outcome. The brute force approach has exponential time complexity and has prohibitively long execution times, even for moderately sized models. BAG-DSM avoids these problems by using a Bayesian optimization approach adapted to qualitative DEX models. BAG-DSM was extensively evaluated and compared to a baseline method on 43 different DEX decision models with varying complexity, e.g., different depth and attribute importance. The comparison was performed with respect to: the time to obtain the first appropriate alternative, the number of generated alternatives, and the number of attribute changes required to reach the generated alternatives. BAG-DSM outperforms the baseline in all of the experiments by a large margin. Additionally, the evaluation confirms BAG-DSM’s suitability for the task, i.e., on average, it generates at least one appropriate alternative within two seconds. The relation between the depth of the multi-attribute hierarchical models—a parameter that increases the search space exponentially—and the time to obtaining the first appropriate alternative was linear and not exponential, by which BAG-DSM’s scalability is empirically confirmed.

Analysis of consumer behavior in buying instant noodles (case studies in the Bogor City Area)

This research aims to find out the main attributes consumers consider in instant noodle purchases, and to know their attitudes and behaviors.The data source in this study was obtained from 167 respondents in Bogor City Area.Statistical analysis used in this study includes analysis of multi-attribute models of fishbein, subjective norms and Theory of reasoned action. The result of fishbein analysis is as follows four most important evaluation attribute is the number of flavor variations of 1.56, then ease of obtaining products, product halalness and quick/practical in serving with scores of 1.53, 1.42 and 1.35 respectively.The smallest evaluation value is given to the gift-giving attribute in the sale of 0.59 packs.This illustrates that respondents consider promotional attributes in the form of gifts less important than other attributes.However, the score is still in an important category. From the behavioral model it appears that of the four brands analyzed having a value of B ~ BI positive (greater than zero) this means the consumer behavior for the above brands is good or positive.Indomie has the largest value of 30.58 compared to other brands describing the attitude of consumers inclined to make purchases against larger Indomie.Keywords: Consumer Behavior, Fishbein Analysis, Instant Noodles, Subjective Norm Analysis, Theory of Reasoned Action

CONSUMERS’ GENERAL BUYING BEHAVIOR OF CONSUMER SERVICES

The content and peculiarities of consumer perception of works and services in the sphere of trade are analyzed. Determining the essence of perception before and after the purchase process, as well as in the consumption process. The model start of consumer behavior of buyers in the market of goods and services is analyzed. Special attention is paid to the formation of loyalty and commitment to the trade enterprise and its products among consumers.Identify the causes of the decline in the performance of marketing tools as they are adequate and effective in practice today. The ways of finding new ways and means of increasing the efficiency of business processes in the sphere of trade and profitability of enterprises are shown.Research on consumer behavior of end consumers is a key prerequisite for building their loyalty to the enterprise itself and the products they offer. The highest degree of loyalty should be considered the status of a supporter, a regular buyer. Forming a contingent of buyers is better than attracting new ones because it is less costly in terms of financing marketing efforts and more profitable. Of course, it is necessary to separately study the behavior of buyers before and during the purchase process and the behavior after purchase, and further generalize the results. Perception at the point of purchase should be considered in terms of multi-attribute models of goods and services.

Acquisition of human capital for organizational sustainability: A BASS-SIR forecasting approach

We investigated the probabilities of acquisition of requisite human capital by new entrants in the institutional network. Graph theories applied in complex social networks using multi-attribute decision models were employed for our study. We coupled the dynamical and complexities of social network analysis with BASS-SIR epidemiological model to ascertain sustainability in the light of internal and external forces in the human capital acquisition. The results show that a new entrant’s ability to acquire human capital within the network increases rapidly and reaches a steady state by the third month. The fractional analysis indicated that a combined effect of internal and external injection of knowledge into the network sees entrants acquiring the required knowledge and work world skills in a relatively shorter time. Finally, the discrete and continuous analyses revealed that relatively even and continuous patterns of information flow reduce the time of reaching a steady state in the industry. We recommend a strong policy on continuous and even rates of training, a high rate of information flow such as internal and external training with the emphasis on internal training systems to gain competitive advantage.

Implementation of Value-based Pricing for Medicines

Value-based pricing (VBP) is well established in markets for common goods and services, but wide consensus on VBP for pharmaceuticals is lacking. In principle, VBP implies that prices are mainly driven by a drug's value (value for money) and that the impact on budget (sustainability) is a second-order driver of price regulation. Although the literature provides descriptive analyses on regulations governing medicine price negotiation, there are few insights on whether and how price negotiation regulations have been implemented. The goal of this article was to cover this information gap for 5 European countries and the United States. VBP has been applied according to two models: (1) direct models in which cost-effectiveness is a driver; and (2) indirect, multi-attribute models characterized by greater discretion on the integration between the different value domains and the evaluation of consistency between costs and value. In these models, cost-effectiveness is not a driver. In addition, it is hard to evaluate within these models the actual implementation of VBP. Identifying whether and how VBP is applied requires a clear predefined link between added value and the premium price, as well as transparency in the way added value is converted into a premium price. In general, for these countries, it remains difficult to determine whether pricing is mostly driven by value (value-for-money) or impact on budget (sustainability). In instances in which thresholds on the incremental cost-effectiveness ratio are used, it becomes easier to understand whether VBP has been implemented. If VBP relies on a multi-criteria approach, greater transparency on which criteria have been used to assess a new drug and how they have been converted into a reasonable price may help in understanding whether a value-based approach has been used.

Integrated method combining analytical and mathematical models for the evaluation and optimization of sustainable supply chains: A Brazilian case study

Studies on the measurement and evaluation of sustainability are fundamental requirements in sustainable supply chain management. Herein, the development of an integrated method for evaluating the sustainability of an oil and gas supply chain is proposed. A method defined as sustainability evaluation and optimization is a combination of analytical and mathematical models. The analytical hierarchy process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEE) are implemented in multi-attribute models. Preemptive goal programming is used in the multi-objective method. Experiments are conducted with the data from a Brazilian oil and gas company. The results demonstrate sustainability performance from 2009 to 2017, with its best performance in 2011. Based on the AHP, experts determined that the environmental parameters are more relevant than the social aspects. Thus, the optimization proposed using the mathematical model to direct spending to the more important parameters for achieving sustainability. Among the environmental factors, the optimization directs expenses toward production/operation and recovery of degraded areas, whereas among the social parameters, it directs expenses toward external social projects. This study contributes to a hybrid model for decision-making that can be replicated in other companies. As a suggestion, this can be combined with other techniques of analytical and mathematical models. A stochastic simulation can also be used to analyze the performance of organizations.

Participation of Women in Logistics Through Innovation

This article relates relevant aspects of business: logistics, innovation, female participation and multicriteria models. One issue that is paying close attention is the participation of women in different social spheres, including business. On the other hand, logistics is related to practically all areas of an organization, which can be visualized, when studying it supported, in the Logistics Model Based on Positions (MoLoBaC). There are other models that interest this work, such as multicriteria models, in particular the multiattribute models with multiplicative factors (MMcFm). Also, companies maintain and prosper thanks to their ability to manage innovation. The confluence of these four fields of knowledge generates the general objective of this research: Use of the different areas of the logistics model based on positions to measure, through a multiattribute model, the female participation in logistics, having as a thread the innovation processes.

Entropy-Based Risk Control of Geological Disasters in Mountain Tunnels under Uncertain Environments.

Uncertainty is one of the main sources of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in the existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value () can better reflect the psychological behaviour of decision-makers. Thirdly, common multi-attribute decision-making models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

Understanding important hotel attributes from the consumer perspective over time

Consumers consider various product attributes when they evaluate products. Researchers and practitioners have used multi-attribute models to understand which product attributes are important for consumers. However, in those models, product attributes are limited and are determined by researchers at the time of the inquiry. In this study, using a longitudinal study of hotel reviews over 6 years, the top 30 important hotel attributes from the perspective of consumers are identified and examined as to how the importance of these hotel attributes has changed over time. Our findings show that staff is the most important attribute with a positive effect on ratings at all times and that other attributes show consistent positive (negative) effects with small changes of importance over the years. Our study provides managerial implications of what attributes hotel managers need to maintain or improve for customer satisfaction.

Multi Stakeholders' Attitudes toward Bt rice in Southwest, Iran: Application of TPB and Multi Attribute Models.

Organisms that have been genetically engineered and modified (GM) are referred to as genetically modified organisms (GMOs). Bt crops are plants that have been genetically modified to produce certain proteins from the soil bacteria Bacillus thuringiensis (Bt), which makes these plants resistant to certain lepidopteran and coleopteran species. Genetically Modified (GM) rice was produced in 2006 by Iranian researchers from Tarom Mowla'ii and has since been called 'Bt rice'. As rice is an important source of food for over 3billion inhabitants on Earth, this study aims to use a correlational survey in order to shed light on the predicting factors relating to the extent of stakeholders' behavioral intentions towards Bt rice. It is assumed and the results confirm that "attitudes toward GM crops" can be used as a bridge in the Attitude Model and the Behavioral Intention Model in order to establish an integrated model. To this end, a case study was made of the Southwest part of Iran in order to verify this research model. This study also revealed that as a part of the integrated research framework in the Behavior Intention Model both constructs of attitude and the subjective norm of the respondents serve as the predicting factors of stakeholders' intentions of working with Bt rice. In addition, the Attitude Model, as the other part of the integrated research framework, showed that the stakeholders' attitudes toward Bt rice can only be determined by the perceived benefits (e.g. positive outcomes) of Bt rice.

From Single Commodity to Multiattribute Models for Locomotive Optimization: A Comparison of Optimal Integer Programming and Approximate Dynamic Programming

We present a general optimization framework for locomotive models that captures different levels of detail, ranging from single and multicommodity flow models that can be solved using commercial integer programming solvers, to a much more detailed multiattribute model that we solve using approximate dynamic programming (ADP). Both models have been successfully implemented at Norfolk Southern for different planning applications. We use these models, presented using a common notational framework, to demonstrate the scope of different modeling and algorithmic strategies, all of which add value to the locomotive planning problem. We demonstrate how ADP can be used for both deterministic and stochastic models that capture locomotives and trains at a very high level of detail.

UMA REVISÃO DE TRÊS PACOTES DE SOFTWARE DEDICADOS A PROBLEMAS MULTIATRIBUTO

In this work we outline and make a critical discussion of three software packages dedicated to multiattribute models, based on a learning oriented paradigm and involving in its development researchers of INESC-Coimbra. Namely, VIP-Analysis Dias and Clímaco 2000) based on the additive model in order to aggregate value functions, but just requiring imprecise information on the scale coefficients; the IRIS system (Interactive Robustness analysis and parameters Inference for multicriteria Sorting problems - Dias e Mousseau, 2003) dedicated to the sorting problematic, according to a pre-defined set of categories, based on the ELECTRE TRI (Yu 1992), but not requiring the decision maker to fix precise values for all parameters of the method; and, finally , an web interface, called “MATRIX”, for a base of methods including: : Simple Additive Weighting and TOPSIS (Yoon and Hwang, 1995), VIKOR (Duckstein and Opricovic, 1980), ELECTRE I (Benayoun et al., 1966; Roy, 1968), ELECTRE III (Roy, 1978), ELECTRE IV (Roy and Hugonnard, 1982), ELECTRE TRI (Yu, 1992) e AHP (Saaty, 1980).

The Main Factors Influencing the Destination Choice, Satisfaction and the Loyalty of Ski Resorts Customers in the Context of Different Research Approaches

The paper summarizes scientific approaches to researches in the field of destination choice, satisfaction and the loyalty of ski resorts customers. Information about existing models and trends from scientific journals are analysed. Multiattribute models are widely used in researches dealing with satisfaction and loyalty. It can be presumed that tourist overall satisfaction is determined by destination image and attribute satisfaction. Tourist attribute satisfaction is also directly influenced by destination image, and destination loyalty is in turn influenced by overall satisfaction. The results will be useful for researchers and practitioners who deal with tourist satisfaction and loyalty in particular for ski resorts operators. This paper represents the initial phase of the project aimed at researching the topical factors with their relationships and links influencing satisfaction and loyalty of ski resort customers in selected countries.

Student assignment involving perceptual mapping via multidimensional scaling and multi-attribute models

Research shows that college students are deficient in statistical skills. There is a need today for the development of learning tools that can help students overcome their anxiety of statistical applications. This study seeks to respond to that need by describing a student assignment involving multivariate statistics. The assignment integrates aspects of perceptual mapping via multidimensional scaling and multi-attribute models. A feedback questionnaire revealed that the assignment was well-received by students and successful in increasing their knowledge of statistics. Students felt the assignment did increase their knowledge of perceptual maps, multi-attribute models, and multidimensional scaling. Students showed an interest in learning more about statistics and marketing research. Since the assignment increased the student's interest in statistics and willingness to learn and use statistics, findings suggest that the students anxiety regarding statistics was reduced.

Does customer service matter? A customer perception of bank services in Islamic countries

This paper aims to explore the possible usefulness of a combined multi-attribute and SERVQUAL service quality model in analyzing how bank customers perceive service quality. Using a survey, the authors measured how customers in one region in a major Saudi Arabia bank perceived service quality. Responses were analyzed with reference to both multi-attribute service quality and SERVQUAL models. The combined model seems to provide some guidance regarding how bank customers perceive service quality. The finding of several items reveals that customers are difficult to please. However, substantial heterogeneity exists in customer perceptions of the service quality items investigated. This exploratory study examines only one bank in specific region in Saudi Arabia, implying a need for additional research applying this combined model and other methods to investigate banking segment. The noticeable spread in conceptions of service quality items suggests that bank managers and personal bankers may benefit from co-creating services with customers. Banks are considered as intermediates on financial markets. Therefore, improved and customized service quality could make customers inclined to invest their resources in ways that promote economic growth. In addition to traditional measurement models, the SERVQUAL may contribute to service quality assessment in private banking.