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Owing to the importance of the portfolio problem in modern financial investment fields, the aim of this paper is to rank and choose suitable stocks in stock markets under vague environment.

Many new principles and methods have been introduced to help the investor to decide which stocks are worth to be chosen. In real word, people prefer to express their attributes by using linguistic terms, so the used data are often imprecise and vague. In this paper, the second method of constrained fuzzy analysis hierarchy process (CFAHP) is used to evaluate the relative weights of the criteria and rank alternatives by fuzzy technique for order preference by similarity to an ideal solution (FTOPSIS).

In this paper, empirical result shows that the proposed method is capable of helping investor to allocate asset in portfolio problems under vague environment.

The proposed method gives a new mathematical framework for portfolio selection. Investors can decide the asset allocation by using the combination of CFAHP and FTOPSIS.

Besides the benefit of sorting feature, the proposed method can be used to obtain the asset allocation.

The aim of the portfolio selection theory is to rank and decide the asset allocations. But it is still a difficult task in deciding which assets should be selected under uncertain environment. The proposed method in this paper has been proved to be an efficient method to deal with vague information in decision-making programs.

This study analyzes the effectiveness of the combined method of CFAHP and TOPSIS in portfolio problem.

The paper aims to develop a framework to facilitate the evaluation of the complexities of working in multi-level governance and partnership and to assess the extent to which collaboration adds value in terms of both process and outcomes.

The paper applies the fuzzy analysis hierarchy process (FAHP) to the design of an evaluation framework for partnerships and uses data from a questionnaire survey in Wuhan, China, to validate the framework.

The paper finds that the effectiveness of multi-level governance and partnerships is primarily determined by such factors as clarity of framework for partnership, consensus on mission statement of strategic partnership, mechanisms for joint initiation and implementation of projects and removal of barriers to flow of resources.

The paper shows that policymakers need to adopt an evaluation approach to improve the effectiveness of multi-level governance and partnerships.

The paper provides a framework for building multi-level governance and partnerships in the Chinese context.

Discussions about digital tourism continue to increase among scholars as Information Communication and Technology (ICT) infrastructure develops. Dynamic changes due to technological aspects have given rise to various developments in the tourism industry. Therefore, this study aims to evaluate the scientific structure of the development of digital tourism topics through a bibliometric analysis approach. In total, 102 publications from research on digital tourism were taken from Scopus database between 2001 and 2021, for further bibliometric analysis using the VOSviewer application. Interesting findings describe the most cited digital tourism publications, the contribution of digital tourism by various authors, institutions, countries, co-citation analysis, bibliographic coupling, and co-occurrence for the main trends of digital tourism. This study compiles a detailed review of digital tourism research. This article adds substantial value to the digital tourism topic by analyzing bibliometric data. It provided scientific information regarding digital tourism for other researchers and future research.

The construction sector has significantly evolved in recent decades, in parallel with a huge increase in the amount of data generated and exchanged in any construction project. These data need to be managed in order to complete a successful project in terms of quality, cost and schedule in the the context of a safe project environment while appropriately organising many construction documents.

However, the origin of these data is very diverse, mainly due to the sector’s characteristics. Moreover, these data are affected by uncertainty, complexity and diversity due to the imprecise nature of the many factors involved in construction projects. As a result, construction project data are associated with large, irregular and scattered datasets.

The objective of this chapter is to introduce an approach based on a fuzzy multi-dimensional model and on line analytical processing (OLAP) operations in order to manage construction data and support the decision-making process based on previous experiences. On one hand, the proposal allows for the integration of data in a common repository which is accessible to users along the whole project’s life cycle. On the other hand, it allows for the establishment of more flexible structures for representing the data of the main tasks in the construction project management domain. The incorporation of this fuzzy framework allows for the management of imprecision in construction data and provides easy and intuitive access to users so that they can make more reliable decisions.

The robust appraisal of exploration drilling concepts is essential for establishing the economic viability of a prospective recovery field. This study evaluates the different concept selection methods that were considered for drilling operations at the Trym field in Norway. The construction of drilling rigs is a capital-intensive process, and it involves high levels of economic risk. These risks can be broadly categorised as aleatoric (i.e. those related to chance) and epistemic (i.e. those related to knowledge). Evaluating risks in the investment appraisal process tends to be a complicated process. Project risks are evaluated using Monte Carlo simulation (MCS) and are based on the fuzzy analytic hierarchy process (AHP). MCS provides a useful means of evaluating variabilities (i.e. aleatoric risks) in oil drilling operations. However, many of the economic risks in oil drilling processes are unanticipated, and, in some cases, are not readily expressible in quantitative values. The fuzzy AHP is therefore used to appraise the qualitatively defined indirect revenues comprising risks that affect future flexibilities, schedule certainty and health and safety performance. Both the Monte Carlo technique and the fuzzy AHP technique found that a cumulative revenue variation of up to 30% is possible in any of the considered drilling options. The fuzzy AHP technique estimates that the chances of profitability being less than NOK 1 billion over a five-year period is 0.5%, while the Monte Carlo technique estimates suggest a more conservative proportion of 10%. Overall, the fuzzy AHP technique is easy to use and flexible, and it demonstrates increased robustness and improved predictability.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this paper is to provide an overview of studies published in the Journal of Entrepreneurship in Emerging Economies (JEEE) between 2014 and 2019. The review also provides suggestions for future research in JEEE.

Integrative literature of 90 empirical and conceptual articles published in JEEE between 2014 and 2019. The selected articles were analyzed using content analysis.

Analysis of the 90 published articles shows that JEEE has covered a number of relevant topics related to entrepreneurship and innovation in emerging economies. In particular, scholars have adopted a variety of methods to describe such activities in emerging economies. The review also highlights the lack of comparative studies in JEEE and studies, which significantly take into account or focus on the emerging economy context.

The findings suggest that future scholars wishing to submit to JEEE should consider taking a more detailed account of the emerging context.

Since its first publication in 2014, this study represents the first review of articles found in JEEE. Specifically, the study provides a platform for future scholars wishing to submit to JEEE to take stock of the studies in the journal, thus giving them a better understanding of the field. The study also provides directions regarding areas of possible future research, which might be of interest to scholars wishing to submit to JEEE.

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.