Site Selection Decision Research Articles

AI-Powered Location Intelligence: Revolutionizing Site Selection and Investment Decisions

This comprehensive article explores the transformative impact of artificial intelligence on location intelligence and site selection in the commercial real estate industry. The article examines how AI-powered systems are revolutionizing traditional approaches to property analysis, investment decisions, and operational efficiency across various real estate sectors. Through an examination of current implementations, benefits, and future trends, this analysis demonstrates how machine learning models, advanced analytics, and real-time data processing capabilities are enabling more accurate predictions, improved decision-making, and enhanced operational performance in the real estate industry. The article highlights the significant advancements in areas such as retail site selection, office space development, and industrial property optimization, while also addressing the quantifiable benefits and return on investment of AI implementation.

Research on Low-Carbon Site Selection Decision Model and Algorithm for Green Logistics

This work proposes a low-carbon site selection decision model and algorithm for green logistics. The focus is to minimize carbon emissions while optimizing the distribution network. With the development of smart shared logistics and increasing environmental awareness, there is an urgent need to tackle issues in urban logistics, including pollution, resource inefficiency, high carbon energy usage, and greenhouse gas emissions. By integrating geographic, environmental, and operational data, the proposed site selection model incorporates multi-objective optimization to balance carbon efficiency with cost-effectiveness in logistics site selection. We employ a hybrid algorithm combining Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to solve the complex decision-making process. The model is tested using real-world logistics data, and the results demonstrate significant reductions in carbon emissions and transportation costs when compared to conventional logistics site selection methods. Further sensitivity analysis reveals that the model is robust under varying transportation demands and geographic constraints. Also, we highlight the role of green logistics in achieving corporate sustainability goals aligning with global carbon neutrality initiatives. We believe this model offers a practical approach to fostering environmentally responsible supply chains and will contribute to the advancement of sustainable logistics operations, helping organizations make informed, eco-friendly decisions in site selection.

Site Selection of Large Shopping Malls in Wanbailin District of Taiyuan City

The construction and site selection of shopping malls are directly related to their commercial operation effectiveness and market competitiveness. Some scholars have conducted extensive research in this field, particularly achieving notable results in terms of influencing factors, methodologies, and technological applications for site selection, yet there are still some deficiencies. Traditional site selection methods primarily rely on qualitative analysis and empirical judgment. However, with technological advancements, Geographic Information System technology has gradually been applied to shopping mall site selection. GIS technology enables the integration of multiple data sources, spatial analysis, and visualization, providing a scientific basis for site selection decisions. This article utilizes ArcGIS software to construct an application model for shopping mall site selection in Wanbailin District. Through spatial analysis, eligible areas are identified, achieving a scientific and visual approach to site selection. By considering the main factors affecting the location of large shopping malls in Wanbailin District and using ArcGIS as the basic platform, an application model is built to find the optimal location for building shopping malls. The results show that introducing GIS into mall location planning improves efficiency and accuracy while providing a reliable basis for scientific location.

Exact methods for the Selective Assessment Routing Problem

AbstractThe Selective Assessment Routing Problem (SARP) is a problem in humanitarian logistics addressing the site selection and routing decisions of rapid needs assessment teams which aim to evaluate the post-disaster conditions of different community groups, each carrying a distinct characteristic. The aim is to construct an assessment plan that maximizes the covering of different characteristics in a balanced way. We explore exact approaches based on mixed integer linear programming. Different mathematical formulations are presented, and theoretical results regarding their strengths are derived. The models are experimentally evaluated on a set of test instances including a real-world scenario.

Future Shorelines: A Living Shoreline Site Selection and Design Decision Support Tool that Incorporates Future Conditions Induced by Sea Level Rise

Most living shoreline site selection and design decision support tools are based upon existing environmental conditions. We developed a web-based, geospatial tool called Future Shorelines that integrates high-resolution landscape elevation data and a matrix of locally derived NOAA Interagency Sea Level Rise Scenarios to characterize future conditions of submergence and shoreline translation induced by sea level rise. Once the practitioner selects a location of interest, sea level rise scenario (e.g., high), and target year (e.g., 2050), the tool will generate plan view and cross-sectional informational graphics specific to their choices. This information can then be paired with other menu options, like parcel ownership, to facilitate the planning and construction of nature-based shoreline stabilization solutions that (1) are located where opportunities for horizontal migration are optimized, (2) remain accessible for monitoring and maintenance, and (3) perform as intended over the design life of the installation. The tool’s menu options and the user interface were informed by project partner input solicited during numerous workshops convened over the duration of the 2-year project. This coproduction created a product that was familiar to the end user and therefore increased the likelihood that it would be utilized by them during the planning and design of living shoreline projects. Although developed for use in the Indian River Lagoon, located along the east-central Florida coast, it can be seamlessly replicated for application in other coastal regions of the USA where the requisite data are available.

Integrating socioeconomic and ecological data into restoration practice.

Driven by the United Nations Decade on Restoration and international funding initiatives, such as the Mangrove Breakthrough, investment in mangrove restoration is expected to increase. Yet, mangrove restoration efforts frequently fail, usually because of ad hoc site-selection processes that do not consider mangrove ecology and the socioeconomic context. Using decision analysis, we developed an approach that accounts for socioeconomic and ecological data to identify sites with the highest likelihood of mangrove restoration success. We applied our approach in the Biosphere Reserve Marismas Nacionales Nayarit, Mexico, an area that recently received funding for implementing mangrove restoration actions. We identified 468 potential restoration sites, assessed their restorability potential based on socioeconomic and ecological metrics, and ranked sites for implementation with spatial optimization. The metrics we used included favorable conditions for propagules to establish and survive under sea-level rise, provision of ecosystem services, and community dynamics. Sites that were selected based on socioeconomic or ecological metrics alone had lower likelihood of mangrove restoration success than sites that were selected based on integrated socioeconomic and ecological metrics. For example, selecting sites based on only socioeconomic metrics captured 16% of the maximum attainable value of functioning mangroves able to provide propagules to potential restoration sites, whereas selecting sites based on ecological and socioeconomic metrics captured 46% of functioning mangroves. Our approach was developed as part of a collaboration between nongovernmental organizations, local government, and academics under rapid delivery time lines given preexisting mangrove restoration implementation commitments. The systematic decision process we used integrated socioeconomic and ecological considerations even under short delivery deadlines, and our approach can be adapted to help mangrove restoration site-selection decisions elsewhere.

Utilizing Big Data Analytics to Delve into the Economic Dynamics of the Catering Industry: A Comparative Analysis Between Traditional and Innovative Catering Sectors in China

This paper aims to delve into the economic changes and developmental trajectories between traditional and emerging gastronomy in China, revealing disparities and contrasts between the two. Initially, the paper meticulously delineates the historical context of traditional gastronomy and the current challenges it faces, encompassing issues such as exorbitant labor costs, the viral transmission risk associated with dine-in services, and restrictions on imported frozen foods. Subsequently, it focuses on the current status and future trends of emerging gastronomy, particularly highlighting the application of advanced data analytics technologies in the culinary domain, such as precision marketing, real-time delivery services, and data-driven site selection decisions. Finally, through a comparative analysis of traditional and emerging gastronomy, the paper puts forth corresponding reform strategies, underscoring the advantages and immense potential for development within the emerging gastronomy sector.

Shopping Mall Site Selection Based on Consumer Behavior Changes in the New Retail Era

As a product of the development of e-commerce over a specific period of time, the “new retail model” breaks the barriers between the traditional retail industry and e-commerce. Supported by Internet technology, it builds a new business model of “physical store + e-commerce + logistics” through the integration of online, offline, and logistics, which also leads to a great change in consumer behavior. Therefore, in order to meet consumer demand and achieve the long-term development of shopping malls, while taking into account the fair allocation of urban space resources, the indicators and methods of shopping mall site selection evaluation in the new retail era will be significantly different from traditional shopping mall site selection decisions. In this paper, the Wuhan East Lake Hi-Tech Zone is selected as the research object, and a comprehensive AHP-GIS assessment model is proposed. By investigating the impact of consumers’ behavioral changes on shopping mall location in the new retail era, a suitability evaluation system containing eight evaluation indicators is constructed, and the weights of each factor are determined using hierarchical analysis. At the same time, GIS is used to process the spatial analysis of the indicators, and combined with the weights of the factors, superposition analysis and quantitative research are carried out. Finally, based on the correlation analysis between ratings and customer flow, the suitability evaluation results are further supported in order to provide a more objective and scientific basis for the location of shopping malls from the perspective of the change in consumer behavior under the new retail model, and to put forward universal suggestions for the construction and development of shopping malls in the future.

Strategic insights in manufacturing site selection: a multi-method approach using factor rating, analytic hierarchy process, and best worst method

The current study focuses on selecting the most suitable site location for a manufacturing industry using the Factor Rating Method (FRM). The study considers six key factors: Raw Materials Availability, Location, Availability of Labor, Transport, Availability of Utilities, and Environmental Impact. The FRM assign weights to each factor based on their relative importance. The results indicate that Raw Materials Availability holds the highest weight, suggesting its critical influence on site selection decisions. Subsequently, the Analytic Hierarchy Process (AHP) and Best Worst Method (BWM) are utilized to prioritize three available location alternatives through pairwise criteria comparisons. The analysis reveals that Location C emerges as the most favorable option, effectively meeting the manufacturing industry’s requirements. The successful application of these methods demonstrates their value in aiding decision-making processes related to site location selection. By considering multiple factors and utilizing structured methodologies, organizations can make informed choices aligned with their specific needs and goals. This research contributes to the existing body of knowledge by providing insights into effective site selection strategies for the manufacturing industry. Further research opportunities exist in incorporating additional factors, addressing real-world constraints, and conducting sensitivity analyses to enhance the accuracy and applicability of site location decision-making.

Weather Variables for Within-Vineyard Awareness of Botrytis Risk

Background and Aims. Botrytis bunch rot (BBR) in cool temperate climates is a key constraint to the consistent supply of grapes to winery specifications. BBR severities have been correlated with specific environmental conditions; however, data-driven applications intended to support crop protection decisions are restricted in access and/or of unknown commercial value. The aims of this study were to evaluate variables providing within-vineyard awareness of BBR risk in Riesling vines. Methods and Results. Descriptors of BBR epidemics from eight site years, 2009–2014, were developed for vine areas of ∼0.5 ha within two regions of Tasmania with different climates. Two variables using the daily Bacchus index, from crop stage E-L 19 to E-L 31 or 34, accounted for >80% of the variance in the final mean BBR severity. A BBR risk index (BBR-I), incorporating the mean daily Bacchus index from E-L 19 to E-L 31 and the median daily vapour pressure deficit of air at 15 : 00 during the late-season interval, accounted for up to 99.5% of the variance in the final mean BBR severity. The late-season interval (days) or median daily RH (%) at 15:00 in the same period accounted for 86.4 or 83.3% of the variance. Spatial variability of BBR severity mapped in 4.8 ha of Sauvignon Blanc in 2018-19 confirmed the need to apply BBR risk indicators at an appropriate spatial scale. Conclusions. Environmental variables with biological relevance served as indicators of BBR risk at the study sites and have the potential to discriminate BBR risk among production regions in Tasmania. Significance of the Study. Study findings are expected to support the development of applications that raise awareness of BBR risk at an appropriate spatial scale for in-season adaption of crop protection, diagnosis of crop protection efficacy, and/or site selection decisions. Accompanying formulae with sample data in Microsoft® Excel will support transitions to automated data analyses.

Blind date: female fossorial amphisbaenians prefer scent marks of large and healthy males.

Selecting a good mate is a decision with important fitness consequences. For this reason, mate choice has promoted the evolution of sexual ornaments signaling the quality of an individual. In fossorial animals, inhabiting visually restricted underground environments, chemical senses should be very important for mate choice. We examined whether sexual chemical signals (substrate scent marks) produced by males of the Iberian worm lizard, Blanus cinereus, a strictly fossorial blind amphisbaenian, provide information to females on morphological traits and health state. We administered corticosterone (CORT) to males simulating a continuous stressor affecting their health. Females preferred settling at sites scent-marked by males in comparison with similar sites with female scent or unmarked sites, but the attractiveness of males' scent differed between individuals. Females preferred scent marks of larger/older males and with a higher immune response, while their body condition and CORT treatment were unrelated to female preferences. Chemical analyses showed that proportions of some compounds in precloacal secretions of males (used to produce scent marks) were correlated with the morphological (body size) and health state (immune response and body condition, but not CORT treatment) of these males. These results suggest that females may make site-selection decisions based on assessing the chemical characteristics of males' scent marks, which were reliably related to some of the traits of the male that produced the scent. Therefore, females might use chemical senses to increase the opportunities to find and mate with males of high quality, coping with the restrictions of the subterranean environment.

毕达哥拉斯模糊环境下的选址决策评估

毕达哥拉斯模糊环境下的选址决策评估

Discussion on the Application of Integrated Aerogeophysical Method in Urban Site Selection and Construction

As the construction of "Belt and Road Initiative" continues to advance, cities and large-scale infrastructure construction will be ushered in along the route, and there is an urgent need to quickly identify the geological situation of the engineering survey needs. Aerial physical prospecting has the characteristics of high efficiency and low cost, which can quickly identify the regional geology in a large area and provide geophysical basis for urban site selection and construction decisions, and has great potential in China’s "Belt and Road Initiative" construction.

Site selection decision for biomass cogeneration projects from a sustainable perspective: A case study of China

Biomass energy has made significant contributions to energy demand and environmental protection. The purpose of this study is to establish a new integrated method adapted to the site selection of biomass cogeneration projects. The highlight lies in the integration of Multiple Criterion Decision Making methods with Geographic Information System at different stages. This study takes Henan Province as an example to introduce the application of this model. Stage I preliminary screening stage: use Geographic Information System and Fuzzy Best Worst Method to classify the suitability level of project site selection within the research area. Identify alternative solutions in areas with high suitability and large patch area. Stage II selection stage: Calculate the indicator weights using Criteria Importance Through Intercriteria Correlation method first; Then use the Multi-attributive Border Approximation Area Comparison method to select the optimal factory site. Using geographic information system technology, the factory is selected to be built in an area with a suitable value greater than 7 in Xiangcheng County, Zhoukou City. Finally, the obstacle model diagnoses the direction of optimizing the location environment. This study provides a theoretical reference for the new construction, renovation and expansion of biomass cogeneration projects.

Optimizing the dam site selection problem considering sustainability indicators and uncertainty: An integrated decision-making approach

Changes of climate, population growth, extended droughts, water scarcity, and sustainability considerations are amongst the concerns that stress more than before the significance of water resources management (WRM). One of the approaches that may assist decision-makers (DMs) in handling water resources is the proper site selection for dam construction. The dam site selection decision is a huge long-term investment and due to multiple decision-making factors, stakeholders or DMs, non-deterministic information in the decision-making process, and ripple effect on many other elements of the economy, meticulous analysis is needed. In this study, dam site selection problem (DSSP) is modeled in the form of binary programming under certainty, uncertainty, and hybrid circumstances. Hence, nadir compromise programming (NCP) model is executed in order to tackle the problem with crisp data. Further, a novel model based on NCP and stochastic programming is suggested to treat the uncertainty. The integration of the proposed models is able to address the problem with crisp and random data. The evaluation criteria are categorized based on sustainability (social, economic, and environmental) and technical indicators for dam site selection. To obtain the criteria weight, an interval group decision-making trial and evaluation laboratory (IGDEMATEL) approach is also applied where experts are able to state their opinions on linguistic terms and interval numbers. A real case study in Iran is then investigated in order to appraise the applicability of the developed methodology. A simulation method is further proposed to assess the obtained results and validate the suggested model's performance. Finally, the IGDEMATEL results are employed to survey the relationships between cause-and-effect criteria. The results obtained from the proposed and simulation models are similar in 83% of the cases, and the remaining difference of 17% is because of the uncertainty governing the problem, as well as the lack of sufficient data for precise decision-making.

Research on key influencing factors for site selection of DC microgrid-based hydrogen-electric hybrid refueling stations

In the context of the dual-carbon economy, HRSs play a critical role as an essential intermediary hub for upstream hydrogen production, midstream hydrogen storage and transportation, and downstream vehicle fueling. The use of renewable energy sources for hydrogen production and refueling has become a topic of great interest, and direct current (DC) microgrid-based HRSs are a promising model. However, there is a lack of research on the key influencing factors for the site selection of electric-hydrogen hybrid refueling stations. To address this research gap, this study reviewed the scientific literature on refueling station site selection and identified 34 site selection factors based on the characteristics of DC microgrid-based electric-hydrogen hybrid refueling stations. The importance of these factors was evaluated through a combination of fuzzy Delphi and LBWA models, and an optimized site selection evaluation index system was constructed. The results showed that hydrogen storage technology, wind speed, hydrogen production technology, lighting conditions, spatial safety, profit risk, and leakage risk are the key factors that influence site selection decisions. After eliminating nine non-important indicators, a site selection index system with 1-4-25 layers factors was established. The proposed key factors and index system have important guiding and reference significance for governments and investors in making site selection decisions and managing electric-hydrogen hybrid refueling station projects.

Site selection decision framework for biomass pyrolysis project based on a mixed method under probabilistic linguistic environment and low carbon perspective: A case study in China

Due to the shortage of fossil energy, pyrolysis has become a promising way for the thermal utilization of biomass resources, so as to partly replace fossil energy as well as achieve efficient resource usage. The site selection of the biomass pyrolysis (BP) project is an important task in the preliminary planning stage of the project. Moreover, since low-carbon development has become a common global goal at present, this paper proposes a decision-making framework from the low-carbon point of view for BP project site selection. Firstly, a complete site selection decision-making criteria system embracing the novel concept of low-carbon development is established for the first time, and the subjective and objective weighting method is integrated into the comprehensive integrated weighting method based on game theory. More importantly, a brand-new distance formula for the probabilistic linguistic term set is defined to measure the deviation between information, which uses expectation, variance and scale function to make the measurement more reasonable. Based on this, an improved TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method is proposed to more accurately determine the best option. Finally, taking Guangdong Province as an example, the best choice for site selection is obtained. This work can provide insightful theoretical basis for the site selection of BP projects.

Using radio frequency identification (RFID) technology to characterize nest site selection in wild Japanese tits Parus minor

Selecting a suitable nest site is critical to the survival and reproduction of birds. Prospecting allows individuals to gather information on the local quality of potential future breeding sites, which may help them make the best nest site selection decision. However, few studies have focused on the direct links between the prospecting activity of breeders and subsequent nest site selection. In this study, we investigated the prospecting pattern of Japanese tits Parus minor during the pre‐breeding period of the first breeding attempt and whether nest site characteristics influence their nest box visiting behaviour and occupied nest site. We used radio frequency identification (RFID) to track the movements of Japanese tits visiting nest boxes and compared nest site characteristics between visited and unvisited (control) nest boxes, as well as between visited and occupied nest boxes. We found that Japanese tits started visiting nest boxes approximately 20 days before breeding, visited an average of six nest boxes and eventually chose the most visited nest box for breeding activities. Japanese tits were more likely to visit nest boxes that had less canopy cover and lower shrub density but a greater total number of surrounding trees and ultimately chose breeding nest boxes with a smaller entrance inclination, in nesting trees with a larger diameter at breast height (DBH) which were surrounded by trees with a larger DBH. Our results suggest that Japanese tits visit several potential breeding sites before choosing breeding nest boxes and that nest site characteristics can influence their prospecting activity and nest site selection.

How Do Institutions of Higher Education Affect Local Invention? Evidence from the Establishment of US Colleges

I use narrative historical data on site selection decisions for a subset of US colleges to identify runner-up locations that were strongly considered to become the sites of new colleges. Using runner-up counties as counterfactuals in a difference-in-difference model, I find that establishing a college causes 62 percent more patents per year. Linking patents to novel college yearbook data reveals that only 12 percent of patents in a college’s county came from that college’s alumni or faculty. I find only small differences in patenting between establishing colleges and establishing other institutions as well as between colleges with different focuses on technical fields. (JEL I23, N31, N32, N71, N72, O31, O34)

Evaluation on Site Selection of Urban Renewal Projects from the Perspective of Space Benefit: Macau Special Administrative Region as an Example

With the advent of the stock-planning era, urban renewal has gradually become an important part of urban construction. Urban renewal is essentially a process of solving the rational redistribution of space. However, blind urban renewal can easily lead to the waste of space resources. Therefore, an appropriate renewal location can maximize the space’s renewal efficiency. Based on the perspective of space benefits, this study constructs an urban renewal site selection evaluation system suitable for Macau SAR from two aspects of social and economic benefits and space benefits and uses the DEA model to verify the evaluation system. Thus, we can more objectively and directly judge the evaluation of benefits in urban renewal site selection, maximize the efficiency of spatial renewal, and provide reference for urban site selection decisions. The results are as follows: Funing Building is the best item among the four renewal projects, and it is also the most suitable target point for development; the super-rich benefit is inefficient in terms of both space benefit and production cost benefit.