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Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office 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, it was aimed to select the most suitable dowelled-leg-and-rail joint (DLRJ) type with multi-criteria decision-making (MCDM) techniques. For this purpose, five types of DLRJ with staggered-rail, flush-rail, lapped-rail, elevated-rail, and mitered-and-lapped-rail were selected as the decision-alternatives and 4-variables consisting of strength, cost, capacity and aesthetics were determined as the decision-criteria. To obtain data, sample tests for the strength values, a work-study analysis for the capacity and cost values, and a questionnaire were performed for the aesthetic superiority values of the joints. In prioritization of the decision criteria and selection and ranking of the alternatives, Criteria Importance through Intercriteria Correlation (CRITIC) + Additive Ratio Assessment (ARAS) hybrid method was used. According to the questionnaire, the most aesthetically pleasing joint was the DLRJ with flush-rail while the DLRJ with lapped-rail was the lowest priority joint type. According to the results of the CRITIC application, strength was the top priority criterion in the selection. The cost, the capacity and the aesthetics followed this respectively. According to the results of the ARAS application, the DLRJ with mitered-and-lapped-rail was optimal while the DLRJ with lapped rail was the last choice option. An increase in the number of criteria, the variables of criteria and the analysis values of these variables are effective factors in the results. [ABSTRACT FROM AUTHOR]

Copyright of Command Control & Simulation / Zhihui Kongzhi yu Fangzhen is the property of Command Control & Simulation Editorial Office 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.)

Objective: The aim of the current research is to identify the effective factors on the cultural model of good governance in government performance monitoring agencies using the Fuzzy ANP method. Methodology: This research is considered applied in terms of its goal and is of a mixed nature. The research population, in a qualitative framework, consists of academic experts and specialists in government performance monitoring agencies, of which 10 individuals were selected through purposive judgment sampling. The data collection tool in this research is the Delphi questionnaire. Findings: The main factors affecting good cultural governance were identified based on the research background and expert opinions, based on structure, law, and value, and a total of 11 sub-criteria were also determined for the main factors. Conclusion: The results of the research indicate that the legal dimension was the most significant factor affecting the cultural model of good governance in government performance monitoring agencies, followed by value and structural factors in subsequent ranks. The main reasons affecting good governance based on culture relate to professional ethics, the suitability of culture with requirements, and the presence of a value system. In this regard, the enumeration of ethical principles in the organization and their institutionalization can be effective. [ABSTRACT FROM AUTHOR]

Introduction: Global climate changes, primarily manifested as global warming and rapid urbanization, exacerbate extreme weather events. Statistics indicate that floods are among the most prevalent and catastrophic natural disasters (Safiah Yusmah et al., 2020: 552). Urban floods caused by heavy rainfall have evolved from gradual accumulation to sudden surges (Masozera et al., 2007: 299; Hallegatte et al., 2013: 802). Therefore, urban flood resilience, crucial for flood control and disaster reduction, has garnered increasing research focus (Obrist et al., 2010: 284; Xu et al., 2018: 5298). The Sendai Framework for Disaster Risk Reduction (2015-2030), endorsed by the World Conference on Disaster Risk Reduction in 2015, and the 2018 Beijing Resilient City Development Plan, underscore the importance of enhancing urban resilience to disasters (Sun et al., 2022: 1). To address the growing risk of natural events, it is essential to strengthen capacities that enable vulnerable communities to better prepare for, cope with, and recover from adverse effects. In disaster management literature, this strategy is commonly referred to as resilience. Resilience, when applied to communities, is defined as “the ability of a community to prepare for, plan, absorb, recover, and adapt to actual or potential adverse events in a timely and efficient manner, including rebuilding and improving essential functions and structures.” A resilient community incurs fewer losses and recovers more swiftly from hazardous events (Cutter et al., 2014: 65; Abdali et al., 2022: 6). Theoretical Framework: The concept of resilience originated from Holling’s seminal work in ecology, aimed at understanding the instability and dynamics of nature. According to Holling, resilience is “the measure of a system’s ability to absorb change and disturbance while maintaining the same relationships between populations or state variables.” However, resilience is not simply “the ability of a system to return to equilibrium after a temporary disturbance” (Holling, 1973: 14-17). In ecological literature, two definitions of resilience emerged: one that encompasses continuity, change, and unpredictability in a nonlinear and non-equilibrium system (ecological resilience), and another that focuses on efficiency, stability, and predictability in a single equilibrium system (engineering resilience) (Holling, 1996: 25; Folke, 2006: 256). Engineering resilience emphasizes rapid and efficient recovery post-disturbance, while ecological resilience is about absorbing changes and ensuring continuity (Pickett et al., 2004: 373). Methodology: This study employs a combined multi-criteria decision-making approach using the Analytic Network Process (ANP), DEMATEL technique, and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). The DEMATEL-ANP model identifies internal relationships between indicators, allowing for pairwise comparisons and weight evaluation, while PROMETHEE ranks solutions based on their proximity to the ideal solution, with the best solution being closest to the ideal point (Chen et al., 2011: 909; Chiu et al., 2013: 49; Thor et al., 2013: 27; Ju et al., 2015: 348-349). Results and Discussion: Resilience in Khorramabad exhibits a clear spatial pattern, with higher resilience in affluent upper city areas and lower resilience in less affluent lower city areas. This disparity highlights the inequitable distribution of urban facilities and services, emphasizing the need for equitable development and access to vital resources. Economic resilience is surprisingly lower in the city’s economic center due to deteriorated infrastructure and the residence of lower socioeconomic strata. Institutional resilience is higher in central areas, benefiting from the concentration of governmental, private, and grassroots organizations. Peripheral areas suffer from inadequate infrastructure, resulting in lower overall resilience. Social capital resilience lacks a specific spatial pattern, with most areas rated as medium to low, indicating weak community connections. Environmental resilience shows that city center areas are more prone to flooding, while higher resilience is observed in different parts of the city, possibly due to land permeability and river positions. Comparative analysis reveals that regions 1, 4, 7, 13, and 17 have the lowest resilience, while regions 23 and 14 rank high. This analysis provides a comprehensive understanding of resilience levels at the city scale, identifying areas requiring further intervention. Conclusion: Mapping the results reveals distinct spatial patterns of resilience and identifies hotspots needing more intervention. Central and western regions, with lower resilience, require more attention. Environmental and infrastructural factors are key, directly relating to land use and planning. The findings can assist Khorramabad’s urban planning organizations in integrating disaster resilience into urban planning, transforming reactive plans into proactive adaptation strategies. Additionally, identifying potential hotspots can aid emergency management institutions in effective disaster risk management. Enhancing social resilience is crucial for community capacity building to prepare for, respond to, and adapt to climate change impacts, guiding local stakeholders in fostering fair development and equitable resource access. [ABSTRACT FROM AUTHOR]

Floating cities have emerged as an efficient long-term solution over unsustainable practiced solutions to combat the rising seas problem; nevertheless, the world lacks an international, official, and comprehensive framework regarding floating cities. Although previous research approached modular floating city design; however, resulted in configurations with various critical design restrictions mainly regarding interlocking capabilities and space utilization. The purpose of this paper is to offer a new systematic strategy for configuring modular and expandable floating cities without such restrictions. This paper explores Euclidean tilings as a strategy to offer numerous configurations based on regular, semi-regular, and demi-regular tilings. Selecting the ideal configuration is complicated; therefore, both quantitative and qualitative data methods were implemented to attain the objectives. Via an extensive literature review, this research derives key factors for configuring floating cities, then sets a brainstorming session with experts for group decision making before providing findings upon calculations via analytic hierarchy process, one of the most used quantitative data methods of multiple-criteria decision analysis. Through comprehensive literature review: seakeeping, modularity, zoning and circulation, and feasibility have been identified as the most significant criteria in floating city research. It explores the qualities and limitations of triangular, squared, hexagonal, octagonal, and dodecagonal platforms. Regarding criteria, seakeeping was the most significant criterion for platform selection by 53.6%. Regarding platforms, the hexagonal platform scored the highest with 25.31%. Relying on this method and the design considerations presented, numerous dynamic configurations can be offered and assessed through specific contexts without any of the past restrictions. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a methodology for identifying urban neighborhoods with severe housing deprivation (SHD) in Iran. The study, in addition to the housing physical determinants and overcrowding, considers household's socioeconomic characteristics as an integral dimension of SHD. It proposes a methodology that adopts census-based data and data-pooling strategy to map the spatial distribution and clustering of housing deprivation (HD) within five selected cities in Iran. First, a hybrid Factor Analysis and Analytic Network Process (F'ANP) model is used to construct a composite housing deprivation index (HDI) composed of eight HD indicators. The composite HDI is then validated using the leave-one-out cross validation method in discriminant analysis, correlation and regression analyses. Second, the composite HDI scores are classified into five categories using standard deviations. Then, spatial data analyses are performed to investigate the presence of spatial autocorrelation. The results confirm that HD in the selected cities is spatially autocorrelated and have a statistically significant pattern of spatial clustering that includes five distinct categories. The neighborhoods that belong to the HD hot spots are considered as the neighborhoods with SHD. The identification and spatial distribution of the neighborhoods characterized by different levels of HD, not only provide a deep knowledge about the existing housing situation, but also can effectively support the revision of the housing planning strategies and actions both the national and local levels. The developed methodology could be replicated for the identification of areas with SHD in the cities of Iran and other developing countries. [ABSTRACT FROM AUTHOR]

Compared with intellectualization, lean is what family small- and medium-sized enterprises (SMEs) should pay more attention to and complete. Lean management implementation (LMI) can lead to better performance, but can be detrimental to non-economic goals, such as socioemotional wealth (SEW) associated with family control. The contradiction between economic goals and non-economic goals makes LMI become a multi-criteria decision-making problem in family SMEs. To address this problem, we propose an evaluation model combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based Analytic Network Process (DANP), and Viekriterijumsko Kompromisno Rangiranje (VIKOR) method. The evaluation model can be used to evaluate and select the optimal lean management scheme that meets the SEW preferences and lean management preferences of family SMEs. Moreover, the evaluation model can also be used to provide targeted improvement suggestions for LMI to improve innovation performance. We construct an evaluation framework based on practical criteria from both lean tools and SEW carriers. These practical criteria can correspond to the activities and goals of the LMI, ensuring the usefulness of the evaluation model. In addition, taking a family SME as an example, we conducted case analysis and sensitivity analysis to verify the evaluation model. The study results provide an important reference for family SMEs to implement lean management. [ABSTRACT FROM AUTHOR]

Many nations are creating E-courts to simplify court operations. However, religious e-Courts take more work to execute. This study has identified religious court e-Court implementation issues and solutions using Delphi and ANP. It first employed Delphi and a literature review to interview experts face-to-face. Eight judges, I.T. workers, and attorneys from three religious court districts analysed the model using a priority scale with an Analytic Network Process (ANP). The study found that infrastructure or equipment from the application of the e-Court system is the main issue, with a geometric mean of 0.306, followed by Human Resources (0.262), the system (0.219), and regulation (0.213). Improving e-Court system regulation (0.850) and infrastructure were the primary solutions (0.770). This paper details cluster priority solutions and issues. This study suggests that the highest religious court authority focuses on infrastructure, human resources, e-Court operational systems, and associated legislations. The government must adopt the e-Court system and registration laws to encourage more active socialising. The study prioritises e-Court implementation issues in the religious courts of Indonesia.

In recent decades, the issues of ecology and environmental sustainability have become a global concern in contemporary urban design. Among various urban elements, water features play a significant role in improving the ecological characteristics of their surrounding environment, especially in hot and arid areas. The aim of this study is to evaluate the ecological characteristics of urban water features comprehensively and quantitatively, which has been overlooked in previous studies, taking their physical characteristics into account. To this end, a multicriteria decision-making method, an analytic network process, was proposed to quantitatively evaluate the ecological characteristics of water features. In this approach, four ecological criteria—microclimate, biodiversity, greenery, and human wellbeing—and ten physical characteristics of water features were considered. Twenty-one experts were asked to complete a questionnaire for pairwise comparisons of all ecological criteria and the influence of physical characteristics. The results showed that vegetation and scale, with the relative influencing values of 0.255 and 0.188, respectively, were identified as the most decisive features influencing ecological criteria. Conversely, texture, with a value 0.023, had the least impact. Moreover, it was shown that water features have the greatest impact on the microclimate compared with other ecological criteria. The results were used to compare water features at the Koohsangi Transregional Park, located in a hot and arid city of Iran. The results of this study lead to a framework that can help urban designers integrate ecological criteria into water feature planning to enhance urban ecology and sustainability.

The risk of both fatal accidents and non-fatal injuries in the construction industry is significantly high in most countries. To reduce this construction safety risk, the proper use of personal protective equipment (PPE) is one of the major measures on the jobsite. In this research, in order to comprehensively assess the PPE plans, a three-phase framework was proposed to identify the optimal solution for PPE planning from a set of alternatives. As a result, four main criteria and fifteen sub-criteria were identified based on a systematic literature review, and a decision-making model integrating the analytic network process (ANP) and VIekriterijumsko KOmpromisno Rangiranje was developed. As the assessment information in the survey was incomplete and vague, the fuzzy sets theory was adopted to transform the linguistic terms into fuzzy numbers for evaluation. The model further calculated the weight of each criterion and prioritized the potential PPE plan alternatives. Finally, the presented model was implemented in a case study to verify its feasibility and applicability for practical construction management. The proposed method enables the selection of the most compromising solution as the optimal PPE plan. This research assists decision-makers and safety planners at construction workplaces to improve the overall safety performance and reduce accident risks, which significantly contributes to construction safety management and practice.

The aim of this study was to study the impact of artificial intelligence (AI) on enterprises in terms of strategy, technology, business operations, and organizational management. This study used grounded theory analysis to identify the influencing factors of AI technology application maturity in Chinese enterprises. Taking Chinese film and television enterprises as an example, this study constructed an AI technology application maturity evaluation index system for enterprises based on the analytic network process (ANP) and evaluated the application maturity of AI technology in enterprises in terms of enterprise strategy, technology, business operations, and organizational management. To comprehensively evaluate and empirically analyze the application maturity of enterprise AI technology, this study calculated the index weight based on the ANP, and combined it with the fuzzy comprehensive evaluation method to construct a comprehensive evaluation model. The research results showed that intelligence strategy was the element that was believed to be most affected by the maturity of enterprise AI technology. For technology, intelligence technology and equipment were the elements that were believed to be affected the most. For business operations, smart shooting was the element that was believed to be affected the most. With respect to organizational management, corporate culture was the element that was believed to be most affected. The results showed that the proposed methods for evaluating the application maturity of enterprise AI technology are scientific and effective. The results of this study provide a reference for promoting the application of AI, implementing the intelligence transformation, and enhancing the core competitiveness of enterprises.

In recent years, the software production industry has experienced significant changes largely caused by extensive growth of globalisation, outsourcing, and competitive pressure. With these changes, risks in the software supply chain (SSC) have become a growing concern. Such risks include product tampering during development or delivery, potential compromises in quality and assurance due to software defects, production delays, and increased production costs. In this context, this study is aimed at evaluating the primary risks in the software supply chain using Bayesian belief networks combined with the analytic hierarchy process and noisy-OR (a generalisation of the logical OR) techniques to reduce the number of queries required of a given decision maker. A numerical example was presented to illustrate the application in which software suppliers were ranked according to their level of risk. The results indicated that, by using the proposed model, decision makers would be able to select a low-risk supplier by evaluating the probability of system failure caused by tampering or the introduction of defective code in the software. In addition, the proposed approach contributes to a better understanding of the risk main factors in an SSC and could be used to support managerial decision-making related to software products. [ABSTRACT FROM AUTHOR]

Carrier selection is a complicated problem as it includes many quantitative and qualitative criteria. Due to the complexity of this issue, many criteria that influence decision making interact with each other, making it necessary to consider these interactions in order to make the best decision. The analytical network process (ANP) method enables us to solve the carrier selection problem of decision making more effectively and realistically. This study, which aims to contribute to the research field, employs the previously unused ANP method, which permits criteria interaction, and investigates the carrier selection problem in order to determine the similarities and differences between different industries' expectations of ocean container carriers. In this context, this study has been applied in three different industries: textiles, white goods, and chemicals. In this way, the study contributes to the literature on ocean container carriers. From the results, the most important criterion for the three shipper groups was found to be reliability. However, there were significant differences in the ranking of other criteria.

University campuses, characterized by their urban amenities, socio-cultural atmosphere, and diverse user population, play a significant role as public places in small cities. The physical layout of campus locations influences our views toward schooling. The concept of an inclusive campus climate refers to how people and groups perceive and interact with the environment within the campus community. The campus atmosphere encompasses the variety of people, their unique experiences, and the interpersonal contact among them. The membership functions of type-1 (T1) fuzzy sets (FSs) are represented in two dimensions, whereas the membership functions of type-2 (T2) FSs are represented in three dimensions. The introduction of this new third dimension allows for the direct modeling of uncertainties by providing more degrees of freedom. In addition, the membership value of T2 FSs is more adept at managing ambiguities. In this paper, an interval type-2 fuzzy analytic network process (IT2 FANP) is used to evaluate the weight of criteria decided by experts in the evaluation of campus climate factors with trapezoidal fuzzy numbers. The aim of this paper is to evaluate the campus climate factors using an IT2 FANP methodology. For this problem, the three main criteria and nine subcriteria were defined by experts. Therefore, the ranking of main criteria is "Physical Environment" > "Conceptual Environment" > "Administrative Environment", and the ranking of subcriteria is found as "Social Environment" > "Exterior" > "Interior" > "Cultural Environment" > "Psychological Environment" > "Inclusive Goal and Perception" > "Economic Factors" > "Accreditation" > "Legislation on Inclusive Design" by IT2 FANP methodology. [ABSTRACT FROM AUTHOR]

Appropriate tree fertilization with essential nutrients is considered as one of the major factors in enhancing the quality and quantity of horticultural crops. The most efficient way to fertilize trees is to dig holes around the trunks and fill them with appropriate chemical and organic fertilizer. Doing this operation with mechanized methods reduces costs and increases productivity compared to traditional methods. In the present study, multi‐criteria decision‐making (MCDM) methods, including deterministic analytical hierarchy process (AHP) and fuzzy analytical hierarchy process (FAHP), technique for order of preference by similarity to ideal solution (TOPSIS), fuzzy TOPSIS (FTOPSIS), and analytic network process (ANP), were used to score and select the appropriate fertilizing method for apple trees based on the growers and expert's perspectives. The criteria, including fertilizing operation cost, crop yield, the percentage of tree damages, ease of entering and moving fertilizing equipment in tree rows, field capacity (with or without machinery), comfort and safety of fertilizing operations, after‐sales service, access to the required machinery and implements, crop selling price, and crop quality, were used in the above‐mentioned methods. The fertilization methods (Hole digging) considered in the present study were traditional fertilization (Shovel), orchard Trencher, motor hole digger, fixed centerline tractor‐mounted hole digger, and off‐set tractor‐mounted hole digger. Based on the results, the priority of mechanized fertilizing methods was determined as tractor‐mounted hole diggers (AHP weight of 0.286, FAHP weight of 0.285, TOPSIS relative proximity of 0.65, and FTOPSIS relative proximity of 0.64), fixed centerline tractor‐mounted hole diggers (AHP weight of 0.219, FAHP weight of 0.158, TOPSIS relative proximity of 0.56, and FTOPSIS relative proximity of 0.62), motor hole diggers (AHP weight of 0.171, FAHP weight of 0.079, TOPSIS relative proximity of 0.46, and FTOPSIS relative proximity of 0.31), and orchard trenchers (AHP weight of 0.12, FAHP weight of 0.057, TOPSIS relative proximity of 0.19, and FTOPSIS relative proximity of 0.20), respectively. Based on the ANP method, off‐set and fixed centerline tractor‐mounted hole diggers had the highest priority (weights of 0.43 and 0.27), followed by trencher (weight of 0.16), motor hole diggers (weight of 0.09), and the traditional method (weight of 0.04). Results showed that applying orchard tractors equipped with mounted diggers, especially off‐set types, can play an important role in enhancing the quantity and quality of apples produced, as well as reducing the costs of fertilizing operations. [ABSTRACT FROM AUTHOR]

The multi-energy complementary ecosystem is an important form of the modern energy system. However, standardized evaluation criteria and the corresponding method framework have not yet been formed, resulting in unclear standards and irregular processes of its construction. To cope with this issue, a novel comprehensive evaluation framework for multi-energy complementary ecosystems is proposed in this study. First, a 5D comprehensive evaluation criteria system, including environment, economy, technology, safety and systematicness, is constructed. Then, a novel multicriteria decision-making model integrating an analytic network process, entropy and preference-ranking organization method for enrichment evaluation under an intuitional fuzzy environment is proposed. Finally, four practical cases are used for model testing and empirical analysis. The results of the research show that the unit cost of the energy supply and the internal rate of return indexes have the highest weights of 0.142 and 0.010, respectively. It means that they are the focus in the construction of a multi-energy complementary ecosystem. The net flows of four cases are 0.015, 0.123, –0.132 and –0.005, indicating that cases with a variety of energy supply forms and using intelligent management and control platforms to achieve cold, heat and electrical coupling have more advantages. [ABSTRACT FROM AUTHOR]

The optimization of the production scheme for enhanced geothermal systems (EGS) in geothermal fields is crucial for enhancing heat production efficiency and prolonging the lifespan of thermal reservoirs. In this study, the 4100–4300 m granite diorite stratum in the Zhacang geothermal field was taken as the target stratum to establish a numerical model of water-heat coupling of three vertical wells. However, relying solely on numerical simulation for optimization is time-consuming and challenging for the determination of the globally optimal production plan. The present study proposes a comprehensive evaluation method for optimizing the performance of EGS power generation based on the integration of particle swarm optimization with backpropagation neural network (PSO-BPNN) and analytic hierarchy process (AHP). Five different PSO-BPNN models were constructed based on the numerical simulation data to predict different EGS power generation performance indexes, including the production temperature, the injection pressure, the total electricity generation, the electric energy efficiency and the levelized cost of electricity. Based on these PSO-BPNN models, the weights of various thermal development evaluation indexes were calculated by AHP to conduct a comprehensive evaluation of the power generation performance of the three vertical wells EGS. The results show that the PSO-BPNN model has good prediction accuracy for EGS prediction of various performance indicators, with a coefficient of determination (R2) exceeding 0.999. The AHP evaluation of all production schemes reveals that the optimal power generation scheme entails a well spacing of 580 m, water injection rate of 56 kg/s, injection temperature of 38 °C and fracture permeability of 2.0 × 10−10 m2. Over a span of 30 years, this scheme can provide a total power generation capacity amounting to 1775 GWh, with an associated LCOE value of 0.03837 USD/kWh. This not only provides a reference for the development and optimization of geothermal systems in the Zhacang geothermal field but also provides a new idea for the optimization design of other geothermal projects. [ABSTRACT FROM AUTHOR]

In developing countries, informal settlements are mainly located in floodplains and wetlands; hence, they are frequently affected by floods. The objective of this study is to demonstrate a methodological approach that integrates the community members' local and indigenous knowledge and GIS-based multi-criteria decision-making using the Analytic Network Process in mapping flood vulnerability in an informal settlement. The study was conducted in Quarry Road West informal settlement located in Durban, South Africa. A mixed-method approach that involved a household survey (n = 359), interviews with key informants (n = 10) and focus group discussions (n = 2) was used in this study. This study's results showed a spatial differentiation of flood vulnerability in the study area. Households along the Palmiet River were highly vulnerable to flooding. A section of the settlement called Mcondo 1 was also highly vulnerable to flooding while maMsuthu had low flood vulnerability. The sensitivity analysis results showed that changing the indicator weights, correspondingly, affected the output of the flood vulnerability map. Therefore, this study can guide decision-makers on how to elicit adequate community participation and comprehensively integrate local and indigenous knowledge with Geographical Information System in mapping flood vulnerability in informal settlements. [ABSTRACT FROM AUTHOR]

Paying attention to sanitary landfill methods and calculating their potential risks are the most logical tools to avoid waste risks. The reduction of environmental consequences caused by unprincipled landfilling, reduction of economic costs of the municipal waste management (WM) system, etc. is among the most important advantages of environmental risk assessment for sanitary landfill which is possible by detecting and evaluating the risks of sanitary landfilling. Therefore, the present research assessed the environmental risk of the sanitary landfilling of Tehran city as a case study. The research was applied-developmental in terms of purpose and detected and classified risks using interviews with experts, qualitative analysis, and previous studies. Finally, the priorities of the main risk clusters in sanitary landfilling were calculated using the analytic network process (ANP). In sanitary landfilling, chemical risks with a weight of 0.289 were ranked first, social risks with a weight of 0.259 were ranked second, and physical risks with a weight of 0.182 were ranked third. In the present study, it was sought to provide preventive and corrective measures by prioritizing the risks to minimize the risks that might occur in the Aradkuh Kahrizak landfilling site in Tehran and spread to other regions due to sanitary landfilling, thereby making it easier for managers to make decisions on waste management in the region and Tehran. [ABSTRACT FROM AUTHOR]

Earth and rock dams are susceptible to various uncertainties during their operational and managerial phases, necessitating timely assessment of their structural integrity to ensure proper safeguarding. In pursuit of an expedient, accurate, and quantitative method for evaluating the health condition of earth and rock dams, this paper introduces a novel approach based on the Analytic Network Process (ANP) unascertained measure theory, along with delineating specific evaluation procedures. Initially, an intricate risk assessment framework for earth and rock dams is constructed, comprising six distinct facets: project quality, operational management, flood damage, instability and damage, penetration Sabotage and other risk factors. Subsequently, the evaluation indices' risk values are ascertained through the application of the unconfirmed measure model, which amalgamates diverse information sources, including numerical computations, inspections, and testing. Further refinement is achieved by employing the ANP for index weighting. Ultimately, the validity of this method for assessing the risk associated with earth and rock dam projects is demonstrated through a practical case study. This empirical validation serves as a significant reference point for enhancing risk control and management strategies in the context of earth and rock dam projects. [ABSTRACT FROM AUTHOR]

The rapid growth of population and increasing complexity of urban infrastructure have led to even greater consideration of new methods of installing and commissioning underground facilities. These facilities and vital artery lines are implemented in various ways, the most important of which is the traditional open-trench and new trenchless technology. Many factors affect the selection of the best method of implementation, and the method and technology of implementation should be determined based on the conditions of the project and area of construction. In the present study, the factors affecting the acceptance and application of trenchless technology and open-trench method in Iran are evaluated using two techniques: analytic hierarchy process (AHP) and analytic network process (ANP), and the results are compared with each other. The statistical population for this research consisted of middle managers, contractors, and engineers from Iran's supervision and design body. For this purpose, factors such as technology, economic, environmental, project productivity, organizational, executive management, individual, and demographic are identified as effective factors in the evaluation of excavation technology using library studies and consulting with experts. The relevant decision-making model was then prepared via interviews with experts. Eventually, components and criteria affecting excavation technology were prioritized through pairwise comparisons and model solving. The results showed that, in the AHP technique, the principal components, i.e., economic, technology, and executive management factors, and the criteria section, direct cost, social costs, and competitive business environment factors, are ranked first to third. In the ANP technique, the principal components, i.e., economic, technology, project productivity factors, and in the criteria section, the factors of the competitive business environment, environment, and social costs, are ranked first to third. This comparison shows that the existence of dependencies between the principal components is effective in prioritizing the elements. [ABSTRACT FROM AUTHOR]

The Analytic Hierarchy Process (AHP) has been a widely used multi-criteria decision-making (MCDM) method since the 1980s because of its simplicity and rationality. However, the conventional AHP assumes criteria independence, which is not always accurate in realistic scenarios where interdependencies between criteria exist. Several methods have been proposed to relax the postulation of the independent criteria in the AHP, e.g., the Analytic Network Process (ANP). However, these methods usually need a number of pairwise comparison matrices (PCMs) and make it hard to apply to a complicated and large-scale problem. This paper presents a groundbreaking approach to address this issue by incorporating discrete Markov Random Fields (MRFs) into the AHP framework. Our method enhances decision making by effectively and sensibly capturing interdependencies among criteria, reflecting actual weights. Moreover, we showcase a numerical example to illustrate the proposed method and compare the results with the conventional AHP and Fuzzy Cognitive Map (FCM). The findings highlight our method's ability to influence global priority values and the ranking of alternatives when considering interdependencies between criteria. These results suggest that the introduced method provides a flexible and adaptable framework for modeling interdependencies between criteria, ultimately leading to more accurate and reliable decision-making outcomes. [ABSTRACT FROM AUTHOR]

Multiple unmanned aerial vehicles (multi-UAVs) formation shape refers to the geometric shape when multi-UAVs fly in formation and describes their relative positions. It plays a necessary role in multi-UAVs collaboration to improve performance, avoid collision, and provide reference for control. This study aims to determine the most appropriate multi-UAVs formation shape in a specific mission to meet different and even conflicting requirements. The proposed approach introduces requirement satisfaction and spherical fuzzy analytic network process (SFANP) to improve the technique for order preference by similarity to ideal solution (TOPSIS). First, multi-UAVs capability criteria and their evaluation models are constructed. Next, performance data are transformed into requirement satisfaction of capability and unified into a same scale. Qualitative judgments are made and quantified based on spherical fuzzy sets and nonlinear transformation functions are developed for benefit, cost, and interval metrics. Then, SFANP is used to handle interrelationships among criteria and determine their global weights, which takes decision vagueness and hesitancy into account and extends decision-makers' preference domain onto a spherical surface. Finally, alternative formation shapes are ranked by their distances to the positive and negative ideal solution according to the TOPSIS. Furthermore, a case study of 9 UAVs performing a search-attack mission is set up to illustrate the proposed approach, and a comparative analysis is conducted to verify the applicability and credibility. [ABSTRACT FROM AUTHOR]

Purpose: Technological innovation has become a significant part of textile and apparel industries. To become distinguished from competitors, it is essential to harness the potentials of the organizations in achieving higher speeds, faster delivery times, more precise research and development processes followed by modern manufacturing techniques, lower inventory and lower costs. This paper aims to present the risk factors, root causes and their impact related to technological innovation. This uncovers deeper problems inherent to the technological innovation process while providing insight to develop a more robust risk management strategy in marking the survival and growth of the organizations in the textile and apparel trade. Design/methodology/approach: Literature review and structured interviews with industry experts were conducted to identify the risk factors and root causes associated with technological innovations related to textile and apparel industries. The impact of root causes to the risk factors was determined through priorities, derived according to analytic network process using Super Decision software. Findings: Impact of the root causes on risk factors take different priorities, highlighting the most alarming root causes, which contribute more to the outcome. This provides insight for a more precise decision-making on the order of prioritization of root causes in managing risks involved. Originality/value: Findings of this research provide insight on the most influential competencies of any textile and apparel organization for a thriving innovation. Profound knowledge on risk factors, root causes and their contribution to the outcome enhances complex decision-making. This ultimately leads to "credible performances" of the technological innovation and optimizing the resources available, which bridges the gap that exists in the current literature. [ABSTRACT FROM AUTHOR]

The substantial rise in automobile ownership and expansion of metropolitan areas in recent decades, especially in emerging nations, has resulted in a severe shortage of parking spaces. This problem not only causes significant traffic congestion and an increase in accidents but also places a considerable financial burden on individuals and worsens air pollution. Despite extensive research on addressing the parking issue, there is still a notable deficiency in effective approaches for selecting the best locations for multi-story parking structures, particularly in major cities in Iran. Hence, acknowledging the significance of effective parking management in addressing these problems, This study aimed to provide a comprehensive framework for choosing parking locations in Shiraz's business district. This study combined the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) with a Geographic Information System to make fuzzy multi-criteria decisions. In determining acceptable locations, numerous aspects such as closeness to business hubs, distance from key roads, land prices, population density, and the feasibility of erecting multi-story parking structures were taken into account using these approaches. The findings revealed that districts 13, 14, 15, 16, 17, and 18 in Shiraz's core area had the most potential for the construction of multi-story parking facilities compared to the other 30 central districts. Additionally, the findings showed that accessibility to major roads, population density, and proximity to trip generators were the most relevant factors in deciding where parking facilities should be located in Shiraz. When the results of the two approaches were compared, it was found that while the models' results were basically similar, the AHP model's user-friendliness made it easier for urban managers and planners to understand and apply. Policymakers and urban planners can use the insights provided by the outcomes of these models to make well-informed decisions on parking infrastructure expenditures. [ABSTRACT FROM AUTHOR]

This article discusses the competitiveness improvement strategies of MSME Blora Batik using the Analytic Network Process (ANP) approach. The study finds that Blora batik has the potential to be competitive by focusing on increasing innovation, diversification, and business productivity. The article also explores different theories and perspectives on diversification strategies and the importance of unique and valuable resources in creating competitive advantages. It provides a methodology for analyzing competitiveness improvement strategies for small and medium-sized enterprises in the batik industry in Blora Regency, Indonesia. Additionally, the article includes a list of references and citations for further research on competitiveness and strategies for SMEs. [Extracted from the article]

Copyright of Journal of Quantitative Research in Social Sciences is the property of Journal of Quantitative Research in Social Sciences / Sosyal Bilimlerde Nicel Arastirmalar Dergisi 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.)

Adaptive security activities are a list of recommended security activities to be integrated smoothly with the software development life cycle (SDLC) to produce a secure application software. Adaptive security activities are needed due to the emergence of factors and constraints which have been determined as one of the reasons for the underutilisation of security activities implementation, especially in the earlier phase of software development process. Security activities selection models were proposed to select and recommend security activities but the models were focused on certain factors or as a solution for specific constraints, and thus the recommended security activities were not adaptive. Consequently, an adaptive security activities selection (ASAS) model was proposed by combining the factors and constraints faced by the development team in selecting security activities. The model consisted of two integrated multi-criteria decisionmaking (MCDM) methods, namely Analytic Network Process (ANP) and Reference Ideal Method (RIM). ANP was used to prioritise and weight the criteria while RIM was used to measure and evaluate the security activities with the value of constraints in regard to each criterion. To validate the model a case study was performed on four inhouse web application development teams in the Malaysian public sector. The proposed model was able to recommend security activities in the requirement and design phase based on different constraints faced by each of the development teams. The model was adaptive due to its flexibility and ability to change and suit different evolved conditions when recommending the security activities. [ABSTRACT FROM AUTHOR]

This paper determines the weights of the key factors for evaluating the performance of the banking system in Iran using the Balanced Scorecard (BSC) and Fuzzy Analytic Network Process (FANP) approaches. This paper first identifies key factors for the performance evaluation and then determines the cause-and-effect relationship between using the DEMATEL approach. The key factors were included in the BSC framework using the experts' opinions and following principles, including the need for all communication to lead to profitability, not considering the causal relationship from more tangible dimensions to intangible dimensions, and eliminating feedback causal relationships. The calculated weights show the maximum importance of the learning and growth dimensions and the minimum importance of the financial dimension. Among the key factors, on-time service is the maximum important, with customer retention being the minimum important. The extracted key factors can evaluate the performance of the country's banking system descriptively and based on the data obtained from declarations or official reports provided by different evaluators. [ABSTRACT FROM AUTHOR]

The selection of construction plans for adverse geological conditions frequently encountered during the construction of bridge pile foundations will have a significant impact on the project's progress, quality, and cost. There is a need for the optimization of multi-attribute decision-making methods, considering the subjectivity in in weight allocation and the practical implementation obstacles. In this study, an evaluation framework for pile foundation construction schemes in karst areas was established. The directed graph and Bellman-Ford algorithm are employed to improve the Analytic Network Process (ANP) in the systematic structure, thereby calculating the subjective weights of various indicators. Simultaneously, based on the concept of dynamic weighting, a multiple linear regression is introduced for analyzing the weights of similar projects, resulting in the derivation of universal weights for the primary indicators within the evaluation system. The combination weights are subsequently determined through the weighted average of the two types of weights. Finally, the comprehensive scores of alternative schemes are computed using the grey-fuzzy evaluation method to enable decision-making in scheme selection. Cloud model, ELECTRE-II, and VIKOR methodologies were utilized for the comparison of results. Combining with a case study of a bridge project in karst development area in southern China, the findings indicate that the improved ANP method possesses practical applicability and yields effective computational results. The introduction of universal weights serves to ameliorate the inherent subjectivity in weight allocation. The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model. [ABSTRACT FROM AUTHOR]

As a decentralised ledger and data management technology, blockchain has attracted increasing interest and has been effectively applied in various areas. Despite its promising potential, there are few studies proposing effective strategies for promoting blockchain, particularly in providing a strategic analysis of blockchain in China's construction management. This study aims to investigate the external and internal environments of blockchain application and determine the roadmaps and strategies for blockchain application in construction management in China. A strength, weaknesses, opportunity, and threat (SWOT) analysis is employed to draw a panorama of the blockchain development status. Six roadmaps and strategies for blockchain application are proposed. By using the Analytic Network Process (ANP), a quantitative analysis was conducted to determine the ranking of SWOT sub-factors and roadmaps and strategies. The results show that 'traceability of information', 'high application threshold', 'national policy support', and 'low informatization level of the construction industry' are the most important sub-factors in strengths, weaknesses, opportunities, and threats respectively. The best roadmaps and strategies are 'improving the informatization level of the construction industry', followed by 'promoting the technological innovation of blockchain' and 'providing standard'. This study facilitates an in-depth understanding of the blockchain application in China's construction management. It will not only help researchers to conduct targeted blockchain research for more efficient project management, but also help practitioners to develop effective strategies for adopting blockchain. [ABSTRACT FROM AUTHOR]

The fire hazard assessment of polymers and the effect of flame retardants constitutes the foundation for preventing and managing fire risks to public safety. This study addresses key challenges by considering intrinsic hazards, indicator volatility and correlations, while overcoming subjectivity in weight assignment and the neglect of flame-retardant treatments. Firstly, we initiate two novel steps of Pearson correlation analysis and predefined comparative scales for indicators, which enhance the objectivity, scalability and repeatability of analytic network process (ANP) weights. Secondly, we utilize the CRITIC method to incorporate indicator volatility and correlations, surpassing the limitations of separate calculations and subsequent combinations. The newly developed pure sample normalization method enhances the interpretability and scientific validity of CRITIC weights. Combining the ANP and CRITIC weights using Nash equilibrium theory, the results rectify the underestimated T -5% from 0.72% to 3.64%, reducing the overestimated PCO 2 , PSP and TSP from 11.98%, 9.62% and 9.59–7.25%, 9.12% and 5.69%, respectively. Finally, the fire hazards value effectively captures the increased fire hazards resulting from specific degraded indicators following flame retardant treatments. The research findings provide a fresh perspective for the safe design of flame-retardant polymers and fire hazard assessment, offering valuable insights for fire risk prevention and management. [ABSTRACT FROM AUTHOR]

Single-valued neutrosophic sets (SVNS) are proficient in conveying fuzzy information within the realm of multiple attribute decision making (MADM), and The TOPSIS method effectively ranks alternatives in MADM. Attribute weight and distance measurement are important steps in TOPSIS method. The focus of this paper is to propose a new attribute weight determination method in the SVNS environment, namely Decision Laboratory and Experimentation Method - Analytic Network Process (D-ANP). A new single-valued neutrosophic distance measure is also defined, namely single-valued neutrosophic Kulcynksi distance, and the effectiveness of the generalized single-valued neutrosophic Kulcynksi distance is proved. Finally, the proposed D-ANP method and the defined Kulcynksi distance are applied to the TOPSIS method of MADM, and the feasibility of the D-ANP method and Kulcynksi distance is verified through application examples. [ABSTRACT FROM AUTHOR]

The distribution of hospital beds can be used as an indicator to assess the distribution of health services. This study aimed to determine and prioritize indicators of hospital bed allocation in Iran. In the first phase of the study, we used a scoping review to identify criteria affecting hospital bed allocation. Then, we applied an expert panel and the Delphi method to localize the criteria. Finally, we carried out Analytic Network Process method based on Decision Making Trial and Evaluation Laboratory technique (DANP), to determine the weight and importance of indicators and to evaluate the causal relationship between them. Based on the scoping review, we identified 75 criteria that influence bed allocation. In 2 Delphi cycles, 28 criteria were selected and included in the DANP phase. The population, the presence of a reference hospital in the region, the type of hospital, the common diseases in the region, and the presence of home care services were the variables that had the most interaction with other variables. The variable of home care services was at the highest level of the causal chain. Bed occupancy rate, average length of stay, waiting list, as well as type and level of the hospital had the highest priority in the allocation of hospital beds. Furthermore, given the importance of home care services, policies should be adopted to expand these services nationwide. The indicators identified in this study will be useful for the development of policies aimed at an equitable allocation of hospital beds. Key Points: The authors identified 75 criteria affecting the distribution of beds through scoping review.The criteria with the highest level of interaction were population, existence of a reference hospital in the area, the type of hospital, common diseases in the area, and existence of home care services.The variable of home care services was at the highest level of the causal chain. [ABSTRACT FROM AUTHOR]

This research paper presents an all-encompassing methodology for multi-criteria decision-making in the apparel sector, with the particular objective of aiding in the determination of the most appropriate location within the CLMV subregion. The research is conducted in three crucial stages. The process began with the administration of a survey to proprietors of garment businesses in both Thailand and the CLMV countries. This survey resulted in the compilation of an exhaustive list of site-selection criteria and sub-criteria. Based on the findings of subject matter-expert interviews, Cambodia (C), Vietnam (V), and Myanmar (M) were identified as feasible alternatives. Subsequently, the questionnaire criteria and sub-criteria were evaluated utilizing the Fuzzy Analytic Network Process (Fuzzy ANP), which involved the utilization of meticulously designed pair-wise comparison matrices and local priorities. Five specialists from the Thai entrepreneurial community affirmed the effectiveness of Fuzzy ANP and expressed interest in expanding manufacturing operations in the CLMV subregion. The optimal location for Thai apparel manufacturers was subsequently determined using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). The results indicated that Vietnam is the most favorable option. In order to improve the dependability of results, an amended mixture-design scenario analysis was implemented. This analysis assessed the sensitivity and dependability of the proposed model in different scenarios, ensuring its applicability in real-world situations. In contrast to traditional models, this study integrates managerial judgments and preferences into the decision-making procedure, thereby accounting for the complex interdependencies among numerous criteria. The suggested methodology functions as a beneficial instrument for decision-makers, both domestic and international, as it integrates effortlessly into the organizational structure of the CLMV region. By harmonizing objectives pertaining to data acquisition, manipulation, retention, and dissemination, this framework not only enables enhanced decision-making processes, but also optimizes system efficiency. [ABSTRACT FROM AUTHOR]

Copyright of Journal of National University of Defense Technology / Guofang Keji Daxue Xuebao is the property of NUDT Press 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.)

The reduction of environmental impact in buildings and the enhancement of environmental performance in the built environment are the key objectives of sustainable development. To achieve this, the adoption of green buildings requires a comprehensive construction approach that focuses on delivering environmentally friendly solutions throughout the entire construction process. This research aims to bridge the gap between theoretical concepts and the practical realities of construction in Iran. It proposes essential criteria and assigns weights to them for creating green buildings based on the opinions of experts from different backgrounds. To understand how buildings are influenced by the environment, society and economics, relevant factors were identified using library research. Web-based surveys involving experts, including architects, engineers, and environmental specialists, were conducted to gather insights into these criteria. A total of 14 criteria were accepted and categorized into economic, environmental, and social dimensions. The Analytic Network Process (ANP) methodology was employed to assess the opinions of 45 expert participants, as provided in the questionnaire. The findings indicate that, among sustainability features, the environmental factor holds the highest significance in Iran, while the social factor is considered the least important. Looking at the sub-criteria, reducing water consumption, financial incentives, and achieving energy efficiency at a reasonable cost are given the highest priority within the environmental, economic, and social aspects of green buildings. [ABSTRACT FROM AUTHOR]

The building construction industry in mainland China is distinguished by one of the highest accident rates and numbers of fatalities. Therefore, risk assessment plays a significant role in preventing safety incidents and economic losses. However, traditional risk assessment methods are mainly experience-based which could introduce significant uncertainties in accident chain estimation, quantitative analysis, and handling with uncertainty. Safety accidents are difficult to estimate, which might lead to inappropriate safety-related decision making. To solve this problem, an innovative quantitative analysis strategy has been developed, generating a loss index for various accidents in the construction site, based on the Bayesian Network and Analytic Hierarchy Process solution. In this solution, the contribution rate of every risk factor to a certain accident can be calculated. Based on those, the loss index of each construction site can be calculated by inputting current risk factors in the construction site. Moreover, the real-time loss index can be estimated which can help the management team with more accurate decision making compared with the traditional approaches. With this model, the safety situation on the construction site can be clarified and the risk priority can be analyzed according to the dynamic condition. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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.)

The objective of this article is to present a proposed application for systematic risk assessment considering the dependence between risks. The proposal relies on a systematic literature review (SLR) as the initial phase, in which the risk classes, management phases and the tools that can be applied to the risk assessment are identified, considering the dependence between them. For this, the system adopted includes the identification and later evaluation of the risks. The evaluation involves the analytic network process (ANP), Monte Carlo Simulation and conditional probability by means of Bayes' theorem. The identification and evaluation of the risks were applied to two links of a piped gas supply chain in Brazil, identified as company X and Y, where six specialists were interviewed in each company in the managerial areas. The ANP indicted that the most critical risk in the links is the demand risk. From this, it was possible through Monte Carlo Simulation to identify the probability of occurrence of events with connection to demand risk: demand (X) / demand risk (Y), with probability of 10%; price risk (X) / demand risk (Y), with probability of 0.64%; and risk of supply (Y) / demand risk (X), with a probability of 0%. This indicates that the highest risk is the risk of demand of firm Y, and therefore mitigation strategies should focus on this risk, as it represents the true cause of supply chain vulnerability, generating risk with the highest probability. [ABSTRACT FROM AUTHOR]

To prevent miners’ unsafe behavior, analytic network process was used to construct the indicator system of influence factors and the indicator weights were calculated. Based on the indicator system, intervention strategies for miners’ unsafe behavior were designed. The system dynamics model of miners’ unsafe behavior was established based on individual, environment, group and management and simulated by Vensim software, then the effects of different intervention strategies on the level of unsafe behavior were discussed. The results show that the primary indicators in order of weight are safety management, personal factors, leadership climate, group climate, work environment, nature of work; secondary indicators with greater weight are safety regulation, safety education and training, safety culture; the reduction of level in miners’ unsafe behavior is accelerated by the intervention strategies, and there is optimal intervention strategy in each intervention aspect; the optimal intervention strategy provides new ideas for strengthening safety management and reducing accidents in coal mines.

The rise of wireless communication has spurred the global adoption of mobile payment services, a trend that is significantly reducing the use of cash. This shift, driven by new technologies and lifestyle changes, not only presents opportunities for businesses but also enhances consumers’ daily activities. Consumers’ and businesses’ willingness to adopt mobile payment services has increased due to factors such as easier access to new technologies, convenience, changing lifestyle choices, and economic conditions. Despite challenges such as limited access to technology, security concerns, and high transaction fees, the potential benefits of mobile payment services are promising. Therefore, this research aims to construct a suitable model for developing a mobile payment service framework that both consumers and businesses are willing to adopt. The proposed model integrates the Delphi method, interpretive structural modeling (ISM), quality function deployment (QFD), an analytic network process (ANP), and fuzzy set theory. To demonstrate the practical application of the model, a case study of developing a mobile payment service framework is presented, showcasing how the model can be used to address real-world challenges and enhance the adoption of mobile payment services. The case study results show that ease of use, system and service quality, and reliability are the most important customer requirements, and encryption, edge computing, authentication, and interoperability are the most important engineering characteristics.