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The purpose of the paper is to develop a model for the selection of knowledge management system (KMS), in which the assessment criteria are defined and the TOPSIS method with multiple distances in fuzzy environment is proposed.

First, the paper establishes the evaluation criteria from functional, performance and economic aspects. Second, a new TOPSIS method is proposed to deal with the linguistic evaluation information. In the proposed method, in order to eliminate the bias of TOPSIS with single distance, six kinds of distances that are commonly used in TOPSIS including Hamming distance, Euclidean distance, D_p,q distance, Hausdorff distance, L₂ distance and vertex distance are extended in fuzzy environment and employed in the TOPSIS to generate six independent pre-rankings. Afterwards these pre-rankings are combined by Condorcet method to generate the final joint ranking.

Since the final ranking is the collective result, the bias in each single pre-ranking is eliminated and the selection is more objective and accurate. The example shows the proposed model is practical.

The linguistic preferences are given in the single granularity linguistic information.

The proposed model can be applied as a tool for decision makers in the evaluation and selection of KMS.

The paper gives an overall evaluation of KMS and proposes the new TOPSIS method with multiple distances in fuzzy environment.

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 paper develops a decision-making model for supplier selection combining quality function deployment (QFD), analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The efficacy of the model was demonstrated by applying it for supplier selection of lithium ion batteries.

The proposed methodology involved identifying customer requirements for lithium ion batteries and translating them to requisite technical characteristics using QFD. Further, separate sourcing, safety and sustainability-related supplier parameters were proposed taking into account the manufacturer's point of view. The relative weight of each parameter was then calculated using AHP, and finally, TOPSIS was used to select the best supplier.

The proposed methodology was applied to six suppliers of lithium ion batteries, and the obtained results were used to select the most and least preferred suppliers.

The obtained results cannot be generalized and are valid to the case environment. However, the proposed approach can be used for any environment related to supplier selection after capturing the corresponding parameters. The proposed approach does not restrict the number of parameters to be considered.

Many researches related to supplier evaluation are reported in literature, but few studies are available related to supplier performance evaluation for lithium ion batteries using QFD, AHP and TOPSIS. The study will provide a guideline for comparing and selecting supplier on the basis of performance in general and its application to lithium ion batteries in specific.

The purpose of this paper is to utilise a “Wuli-Shili-Renli (WSR)” system approach to create models for complex smart building energy management and evaluate the establishment of a building energy management platform.

The complexity and diversity of the data and demands of the energy management platform mean that it is necessary to analyse comprehensively. This paper uses a WSR system approach to handle, and optimise, the relationship between demands and participants and improve the whole platform. Then, this paper establishes comprehensive evaluation models to analysis the current energy management platforms by using the best integration platform as the baseline.

The WSR conceptual model clarifies the relationship between the elements and elements of the energy management platform clearly and provides the appropriate analytical methods with which to resolve key platform construction issues. The comprehensive evaluation based on a WSR system approach can take into account the systematic effect, so it is more accurate.

The correlation degree between the layers of the energy management platform is rarely reflected.

This paper improves the modelling method used in the WSR system approach and demonstrates that the comprehensive evaluation based on the WSR system approach analyses the energy management platform for public buildings in a synthetic approach.

The purpose of this paper is to assess the role of artifacts in the knowledge management field in the past 18 years (1997-2015) and to identify directions for future research.

The authors conducted a systematic literature review of 101 articles published in seven journals retrieved from EBSCO and Google Scholar online research databases. The framework for analysis included 13 codes, i.e. author(s), title, year of publication, typology, theoretical lens, categorizations, methods for empirical work, relevancy, level of analysis, keywords, findings, research themes and future research directions. Codes were analyzed using qualitative and quantitative methods.

The findings lacked cumulativeness and consistency in the current knowledge management debate. Empirical works outnumbered conceptual contributions by two to one, and the majority of papers focused at the organizational level of analysis. Knowledge management systems, knowledge sharing and digital archives were the major research themes connected to artifacts, together with other closely aligned concepts such as learning and online learning, knowledge transfer and knowledge creation.

This study has temporal and contextual limitations related to covered time span (18 years) and journals’ subscription restrictions.

This paper is a first attempt to systematically review the role of artifacts in knowledge management research and therefore it represents a primary reference in the knowledge management field. It provides directions to future theoretical and empirical studies and suggestions to managerial practices.

In organizations, knowledge intensive activities are mainly task oriented. Finding relevant completed tasks to the new task and providing task-related knowledge to workers facilitate the knowledge reuse. However, relevant tasks are not easily found in the huge amount of completed tasks. The purpose of this paper is to assist the worker to find the required knowledge for the task at hand by reusing the knowledge related to relevant competed tasks.

First, the task profile is constructed. Relevant degrees to categories which tasks to are derived by multi-granularity fuzzy linguistic method. The stages of completed tasks are identified by the modified KNN method. Second, similar completed tasks on categories are retrieved and then the relevant tasks are selected from the retrieved similar tasks by multi-granularity fuzzy linguistic method. Third, the worker’s current task stage is derived by calculating the similarity between the rated knowledge and the knowledge in the stage of completed tasks. Finally, the knowledge is recommend based on stage relevance, relevance of the completed tasks and importance of the knowledge.

The proposed method helps the worker find the knowledge related to the task at hand by finding and reusing the completed tasks. The experimental results show that the proposed method performs well and can fulfill the worker’s’ knowledge needs. The use of the linguistic term set with preferred granularities instead of precise numbers facilitates the expression of the opinions. The recommendation stage by stage makes the knowledge recommended more precisely. The obtained linguistic weight of the knowledge makes the recommended results understood more easily than the numerical values.

In the study, the authors just focus on the codified knowledge recommendation. However, there is another kind of knowledge named tacit knowledge, which exists in the mind of the experts. The constructing and updating of the expert profile can be investigated. Meanwhile, the new recommendation method which considers more factors also needs to be studied further.

The paper includes implications for the development of the knowledge management system. The proposed approach can be applied as a tool of knowledge sharing. It facilitates the finding of the knowledge that is related to the task at hand.

The paper provides new ways to find the relevant tasks and the related knowledge to the task at hand. Meanwhile, the new method to recommend the knowledge stage by stage is also proposed. It expands the research in the knowledge sharing and knowledge recommendation.

This research proposes a text analytics–based framework that examines the utility of online customer reviews in evaluating automobile manufacturers and discovering their consumer-perceived weaknesses.

The proposed framework integrates aspect-level sentiment analysis with the house of quality (HoQ), TOPSIS, Pareto chart and fishbone diagram. While sentiment analysis mines and quantifies review-embedded consumer opinions on various automobile attributes, the integrated HoQ-TOPSIS analyzes the quantified opinions and evaluates the manufacturers. The Pareto charts assist in discovering consumer-perceived weaknesses of the underperforming manufacturers. Finally, the fishbone diagram visually represents the results in the form with which the manufacturing community is acquainted.

The proposed framework is tested on a review data set collected from CarWale, a well-known car portal in India. Selecting five manufacturers from the mid-size car segment, the authors identified the worst-performing one and discovered its weak attributes.

The proposed framework can help the manufacturers in evaluating competitor; identifying consumers' contemporary interests; discovering own and their competitors' weak attributes; assessing the suppliers and sending early warnings; detecting the hazardous defects. It can assist the component suppliers in devising process improvement strategies; improving their customer network; comparing them with competitors. It can support the customers in identifying the best available alternative.

The proposed framework is first of its kind to integrate the sentiment analysis with (1) HoQ-TOPSIS to assess the manufacturers; (2) Pareto chart to discover their weaknesses; (3) fishbone diagram to visually represent the results.

The purpose of this paper is to develop a method for solving the multiple attribute decision-making (MADM) problem in which the decision maker can provide the five types of attribute aspirations, namely: benefit type with requirements; cost type with requirements; interval type; benefit type; and cost type.

First, for each type of attribute aspiration, the calculation formula of utility values of alternative concerning attributes is given. Then, using the calculation formulae, the attribute values are transformed into the corresponding utility values. On the basis of this, the overall ranking value of each alternative is calculated. Further, a ranking order of alternatives can be determined according to the obtained overall ranking values.

Research shows that it is necessary to develop the method for MADM with attribute aspirations. The example shows that the proposed method is applicable.

The proposed method can be applied to the selection of wastewater treatment technologies or other areas.

This paper proposes a new MADM method with multiple types of attribute aspirations. It develops and enriches the existing MADM methods.

Supplier selection is a complex multiple criteria decision (MCDM) problem which directly depends on decision makers’ choice. Some decisions are getting involved with linguistic variables and they are not mathematically operable. To solve a typical decision problem through MCDM techniques, a number or a numerical interval should be defined. The purpose of this paper is to focus on that numerical interval and in a case of supplier selection, the aim is to close the decisions to the real number that the decision maker mentions and this number is in a numerical interval.

The proposed method deals with grey relational analysis (GRA) and develops it by applying triangular fuzzy numbers. The grey numbers have two defined bounds; the proposed method defines two fuzzy bounds for each grey attribute. In the proposed method, the fuzzy membership function has been employed for each bounds of grey attribute to make them to fuzzy bounds with two undefined bounds. Also to make comparison, with employing of TOPSIS technique, both of the grey fuzzy combination decision matrix and the original grey decision matrix are obtained.

The results indicate that, except to the ideal solutions, the grey relation coefficient for each alternative is too close to each other. Indeed, they are too close to zero. Applying the proposed method in problem of supplier selection shows the difference between two selected supplier in proposed method and the original grey method.

As mentioned heretofore this paper aims to make decision makers’s decision more accurate and actually there is no other researches which used this combination method.

In today’s highly competitive business environment, the main approach of all businesses is to optimally provide customers’ requirements and gain their satisfaction and trust. The process of value creation for customers consists of value chain activities which are concentrated on providing maximum level of customers’ needs. The purpose of this paper is to propose a holistic model by which the quality, the transferred value to customers and the firm’s competitive advantage would be improved simultaneously under budget constraint.

This study uses a combination of several quality management (QM) tools including SERVQUAL, Kano’s model, quality function deployment and knapsack problem. Moreover, the triangular fuzzy logic is used throughout the model to address data uncertainty and increase the model flexibility. The proposed model includes five steps which are implemented in the case study of life-insurance services.

The lack of coordination and cooperation between the people working in the inherently related sections leads to incorrect decisions and also the failure in implementation of adopted decisions. Hence, the interface between quality and strategic management should be well considered in organizations. The model generates an integrated vision to the process of decision making in this interface. The framework has several significant outcomes which would be used by both researchers and practitioners.

The study shows that the individual elements of decision-making process in the interface between quality and strategic management are related to each other, recommending the need to coordinated and consistent effort between different parts of a firm. The results are limited by the sample size and geography of the survey.

This paper is among the few in the literature that have presented a holistic and step-by-step approach to the decisions on the intersection between two areas of quality and strategic management, recommending the managers to not have insular look to the issues and try to make a sufficient and efficient relationship between the different sections. This study is an important step in reflecting these relations and the need to create an integrated decision model.