Improving candy industry competitiveness: Retailers’ perception regarding customer satisfaction

This study aims to classify service quality elements in candy industry in order to determine their instrumentality to customer satisfaction. To address this purpose, a Fuzzy Kano questionnaire was distributed to 512 major retailers of candy products of four predominant candy companies in Iran. Subsequently, we calculated satisfaction increment index (SII) and dissatisfaction decrement index (DDI) for each of the quality elements. Brand name and quality are considered as must-be elements, while availability of credit purchases is considered as indifferent element by the majority of retailers. Eight out of 24 studied elements are found to be considered as attractive elements by majority of customers. Regular visits element ranks first in terms of satisfaction increment index (SII). This paper provides helpful insight for marketers to prioritize improvement of different quality elements. Therefore, this paper helps organizations to perceive their customers needs more thoroughly and improve their customer satisfaction policy.     

Sustainable efficiency drivers in Eurasian airports: Fuzzy NDEA approach based on Shannon's entropy

This research explores the physical infrastructure and flight consolidation efficiency drivers of Eurasian airports regarding their infrastructure and movement productivity levels. A novel Fuzzy Double-Frontier Network DEA (FDFNDEA) model is proposed to investigate the relationship between desirable (freight and passenger turnovers) and undesirable (pollutant emission levels due to aircraft movements) outputs against the respective infrastructure usage, fuel consumed, and movements performed at each of the 23 Eurasian airports from 2000 to 2018. This balance between desirable and undesirable outputs emerges spatially and temporally due to the evolution of the airport system's productive resources at each one of the Eurasian countries over the period observed. Shannon's entropy is used as the cornerstone to quantify the input and output vagueness of this evolution in Triangular Fuzzy Numbers (TFN), thus allowing the accurate building of alternative optimistic and pessimistic double-frontier efficiency. Differently from previous research, Shannon's entropy is the key for measuring input and output vagueness levels in light of the maximal entropy principle. This principle states that the distribution that best represents the current state of knowledge is the one with largest entropy. Maximal entropy yields bias-free decision-making in the sense that the input/output distributional profiles for Eurasian airports contain the maximal possible heterogeneity, working as a robust or best/worst-case scenario against eventual unconsidered assumptions. Hence, optimistic and pessimistic Malmquist Productivity Indexes (MPI) for overall and each stage productivity results are subsequently regressed against contextual variables related to airport characteristics and regional socio-demographic and economic indicators of each Eurasian country using bootstrapped Cauchy regressions. The findings revealed the spatial heterogeneity of productivity factors and airport performance across Eurasia. Results also demonstrated the negative impact of income inequality and the positive impact of private participation on technological progression in the Eurasian airport industry.     

跨界创新在突破性技术创新模糊前端的作用机制

基于“互联网+”大背景，跨界创新成为实现突破性技术创新的重要形式。通过现有文献分析，构建了跨界创新在突破性技术创新模糊前端的作用模型，并运用案例研究法，以无人驾驶汽车为例对模型进行释义。研究表明，跨界创新在突破性技术创新模糊前端起到重要作用，跨界创新可分为跨界搜索与跨界合作，跨界搜索有助于创意搜集和创意筛选，识别突破性技术创新机会；跨界合作有助于提升研发效率和成功率；跨界搜索与跨界合作相辅相成，共同致力于突破性技术研发成功。     

高校跨学科创新团队知识互动程度评价研究

知识互动程度评价对改善高校跨学科创新团队知识互动具有重要意义。在界定高校跨学科创新团队知识互动及知识互动程度内涵的基础上，创新性地从知识互动深度、互动广度、互动时间3个维度建立知识互动程度评价指标体系。进一步地，采用三角模糊权重、熵权和模糊积分相结合的方法，构建知识互动程度评价模型。最后，选取一所高校跨学科创新团队进行实例分析，验证评价模型的可操作性，可为高校跨学科创新团队知识互动程度评价提供一个新视角。     

Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair

Traffic congestion is an unpreventable problem to avoid in a transportation network and it has negative effects on traffic accident, time wasting, traffic delay and safety problem. Besides, in transportation networks, drivers do not want to deal with traffic jam while traversing between specified origin-destination pair. Therefore, traffic assignment (TA) is imperative to improve traffic management, transportation safety, time, and cost savings. System Optimum Traffic Assignment Problem (SOTAP) is a kind of TA model which aims to minimize the total system travel time on the network, and satisfies the flow conservation constraints. To model the SOTAP more realistically, the imprecise parameters can be taken as fuzzy. Therefore, in this paper, we focus on converting the conventional SOTAP to a fuzzy quadratic programming problem (QPP) which is named System Optimum Fuzzy Traffic Assignment Problem (SOFTAP). Here, link travel time is expressed with BPR function as generally used in the literature by converting to fuzzy except link-dependent parameters. Thus, the nonlinear objective function of SOFTAP is expressed in terms of fuzzy link flows and fuzzy link travel times. A solution approach from the literature is modified to the reconstructed SOFTAP.     

Dynamic management of aircraft stand allocation

This paper aimed to present an original approach for solving the aircraft stand allocation (SA) problem dynamically when due to operational disturbances, the planned allocation cannot be accomplished. The proposed Multiple-criteria Dynamic Stand Allocation (MDSA) method uses fuzzy logic to support decision-making under uncertainty. The MDSA method provides effective solutions in a short time, necessary for traffic management in case of delays, emergency, and untypical cases. It considers partially conflicting points of view of different airport users (airport managers, air traffic controllers, airlines, handling agents, and passengers) and may significantly support managers on the SA problem. The approach proposed can also be used for creating an initial SA plan for a considerable number of aircraft.     

Diversified behavioral portfolio as an alternative to Modern Portfolio Theory

The traditional mean–variance approach has been complemented by alternative theories that use risk measures different from standard deviation of returns or involve additional distributional features of returns like skewness and kurtosis. We propose a portfolio choice model that combines different distributional characteristics of the returns in the decision-making making process, considering preferences of investors which are modeled as non-statistical uncertainties of investors using fuzzy theory. We use 20 stocks of the S&P500 from January 2013 to December 2017. We assess the obtained portfolios’ performance, and the diversified behavioral portfolios outperform than the mean–variance portfolio. This methodological proposal can be seen as a strong managerial tool to make investment portfolio decisions.     

A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management

This study assesses supplier selection at the beginning of project management to establish an evaluation system corresponding to blockchain tracing anti-counterfeiting platforms (BTAP). First, this paper determines 20 evaluation criteria from the four dimensions of platform overview, core technology, application support, and operations management. On this basis, multi-criteria decision making (MCDM) based on customer needs is proposed, which consists of three main steps. First, quality function deployment (QFD) and the best and worst method (BWM) are used to evaluate the four dimensions of the BTAP and specific evaluation criteria from the perspective of customers to obtain the criteria weight. Then, this method uses the extended Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) approach to sort the alternatives. Finally, the improved decision making trial and evaluation laboratory (DEMATEL) method is used to analyse the relationships between the 20 criteria in the four dimensions. The feasibility and effectiveness of this method are verified by an example. According to the sensitivity analysis and comparative analysis, the results show that this method can evaluate blockchain anti-counterfeiting enterprises. The main conclusions are as follows: the core technology is the most important factor influencing the choice of a BTAP project, and the role of application support in evaluation cannot be ignored.     

GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul,Turkey

Fire stations play a central role in protection and response activities as part of emergency management services in cases of fire incidences. With the rising urban populations and city expansions, the demand for more fire services resultantly increases. It then becomes critical to effectively plan the location of emergency facilities to adequately service the population and ensure the protection of lives and infrastructure. This study, therefore proposes the use of the fuzzy extension of the Multi-Criteria Decision-Making (MCDM) method of Analytical Hierarchical Process (AHP), hence called fuzzy AHP, integrated with Geographic Information Systems (GIS) approach to optimally site new fire stations for the case of Istanbul region. This proposed fuzzy approach simulates the subjective expert judgements for the preferences of the six criteria assessed for fire station suitability mapping and thereby accounted for the uncertainty of crisp comparison values via triangular fuzzy numbers (TFNs). The criteria weights evaluated from this procedure were used in a weighted overlay analysis of the reclassified criteria map layers in ArcGIS to generate a fire station suitability map. These resultant fuzzy AHP criteria weights were validated using another MCDM technique, called Best-Worst Method (BWM) and found to be comparable and consistent. The criteria that had the strongest influence on the selection of sites for fire stations were identified to be: the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with associated weights of 33.3%, 24.4% and 15.2%, respectively. Based on a thorough assessment within the areas represented by class values ranging from 3 to 5 on the suitability map, a total of 34 new fire station sites were selected complementing the existing 121 fire stations. Further, a prioritization analysis from low, medium to high, was performed to plan the phases for the construction of new fire stations in view of competing budgetary needs and resource constraints. The methodology to achieve this was proposed and modelled for enhancing the decision-making process in urban fire station site selection studies.     

An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry

Driven by business strategies, digital transformation (DT) facilitates dramatic change in air passenger behavior. This study aims to determine and analyze different DT strategies (DTSs) with the help of an integrated SWOT-based fuzzy AHP-MARCOS methodology that is proposed for the first time in the literature for this purpose. This methodology is validated with a case study concerning the airline industry in Turkey. The weights of the SWOT factors are determined with the fuzzy AHP method. The fuzzy MARCOS approach is used to select the most suitable DTS. The most appropriate strategy is obtained as “focusing on differentiated digital customer experience and service quality by the adaptation of business models to DT to provide benefits”.