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Public postal organisations aim to determine the optimal locations for postal delivery service branches to enhance service quality, increase operational efficiency, reduce costs, and optimise resource utilisation. In this paper, we consider how to enhance the process of identifying suitable sites for these branches in Istanbul, Turkey, through a case study that evaluates land-use categories – and their influence on demand for postal services – within different districts so as to pinpoint the most appropriate locations for service branches. We employ Kernel Density Estimation (KDE) analyses in conjunction with Geographic Information Systems (GIS) to optimise the service network. This optimisation aids in deciding whether to close underperforming branches or to establish new branches in neighbourhoods with higher demand. Turkish postal delivery system statistics serve as the basis for our case study. Consequently, this study provides valuable insights into the selection of postal service branch locations and offers practical implications for improving branch accessibility in relation to spatial variability in demand. Such applied insights can be crucial for administrators and policymakers when making informed decisions regarding long-term location planning and initiatives across various sectors. [ABSTRACT FROM AUTHOR]

Given that the chemical industry is the foundation and pillar of the national economy, explorations of its spatial evolution characteristics and influencing factors are of paramount importance for optimizing regional industrial spatial layouts and promoting high-quality development. This study focused on 10, 596 chemical enterprises in Guangdong Province and employed spatial analysis methods to delineate the spatial evolution characteristics of the chemical industry in Guangdong from 2000 to 2021 from an industrial chain perspective. Additionally, we applied a negative binomial regression model to analyze the factors affecting the location choices of chemical enterprises. The following are the main conclusions drawn from the results obtained: (1) Overall, the spatial distribution of the chemical industry in Guangdong Province exhibited a southwest-tonortheast trend, with the center shifting along a southeast-to-northwest axis, accompanied by a gradual reduction in distance. This resulted in a general pattern of "agglomeration in the Pearl River Delta region, diffusion along river corridors, and peripheral expansion." The specific spatial distribution pattern can be described as a "central core and two belts," aligning with the industrial development strategies that are driving the western and eastern regions of Guangdong in concert with the Pearl River Delta region. (2) Agglomeration effects within different industrial chains were strengthened and exhibited variations in distribution. Upstream industries were primarily concentrated in Maoming, transitioning from being dispersed to being densely agglomerated and gradually forming a core area in Maoming and a sub-core area on the east bank of the Pearl River. Midstream industries were primarily clustered in the Pearl River Delta and Maoming, with limited distribution in other regions, displaying a pattern of "significant agglomeration in the Pearl River Delta, the emergence of new hotspots in Maoming and Zhanjiang, and scattered development in other areas." Downstream industries clustered in the Pearl River Delta region and expanded toward the northwest, featuring a "significant increase in agglomeration in the Pearl River Delta, with a noticeable gap compared with other regions." (3) Spatial correlations within the chemical industry gradually strengthened, with downstream industries displaying the strongest associations. With regard to inter-industry chain associations, midstream and downstream industries exhibited the closest spatial connections, whereas those between upstream and downstream industries were relatively weaker. (4) The spatial layout of the chemical industry was driven by multiple factors, including location conditions, socioeconomic factors, government actions, and industry linkages. Notably, transportation infrastructure, economic development, labor costs, environmental regulations, and industrial foundations significantly influenced the spatial layout. Furthermore, the factors influencing the spatial distribution of chemical enterprises in different industrial chains varied. Upstream industries tended to favor regions with stringent environmental regulations and higher labor costs. Midstream industries leaned toward areas with good water transportation, strong economic foundations, high labor costs, stringent environmental regulations, and robust industrial bases. Downstream industries shared similar influencing factors with midstream industries and preferred regions with strong industrial links. This study makes two main contributions. The theoretical findings enrich the field of geographical research on the chemical industry and provide specific references for the spatial layouts of other industries. In practical terms, this study is valuable for capturing and reflecting the evolving spatial patterns of the chemical industry and providing decisionmaking references for local governments seeking to promote its transformation and development. [ABSTRACT FROM AUTHOR]

Epidemic diseases dramatically change the nature of waste. The waste generated from a diverse range of medical and hazardous waste such as infected masks and gloves places a heavy burden on waste treatment systems. Disposal of this waste is vital to prevent pollution and protect natural resources. Source-separated collection is a crucial step in the disposal process. This study focuses on using geographic information systems-based Pythagorean fuzzy decision analysis to determine the location for face masks and gloves waste disposal boxes during the pandemic in Samsun city, Turkey. First, spatial analysis is carried out using geographic information systems to generate maps based on selected criteria. Subsequently, the analytic hierarchy process strengthened by interval-valued Pythagorean fuzzy numbers is utilized to obtain the criteria weights. A set of suitable locations for waste disposal boxes is identified according to the criteria weights and three additional conditions specified by the expert group. The technique for order preference by similarity to ideal solution method is used to rank the locations. Sensitivity analysis is performed to illustrate how the ranking of the alternative locations is affected by changes in the criteria weights. The proposed model is compared with Pythagorean fuzzy analytic hierarchy process-complex proportional assessment. [ABSTRACT FROM AUTHOR]

Given that the chemical industry is the foundation and pillar of the national economy, explorations of its spatial evolution characteristics and influencing factors are of paramount importance for optimizing regional industrial spatial layouts and promoting high-quality development. This study focused on 10,596 chemical enterprises in Guangdong Province and employed spatial analysis methods to delineate the spatial evolution characteristics of the chemical industry in Guangdong from 2000 to 2021 from an industrial chain perspective. Additionally, we applied a negative binomial regression model to analyze the factors affecting the location choices of chemical enterprises. The following are the main conclusions drawn from the results obtained: (1) Overall, the spatial distribution of the chemical industry in Guangdong Province exhibited a southwest-to-northeast trend, with the center shifting along a southeast-to-northwest axis, accompanied by a gradual reduction in distance. This resulted in a general pattern of "agglomeration in the Pearl River Delta region, diffusion along river corridors, and peripheral expansion." The specific spatial distribution pattern can be described as a "central core and two belts," aligning with the industrial development strategies that are driving the western and eastern regions of Guangdong in concert with the Pearl River Delta region. (2) Agglomeration effects within different industrial chains were strengthened and exhibited variations in distribution. Upstream industries were primarily concentrated in Maoming, transitioning from being dispersed to being densely agglomerated and gradually forming a core area in Maoming and a sub-core area on the east bank of the Pearl River. Midstream industries were primarily clustered in the Pearl River Delta and Maoming, with limited distribution in other regions, displaying a pattern of "significant agglomeration in the Pearl River Delta, the emergence of new hotspots in Maoming and Zhanjiang, and scattered development in other areas." Downstream industries clustered in the Pearl River Delta region and expanded toward the northwest, featuring a "significant increase in agglomeration in the Pearl River Delta, with a noticeable gap compared with other regions." (3) Spatial correlations within the chemical industry gradually strengthened, with downstream industries displaying the strongest associations. With regard to inter-industry chain associations, midstream and downstream industries exhibited the closest spatial connections, whereas those between upstream and downstream industries were relatively weaker. (4) The spatial layout of the chemical industry was driven by multiple factors, including location conditions, socioeconomic factors, government actions, and industry linkages. Notably, transportation infrastructure, economic development, labor costs, environmental regulations, and industrial foundations significantly influenced the spatial layout. Furthermore, the factors influencing the spatial distribution of chemical enterprises in different industrial chains varied. Upstream industries tended to favor regions with stringent environmental regulations and higher labor costs. Midstream industries leaned toward areas with good water transportation, strong economic foundations, high labor costs, stringent environmental regulations, and robust industrial bases. Downstream industries shared similar influencing factors with midstream industries and preferred regions with strong industrial links. This study makes two main contributions. The theoretical findings enrich the field of geographical research on the chemical industry and provide specific references for the spatial layouts of other industries. In practical terms, this study is valuable for capturing and reflecting the evolving spatial patterns of the chemical industry and providing decision-making references for local governments seeking to promote its transformation and development.

ABSTRACTManaging sustainable and digital transformations in the water industry is a challenge. The identification of freshwater resources for green hydrogen production is necessary for the energy transition away from fossil fuels such as oil and gas. This can be achieved through the sustainable flood retention basin (SFRB) concept for identifying optimal locations for the retention of surface water. This unbiased concept helps in conflict resolution between stakeholders with water rights. Moreover, it serves as a simple tool to produce a digital water supply atlas based on dimensionless parameters with the short names’ population density, location advantage, precipitation, groundwater level, water rights, SFRB, excess running water and proximity to networks. While the first five parameters can be determined during a desk study, the last three parameters require site visits for verification purposes. Germany was used as a representative case study country to demonstrate the proposed methodology to obtain a water atlas based on mapped weighted values. The Kaiserstuhl in Germany served as a worked calculation example indicating well above average potential for water storage using existing retention basins. The water atlas can be used to supplement a (green) hydrogen atlas, supporting decision-makers in building hydrogen infrastructure.

Amid rising global demand for renewable energy, geothermal power emerges as a vital, low-carbon solution to enhance energy security and sustainability. Taiwan, strategically located on the seismically active Pacific Ring of Fire, possesses an untapped geothermal potential that is underutilized due to complex site selection challenges. This study specifically addresses the need for a more precise and psychologically attuned site selection process, aiming to optimize the development of geothermal resources in regions with complex geological settings. Utilizing the Modified Bounded Rationality Data Envelopment Analysis (MB-DEA) model, this research integrates traditional DEA with bounded rationality to factor in the risk preferences of decision-makers, offering a novel approach that enhances accuracy in evaluating geothermal sites. This study addresses the critical challenge of accurately selecting geothermal energy sites in geologically complex regions like Taiwan, where traditional methods fall short, aiming to significantly boost the efficiency and effectiveness of geothermal energy exploitation as part of Taiwan's transition to renewable energy sources. Applied to 30 potential sites across Taiwan, our model provides a detailed assessment based on technical, economic, and psychological criteria, revealing variations in site suitability influenced by stakeholder risk attitudes. Key locations such as Datun Mountain, Maoxing, and Taolin consistently rank highly, confirming their robust potential irrespective of risk preferences. At the same time, other sites show marked sensitivity to shifts in decision-making attitudes. This work significantly advances the methodology of renewable energy site selection by demonstrating the utility of incorporating psychological factors into analytical models, which not only refines decision-making processes but also aligns with Taiwan's strategic energy planning goals. This study also underscores the importance of accurate geographical data in complex terrains, suggesting further refinement and dynamic integration of bounded rationality for future research. [ABSTRACT FROM AUTHOR]

Location choice for outward foreign direct investment (OFDI) is key to companies' strategic decision-making on internationalization. We provide a comprehensive framework for Chinese companies selecting OFDI locations based on an eclectic (OLI) paradigm and neo-institutional economics. We reveal that investment motivation and host country's quality of institutions and bilateral institutional distance play interactive, complex roles in China's location choice for direct investment in ASEAN. Chinese companies prefer investing in ASEAN countries with better institutional quality, especially higher political stability, absence of violence/terrorism, government regulatory quality, and rule of law. Institutional quality significantly promotes market-seeking, efficiency-seeking, and resource-seeking investments; among institutional quality factors, rule of law and corruption control significantly promote market-seeking, resource-seeking, and efficiency-seeking investments, while regulatory quality and government effectiveness significantly promote market-seeking and efficiency-seeking investment. The better the host country's institutional quality, the more attractive it is for market-seeking and efficiency-seeking investments, but less for resource-seeking investments. [ABSTRACT FROM AUTHOR]

Mass rapid transit (MRT) maintenance systems enable owners to make optimal decisions for site selection and preventive maintenance plans while considering the total operating costs. To ensure that the MRT planning system is effective, it is essential to construct a maintenance cost plan. This study implements the mathematical planning method to establish a comprehensive plan for route maintenance and preventive maintenance for the Taoyuan MRT based on the minimum total operating cost as the target, and meets the practical emergency repair time limit, site location distance and other relevant constraints. This study developed and evaluated novel heuristic algorithms with CPLEX software. Sensitivity analysis was also conducted to test the model's effectiveness. The proposed model establishes the optimum maintenance cost and finds the critical parameters that affect overall cost within 1% error, maintaining service quality. The proposed model is an accurate tool for engineers to reduce time-consuming procedures. [ABSTRACT FROM AUTHOR]

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With the future of green energy relying on increases in green-energy production scale to support demand, placing importance on location selection for new energy production methods is going to be vital to secure a zero-carbon future. In this paper, a method called H2Locate is introduced to conduct a down selection sequence for identifying hydrogen production plant location within a defined region. Following the method, resource availability, energy availability, and social impact metrics are analyzed to understand which variables are most vital and what data must be obtained to achieve confidence in the selection of an implementation location. An illustrative example using Oklahoma as the region is produced to demonstrate the proposed method. The counties within Oklahoma are analyzed to identify potential subregions for implementing a hydrogen production plant. Excel-based software, The Probability of Hydrogen Implementation (PHI), using publicly available data regarding energy, resources, and social variables is utilized to carry out the proposed method. Considering the illustrative example with a 290 MW alkaline electrolysis facility, we find that Kay County, Johnston County, Caddo County, and the counties directly surrounding them are the most suitable locations in Oklahoma for the implementation given variables related to the desired energy, resource, and social metrics. • The H2Locate down selection method guides hydrogen production plant location selection. • Analyzes 7 hydrogen hub reports to identify key hydrogen industry variables. • Categorizes energy, feedstock, and social factor variables utilized in the H2Locate method. • An illustrative 290 MW alkaline electrolysis example in Oklahoma identified Kay, Johnston, and Caddo counties as prime locations. [ABSTRACT FROM AUTHOR]

Given the increasing relevance of lunar activities, the location selection for in situ resource utilisation (ISRU) facilities is necessary for identifying the most suitable configuration duringmission planning. To gather information about the dominant location dependencies, a scenario is established wherein an ISRU product is exported to an orbital depot and its mass costs are used for classification. In the selected scenario, oxygen is produced in an ilmenite reduction plant and subsequently exported to the lunar gateway via an oxygen--hydrogen fuelled launcher operated in a round-trip to refuel oxygen at the lunar surface and hydrogen at the lunar gateway. This showed that the transport cost variations could be avoided entirely or have a recessive influence on the mission's total costs over an extended period of time, such as 20 years. The identification of the top-10 most optimal locations for various resolutions was altered only slightly upon consideration of flight costs as compared to considering only the ISRU factors; this indicates the insignificance of flight cost dependencies for the analysed case. [ABSTRACT FROM AUTHOR]

When solving problems related to capital investments in the company, it is necessary to work out the problem in detail and take into account as many influential parameters as possible in order to make the optimal decision. One such problem is the selection of the main warehouse location for the needs of a given company with dispersed centers. Multi-criteria decision-making methods can be applied to successfully solve such complex problems. In this paper, the EDAS method will be applied to achieve the optimal selection of the location of the main warehouse in a company with several dispersed centers. [ABSTRACT FROM AUTHOR]

Offshoring location selection is a crucial decision for firms in terms of competitiveness, flexibility, productivity, and profitability. Determining an efficient and appropriate location for offshoring has been a substantial multicriteria decision-making (MCDM) problem. Considering that the outcome of an MCDM method alone can be misleading, a novel hybrid approach is presented in this study. Thus, five MCDM methods are utilized to solve the problem, and the results of four MCDM methods are integrated to assure an optimal offshoring location. A FuzzyAHP (analytical hierarchy process) integrated with the technique for order preference by similarity to ideal solution (TOPSIS), additive ratio assessment (ARAS), elimination et choix traduisant la realité (ELECTRE), and weighted sum method (WSM) methodology is proposed for the appraisal and selection of the optimal offshoring location. In this context, fifteen alternative locations are determined based on the attractiveness of the locations in terms of offshoring. Fuzzy-AHP is implemented to analyze the problem's structure and find the weights of the quantitative and qualitative criteria. Consistency tests are implemented to assess the quality of inputs of an expert. Then, TOPSIS, WSM, ARAS, and ELECTRE are used to evaluate and rank the candidate locations and present a comparative analysis. By considering fifteen countries and using real data, offshoring location selection is conducted through the proposed methodology. Moreover, sensitivity analysis is made to diminish the subjectivity and assess the robustness of the techniques. The results demonstrated that giving more weights to the labor characteristics and proximity to market criteria might improve the quality of the best offshoring country index. [ABSTRACT FROM AUTHOR]

Introduction: Location selection is vital in all types of businesses, including retail, wholesale, service, and manufacturing. This is particularly true for retail businesses, where location often plays a determining role in the success or failure of commercial activities. Agglomeration economies, where stores physically cluster together to gain mutual benefits, are common in retail. In Kazeroon City, many retail activities, especially clothing stores, have traditionally been located in the city center, within the Bazaar or nearby shopping centers. However, in recent years, a noticeable shift has occurred, with some stores opting for street locations instead. This research seeks to explore the reasons behind this trend of avoiding retail agglomeration and the criteria for selecting locations on the street. 2. Theoretical Framework Retail agglomeration occurs when similar or complementary retailers cluster in or near a location, creating a pull factor for both retailers and customers. This concept is a foundational element in economic studies and urban planning. Retail patterns can be categorized hierarchically, from central business districts to isolated store clusters, and by their form into planned or unplanned, linear, or isolated clusters. Three types of retail agglomerations are commonly distinguished: evolved such as central business districts, created such as shopping malls, and hybrid like retail parks. Furthermore, these agglomerations can be classified as planned or unplanned, depending on their level of management and organization. Various theories such as Central Place Theory, the Spatial Interaction Model, Bid Rent Theory, and the Principle of Minimum Differentiation provide insight into how retailers distribute themselves spatially within cities and why they form agglomerations. 3. Methodology This research employs a qualitative approach to collect and analyze data. Kazeroon, a city in Iran’s Fars Province, has over 4,877 active economic activities, 395 of which are clothing stores. Of these, 330 are located within the Bazaar or shopping centers (i.e., retail agglomerations), while 65 are located on the street. Data was gathered through face-to-face interviews with 24 street-based clothing vendors, and content was analyzed using MaxQDA software. Spatial analysis was conducted using GIS Pro software to map the spatial distribution and configuration of stores. 4. Results and Discussion The primary reasons for retailers choosing street locations over the Bazaar included factors such as business hours, accessibility, parking availability, social networks, store atmosphere, the size of the shop, COVID-19 impacts, ownership, costs, and the unavailability of empty shops within the Bazaar. These factors can be divided into two categories: nonspatial factors e.g., business hours, social networks, ownership and spatial factors e.g., accessibility, parking availability, store size). Interviews revealed that retailers were attracted to street locations because of convenient customer parking, high visibility, active streets, and proximity to major urban centers. These factors, as well as store size and ownership arrangements, were commonly cited as critical considerations in selecting a location. The deductive approach based on theoretical foundations and past research revealed that parking availability, visibility, active street life, and proximity to major attractions were frequently mentioned by interviewees. Proximity to complementary stores, rental costs, and proximity to competitors were also noted but were not as prominent as in previous studies. The findings suggest that while proximity to complementary stores and cost considerations are significant in other research, in the case of Kazeroon, these factors were less influential. The unique conditions of the city, such as the lack of adequate parking near the Bazaar, shifted the emphasis towards street locations, where customer access is easier due to marginal parking availability. Active street life, visibility, and proximity to major land uses remain consistent with findings from other studies. Notably, the influence of the COVID-19 pandemic, the growing role of social networks, and the atmospheric quality of street stores emerged as differentiating factors in this study, contrasting with findings from other research. Ownership arrangements and contract types also played a significant role in location decisions, providing an additional layer of complexity not often addressed in traditional retail studies. Moreover, it was discovered that some clothing stores are moving away from the city center and forming new retail clusters on the outskirts, creating new agglomerations. 5. Conclusion The findings of this research underscore that store ownership is a significant factor in avoiding central city locations, as owning property eliminates the need to pay rent, reducing the perceived benefits of agglomeration. Additionally, the rise of social networks as a customer acquisition tool has decreased the reliance on physical proximity to the Bazaar. Limited business hours within the Bazaar, particularly closing on holidays and early evening closures, along with the confined atmosphere of shopping malls, have prompted retailers to establish street-based locations. Among the most critical factors influencing this decision is the ease of customer access, particularly due to the availability of marginal parking. Factors such as active street life, high visibility, and proximity to significant land uses are consistent with previous studies on retail location selection. However, the influence of proximity to competitors and complementary stores, which are frequently emphasized in the literature, were less significant in this study. The research also highlights that certain retailers, far from the city center, are forming new agglomerations in less central areas, indicating the emergence of new retail patterns in Kazeroon. This research contributes to the understanding of retail location dynamics, particularly in smaller cities like Kazeroon. It suggests that retailers prioritize factors that facilitate customer convenience, such as parking and accessibility, over traditional agglomeration benefits. The findings have implications for urban planners and policymakers, particularly in addressing the infrastructural needs of non-central retail areas. [ABSTRACT FROM AUTHOR]

The land and urban space have been changed, expanded and enriched in terms of natural, physical, economic and social aspects. However, the use of land and the location of sports uses, which is a public and vital resource, must be done with basic planning. In this regard, the present study deals with the qualitative analysis of the location selection of sports uses in Zahedan using multi-indicator decision-making techniques. The method of this research is descriptive-documentary and analytical, and the relevant information has been collected in the field and in the library. Research data and information have been used using five evaluation matrices (proximity, accessibility, safety, topography and foundations) as well as Swara weighting model and Mabac ranking. The results of the five evaluation matrices (access, proximity, safety, topography and comfort) indicate that the sports halls of Zahedan city are not in a good condition in terms of safety and proximity, which is due to the lack of safe sidewalks. For elderly and disabled people, it is the lack of police stations, the lack of safe and secure sidewalks, the lack of safety of roads and areas, and the lack of access to parks and green spaces, as well as religious centers. The results of Mabak's decision-making model show that Imam Ali Sports Complex is in the first place, Kausar Sports Complex is in the second place, Moin Sports Hall is in the third place, Shahid Kargaran Sports Hall is in the fourth place and Shahid Beheshti Sports Complex is in the fifth place. Are placed On the other hand, Shirabad Hall is ranked 20th and Karimabad Hall is ranked last. Therefore, according to the indicators of safety, proximity, accessibility, and comfort, special attention should be paid to the salons of Karimabad and Shirabad, which are located in the suburbs of the city. [ABSTRACT FROM AUTHOR]

As one of the world's major emerging economies, Thailand's influence in OFDI has been expanding, and its geographical distribution has become increasingly diversified, which is representative. Based on this, analyzing Thai OFDI's temporal and spatial evolution characteristics from 2009 to 2019, the stepwise regression method is used to test the impact of the four-dimensional distance of geography, economy, system and culture on the location selection of Thai OFDI, in order to provide theoretical and practical reference for optimizing the location selection of developing countries. The results show that: (1) the OFDI flow in Thailand shows a fluctuating upward trend. But the investment flow decreased significantly from 2014 to 2015 and 2019 due to domestic political turmoil, large-scale divestment of individual enterprises and other factors. (2) While maintaining a large amount of investment in traditional advantageous industries, Thailand has actively expanded its investment industry, but the overall investment structure is at a lower level. (3) With the expansion of the scale of Thailand's OFDI, its location choices around the world are more diverse, showing a trend of radiation diffusion to central and Western Asia, Africa and South America. The spatial imbalance has weakened, but the overall is still prominent. (4) Geographical distance significantly inhibits the location choice of Thai OFDI, while economic distance plays a positive role in the choice of OFDI. Different from the research results based on developed countries, Thai investors tend to host countries (regions) with large institutional distance, and cultural distance has little impact on them. In view of this, developing countries in similar situations with Thailand should fully consider the influence of distance, weaken the blocking effect of geographical distance on OFDI, and actively improve their own economic development level and political stability. [ABSTRACT FROM AUTHOR]

This study has investigated the impact of contextual distance between home and host countries on the location choice of Chinese multinational enterprises in Asia and Europe, with special attention to the impact of the Belt and Road Initiative (BRI). Through our analysis, we have extended existing IB research of contextual distance to include some new dimensions, such as the policy alignment between home and host countries, existence of home country's business networks, ethnic communities, and language and cultural institutions in host countries, as well as their historical links. The effects of these factors are also contrasted by the ownership attributes of investing firms, i.e. Chinese SOEs and POEs, to detect the importance of firm-level factor in influencing the effect of contextual distance. The analysis of 4437 Chinese greenfield investment projects between 2003 and 2019 in Europe and Asia – based on a conditional logit model – provided support but also qualified some of our hypotheses, which constitute our main contribution to the theoretical and empirical literature on the location choice of Chinese multinational enterprises in general and on Chinese investment along the Belt and Road (B&R) in particular. [ABSTRACT FROM AUTHOR]

Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study. [ABSTRACT FROM AUTHOR]

Energy conservation and emission reduction are important policies vigorously promoted in China. With the continuous popularization of the concept of green transportation, electric vehicles have become a green transportation tool with good development prospects, greatly reducing the pressure on the environment and resources caused by rapid economic growth. The development status of electric vehicles has a significant impact on urban energy security, environmental protection, and sustainable development in China. With the widespread application of new energy vehicles, charging piles have become an important auxiliary infrastructure necessary for the development of electric vehicles. They have significant social and economic benefits, so it is imperative to build electric vehicle charging piles. There are many factors to consider in the scientific layout of electric vehicle charging stations, and the location selection problem of electric vehicle charging stations is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Combined Compromise Solution (CoCoSo) technique and CRITIC technique have been utilized to deal with MAGDM issues. Spherical fuzzy sets (SFSs) can uncover the uncertainty and fuzziness in MAGDM more effectively and deeply. In this paper, on basis of CoCoSo technique, a novel spherical fuzzy number CoCoSo (SFN-CoCoSo) technique based on spherical fuzzy number cosine similarity measure (SFNCSM) and spherical fuzzy number Euclidean distance (SFNED) is conducted for dealing with MAGDM. Moreover, when the attribute weights are completely unknown, the CRITIC technique is extended to SFSs to acquire the attribute weights based on the SFNCSM and SFNED. Finally, the SFN-CoCoSo technique is utilized for location selection problem of electric vehicle charging stations to prove practicability of the developed technique and compare the SFN-CoCoSo technique with existing techniques to further demonstrate its superiority. [ABSTRACT FROM AUTHOR]

Solar energy is one of the sources of renewable energy which is clean, affordable, and limitless. Despite Bangladesh having a significant potential for solar energy for its excellent geographic location, relatively low research work on location selection for the establishment of solar plants and little attempt has been taken to expand the solar energy industry. The optimal location for a solar plant to be built is the main objective of this research. Considering several aspects, five potential locations are selected utilizing the geographic data to find the optimal location and the Analytic Hierarchy Process (AHP) which is one of the multi‐models assessment techniques implemented to get the ideal site for solar power plants. While applying this method, some expert survey has been done via Google Form where some of the principal impact factors are set up like questionnaire and obtained the weight for the criteria for the AHP method. The results of the current analysis indicate that Rajshahi is obtained as best location for solar plant establishment followed by Ishwardi, Chattogram, Chuadanga, and Mymensingh. This work will enable to propose an effective, practical, and structured decision‐making framework that could aid policymakers in Bangladesh to select the best locations for solar farms. [ABSTRACT FROM AUTHOR]

Abstract The development opportunities and high-performance capacity of offshore wind energy project depends on the selection of the suitable offshore wind power station (OWPS) location. The present study aims to introduce a decision-making model for assessing the locations for OWPS from multiple criteria and uncertainty perspectives. In this regard, the concept of interval-valued intuitionistic fuzzy set (IVIFS) is utilized to express uncertain information. To quantify the degree of difference between IVIFSs, an improved distance measure is proposed and further utilized for deriving the objective weights of criteria. Numerical examples are discussed to illustrate the usefulness of introduced IVIF-distance measure. The RANking COMparison (RANCOM) based on interval-valued intuitionistic fuzzy information is presented to determine the subjective weights of criteria. With the combination of objective and subjective weights of criteria, an integrated weighting tool is presented to find the numeric weights of criteria under IVIFS environment. Further, a hybrid interval-valued intuitionistic fuzzy Weighted integrated Sum Product (WISP) approach is developed to prioritize the OWPS locations from multiple criteria and uncertainty perspectives. This approach combines the benefits of two normalization tools and four utility measures, which approves the effect of beneficial and non-beneficial criteria by means of weighted sum and weighted product measures. Further, the developed approach is applied to the OWPS location selection problem of Gujarat, India. Sensitivity and comparative analyses are presented to confirm the robustness and stability of the present WISP approach. This study provides an innovative decision analysis framework, which makes a significant contribution to the OWPS locations assessment problem under uncertain environment.

Reasonable pricing of construction land quota (CLQ) and construction land (CL) is conducive to improving the enthusiasm for farmers’ land reclamation to generate more quotas. Existing literature points out that the current pricing mechanism based on the quota reclamation cost of construction land is not sufficient to protect the rights and interests of farmers in the process of withdrawing from homestead land. However, they have not conducted in-depth research on the quota pricing mechanism based on the characteristic value of the quota. This study constructs a two-stage sequential first-price auction (SFPA) behavioural model with regret, and studies the effect of regret on the CLQ and CL bidding price. Through theoretical and numerical analysis, we found that developers’ regret for quota winning and land failure decreased the quota bidding price and farmers’ income. By contrast, developers’ regret for quota failure and land winning will increase the quota bidding price and farmers’ income. The quota bidding price and farmer income with location selection are higher than those without selection. The quota bidding price and farmer income with location selection decrease as the number of developers increases. Therefore, the optimal decision of the government is to make use of the quota loser’s regret in the first stage by revealing the highest price of the quota, and to make use of the land winner’s regret in the second stage by revealing the second highest price of the land, thereby improve the supply of the quota and farmers’ income. The government provides developers with the location selection to further increase the quota bidding price and farmers’ income. Our new theoretical model is suitable for pricing CLQ and CL by effectively revealing developers’ private information.

The development opportunities and high-performance capacity of offshore wind energy project depends on the selection of the suitable offshore wind power station (OWPS) location. The present study aims to introduce a decision-making model for assessing the locations for OWPS from multiple criteria and uncertainty perspectives. In this regard, the concept of interval-valued intuitionistic fuzzy set (IVIFS) is utilized to express uncertain information. To quantify the degree of difference between IVIFSs, an improved distance measure is proposed and further utilized for deriving the objective weights of criteria. Numerical examples are discussed to illustrate the usefulness of introduced IVIF-distance measure. The RANking COMparison (RANCOM) based on interval-valued intuitionistic fuzzy information is presented to determine the subjective weights of criteria. With the combination of objective and subjective weights of criteria, an integrated weighting tool is presented to find the numeric weights of criteria under IVIFS environment. Further, a hybrid interval-valued intuitionistic fuzzy Weighted integrated Sum Product (WISP) approach is developed to prioritize the OWPS locations from multiple criteria and uncertainty perspectives. This approach combines the benefits of two normalization tools and four utility measures, which approves the effect of beneficial and non-beneficial criteria by means of weighted sum and weighted product measures. Further, the developed approach is applied to the OWPS location selection problem of Gujarat, India. Sensitivity and comparative analyses are presented to confirm the robustness and stability of the present WISP approach. This study provides an innovative decision analysis framework, which makes a significant contribution to the OWPS locations assessment problem under uncertain environment. [ABSTRACT FROM AUTHOR]

In this study, it is aimed to integrate CODAS method with circular intuitionistic fuzzy sets as a new solution method for MCDM problems. Containing a radius notation with degrees of central membership and non-membership degrees is the main advantage of circular intuitionistic fuzzy in decision making. On the other side, Combinative Distance-based Assessment (CODAS) method contains many advantages such as basing on two types of distance calculations (Euclidean and Taxicab distances) comparing with other MCDM methods. When the advantages of circular intuitionistic fuzzy sets and CODAS method are considered, proposed circular intuitionistic fuzzy CODAS method (CIFS-CODAS) presents many superiorities compared to other MCDM techniques. By this way, an application for green logistics park location selection will be handled by using CIFS-CODAS to show the validity of the methodology. After, a comparative analysis with intuitionistic fuzzy CODAS (IFS-CODAS), intuitionistic fuzzy TOPSIS (IFS-TOPSIS) and intuitionistic fuzzy EDAS (IFS-EDAS) methods will be performed for green logistics park location selection problem to confirm the robustness of presented method. Green logistics and Green Deal are also emphasized considering environmental factors as a scope of the article. Finally, the results will be evaluated in the context of the logistics sector and green logistics. [ABSTRACT FROM AUTHOR]

World's energy sources are depleting while the need for alternative energy resources is increasing. Hydrogen energy is an essential alternative and its use in transportation sector through Hydrogen Fuel Cell Vehicles (HFCV) is increasing day by day. For HFCV to become widely used, however, it is necessary to establish a good infrastructure, i.e., hydrogen should be accessible. In this study, we investigate the problem of locating Hydrogen Refueling Stations (HRS) in İstanbul, the most crowded city of Turkey. The problem is addressed with multi-period set covering model and the different population densities in the city are integrated with a modification of this model. Due to the long computational time required by the multi-period set-covering model, two heuristics, namely the iterative model and the reduced model, are proposed. The results indicate that for a geographically distinct city like İstanbul, using Euclidean distance may yield very drastic conclusions, hence should be avoided. It is also shown that the HRS are densely located in areas with high population, and one should trade-off between the total distance to be travelled by the drivers and being served by one of the closest stations. In a multi-period setting where stations are opened incrementally, the findings from two different heuristics favor different stakeholders: the iterative model offers advantages from the perspective of decision-makers, while the multi-period model with an optimality gap is advantageous from the perspective of customers. We also introduce the partial coverage model, which serves as a combination of set covering and p-median models, to analyze the transition if the demand is fulfilled incrementally, not completely. It turns out that less number of stations are sufficient to meet high demand, but the number increases significantly if all demand should be satisfied. • Location selection of hydrogen refueling stations is studied. • A modified version of set covering model with real distances is used. • The trade-off between total distance and service from close stations demonstrated. • The final periods of different solutions yield similar results. • Quality of other periods depends on the solution method. [ABSTRACT FROM AUTHOR]

Timely delivery of products to customers is the great importance for retailers in supply chain management. Vending machines are one of the most effective retail tools for consumers to get the product they want at any time. With the developing technology, retailers tend to establish distribution with vending machines to provide faster service to the consumer. At this point, one of the primary objectives is to make the location selection decisions for these vending machines. The most suitable location selection decision includes the evaluation of each alternative under the specified criteria in a problem where there are multiple alternative locations. The present paper proposes a novel modified Delphi-based spherical fuzzy analytical hierarchy process (SFAHP) integrated spherical fuzzy combinative distance-based assessment (SFCODAS) methodology to the vending machine location selection (VMLS) problem. After determining the main and sub-criteria hierarchically, the Modified Delphi method is used to consolidate the opinions of the experts regarding the criteria and integrate them into the study. The main and sub-criteria weights are provided by the SFAHP method. And the most suitable location is determined by the SFCODAS method by ranking among the alternative locations according to these weighted criteria. The case study of VMLS is presented for a retail firm in Istanbul. Sensitivity analysis is performed to measure the flexibility of the proposed methodology. To validate the applicability of the proposed methodology, comparison analysis is presented with the results of the spherical fuzzy weighted aggregated sum-product assessment (SFWASPAS) method. Finally, the conclusions and future directions are discussed in the study. [ABSTRACT FROM AUTHOR]

Copyright of Geomatik is the property of Murat Yakar 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.)

With the ever-increasing global temperatures, the long-term climate change trend has become an essential part of global investor strategies. Before dealing with the reduction of international direct investment caused by climate change, governments and enterprises should clarify the causal relationship between temperature change and international direct investment, as well as the impact mechanism. This paper empirically examines the impact of host country temperature changes on the probability and scale of international direct investment inflows using data on Chinese enterprises' foreign direct investment and the temperature of each host country from 2009 to 2019. The results show that a 1% increase in host country temperature decreases the probability of Chinese firms' FDI inflows by 5.92% and reduces the size of FDI by 2.60%. The host country's temperature change has a cumulative effect on inhibiting Chinese enterprises' direct investment. The mechanism analysis shows that high temperatures increase the number of meteorological disasters, causing economic losses and reducing economic growth rates, which in turn inhibit direct investment from China. The negative effect of host country temperature change on firms' location choice for international investment is more significant in manufacturing, non-state, and low R&D investment firms. [ABSTRACT FROM AUTHOR]

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design 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.)

Copyright of Online Journal of Art & Design is the property of Online Journal of Art & Design 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.)

As the "pearl at the top of the manufacturing industry," the widespread use of robots is affecting the employment decisions of individual workers. This paper contributes to our understanding of this subject by analyzing the impact of imports of industrial robots on employment location choice at the inter-provinces level in China. The analysis applies a logit approach to microdata from the China Customs Database and China Labor Dynamics Survey. The results suggest that robot import positively affects employment location choice, supporting the theory of "coexistence" between intelligent robots and the labor force. Specifically, industrial robots attract skilled workers via the creation effect and drive away routine labor via the substitution effect, but the creation effect is greater than the substitution effect. Finally, the authors discuss the channels from the perspectives of "skill-biased" and "routine-biased." [ABSTRACT FROM AUTHOR]

Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study.

The adverse effects of coal and gas energy production with the subsequent rapid increase in energy consumption emphasize the importance for Australia to adopt more renewable energy sources to counteract these dismissive contributions to climate change. This work presents a data mining approach for optimally selecting the best locations for installing a distributed hybrid renewable energy generation system for rural regions in Western Australia. The K-Means and K-Medoids clustering algorithms were used to divide the constructed dataset into clusters. In total, 69 locations were selected for the overall dataset, proceeding with the filtering process. The returned cluster data were graphically rendered on a Western Australia map for the region. The clustering algorithms were evaluated using the Dunn index, such that K-Means performed to a higher degree than K-Medoids, given our dataset's nature. After passing the generated clusters to HOMER software to generate the potential wind and solar energy output for each centroid, K-Medoids produced a set of locations that generated higher solar and wind energy on average. However, due to the reduced internal validation, K-Medoids might not be as valuable as K-Means, it does not cluster the data points very well, and within-cluster location energy requirements are not considered in our study.

Summary: With the advancement of global positioning systems and communication technologies, location‐based services (LBS) have become widely used. However, user location privacy is vulnerable during service exchange, and location‐related queries may result in serious privacy disclosure issues. In this article, considering that attackers may make use of auxiliary information to track a mobile user, we propose a real‐time privacy‐preserving scheme based on the grouping of queries in continuous LBS. In this scheme, we first design the probability density functions to select k−1$$ k-1 $$ virtual locations. Then, we group these virtual locations and the query location of the user into several queries. Simultaneously, we send these grouping queries to the LBS server. Following the steps outlined above, grouping queries can be used to conceal the true query. Moreover, the results of security analyses and performance evaluations show that the proposed scheme is effective and secure. [ABSTRACT FROM AUTHOR]

One of the main causes of the significant commercial vehicle traffic in the city region is last-mile deliveries. Parcel lockers, which are one of the easiest and most environmentally friendly solutions for last-mile delivery, are one of the most studied subjects recently. The parcel locker ensures consumer privacy while being quick and efficient. Its full-time service can effectively address the issue of student and office worker pickup. In this paper, the location of a parcel locker intended to be established in the most convenient location in Beşiktaş district of İstanbul, Turkey has been determined. This problem can be solved using a multi-criteria decision-making (MCDM) structure due to the availability of numerous aspects that must be considered while choosing the optimum location. Additionally, the benefit of fuzzy logic is employed to translate expert opinions into mathematical expressions and incorporate them into decision-making processes. To choose the ideal location for the parcel locker, a novel model integrating the Bayesian Best Worst Method (B-BWM) and Pythagorean fuzzy Weighted Aggregated Sum Product Assessment (PF-WASPAS) approaches is proposed for the first time in the literature. Additionally, a sensitivity analysis is conducted to evaluate the model's robustness. As a consequence, the suggested model effectively identifies the best location for a parcel locker in Istanbul. [ABSTRACT FROM AUTHOR]

With the aim of promoting energy conservation and emission reduction, electric vehicles (EVs) have gained significant attention as a strategic industry in many countries. However, the insufficiency of accessible charging infrastructure remains a challenge, hindering the widespread adoption of EVs. To address this issue, we propose a novel approach to optimize the placement of charging stations within a road network, known as the charging station location problem (CSLP). Our method considers multiple factors, including fairness in charging station distribution, benefits associated with their placement, and drivers' discomfort. Fairness is quantified by the balance in charging station coverage across the network, while driver comfort is measured by the total time spent during the charging process. Then, the CSLP is formulated as a reinforcement learning problem, and we introduce a novel model called PPO-Attention. This model incorporates an attention layer into the Proximal Policy Optimization (PPO) algorithm, enhancing the algorithm's capacity to identify and understand the intricate interdependencies between different nodes in the network. We have conducted extensive tests on urban road networks in Europe, North America, and Asia. The results demonstrate the superior performance of our approach compared to existing baseline algorithms. On average, our method achieves a profit increase of 258.04% and reduces waiting time by 73.40%, travel time by 18.46%, and charging time by 40.10%. [ABSTRACT FROM AUTHOR]

Actively responding to climate change and accelerating the realization of carbon emission reduction are the common goals of global sustainable development. Hydrogen energy, as a "zero carbon emission" secondary energy, is playing an increasingly important role on the world energy stage. Hydrogen energy infrastructure (focusing on hydrogen refueling stations) is a key infrastructure in the transition to a hydrogen economy. However, the indicators that influence the location selection of hydrogen refueling stations (HRSs) are specific and have complex relationships, and current research still lacks a comprehensive analysis of its location selection decision-making indicators. Based on this research gap, this study proposes a hybrid fuzzy decision-making approach to determine the relationship and degree of influence between indicators. Firstly, this study identified 18 decision indicators that influence location selection from four dimensions: policy, economy, society, and environment. Subsequently, semi-structured interviews were used to initially assess the relationship between indicators. Finally, by using interpretive structural modeling and the fuzzy decision-making trial and evaluation laboratory (ISM-FDEMATEL), a 7-level structural model is established, which clarifies the complex relationship between indicators and the individual attributes of each indicator. The research results show that the indicators of the policy dimension have a more significant influencing degree than the other three dimensions and have a greater influence on the entire indicator system; the indicators of the economic dimension have a higher influencing degree and are easily influenced by other indicators. These findings will benefit policymakers and practitioners to prioritize and manage their resources effectively and efficiently and provide a valuable reference for advancing the sustainable development of the infrastructure for hydrogen energy. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the most suitable areas for greenhouse sites and the suitability of the sample sites in Aydin region by using Geographic Information System (GIS) and Multi-Criteria Decision Analysis methods. For this purpose, in line with the literature researches and expert opinions, five main location selection criteria (topography, soil, climate, water and economy) and two separate location selection constraints (land use capability class and distance from the surface water resources) were considered. In addition, 160 sample sites were selected from existing greenhouse sites in the study area through purposeful sampling method and their suitability was questioned. The scoring and pairwise comparison methods used in the Analytical Hierarchy Process (AHP) method were preferred for weighting the evaluation criteria. In the review, according to all criteria and constraints, it was determined that 2.4% of the study area was “most suitable”, 33.4% was “suitable”, 31.4% was “moderately suitable”, 0.7% was “slightly suitable”, 29.6% was “unsuitable”, and 2.5% was “out of evaluation” area. In addition, it was determined that 1.9% of the sample sites selected were “most suitable”, 10.1% were “suitable”, 0.6% were “moderately suitable”, and 87.3% were “unsuitable”. According to these results, it was understood that the lands in the study area were not generally suitable for the greenhouse site in terms of the distance from the surface water resources and the land use capability class. In addition, recommendations have been made for realizing more comprehensively the selection of suitable places for greenhouse production and other agricultural production areas in both study area and other fields. [ABSTRACT FROM AUTHOR]

Convenience stores, as the main carrier of retail commerce, the reasonable spatial distribution of convenience stores is very important for the implementation of the strategy of ex‐ panding domestic demand and unblocking the economic cycle. Based on the POI data of Nan‐ jing, kernel density estimation, buffer zone analysis, and ordered multicategorical logistic were used to explore the spatial distribution characteristics and causes of location selection of conve‐ nience stores in Nanjing. The study finds that: (1) The spatial distribution of convenience stores in Nanjing generally presents an unbalanced development pattern of "one main store and many vice stores", which is concentrated in the main urban area of Jiangnan, gathered in the new main urban area of Jiangbei in a small range, and scattered in the sub urban area with low density. (2) Based on the distribution and identification of convenience store hotspots in road grid cells and subway stations, it is found that convenience stores have obvious distribution characteristics along the roads and parallel distribution characteristics with subway stations, but the distribution of different stations varies greatly. (3) The spatial clustering characteristics of each brand of convenience stores are different, but they basically match with their respective brand positioning and business strategies, and complement the layout of urban shopping areas. (4) Factors such as traffic, population and rent affect the spatial distribution of convenience stores, and there are differences in the degree of influence. The research results provide scientific basis and theoretical support for optimizing the spatial layout of commercial outlets and commercial planning work, etc. [ABSTRACT FROM AUTHOR]

Context: The leisure-fishery (LF) industry is an industry that provides fishing activities for recreation and sports. A well-designed layout of LF can reduce resource allocation costs, give play to regional advantages, and maximise utility. Aims: This paper aims to provide a spatial evolutionary understanding of the development of leisure fishery, and on this basis provide guidance for the future development of leisure-fishery industry, focusing mainly on Zhejiang, an important coastal province of China. Methods: ArcGIS spatial analysis tool was used to calculate the nearest-neighbour index, outlier analysis, kernel-density analysis, clustering, and coefficient of variation, to analyse the spatial-distribution characteristics of LF units and influencing factors of the spatial distribution in Zhejiang Province. Key results: The results showed significant differences in the distribution density of LF units among cities in Zhejiang. Traffic, market, and scenic-spot location significantly affected the distribution of LF units in Zhejiang Province. Furthermore, population and economics also affected the spatial distribution of LF units. Conclusions: The main influencing factors of LF were closely related to traffic, market, and scenic spots. Implications: Future policy making should focus on the siphoning effects of infrastructure by achieving more rational transport planning and market incentives. A well-designed layout of leisure-fishery (LF) industry can reduce resource-allocation costs, give play to regional advantages, and maximise utility. LF units in Zhejiang Province were selected as the research objects. The results showed significant differences in the distribution density among different cities. Traffic, market, and scenic-spot location significantly affected the distribution of LF units in Zhejiang Province. [ABSTRACT FROM AUTHOR]