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Focuses on the applications of fuzzy set theory as a tool for the construction of multi‐criteria decision functions from specifications expressed in natural language. Starting with the ability to represent individual criteria satisfactions in terms of membership of fuzzy subsets, shows how different types of linguistic specifications are implemented. Consideration is given to the representation of trade‐offs between criteria, quantifier‐guided aggregations, conditioned criteria and possibilistically qualified criteria.

Neuromarketing, which is an interdisciplinary area, concentrates on evaluating consumers’ cognitive and emotional reactions to different marketing stimuli. In spite of advantages, neuromarketing still requires development and lacks a strong theoretical framework. Techniques that are used in neuromarketing studies have different superiorities and limitations, and thus, there is a need for the evaluation of the relevance of these techniques. The purpose of this study is to introduce a novel integrated approach for the neuromarketing research area.

The proposed approach combines 2-tuple linguistic representation model and data envelopment analysis to obtain the most efficient neuromarketing technique. It is apt to handle information provided by using both linguistic and numerical scales with multiple information sources. Furthermore, it allows managers to deal with heterogeneous information, without loss of information.

The proposed approach indicates that functional magnetic resonance imaging (fMRI) is the best performing neuromarketing technology. Recently, fMRI has been widely used in neuromarketing research. In spite of its high cost, its main superiorities are improved spatial and temporal resolutions. On the other hand, transcranial magnetic stimulation (TMS) and positron emission tomography (PET) are ranked at the bottom because of their poor resolutions and lower willingness of participants.

This paper proposes a common weight data envelopment analysis (DEA)-based decision model to cope with heterogeneous information collected by the experts to determine the best performing neuromarketing technology. The decision procedure enables the decision-makers to handle the problems of loss of information and multi-granularity by using the fusion of 2-tuple linguistic representation model and fuzzy information. Moreover, a DEA-based common weight model does not require subjective experts’ opinions to weight the evaluation criteria.

Presents some factors that influence the design of workplace and worker loading in the process of sewing garments. Researches both existent and suggested work methods in workplace design and worker’s loading, with regard to sewing men’s shirts. The use of the suggested working method enables minimization of measured working time of the analysed technological operation of 21.77 per cent. The estimation, by OVACO working postures analysing system, the OWAS method shows that worker’s loading for a newly designed workplace compared to the suggested working method brings, in principle, advantages for the workers.

The purpose of this paper is threefold: to describe the equity-oriented design of a publicly accessible and openly networked computer-supported collaborative learning (CSCL) initiative that has supported educator discussion about equity topics; to identify design principles for equity-oriented design in open education; and to propose a model for the design of open learning initiatives that are mutually committed to educational equity and educational openness.

This paper draws from design-based research methodology, specifically design narrative and the worked example. The paper is one response to the need for more “designerly work” in the learning sciences, generally, and more specifically in domains such as CSCL.

Four design principles are identified that informed the equity-oriented creation and iteration of the Marginal Syllabus, an open CSCL initiative: leveraging the open web, fostering multi-stakeholder partnerships, working with open content and engaging professional learning as an open practice. This paper also advances the open palimpsests model for equity-oriented design in open education. The model integrates design principles to assist CSCL and open education designers and researchers in creating or iterating projects to be more equity-oriented learning opportunities.

This paper’s design narrative identifies Marginal Syllabus design principles and advances the open palimpsests model for equity-oriented design in open education. The design narrative demonstrates how critical perspectives on the relationship between equity and digital technology can encourage collaboration among diverse project stakeholders, attune to the dynamics of power and agency and respond to the worldly needs of partners and participants.

The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic fuzzy ordered weighted averaging weighted averaging (OWAWA) distance TOPSIS (IFOWAWAD-TOPSIS) method for intuitionistic fuzzy multiple-criteria decision making (MCDM) problems.

Based on the OWAWA operator, the authors develop the intuitionistic fuzzy OWAWA distance measure, then the IFOWAWAD-TOPSIS method is obtained by using the IFOWAWAD and traditional TOPSIS.

The developed IFOWAWAD-TOPSIS method can overcome the drawback of traditional TOPSIS method that cannot consider both the subjective information of attributes and the attitudinal character of decision maker.

Clearly, this paper is devoted to the OWA operator, MCDM and intuitionistic fuzzy theory.

The developed method is applicable in a wide range of situations such as decision-making, statistics, engineering and economics. A numerical example concerning investment selection is given to illustrate the practicability and usefulness of the proposed approach.

This paper fulfils an identified need to study how to make a decision considering both the subjective information of attribute and the attitudinal character of decision maker in intuitionistic fuzzy environment.

There is an increasing interest in the use of knowledge graphs to represent real-world knowledge and a common need to manage imprecise knowledge in many real-world applications. This paper aims to study approaches to solve flexible queries over knowledge graphs.

By introducing fuzzy logic in the query answering process, the authors are able to obtain a novel algorithm to solve flexible queries over knowledge graphs. This approach is implemented in the FUzzy Knowledge Graphs system, a software tool with an intuitive user-graphical interface.

This approach makes it possible to reuse semantic web standards (RDF, SPARQL and OWL 2) and builds a fuzzy layer on top of them. The application to a use case shows that the system can aggregate information in different ways by selecting different fusion operators and adapting to different user needs.

This approach is more general than similar previous works in the literature and provides a specific way to represent the flexible restrictions (using fuzzy OWL 2 datatypes).

The economic effects resulting from the commitment to ISO 9001 certification is a controversial issue. Many authors have concluded about the positive economic effects resulting from the establishment of quality systems in accordance with the requirements established in the ISO 9001 standard, but other authors have not appreciated this positive relationship. The purpose of this paper is to provide a model that facilitates the valuation of the ISO 9001 quality system.

In the process of developing a valuation model, given the uncertainty this process involves, the use of fuzzy math is very useful. First, as for an internal valuation method, the authors highlight the discounted cash flow in a fuzzy environment. The internal valuation will be completed by external expert opinions. To improve the information supplied by experts, the paper makes use of the experton theory. In this context, the authors propose the aggregation of the experts’ opinion by using basic defuzzification distribution (BADD)-fuzzy induced ordered weighted averaging. Finally, the results undergo contra-expertise. After presenting the theoretical model, the authors proceed with its application by using a case study.

The paper develops a new method for the economic evaluation of the ISO 9001 certification.

The authors propose the valuation of ISO 9001 quality management system, and they do it using some interesting tools which fuzzy logic offers. In this way, it is possible to eliminate subjectivity and improve the final results.

There is still little support for the consumer decision‐making process on the web, especially when prices are not the primary property of a product. Reasons for that are complex product specifications as well as often volitional weak interoperability between e‐commerce sites. This paper aims to address this issue.

The semantic web is supposed to make product information more interoperable between different sites. Additionally, some products with limited time frames of availability, like real estates or second‐hand cars, require periodical searches over several days, weeks, or even months. For those kinds of products existing systems cannot be applied. Instant information about new offers on the market is therefore crucial. Wireless access to the web enables services to become instantaneous and to provide up‐to‐date information to users.

This paper presents a framework which is based on multivariate product comparison allowing users to delegate search requests to an agent. The success of the agent depends heavily on the matching algorithm. Fuzzy utility functions and the analytical hierarchy process are a very feasible combination for the scoring of offers.

The proposed system supports users finding products on the web matching specific user preferences and instantly informs them when new items become available on the virtual market. As a specific use case the framework is being applied to the real estate sector, because especially for this sector several shortcomings of the current support have been identified.

Incorporating users’ behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users among which commonly used the triple of attractiveness, examination and satisfaction. Inspired by this fact and considering the psychological definitions of these concepts, this paper aims to propose a novel learning to rank by redefining these concepts. The attractiveness and examination factors could be calculated using a limited subset of information retrieval (IR) features by the random forest algorithm, and then they are combined with each other to predicate the satisfaction factor which is considered as the relevance level.

The attractiveness and examination factors of a given document are usually considered as its perceived relevance and the fast scan of its snippet, respectively. Here, attractiveness and examination factors are regarded as the click-count and the investigation rate, respectively. Also, the satisfaction of a document is supposed to be the same as its relevance level for a given query. This idea is supported by the strong correlation between attractiveness-satisfaction and the examination-satisfaction. Applying random forest algorithm, the attractiveness and examination factors are calculated using a very limited set of the primitive features of query-document pairs. Then, by using the ordered weighted averaging operator, these factors are aggregated to estimate the satisfaction.

Experimental results on MSLR-WEB10K and WCL2R data sets show the superiority of this algorithm over the state-of-the-art ranking algorithms in terms of P@n and NDCG criteria. The enhancement is more noticeable in top-ranked items which are reviewed more by the users.

This paper proposes a novel learning to rank based on the redefinition of major building blocks of the CMs which are the attractiveness, examination and satisfactory. It proposes a method to use a very limited number of selected IR features to estimate the attractiveness and examination factors and then combines these factors to predicate the satisfactory which is regarded as the relevance level of a document with respect to a given query.

With the emerging technologies, collecting and processing data about the behaviors of customers or employees in a specific location has become possible. The purpose of this paper is to evaluate existing data collection technologies.

Technology evaluation problem is handled as a multi-criteria decision-making (MCDM) problem. In this manner, a decision model containing four criteria and eight sub-criteria and four alternatives are formed. The problem is solved using hesitant analytic hierarchy process (AHP) and trapezoidal fuzzy numbers (TrFN).

The results show that the most important sub-criteria are: accuracy, quantity, ıntrospective and cost. Decision makers’ evaluate for alternatives, namely wireless fidelity (WiFi), camera, radio-frequency identification and Bluetooth. The best alternative is found as Bluetooth which is followed by WiFi and Camera.

Technology evaluation problem, just like many other MCDM problems are solved using expert evaluations. Thus, the generalizability of the findings is low.

In this paper, technology selection problem has been handled using hesitant AHP for the first time. In addition, the original methodology is extended by using TrFN to represent the expert evaluations in a better way.