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This paper aims to introduce a hierarchical fuzzy system for an online review analysis named FLORA. FLORA enables tourists to decide their destination without reading numerous reviews from experienced tourists. It summarizes reviews and visualizes them through a hierarchical structure. The visualization does not only present overall quality of an accommodation, but it also presents the condition of the bed, hospitality of the front desk receptionist and much more in a snap.

FLORA is a complete system which acquires online reviews, analyzes sentiments, computes feature scores and summarizes results in a hierarchical view. FLORA is designed to use an overall score, rated by real tourists as a baseline for accuracy comparison. The accuracy of FLORA has achieved by a novel sentiment analysis process (as part of a knowledge acquisition engine) based on semantic analysis and a novel rating technique, called hierarchical fuzzy calculation, in the knowledge inference engine.

The performance comparison of FLORA against related work has been assessed in two aspects. The first aspect focuses on review analysis with binary format representation. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, is achieved with the highest values in precision, recall and F-measure. The second aspect looks at review analysis with a five-point rating scale rating by comparing with one of the most advanced research methods, called fuzzy domain ontology. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, returns the closest results to the tourist-defined rating.

This research advances knowledge of online review analysis by contributing a novel sentiment analysis process and a novel rating technique. The FLORA system has two limitations. First, the reviews are based on individual expression, which is an arbitrary distinction and not always grammatically correct. Consequently, some opinions may not be extracted because the context free grammar rules are insufficient. Second, natural languages evolve and diversify all the time. Many emerging words or phrases, including idioms, proverbs and slang, are often used in online reviews. Thus, those words or phrases need to be manually updated in the knowledge base.

This research contributes to the tourism business and assists travelers by introducing comprehensive and easy to understand information about each accommodation to travelers. Although the FLORA system was originally designed and tested with accommodation reviews, it can also be used with reviews of any products or services by updating data in the knowledge base. Thus, businesses, which have online reviews for their products or services, can benefit from the FLORA system.

This research proposes a FLORA system which analyzes sentiments from online reviews, computes feature scores and summarizes results in a hierarchical view. Moreover, this work is able to use the overall score, rated by real tourists, as a baseline for accuracy comparison. The main theoretical implication is a novel sentiment analysis process based on semantic analysis and a novel rating technique called hierarchical fuzzy calculation.

The objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision.

The paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered.

Use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems.

The proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective.

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.

In this paper, fuzzy hierarchical analysis (FHA) is used to explore the process by which the criteria weights of the Taiwan National Quality Award (TNQA) are assigned by TNQA committee members. Each member is allowed to employ fuzzy scales in place of exact scales. Each pairwise comparison of criteria is made through a questionnaire from each TNQA committee member. The membership function of trapezoidal fuzzy numbers is introduced to specify TNQA committee members’ intentions. After FHA, the reasonable range of each criterion weight of TNQA is determined. The current criteria weights of TNQA are properly verified.

The purpose of this paper is to identify, model, analyze and prioritize the barriers in implementing sustainable practices in rubber products manufacturing industry in Kerala, a state in South India. This research provides a more reliable quantitative measure of association of the barriers in the implementation of sustainable practices in the rubber products manufacturing sector.

Interpretive structural modeling (ISM) is used to develop the hierarchical relationships among the barriers in the implementation of sustainable supply chain practices in the rubber products manufacturing sector. The hierarchical structure among the barriers is framed using the experts’ opinion. Cross-impact matrix multiplication applied to the classification (MICMAC) analysis is integrated with the output of ISM to classify the barriers into different categories based on the driving power and the dependence power. The driving power and the dependence power of the barriers obtained from ISM constitute two criteria for prioritizing the barriers. The change management required is considered as the third criterion. The fuzzy-analytic hierarchy process (F-AHP) methodology is adopted to prioritize the barriers based on these three criteria.

The hierarchical relationship obtained through ISM methodology shows that lack of government initiatives and lack of benchmark on sustainability measurement in Indian conditions are the major barriers in implementing sustainable practices in the rubber products manufacturing sector. These barriers lead to the lack of management commitment for the implementation of sustainable practices in the organizations under study. The prioritization obtained through the F-AHP method suggests that lack of top-level management commitment, lack of motivation, lack of government initiatives and high initial cost of implementation are some of the major barriers in implementing sustainable practices in the organizations.

In the application of the ISM methodology, the contextual relationship between the barriers specified by the experts and their preferences may involve bias. Another limitation of this research is that the modeling and prioritization of the barriers are executed based on the opinion of experts from rubber product manufacturing companies in one state only.

To the best knowledge of the authors, this research is the first study on the identification and prioritization of the barriers in sustainable supply chain implementation in the rubber products manufacturing sector. Modeling the inter-relationship among the barriers using ISM technique and prioritizing the barriers using F-AHP are the novel features of the contributions of this work.

Risk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.

In order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.

Initially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.

The findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.

This study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.

This study has two purposes. The first is to identify the determinants influencing the selection of a container number recognition system via a quantitative method to thereby establish an evaluation structure. The second purpose is to conduct an empirical study to determine the weights of the criteria and alternatives.

The exploratory factor analysis (EFA) and fuzzy analytic hierarchy process (AHP) were applied to determine the evaluation structure and weights of the criteria and alternatives, respectively.

An empirical study based on a dedicated terminal at Keelung Port is conducted. The result demonstrates that the radio-frequency identification (RFID) system is a suitable system for the terminal under consideration in this study.

The value of this study is twofold. First, EFA was applied to extract common factors from a wide questionnaire survey, thereby establishing a hierarchical analysis structure. This method and comprehensive evaluation structure are useful references for both practitioners and researchers to deal with problems of gate automation. Second, fuzzy AHP was used to decide the weights of the hierarchical structure. The weights obtained by this method are more objective and rational as the imprecision expressions in returned samples have been considered and dealt with.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

The gradual ageing of global population has necessitated the creation of conducive and supportive food and beverage environments for older adults. This study identifies the key evaluation criteria for senior-friendly restaurants and examines the importance of each criterion.

This study uses the fuzzy analytic hierarchy process (FAHP) to synthesis the key evaluation criteria for senior-friendly restaurants and analyses the weights of these criteria. It identifies and prioritises four main criteria and twenty sub-criteria in the hierarchical framework by employing the sophisticated approach.

The results indicate that the main criteria ranked by importance are “barrier-free environment”, “food quality”, “service quality” and “corporate social responsibility (CSR)”. There are five most important sub-criteria, such as “simple and intuitive use” and “perceptible information” belonging to the main criterion “barrier-free environment”, “hygiene and safety” and “food freshness” belonging to the main criterion “food quality” and “assurance” belonging to “service quality”. Incorporating the analytical findings, this study suggests the key evaluation criteria to facilitate the construction and development of senior-friendly restaurants.

The precisely hierarchical model and key criteria proposed in this study provide clear guidelines for managers of senior-friendly restaurants to develop feasible strategies and also contribute to the theoretical development of food-friendly environments and services for elderly consumers.

The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers.

First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model.

The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers.

Future studies are suggested to design models having fuzzy constraints such as budget and resources. Moreover, for future studies, non-linear membership functions can be used.

Actual projects are provided from the Turkish IS company for prioritizing process and a hypothetical mathematical model is demonstrated using illustrative data.

This study contributes to the relevant literature by proposing a comprehensive model considering many conflicting ideas of decision makers on quantitative and qualitative criteria, and evaluating projects in an integrated way including FAHP and FMOLP.