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The urgent need to move toward a more sustainable and low-carbon economy has gained increased attention in recent years. There is a global drive to reduce greenhouse gas emissions and address the causes of climate change since its effects are becoming more and more obvious. The study identified several potential green infrastructure projects that could have a significant positive impact on sustainable development in China. The core criteria and sub-criteria for impact investing in green infrastructure were determined by the panel through a Delphi process, and they were then analyzed and weighted using the fuzzy Analytical Hierarchy Process (AHP) method. According to the study's findings, environmental impact was considered the most crucial factor when making decisions to invest in green infrastructure. The economic and social impacts are indicated as the second and third influential factors, respectively. In order to promote impact investing in green infrastructure for sustainable development in China, the study offers several policy recommendations. These recommendations include developing rules and regulations that encourage private sector investment, raising public awareness and participation, forming alliances between the public and private sectors, offering financial support and incentives, and building programs that will help China's green infrastructure industry build its capacity. [ABSTRACT FROM AUTHOR]

Natural aquifers used for human consumption are among the most important resources in the world. The Locumba basin faces significant challenges due to its limited water availability for the local population. In this way, the search for possible aquifer recharge zones is crucial work for urban development in areas that have water scarcity. To evaluate this problem, this research proposes the use of the hybrid Fuzzy AHP methodology in conjunction with the TOPSIS algorithm to obtain a potential aquifer recharge map. Ten factors that influence productivity and capacity in an aquifer were implemented, which were subjected to Fuzzy AHP to obtain their weighting. Using the TOPSIS algorithm, the delineation of the most favorable areas with high recharge potential was established. The result shows that the most influential factors for recharge are precipitation, permeability, and slopes, which obtained the highest weights of 0.22, 0.19, and 0.17, respectively. In parallel, the TOPSIS result highlights the potential recharge zones distributed in the Locumba basin, which were classified into five categories: very high (13%), high (28%), moderate (15%), low (28%), and very low (16%). The adapted methodology in this research seeks to be the first step toward effective water resource management in the study area. [ABSTRACT FROM AUTHOR]

The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The 'cleaning' factor has the highest weight, and 'updating' is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals. [ABSTRACT FROM AUTHOR]

The fifth industrial revolution emphasizes human-robot collaboration to enhance transformation processes. While collaborative robots (cobots) are increasingly attracting interest in various industries, integrating them into assembly lines remains challenging. This paper aims to investigate whether cobots are replacing traditional robots or if a synergy between both technologies is essential in the era of Industry 5.0 to maximize benefits. The real case study presented provides a comparison between robots and cobots in an automotive factory using the Fuzzy AHP methodology. The results indicate that cobots are advantageous in production units with low-volume and high-variability tasks. However, they fall short of the reliability, precision, and productivity that traditional robots offer for repetitive tasks. Finally, a framework is proposed to guide decision makers in adopting the suitable solution to their needs while ensuring optimal performance as well as workers wellbeing. [ABSTRACT FROM AUTHOR]

The objective of the study was to investigate different factors that influence the intention to purchase green vehicles and prioritize these factors to identify the most critical factor. The use of green vehicles, such as electric or hybrid vehicles, can significantly reduce greenhouse gas emissions, air pollution, and dependence on fossil fuels. Therefore, purchasing green vehicles can contribute to sustainable development by reducing the negative impact of transportation on the environment. Fuzzy AHP is an extension of the traditional AHP method that incorporates fuzzy logic. AHP breaks down complex problems into hierarchies of criteria and alternatives, enabling evaluation and prioritization. The study used fuzzy AHP to rank factors influencing individuals' intention to purchase green vehicles, based on 302 responses. Fuzzy AHP allows for flexible assessment considering uncertainties in decision-making. Harman's single-factor test was conducted to verify common method bias. The results revealed six factors that affect intentions to purchase green vehicles, with environmental concern (EC) being the most crucial and mass media influence (MMI) the least significant factor. However, as the study was conducted in India only, the generalizability of the findings to other countries may be limited. Additionally, the study is cross-sectional, and several factors that could have a significant impact on customers' purchase intentions are not included in the analysis. The study has implications for managers, practitioners, and government agencies. The use of fuzzy AHP in the proposed conceptual framework adds to the literature by providing a better empirical understanding of the primary determinants of customers' purchasing behaviour concerning green vehicles in India. The research also introduces fuzzy AHP as one of the multi-criteria decision-making (MCDM) techniques in the field of green vehicle purchasing, offering a comprehensive view of the significant motivations behind people's favourable attitude towards green vehicles from a theoretical perspective. [ABSTRACT FROM AUTHOR]

Despite presenting several advantages in relation to the mortar coating performed by hand labor traditionally carried out in Brazil, there is little knowledge available about mortar pumping systems. Thus, selecting a mortar pump system is not a trivial procedure, and there are no significative studies published in the specialized literature to fully understand the decision criteria applying to this equipment selection. Therefore, the present study aimed to identify the relevant criteria and quantify their importance in the selection of this equipment, by developing a framework combining both mortar pump specialists expertise and fuzzy analytic hierarchy process method to aid this decision making process. Results showed that acquisition cost and quality are the most relevant criteria, representing togheter around 2/3 of the decision weight, while technical and operational aspects account for aproximatelly 1/10 of relevance in the equipment selection. [ABSTRACT FROM AUTHOR]

Purpose: This research has been carried out to study the impact of critical success factors (CSFs) on successful project management of projects in the manufacturing sector. These success factors will pave the way for the successful completion of projects for the manufacturing sector. CSFs play a vital role in the timely conclusion of projects in any organization. For the projects to be successful certain essential factors must be taken into account. These essential factors are identified through this research. Design/methodology/approach: During this study an adaptive survey of the literature was conducted, after a detailed literature review certain success factors were identified for project management in the manufacturing sector. The number of success factors was reduced to 40 factors based on the level of incidence in the literature. The length of the questionnaire was also given due importance to make the survey more interesting and effective. After that Fuzzy Delphi Method (FDM) was employed to screen the most essential factors. In the end, the Fuzzy Analytical Hierarchical Process (FAHP) was used to rank these factors in order of importance. Findings: Project Manager Leadership Skills, Economic Environment, Top Management Support, Project Planning, Clear and realistic Goals, and Financial Support have come out to be the most important CSFs for successful project management in the manufacturing sector. Originality/value: This is novel research to identify CSFs for project management in the manufacturing sector. Previously, most of the studies remained focused on construction and software projects. [ABSTRACT FROM AUTHOR]

Fire frequencies have increased in the natural ecosystems of northeastern Iran because of natural and human factors in the recent years. This study models and maps the danger of fire in natural ecosystems in Northern Khorasan Province in northeastern Iran. First, the hierarchical structure of the main fire-influencing factors (physiographic, climatic, vegetative, and human-made factors) and their sub-factors was determined. The data describing these effective factors were acquired from different sources (satellite images, field survey, etc.) and were converted into the maps in raster format (30 m by 30 m pixel size) in the GIS. A map of past fires in the province was developed from data of the Northern Khorasan Natural Resources Administration and from the fire product of the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. The weights of each of the factors and sub-factors were determined using FAHP (Fuzzy Analytic Hierarchy Process). A fire-danger map was obtained by overlapping all effective-factor maps in the GIS. The raster values were categorized into five fire-danger classes. The results were validated by comparison to the past fires using OA (Overall Accuracy), and kappa index. Results demonstrated that the human-influence factor, with weight of 0.48, is the most effective variable in fire-danger modeling in the Northern Khorasan Province. The fire-danger map indicated that very high-danger and high-danger areas cover 54.65% of the province, a spatially extensive amount of land having high fire likelihood. In statistical terms, the accuracy of fire danger map was high with OA of 96%, and the kappa index of 0.85, reflects the high accuracy of fire-danger prediction in the study area. The fire danger map of the study area provides a baseline for informed fire management, mitigation, and prevention decisions in the natural ecosystems of Northern Khorasan Province. This map could be very useful for forecasting future fires in northeastern Iran. [ABSTRACT FROM AUTHOR]

This feasibility study explores the viability of solar PV-powered Reverse Osmosis (RO) desalination in five locations in Visakhapatnam, India. The assessment integrates technical, economic, environmental, social, and political considerations using Multi-Criteria Decision Analysis (MCDA) with Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) methods to handle uncertainties in decision-making. The study evaluates the technical feasibility of the integration, conducts economic analysis, examines environmental impacts, investigates social benefits, and challenges, and analyzes the political landscape. The former emphasizes the significance of understanding challenges and potential solutions associated with RO desalination, aiming for sustainable development aligned with local and global goals. Yarada and Bheemili were the most suitable locations selected based on Fuzzy TOPSIS and Fuzzy AHP, respectively. The study also highlighted the need for public awareness and government support for desalination projects. [ABSTRACT FROM AUTHOR]

Using enterprise resource planning provides benefits and added value regarding enterprise processes' efficiency, integration, and effectiveness. However, while selecting the ERP software, parameters in various categories, such as the enterprise's requests, the services of the consultant firm, and the employee's participation, should be considered. When determining between options, the parameters taken into consideration may differ from one another or be imprecise. This study aims to ascertain the criteria that Small and Medium-Sized Enterprises (SMEs) that intend to invest in ERP software should pay attention to when selecting ERP software. The ERP usage process of the enterprise, the success of ERP within the company, the ERP installation process, the ERP company's support service, and the focus on the parameters of meeting the expectations from the ERP system were made. The obtained information was evaluated with the fuzzy AHP technique. It was decided that the most significant criterion that the enterprise should pay attention to in the selection of ERP is the success of ERP within the company and meeting the expectations of the ERP system, and a suggestion was presented in this direction. [ABSTRACT FROM AUTHOR]

Electronic banking grants users access to banking services virtually and offers convenience, ease of use, low cost, time saving, fast delivery and online bill payment. These services are mostly provided through websites; hence evaluation of its quality and services are very important. Website quality evaluation entails numerous dimensions and attributes and the processes which are critical as well as complex requires quality, accuracy and objectivity. This paper surveys the criteria and methodologies that have been used over years in e-banking websites quality as well as e-services quality evaluation. The survey covers articles within a five-year period from 2018 - 2022 which mostly focus on e-banking websites quality evaluation. Twenty-three articles which met the inclusion and exclusion criteria set by the authors are used for the study. Results show that the average number of criteria used in most studies are six with security, privacy and ease-of-use taking the lead as the mostly used criteria across different studies. Also, various types of multi-criteria decision-making model were used by different and there is none that is dominant among them. It was observed that fuzzy type of the various types of multi-criteria decision-making models are mostly used in many studies. In general, studies with focus on e-banking websites quality are not yet given much attention in the literature. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Journal of Maritime & Marine Sciences is the property of Ordu University, Fatsa Faculty of Marine Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, we address a critical aspect of the routing protocol for low-power and lossy Networks (RPL), namely the selection of the parent node, which plays a pivotal role. As IoT networks expand rapidly, tackling data congestion becomes increasingly crucial. The conventional RPL algorithm, initially designed for smaller networks, lacks mechanisms for balancing loads during parent–child node assignment and does not consider congestion scenarios. To overcome these limitations, we propose a novel objective function (OF) tailored specifically for the RPL algorithm. This OF integrates network load and congestion conditions using an Adaptive fuzzy multi-criteria decision-making approach, combining fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution (TOPSIS) techniques. By redefining the process of selecting parent nodes, our approach enhances the efficiency of data transmission, alleviates congestion, and optimizes the performance of IoT networks. Our method introduces a multi-criteria decision-making framework for parent node selection, ensuring that the chosen parent node is both free of congestion and balanced in load, resulting in efficient forwarding of data packets. We prioritize parent node selection based on five crucial criteria, directly addressing load and congestion challenges in IoT networks. Through fuzzy AHP, we determine the relative importance of each criterion, while the TOPSIS method aids in ranking alternatives. This comprehensive approach provides a robust solution to mitigate network congestion, optimize load distribution, and enhance IoT network performance amidst dynamic growth. Implementing the algorithm using Contiki OS and the Cooja simulator, our results demonstrate 0–15% reduction in delay, 20–30% lesser energy consumption, and 10–25% reduction in packet overflow rate while maintaining network throughput by 15% as compare to CQARPL, CAFOR and QHCA and enhancing overall performance. [ABSTRACT FROM AUTHOR]

This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes work itself, supervision, coworkers relationship, salary and benefit, career opportunities, job stress, perceived risk, and job insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are work itself, job stress perceived risk, and job insecurity. In addition, this study's results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions. [ABSTRACT FROM AUTHOR]

Decision makers consistently face the challenge of simultaneously assessing numerous attributes, determining their respective importance, and selecting an appropriate method for calculating their weights. This article addresses the problem of automatic generation control (AGC) in a two area power system (2-APS) by proposing fuzzy analytic hierarchy process (FAHP), an multi-attribute decision-making (MADM) technique, to determine weights for sub-objective functions. The integral-time-absolute-errors (ITAE) of tie-line power fluctuation, frequency deviations and area control errors, are defined as the sub-objectives. Each of these is given a weight by the FAHP method, which then combines them into an single final objective function. This objective function is then used to design a PID controller. To improve the optimization of the objective function, the Jaya optimization algorithm (JOA) is used in conjunction with other optimization techniques such as sine cosine algorithm (SCA), Luus–Jaakola algorithm (LJA), Nelder–Mead simplex algorithm (NMSA), symbiotic organism search algorithm (SOSA) and elephant herding optimization algorithm (EHOA). Six distinct experimental cases are conducted to evaluate the controller’s performance under various load conditions, with data plotted to show responses corresponding to fluctuations in frequency and tie-line exchange. Furthermore, statistical analysis is performed to gain a better understanding of the effectiveness of the JOA-based PID controller. For non-parametric evaluation, Friedman rank test is also used to validate the performance of the proposed JOA-based controller. [ABSTRACT FROM AUTHOR]

Over the past few decades, flood disasters have emerged as the predominant natural hazard in Cyprus, primarily driven by the escalating influence of climate change in the Mediterranean region. In view of this, the objective of this study is to develop a geospatial flood risk map for the island of Cyprus by considering 14 flood hazard factors and five flood vulnerability factors, utilizing geographic information systems (GIS) and remotely sensed datasets. A comparative assessment was conducted for hazard mapping, employing statistical methods of frequency ratio (FR) and FR Shannon's entropy (FR-SE), and multi-criteria decision analysis method of fuzzy analytic hierarchy process (F-AHP). The main findings indicated that the FR method exhibited the highest predictive capability, establishing it as the most suitable approach for flood hazard mapping. Additionally, vulnerability factors were aggregated using F-AHP to generate the vulnerability map. The resulting flood risk map, which is the product of flood hazard and flood vulnerability, revealed that 9% of the island was located within highly risky regions, while 13.2% was classified as moderate risk zones. Spatial analysis of these high-risk areas indicated their concentration in the primary city districts of the island. Therefore, to mitigate future risks within these cities, an analysis of potential expansion zones was conducted, identifying the best-suited zone exhibiting the lowest risk. The generated flood risk map can serve as a valuable resource for decision-makers on the island, facilitating the integration of flood risk analysis into urban management plans. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Business & Projects / Revista de Gestão e Projetos is the property of Revista de Gestao e Projetos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change threatens human survival and development. Cities, as the main gathering places for human production and life, serve as the focal points for the implementation of the policies related to energy efficiency, energy transition, and environmental protection. This study constructs an index system for the evaluation of carbon-neutral cities from the perspectives of carbon sources and carbon sinks. The system includes thirteen indicators under six dimensions. It combines objective and subjective data (i.e., statistical data and expert evaluations) by integrating two approaches: the fuzzy analytic hierarchy process (fuzzy AHP) and vise kriterijumska optimizacija i kompromisno resenje with hesitant fuzzy sets (HFS-VIKOR). We verify the efficacy of the proposed approach through a case study of thirteen low-carbon pilot cities in China. The results indicate that among these cities, Shenzhen performs the best, followed by Guangzhou and Hangzhou, while Kunming, Baoding, and Tianjin show poor performance in terms of carbon neutrality. Kunming and Baoding exhibit shortcomings mainly in carbon sources, while Tianjin faces deficiencies in both carbon sources and carbon sinks. Sensitivity analysis and comparative analysis show the availability and effectiveness of the proposed method. The proposed radar chart further highlights the improvement directions for each city to achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

Cage farming in brackishwater resources is an emerging activity in India. Scientific planning and implementation would promote livelihood enhancement and sustainable development for the coastal community. Lagoons and backwaters are often developed for tourism and water sports activities. Identification of potential cage farming locations would improve aqua tourism and generate additional revenue for the fisherman. Hence, this study aims to locate viable cage farming locations in the Muttukadu brackishwater ecosystem, one of the most important lagoon systems on the east coast of Chengalpattu district, Tamil Nadu, for aqua tourism development. Water quality, environmental, and accessibility factors were considered the main factors for identifying suitable cage farming sites. Fourteen designated sampling points covering the lagoon were identified, and water samples were collected and analyzed at monthly intervals from December 2019 to January 2022. Each factor was further sub-classified and ranked by assigning appropriate weightage using the fuzzy analytic hierarchy process (FAHP), one of the multiple-criteria decision-making (MCDM) methods. For sustainable farming, it is important to consider ecologically sensitive areas and other constraining factors. ArcGIS Pro was used to map all the factors for identifying potential cage farming sites. The result shows the potential area available for cage farming development is about 11.52 ha, out of which 0.93 ha is highly suitable, and 10.59 ha is moderately suitable. [ABSTRACT FROM AUTHOR]

The issue of water contamination in reservoirs and watersheds due to the irregular use of fertilizers and uncontrolled occupation by riverside populations has worried managers operating hydroelectric plants. The increase in the levels of certain physical–chemical parameters causes problems of accelerated deterioration of equipment and clogging of water pipes. Within this context, here we estimate a specific water quality index (WQI) for hydroelectric plants. The novelty of this article is to use expert consultation to select the most critical parameters that cause damage to the dam structures and mechanical equipment. We propose a method carried out in three steps: selection of specific parameters for hydropower plants and fuzzy MCDA estimation of their weights; fuzzification of sub-indices; and estimation and classification of the WQI. In this last step, the sub-indices are defuzzified and weighted for classification according to the degree of membership in a fuzzified scale. Fuzzy logic deals with variables that do not allow objective classification, given that the limits between classes are imprecise or non-statistical, such as the parameters analyzed in this study. These thresholds are fuzzy numbers, so the treatment of the sub-indices must follow this logic. We obtained a specific classification for the water quality upstream of the Corumbá IV Hydroelectric Plant, located in the central region of Brazil. Observing the individual ratings of each parameter obtained before aggregation, although producing results for drinking water set by Brazil's National Environmental Council, presents concentrations of some parameters that, if not controlled, could harm the hydroelectric plant. [ABSTRACT FROM AUTHOR]

This paper investigates the Indoor Environmental Quality (IEQ) factors influencing occupant satisfaction in commercial buildings in Iran, contrasting the views of building experts (architects and engineers) with those of building occupants. Employing the fuzzy analytical hierarchy process (FAHP), this study focuses on the four primary IEQ factors: thermal comfort, indoor air quality, visual comfort, and acoustic comfort. The study aims to bridge the gap between expert evaluations and occupant perceptions of IEQ factors in commercial buildings in Iran. By examining the disparities in prioritising IEQ factors between these two groups, the study sheds light on the complexities of IEQ assessment and highlights the importance of considering diverse perspectives in optimising indoor environments. Our methodology includes a survey conducted among 30 building experts (15 architects and 15 building engineers) and 102 occupants, employing FAHP to derive the relative importance weights of each IEQ factor. The results highlight significant disparities between architects, engineers, and occupants in prioritising these factors. Architects emphasise visual comfort (42%), while engineers and occupants view thermal comfort (53% and 41%) as the most crucial factor for occupant satisfaction. The study underscores the complexity of IEQ in commercial buildings and the diverse perspectives influencing its assessment. It contributes to the broader discourse on optimising IEQ, emphasising the need for a comprehensive approach that encompasses both technical expertise and occupant experience. [ABSTRACT FROM AUTHOR]

Women's empowerment programs play a critical role in achieving the United Nations' (UN's) sustainable development goal of "Gender Equality". However, non-profit organizations (NPOs) running women's empowerment (WE) programs face challenges in monitoring, assessing, and evaluating the social impact (SI) and program performance due to the lack of solid guidelines. This study aims to analyze the impact and outcome evaluation indicators of WE programs by providing a quantitative tool. A multi-criteria decision-making (MCDM) model is proposed to identify and prioritize the performance indicators by utilizing Fuzzy TOPSIS (FTOPSIS) and Fuzzy AHP (FAHP) in a combined methodology. Results validated the identification and classification of the indicators by their importance and viability. In a qualitative study with NPOs working on WE in Turkey, social impact and outcome evaluation indicators are defined and ranked by criteria set in the proposed combined MCDM framework. The study aims to contribute to the theoretical frameworks and practices on social impact and outcome evaluation of women's empowerment. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this paper is to identify, screen and prioritize customer requirements (CRs) for men's denim jeans. Moreover, the effect of demographic factors on the primary evaluation criteria has been examined. Design/methodology/approach: The study was initiated by the growing complaints about denim jeans products of a local manufacturing company. First, 24 CRs were identified from the literature and customer complaints. Then, a survey was conducted to rate the identified CRs and solicit more CRs through closed-ended and open-ended questions, respectively. From the survey, 368 usable responses were collected while the participants were shopping in 14 local retail shops. After analyzing the data using factor analysis, univariate and multivariate analysis of variance (MANOVA), and content analysis, the resulting 15 criteria were prioritized by experts' pairwise comparisons employing the fuzzy analytic hierarchy process (AHP). Findings: Factor analysis extracted six components (primary criteria) including design cues, pocket design, comfort, size and fit, fashionability, and extrinsic cues from the CRs included in the closed-ended questions. MANOVA showed that age and frequency of purchasing denim jeans significantly affected the primary criteria, while educational level and frequency of wearing denim jeans did not. The weights from the fuzzy AHP revealed that colour fastness, price, durability, fabric weight, workmanship, side pocket design and fit as the most important CRs. Moreover, consumers preferred regular fit, stitched round side pockets, patch back pockets and stretchable denim fabric. Research limitations/implications: The limitations of the study are discussed in the body of the paper in Section 7. Originality/value: The paper presents exploratory findings on denim jeans evaluation criteria in a developing country's context. Moreover, the application of fuzzy AHP for prioritizing denim jeans' CRs is unique. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques. [ABSTRACT FROM AUTHOR]

Productivity is one of the most important measures used to determine the growth and development level of countries or sectors. A wide variety of projects have been planned and implemented to increase agricultural productivity. The productivity to be obtained in agriculture; Soil conditions, climate, seeds, fertilizer, pesticides, labor and agricultural mechanization directly affect it. Agricultural mechanization is the realization of agricultural activities by using energy together with agricultural tools and machines. Agricultural mechanization; It is an important agricultural production technology that helps increase agricultural productivity. Due to the inadequate maintenance planning of agricultural machinery, agricultural machinery cannot be utilized at the desired level in agricultural production. Most agricultural equipment is subject to frequent changes in speed and direction of movement while operating. Damage that can be seen on a single machine; It also causes other machines to malfunction. During the year, especially in the months when agricultural activity is high, excessive working tempo can cause tractors to malfunction. The breakdown of tractors causes disruptions in agricultural activities. In addition, the breakdown of tractors increases the repair costs. Since there is no tractor maintenance planning, farmers face interruptions in agricultural activities due to tractor malfunction. However, tractor malfunctions may cause cost and economic losses. For these reasons, there is a need for appropriate maintenance planning of agricultural machinery in order to continue agricultural activities without disruption. Maintenance planning; It consists of a set of preventive activities to improve the reliability and availability of any system. The main purpose of this study is to determine and rank the importance level weights of the criteria that are important for agricultural machinery maintenance planning using the fuzzy AHP method. Fuzzy AHP method, which provides ease of application, was preferred in determining the Criterion Weights. The research proposes a framework to determine the weights of appropriate criteria for care planning selection through a combined approach of fuzzy multi-criteria decision making involving relevant stakeholders. On the basis of the prioritization of criteria of tractor maintenance planning (TMP), it was found from the ranking that checking for all fluid levels (TMP1) ranked first. This respectively is followed by checking for general conditions (TMP4), checking for tires and wheels (TMP2) and checking for batteries (TMP3). With the results of the study, a guide was created for farmers and other stakeholders, as well as decision makers, to help plan the maintenance of machines in better working conditions. It is also thought that this study will be encouraging for other studies. [ABSTRACT FROM AUTHOR]

With the advent of the Internet era in recent years, social music education has gradually shifted from the original entity education mode to the mode of entity plus network teaching. No matter for school music education, professional music education or social music education, the teaching quality is the most important evaluation index. This research firstly found out the basic dimensions that accord with the teaching quality required by the three parties, constructing the quality evaluation index system; and then, on the basis of expounding the connotation of each index, it determined the weight of each index by using method of fuzzy analytic hierarchy process, providing ideas and methods for scientific, objective and comprehensive evaluation of the teaching quality of network education APP. [ABSTRACT FROM AUTHOR]

The textile supply chains (TSCs) are exposed to unprecedented risks which can disrupt the sustainable process of the manufacturing industries. It is necessary to analyze the impact of risks and to create reliability in the end-to-end supply chain. The aim of this research is to identify the supply chain reliability (SCR)-related risks and proposed a risk mitigation model based on a systematic toolkit of strategies for handling the risks. For this purpose, a total of 10 key SCR-related risks have been recognized and prioritized using a detailed review of the literature and industrial expert's opinions. A risk mitigation methodology is presented for improving SCR through its relevant criteria, i.e. risks factors, based on the intensity of importance. This study focuses in determining and evaluating the key potential risks through the blend of mathematical multi-criteria decision-making (MCDM) methods namely fuzzy FMEA, fuzzy AHP, fuzzy TOPSIS, and sensitivity analysis. This study develops a novel approach for objectively projecting future supply chain risks that can be managed timely in achieving SCR. This study also contributed to fill the existing literature gap for prioritization of key risks in the TSCs. The results highlight how postponement in supply chain risks is identified as highly prioritized whereas, manufacturing risks are ranked as second highly prioritized, and disruption risk is ranked as the last one. The concerned stakeholders can adopt the proposed structured methodology as a way forward in formulating risk mitigation strategies and tackling the SC risks in achieving the optimal level of supply reliability. [ABSTRACT FROM AUTHOR]

Selecting a sustainable facility location is a crucial strategy for manufacturing companies to achieve long-term success in today's competitive environment. Various quantitative and qualitative criteria with different importance in a multiple level structure must be considered and aggregated to assist the company in decision-making. How to determine these criteria weights and select the sustainable manufacturing facility locations have become research questions. To resolve this problem, this paper proposes a total distance ranking approach to fuzzy analytic hierarchical process (AHP)-based multiple criteria decision-making (MCDM) method. Currently, the membership functions of fuzzy weighted ratings in the MCDM with a multilevel structure cannot be developed. A ranking method is needed to defuzzify those fuzzy numbers used for fuzzy AHP and qualitative criteria in the MCDM for better executing decision-making procedure. The total distance ranking method related to the centroid on x-axis, centroid on y-axis and the distances of centroids point to the two tangent lines of a fuzzy number are considered in the proposed ranking approach. Formulas of the proposed approach will be presented, and some properties will be investigated to derive formulas for trapezoidal and triangular fuzzy numbers. A comparison with relevant ranking methods will be made to show the advantages of the proposed ranking approach. The proposed ranking approach is then applied to defuzzify the fuzzy numbers used in fuzzy AHP and linguistic values under qualitative criteria to obtain the criteria weights under multi-level structure and crisp values under qualitative criteria, respectively. The final scores of alternatives can be obtained by aggregating crisp criteria values and their corresponding weights by simple additive weighting method to obtain the ranking result. A numerical example will be conducted to show the effectiveness of the proposed model. Finally, a comparison with Best-Worst method (BWM) will be presented to show the persuasiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Employability skills are a significant concern for both graduates and practitioners. However, there is limited research on identifying and prioritizing factors affecting employability from experts' perspectives, particularly in emerging economies. To prioritize the perceived employability skills of stakeholders', a hybrid fuzzy AHP-TOPSIS approach was used from the perspective of subject experts rather than just relying on the student's perspective. Criteria and sub-criteria are identified and finalized with the help of the literature and the expert's opinions. 45 experts' (industry, academician, and students) opinions are taken into consideration. Secondly, fuzzy AHP is implemented to get the weights of identified criteria and sub-criteria to rank them. Thirdly, these weights are used in the fuzzy TOPSIS approach to rank the five alternatives. 'Soft Skills' is the most important criteria and 'Personal Qualities' is the least important criteria having the normalized weight of 0.355 and 0.043 respectively. The most important sub-criteria among all sub-criteria are 'Innovation Skills' followed by 'Methodological Skills'. The least important sub-criteria is 'Self-Esteem'. This unique empirical study identifies factors impacting graduate employability, prioritizes criteria and sub-criteria, and recommends the optimal candidate using an integrated fuzzy AHP-TOPSIS approach. [ABSTRACT FROM AUTHOR]

The disassembly of end-of-life (EoL) products is of high concern in sustainability research. It is important to obtain reasonable disassembly depth during the disassembly process. However, the overall safety of the disassembly process is not considered during the disassembly depth optimization process, which leads to an inability to accurately obtain a reasonable disassembly depth. Considering this, a multi-objective disassembly depth optimization method for EoL smartphones considering the overall safety of the disassembly process is proposed to accurately determine a reasonable disassembly depth in this study. The feasible disassembly depth for EoL smartphones is first determined. The reasonable disassembly process for EoL smartphones is then established. A multi-objective function for disassembly depth optimization for EoL smartphones is established based on the disassembly profit per unit time, the disassembly energy consumption per unit time and the overall safety rate of the disassembly process. In order to increase solution accuracy and avoid local optimization, an improved teaching–learning-based optimization algorithm (ITLBO) is proposed. The overall safety of the disassembly process, disassembly time, disassembly energy consumption and disassembly profit are used as the criteria for the fuzzy analytic hierarchy process (AHP) to evaluate the disassembly depth solution. A case of the 'Xiaomi 4' smartphone is used to verify the applicability of the proposed method. The results show that the searchability of the non-inferior solution and the optimal solution of the proposed method are improved. The convergence speeds of the ITLBO algorithm are 50.00%, 33.33% and 30.43% higher than those of the TLBO algorithm, and the optimal solution values of the ITLBO algorithm are 3.91%, 5.10% and 3.45% higher than those of the TLBO algorithm in three experiments of single objective optimization. [ABSTRACT FROM AUTHOR]

The structure of underground coal mines is vulnerable to many mishaps because of the challenging conditions of production and the unique features of the earth. These incidents could cause significant financial and production losses for the mines in addition to worker injury, disability, or death. In coal mines, methane explosions are a frequent threat. Establishing a safe work environment requires managing these problems with an accident control method. The current study used the fuzzy TOPSIS and fuzzy AHP techniques for this aim. The framework was used to tackle the four-alternative problem of underground coal mine explosion control method selection. To identify potential risks of a methane explosion, a data gathering survey was conducted as part of the suggested hybrid methodology. The fuzzy AHP was used to compute the fuzzy weights of the hazards. "Improper ventilation system" is ranked highest out of the 34 sub-risk factors. The fuzzy TOPSIS was then utilized to rank the explosion control methods using the weights. To assess the viability of the study's conclusions, a sensitivity analysis was carried out. The findings indicate that "improving safety technology" and "financial investments" are the best ways to reduce such events. The results additionally indicate that the fuzzy TOPSIS approach in combination with the fuzzy AHP provides a helpful framework for dynamically assessing mine methane explosion accidents. [ABSTRACT FROM AUTHOR]

Land gets contaminated due to different human activities like illegal industrial discharges, mining activities, and spillage of chemicals. The pollutants released through these activities can have prolonged effects on the environment and human health. Therefore, there is a need for immediate remediation of the contaminated site. Different remediation technologies are available for remediating a land contaminated with a particular contaminant. Selection of the most appropriate remediation technology among all those available would help in quick and efficient remediation of the land. There are multiple factors deciding the appropriateness of a technology for a given case. 'Remediability' is a term introduced in the scientific literature recently to describe the ease with which a contaminated land can be remediated and 'Remediability Score (RS)' quantifies remediability in a 0–100 scale. The higher the value of RS, the greater is the difficulty for remediation. The factors influencing remediability were presented before a group of experts in a Delphi process for assigning comparative importance. From the importance score obtained in a Saaty scale of 1 to 9, the weights of factors were calculated using Fuzzy AHP. The overall RS was calculated by taking the weighted impact of the factors after their magnitudes were normalized. RS for the various remediation technologies feasible for a contaminated site, Kuzhikandam, near Kochi, Kerala was calculated. The site was revealed to be contaminated with heavy metals and organic compounds in a field investigation. The most suitable technology for remediating the selected site was found to be vitrification with an RS of 22. The next best technology, stabilization/solidification, had an RS of 25. The study showed that RS can be a reliable matric for selecting the most suitable remediation technology for a contaminated site. [ABSTRACT FROM AUTHOR]

Simple Summary: Beekeeping is an activity that supports agriculture and wildlife on earth, so it is very important to provide accurate information that is able to help in increasing the profitability of beekeeping and valorize pollination services. In this paper, a new methodology is proposed to assess beekeeping potential using Geographic Information Systems (GIS) and the Analytical Hierarchy Process. The proposed tool will support decision making by selecting the best apiary locations to maximize honey production and, consequently, the risks of losing bee colonies will be reduced. The Suitability map (apiary aptitude map) allows for validating the best locations for apiaries (considering the spatial and floristic resources use), and the aptitude for installing new apiaries or moving existing ones. In this sense, the application of Multi-criteria GIS Analysis, in the context of beekeeping planning, is a useful tool for the Beekeepers Association to manage honeybee resources within the territory in order to maximize their profit, and for government agencies to implement promotional measures and policies to maximize food support needs and mitigate spared diseases. Beekeeping management is greatly influenced by spatial factors (e.g., land use/land cover, roads, or electrical energy networks), so GIS are a powerful tool to overlap and relate a variety of spatial data levels and, consequently, a very useful tool for beekeeping activity planning. This study was developed within the intervention area of three controlled zones managed by Portuguese Beekeepers Associations. The methodology, based on multi-criteria decision analysis, integrates several criteria, such as hydrographic networks, road networks, soil occupation, solar radiation, and electromagnetic radiation sources. These criteria were proposed and evaluated through online questionnaires carried out with beekeepers. Concerning the selected criteria and the respective geographical data, the most relevant were land use/land cover and water availability, with a significance of 44% and 24%, respectively. The beekeeping suitability map enabled us to evaluate the degree of compliance for the actual location of apiaries, with 60% of the apiaries being installed in high potential areas. In the context of beekeeping planning, the potential of the techniques applied seems to be an important tool for optimizing the location of apiaries and the profitability of beekeeping. [ABSTRACT FROM AUTHOR]

This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes work itself, supervision, coworkers relationship, salary and benefit, career opportunities, job stress, perceived risk, and job insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are work itself, job stress perceived risk, and job insecurity. In addition, this study's results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions. [ABSTRACT FROM AUTHOR]

In today's digital age, businesses are tasked with adapting to rapidly advancing technology. This transformation is far from simple, with many companies facing difficulties navigating new technological trends. This paper highlights a key segment of a comprehensive strategic model developed to address this challenge. The model integrates various planning and decision-making tools, such as the Balanced Scorecard (BSC), Objectives and Key Results (OKR), SWOT analysis, TOWS, and the Spherical Fuzzy Analytic Hierarchy Process (SFAHP). Integrating these tools in the proposed model provides businesses with a well-rounded pathway to manage digital transformation. The model considers human elements, uncertainty management, needs prioritization, and flexibility, aiming to find the optimal balance between theory and practical applications in real-world business scenarios. This particular study delves into the use of SFAHP, specifically addressing the challenge of effectively selecting the most suitable strategy among various options. This approach not only brings a new perspective to digital transformation but also highlights the importance of choosing the right strategy. This choice is crucial for the overall adaptation of businesses. It shows how carefully applying the SFAHP method is key. Combining this with a successful digital transformation strategy is essential. Together, they provide practical and efficient solutions for businesses in a fast-changing technological environment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Turkish Operations Management (JTOM) is the property of Ankara Yildirim Beyazit University Journal of Turkish Operations Management (JTOM) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The purpose of this paper is to propose a disruption claim management (DCM) life cycle and a risk management framework to provide comprehensive guidance to construction practitioners for facilitating effective and efficient DCM. Design/methodology/approach: DCM life cycle was initially developed through a focus group discussion (FGD) with the participation of the construction practitioners who have diverse experiences about DCM. The life cycle is comprised of 6 phases and also includes proper reactions of the owners and contractors. Then, 42 risk factors that can impact the deliverables of DCM were identified through a literature review and an additional FGD session. This was then followed by a Fuzzy Analytical Hierarchy Process (FAHP) which was performed to evaluate the importance of each risk factor in terms of the factor's impact on the success of DCM. Additionally, consistency analysis was performed to further maximize the reliability of the results. Findings: Findings revealed that a proactive and systematic approach should be adopted and DCM practices should be initiated before any disruption event is triggered. Accordingly, the proposed framework recommends DCM practices to be initiated early in the contract development phase since compensation for the disruption might be recovered only to the extent that the contract permits. The contract-related risks were given top priority by the experts so that the results of the fuzzy AHP analysis also verified the significance of the contract development phase. Besides contract-related risks, risks related to insufficient site observation, ignorance of the project team, cognitive bias and conflict of interest were determined as the most significant DCM risks, needing an urgent and sophisticated risk response plan. Lastly, results suggested that "Site observation and record-keeping" is the most formidable phase since the phase's implementation on a continuous basis could create unforeseen organizational challenges such as mismanagement of project records, especially in the dynamic and turbulent environment of the construction projects. Originality/value: Disruption – which is caused mostly by change – is inevitable in construction projects due to their sophisticated nature. DCM, therefore, becomes crucial to compensate losses of contractors and eliminate or diminish the prolonged dispute resolution process. Existing studies, however, do not provide a comprehensive theoretical basis for the DCM life cycle and DCM life cycle's potential risks so that DCM life cycle's promising benefits can hardly be materialized. Thus, developing a DCM life cycle and associating DCM life cycle with risk management, this study is highly believed to make a promising theoretical contribution to the DCM domain since this is one of the earliest attempts in the literature. Additionally, this research provides construction practitioners with an insight into the effective implementation of DCM practices in construction projects. [ABSTRACT FROM AUTHOR]

This paper presents a flexible framework that aims at estimating the risk of structural failure in sewer pipes by utilizing limited or imperfect data. To this end, classical risk analysis is enhanced by incorporating fuzzy logic and multi-criteria decision making. To account for the multi-dimensionality of collapse risk at the pipe level as a decision parameter, its distinct impacts on the environment, traffic and road condition, and quality of life are taken into account. The proposed method is applied to the sewer network of Tehran, the capital of Iran. Results show how the integration of different risk indexes can influence the criticality of pipelines for the selection of rehabilitation activities. While using the first individual risk index, only considering the risk posed to the natural environment by a collapsing pipe in terms of contamination, approximately half of the pipe lengths are classified as extremely critical by the clustering algorithm. However, when the integrated risk is calculated, this cluster encompasses only approximately 30% of the total pipe length. With a database that contains various levels of uncertainty (from 10 to 60%), the predictive reproducibility for the exact same risk cluster is above 20% and above 50% for the same or only marginally better or worse. Furthermore, pipelines that are predicted to have a better risk class than the situation without considering uncertainty, thereby underestimating the likelihood of failures or consequences, are below 15%, showing a measure of quite good robustness. Considering the budget constraints of utilities, the proposed method can be applied to any urban, aiding in the identification of high-risk sections. Nevertheless, incorporating physical validation might be beneficial for further improving the analysis. [ABSTRACT FROM AUTHOR]

The construction industry has a significant multiplier effect on the economy as a whole. It provides the basis upon which other sectors can grow by constructing the physical facilities required for the production and distribution of goods and services. Building construction projects is one of the major development constraints in developing countries since their development highly depends on the growth of their physical infrastructures. Developing countries allocate a considerable amount of their scarce financial resources towards the development of their infrastructure needs. However, most of these infrastructure projects in developing countries encounter considerable quality management controlling problems, especially in public building construction projects. These results in decreasing customer satisfaction, lower productivity, and decreased service delivery times. Thus, the study focuses on exploring fuzzy AHP approaches for quality management control practices in public building construction projects. The data analysis for this study was carried out by using fuzzy AHP methods. This method is used to determine the preference weights of the input variables and for ranking. To achieve the objective, the data were collected from primary and secondary sources. Microsoft Excel was used as an analysis tool. The study revealed that quality management plans and quality management control tools are identified as mostly practiced quality management control systems in public building construction projects. Finally, it can be recommended that the project participants implement and communicate the organization's mission, vision, strategy, policies, and processes throughout the organization to enhance the productivity of the projects. [ABSTRACT FROM AUTHOR]

Air pollution exerts a profound impact on both public health and the natural environment. In India, festivals like Diwali also contaminate the air by releasing pollutants into the atmosphere. It is essential to identify the most polluted region by estimating these pollutants. Since air quality assessment involves multiple air pollutants, there may be inherent uncertainty associated with data. This study employs a fuzzy Multi Attribute Decision Making (MADM) framework fuzzy Analytical Hierarchy Process-Entropy-fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FAHP-Entropy-FVIKOR) to model the impact of air pollution as a decision-making problem to address the uncertainty and assess the air quality during the Diwali festival from 2019 to 2021 in Tamil Nadu, India. An integrated weighting approach is utilised to determine the weights of the air pollutants using a fuzzy Analytical Hierarchy Process and Entropy methods. Mainly, the fuzzy VIKOR approach is employed to rank the polluted regions. The validation of the proposed model is established through a comparative analysis using Spearman's rank correlation with two other existing fuzzy MADM methods. Furthermore, a sensitivity analysis is conducted to evaluate the influence of priority weights and the interdependence of pollutants in determining regional rankings. The results conclude that a strong positive correlation is attained between the proposed and existing methods and the highest levels of air pollution during the festival period are observed in Gandhi Nagar (2019), Rayapuram (2020), T. Nagar, Sowcarpet and Triplicane (2021) in their respective years. These findings substantiate the consistency and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Purpose: Identifying the barriers that hinder the circularity in the wine industry in Bulgaria and proposing a preliminary circular economy (CE) index for ranking in order of importance the barriers for providing a suitable and replicable model through the contextualization of the study applied at the territorial level. Design/methodology/approach: The article adopts a Fuzzy AHP methodology based on 6 main barriers and 19 sub-barriers to find the weights of the barriers and rank them. The study was conducted in Bulgaria, and it consists of a questionnaire with pairwise comparisons to ask for expert opinions of members of the Executive Board of the National Association of Bulgarian Vinegrowers and additional members of the regional vine and winegrowing chambers. Findings: The study identifies training and education and environmental barriers as the most important among the main barriers whereas, economic barriers are assessed as low impact. Considering the sub-barriers, lack of consumer awareness and interest, unclear taxation for CE, lack of knowledge about environmental emissions (carbon, water etc.) within the supply chains, and lack of digital trends are determined as the most significant sub-barriers. Research limitations/implications: The preliminary CE index can be practically used and tested, when necessary, by each winemaker according to their understanding and opinion of CE barriers and sub-barriers. The ranking within the CE index can lead winemakers also to decisions related to the company's social policy. Originality/value: The study uses the Fuzzy AHP methodology with expert opinions to analyze and weigh the main barriers to achieving CE at the micro-level. [ABSTRACT FROM AUTHOR]

Copyright of Social Sciences Studies is the property of Social Sciences Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the present marketing environment, choosing the right suppliers is very difficult for any construction company. Current supplier selection models in the construction industry often suffer from limitations such as incomplete criteria coverage, inadequate handling of uncertainties, and oversimplification of decision-making, leading to sub-optimal supplier choices and project risks. This paper aims in selecting the best suppliers among the different M-Sand environment suppliers. In this study 13 qualitative criterions are selected by the expert team. For handling the attributes, uncertainties, vagueness associated with supplier selection problems the Fuzzy Delphi, Fuzzy Analytical hierarchal Process (AHP) and Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) methods were chosen. In the first phase of this study, Fuzzy Delphi Method is employed to select the 5 significant criterions. These criterions can be used to help the construction company in the direction to choose the right suppliers at the end. During the second phase, one of the significant Multi-criteria Decision Making Method called AHP is employed with extended support of fuzzy logic to evaluate the weightage of each criterion. Further ranking of various alternative suppliers are done by Fuzzy TOPSIS model. The ranking results indicate that A2 is the best supplier followed by A1 and A2. The third phase of this study deals with analyzing both the qualitative and quantitative criteria, hence Data Envelopment Analysis (DEA) is adopted to correlate the criteria. This is done to select efficient suppliers. The develop model is demonstrated in the construction industry. [ABSTRACT FROM AUTHOR]

Walkability is an important aspect of the built environment, influencing the degree and intensity of walking. Very little research effort has been made in cities of developing countries like India to incorporate the user's perspective in evolving walkability indices. This research study is an attempt to develop a walkability index from the user's perspective in a developing environment, which shall aid the city planners in evaluating the quality of the walking environment objectively and systematically. For the development of the walkability index in the present study, empirical investigations were carried out in the Dwarka sub-city comprising street surveys incorporating pedestrian perspective and pedestrian counts. A fuzzy analytical hierarchy process with extent analysis has been performed, incorporating user ratings on critical walkability parameters to estimate the criteria weights and evolving a new path-level walkability index. It is concluded that this index exhibits a better correlation with pedestrian count when compared to the walkability index based on the existing prevalent approach adopted in the Indian context. The new walkability index will aid city planners in identifying specific pedestrian-related shortcomings as well as assist in evolving informed decision making to prioritize infrastructure investments. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agroindustrial Technology / Jurnal Teknologi Industri Pertanian is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The study aims to facilitate the medical tourists visiting emerging countries for various kinds of ailments by ranking the possible destinations to avail medical treatments. Design/methodology/approach: A Fuzzy Analytical Hierarchical Process (FAHP) with a mixed-method approach is applied to analyze data collected from patients and substantiate it with medical tour operators in India to gain managerial insights on the choice-making patterns of the patients. Findings: India is a preferred emerging market location due to the low cost and high medical staff quality. India offers value for money, whereas Singapore and Thailand are preferred destinations for quality and technology. Research limitations/implications: The study will facilitate the emerging markets' governments, hospitals and medical tourists to understand the importance of various determinants responsible for availing medical treatment outside their country. Practical implications: The study recommends that cost and quality care are the patients' prime focus; government policies must provide clear guidelines on what the hospitals and country environment can offer and accordingly align the marketing strategies. Originality/value: This study is the first attempt to rank various factors affecting medical tourism using the FAHP approach. [ABSTRACT FROM AUTHOR]

The fishing shipyard in Banda Aceh City is a privately owned shipyard and is managed in a family manner. The shipyard here is active in carrying out maintenance, repair and construction of new ships when there is demand from consumers. The shipyards in Banda Aceh City generally make ships made of wood. The problem that is currently being faced is that there are many abandoned ships due to lack of finance, natural resources, human resources and environment, this is an obstacle to the progress and development of shipyards. The purpose of this study was to determine the inhibiting factors that exist in shipyards in the city of Banda Aceh and find alternative solutions to these problems. The method used in this study was a survey method used to look at existing symptoms and collect data on the factors related to research variables and then analyzed using the Fuzzy AHP method. The results of this study indicate that the financial inhibiting factor is the most influential factor in shipyards with a resulting value of 0.4635, the inhibiting factor of Natural Resources is worth 0.35675, the inhibiting factor of Human Resources is worth 0.2865 and the inhibiting factor from the environment is the inhibiting factor which is the lowest or less influential with a value of 0.14325. The alternative solutions to financial problems are capital loans and investments. An alternative for natural resources is the addition of a minimum stock to anticipate stock scarcity and delays in the delivery of materials and tools. The alternative for human resources is the existence of an office, organizational structure, and division of tasks as well as raising awareness of occupational health and safety. As for the alternatives for the environment, namely the need for buildings or installation of tarpaulins for the areas where ships are built, good land management and studies of other natural impacts. [ABSTRACT FROM AUTHOR]