Search results

The purpose of this research is to explore the critical success factors of mobile animation games, by exploring the game itself, information systems, game motivation and promotional activities, as well as conducting research and analysis on mobile animation game players.

This research used the Analysis Hierarchy Process (AHP) method and the consistent fuzzy preference relationship for data analysis. In this study, collect 1,286 valid questionnaires through online questionnaire surveys. And comparing the two games “Legend Showdown” and “Tower of Gods and Demons”, players believe that the more successful mobile animation game is “Legend Showdown”.

Through experimental design, and the consistent fuzzy preference relationship for data analysis. The results found that the critical factors considered by the player in relation to the mobile animation game were firstly the information system, followed by promotional activities, game motivation and finally the game itself.

Because this research does not involve the concept of fuzzy theory at all, it is easy to produce subjective, uncertain and ambiguity issues when comparing pairwise. We recommended that follow-up researchers can use fuzzy semantic preference relations to solve this problem.

This study proposed a new approach that takes the critical factors for the mobile animation game. According to the research results, the critical success factor of mobile animation games is the information system, as it could provide a reference direction for game manufacturers when designing or formulating marketing strategies in the future.

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

The purpose of this paper is to apply a fuzzy LinPreRa cognitive map to evaluate the interaction and importance of factors affecting the development of strategic alliance partnerships between the outlying island duty-free shops and existing collaboration firms in duty-free shops. Meanwhile, the key factors should be considered in establishing strategic alliance partnerships while analyzing and comparing the perspectives of owners for outlying island duty-free shop and partner vendors of collaborating firms along with differences of influencing key factors on partnership quality.

This study incorporates a fuzzy linguistic preference relation analytical network process (fuzzy LinPreRa ANP) in the fuzzy cognitive map (FCM) method to formulate a fuzzy LinPreRa cognitive map to evaluate the interactions and importance of key factors and the conditions of interactive impacts during the establishment of strategic alliance partnerships. The authors use the outlying island duty-free shops in Taiwan as the empirical subject to illustrate how the fuzzy LinPreRa cognitive map is applied. In-depth, interviews and questionnaire surveys are conducted to collect and evaluate respondents concerning key factors affecting strategic alliance partnerships establishment.

The following three findings based on the results of empirical analysis: first, the administrative behavioral patterns of managers for strategic alliance partnerships encompass shared values and goal coherence, while the associative statements are located on the first layer of fuzzy LinPreRa cognitive map core associations, which illustrates that businesses attach great importance to conceptual ideas. Second, integrity and reputations of both parties are the governing mechanism of strategic alliance partnerships, influencing mutual reputation. Third, the relationship of strategic alliance partnerships refers to the profit opportunities of both parties and their ability to respond to the market, including future development, regional indicators, marketing capabilities, brand multiplicity and customer retention. However, it can be inferred that such associative factors are located in the outer layer or belong to noncore associations, which means that both parties’ abilities to respond to market reactions are weakened.

This study provides valuable relationship managerial strategies to maintain long-term partnerships for outlying island duty-free shops and their alliance collaborating firms including strengthened relationships of both parties’ managers to achieve common values and consistent objectives; improved beneficial value of both parties in strategic alliance partnerships; continued close communications to enhance the quality of strategic alliance partnerships; and establishment of personnel training mechanisms and strict formulation of management rules for strategic alliance partnerships.

The main valuable contributions are included the fuzzy LinPreRa cognitive map by combining two different decision methods including FCM and fuzzy LinPreRa ANP is proposed to help decision makers to improve the evaluation quality and calculation efficiency for critical elements’ interaction and importance; the fuzzy LinPreRa cognitive map can clarify considering significant factors when maintaining strategic alliance partnerships and further provide valuable relationship managerial strategies to maintain long-term relationships for duty-free shop owners and their alliance collaborating firms.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

Consistency and consensus are two important research issues in group decision-making (GDM). Considering some drawbacks associated with these two issues in existing GDM methods with intuitionistic multiplicative preference relations (IMPRs), a new GDM method with complete IMPRs (CIMPRs) and incomplete IMPRs (ICIMPRs) is proposed in this paper.

A mathematically programming model is constructed to judge the consistency of CIMPRs. For the unacceptably consistent CIMPRs, a consistency-driven optimization model is constructed to improve the consistency level. Meanwhile, a consistency-driven optimization model is constructed to supplement the missing values and improve the consistency level of the ICIMPRs. As to GDM with CIMPRs, first, a mathematically programming model is built to obtain the experts' weights, after that a consensus-driven optimization model is constructed to improve the consensus level of CIMPRs, and finally, the group priority weights of alternatives are obtained by an intuitionistic fuzzy programming model.

The case analysis of the international exchange doctoral student selection problem shows the effectiveness and applicability of this GDM method with CIMPRs and ICIMPRs.

First, a novel consistency definition of CIMPRs is presented. Then, a consistency-driven optimization model is constructed, which supplements the missing values and improves the consistency level of ICIMPRs simultaneously. Therefore, this model greatly improves the efficiency of consistency improving. Experts' weights determination method considering the subjective and objective information is proposed. The priority weights of alternatives are determined by an intuitionistic fuzzy (IF) programming model considering the risk preference of experts, so the method determining priority weights is more flexible and agile. Based on the above theoretical basis, a new GDM method with CIMPRs and ICIMPRs is proposed in this paper.

Software-as-a-Service (SaaS) has the potential to provide substantial opportunities for organizations to improve their information technology without cost and management concerns. However, organizations have not utilized it to the desired level because it is very challenging for them to completely transform their basic conventional methods of running software into SaaS as a high-tech method. On the other hand, organizations have doubt which factors should be mostly considered if they want to move to SaaS. Therefore, investigating the adoption of SaaS can contribute organizations to benefit from this technology. The purpose of this paper is to provide a good insight into SaaS technology adoption.

Considering Technology, Organization and Environment (TOE) framework and diffusion of innovation (DOI) theory as the basis, 22 university experts expressed their idea about the proposed model of SaaS adoption. Then, 30 IT professional in 15 IT enterprises that had adopted SaaS were asked to fill the questionnaire related to fuzzy Analytic Hierarchy Process (AHP) based on linguistic preference relations (LinPreRa) in order to rank the submitted criteria.

The findings demonstrate that all attributes of Technology (relative advantage, compatibility, complexity, trialability, observability and security and privacy), Organization (IT resource, sharing and collaboration culture) and environment (competitive pressure, social influence) are influential in the adoption of SaaS. Moreover, the top five influential factors are relative advantage, competitive pressure, security and privacy, sharing and collaboration culture and social influence based on adopter’s opinions.

For researchers, this study provides a useful literature, which can help them in related subject. In addition, it applies IT adoption theories in SaaS context that can be extended in future studies. For organizations, this study derives priority of factors by which they can make strong decisions about adoption of SaaS.

This study contributes to the adoption of SaaS technology using well-known IT adoption theories. A version of Fuzzy AHP based on LinPreRa was used in order to cover the limitations of previous methodologies of ranking the criteria.

The purpose of this paper is to improve the complicated pairwise comparison problem and the consistency of analytic hierarchy process (AHP), the consistent fuzzy preference relation (CFPR) method is applied to select the best fashion design scheme in this study.

The first stage is to review the traditional AHP for fashion design scheme evaluation. The second stage is based on the procedure of CFPR to select the best fashion design scheme. The procedure includes: establishment of the fuzzy preference relation matrix of pairwise comparisons, calculation of criteria weight, and calculation of the evaluation value for ratings of fashion design schemes with respect to criteria. The final stage is to compare the procedures and results between AHP and CFPR for the evaluations of fashion design schemes.

For fashion design scheme selection, there are 76 data for fashion design scheme evaluation in AHP, but only 31 in CFPR. Comparing both AHP and CFPR methods, the rankings of the criteria weight are identical and the priority scores of the fashion design scheme are similar. The CFPR is more efficient than AHP, obviously, to solve the inconsistency of hierarchical decision-making problem.

This paper proposes the CFPR method for the selection of the best fashion design scheme. According to the finding of this study, the CFPR is proposed as a practicable option for solving complicated pairwise comparison problems in fashion design decision.

The purpose of this paper is to evaluate multiple criteria and sub‐criteria of e‐SQ with the interdependence perspective, utilising three phases of measurement for the proposed e‐SQ evaluation.

The paper utilises literature reviews to address the question of interdependence in the context of e‐SQ and constructs an interdependent network structure for e‐SQ evaluation. Then a method and three phases of measurement are proposed that combine the consistent fuzzy preference relations method with the analytic network process (ANP) technique, to evaluate e‐SQ by using senior experts who work at travel web site companies as research participants.

First, this study discovered the interdependence perspective of criteria and sub‐criteria for e‐SQ evaluation. Second, it was found out that the weights of criteria and sub‐criteria have reverse situations after considering the interdependence perspective. Third, the findings indicate that the interdependence perspective among criteria and sub‐criteria should be taken into consideration, and the authors remind practitioners of the need to implement overall improvements instead of independently addressing each criterion or sub‐criterion of e‐SQ individually.

The authors propose a scientific and systematic method for e‐SQ evaluation that can enable managers of online web sites to determine the important factors, and further to achieve total e‐SQ control management. Moreover the proposed method can deal with imprecise information when evaluating e‐SQ, as well as considering interdependent relationships among factors, and is thus faster and more efficient at addressing the inconsistency problems involved in multiple decision making than conventional methods.

Interest in investigating key supplier relationships from both academic and corporate spheres has increased in recent years. However, it is difficult to develop a sustainable and effective model for evaluating key supplier relationships because the information available in the practical environment is often uncertain and asymmetric. The purpose of this paper is to identify critical factors concerning key suppliers selection derive from resource-based view and construct a hierarchical evaluation framework which has elements of implied change or transformation of the firm’s resources for operation strategies when evaluating key suppliers relationships. Moreover, the authors propose a fuzzy preference relations (FPR) model, with a hierarchical evaluation framework, to address the imprecise and inconsistent information used by managers to evaluate key supplier relationships and further to select appropriate suppliers.

The FPR model based on the consistent FPR methodology not only provides an efficient and systematic evaluation for key supplier relationships by using the performance and evaluation scores of each key supplier, but also solves problems arising from the conventional multi-criteria analysis approach. This methodology is faster to execute and enhance the consistency and accuracy with regard to the decision makers’ judgments. To illustrate how the model is created and assessed, the authors use the TFT-LCD TV panel manufacturing industry as an empirical subject.

The FPR model holds promise for assisting TFT-LCD TV manufacturers in evaluating key supplier relationships with TFT-LCD TV panel suppliers. The findings indicate that first, “the supplier’s product quality” is the most important factor when evaluating key supplier relationships, followed by “selling price set by the supplier” and “specialized supplier development capability”; second, after the 1980s, all suppliers had similar delivery capabilities with only small differences in delivery times, such that the relative importance of “time required for shipments” has become less significant, and customer awareness of the “customer assistance and service” factor has been heightened; third, the provision of excellent product quality and attractive low prices by suppliers requires technical capability, therefore, from the perspectives of industry experts, “specialized supplier development capability” is far more important than “time required for shipments”; and fourth, TFT-LCD TV manufacturers need to focus on their product quality performance continually, and concentrate on applying process technology strategy as well as product and service development strategy to build up “difficult to imitate resources” for competitive advantages.

The main contribution is to provide managers with an efficient and systematic model that can evaluate the performance of key supplier relationships in terms of critical factors derived from resource-based theories. By focussing on employing the proposed model with successful management for key supplier relationships, the authors hope to help buying companies improve the benefits of supplier relationships. Because of the uncertainties and complexities of real strategy making in TFT-LCD TV panel industry, the authors offer a model that implicitly assume that managers can have influences over the strategic direction of their organization.