Location Decisions Research Articles

The Effect of Accessibility and Facility Location Logistics on the Decision Intention of Senior Citizens to use Elderly Care Centers in Thailand: the Mediating Roles of Perceived Service Quality and Perceived Hygiene

Objective: This research aimed to study the impact of accessibility and facility location logistics on the decision-making intention to use an elderly care center. Theoretical Framework: The focus was placed on studying the effect of accessibility and facility location logistics on the decision intention with two mediating variables: perceived service quality and perceived hygiene. Method: The research is based on quantitative research. The sample group consisted of 400 elderly people aged 60 years and over who were interested in or considering using an elderly care center in Bangkok and its vicinity. They were selected by convenience sampling. Data collection was conducted through a questionnaire. The data analysis used the structural equation modeling (SEM) technique. Results and Discussion: The results of the analysis revealed that accessibility and facility location logistics had a direct impact on decision intention. In addition, perceived service quality and perceived hygiene acted as significant mediating variables between accessibility and facility location logistics and decision intention. Research Implications: The results of this study have practical implications for helping elderly care centers improve accessibility and locations to increase the satisfaction of the elderly and their families contributing to achieving SDG-related health and well-being goals, as well as theoretical implications for expanding the understanding of the role of logistics and service quality factors in the decision to use elderly care center services. Originality/Value: The value of this research lies in analyzing the role of accessibility and location of elderly care centers, with an emphasis on their relationship with service quality and perceived cleanliness by users.

Improvement of the Reliability of Urban Park Location Results Through the Use of Fuzzy Logic Theory

Green areas, thanks to their relatively unified natural systems, play several key roles. They contribute to the proper functioning and sustainable development of cities and also determine the quality of life for their inhabitants. As a result, urban planners and policy-makers frequently aim to maximize the benefits of green spaces by creating various programs and strategies focused on green infrastructure development, such as the Green City initiative. One of the objectives of this program is to create new urban parks. This research focuses on developing a new method for selecting sites for urban parks, taking into account factors related to the environment, accessibility, and human activity. The research was carried out for the area of Ciechanów city. To make the city areas more attractive to residents, the authorities aim to increase green spaces and also revitalize the existing greenery. The combination of the Fuzzy AHP method and fuzzy set theory (selecting appropriate fuzzy membership for each factor), along with the use of large and diverse geospatial datasets, minimized subjectivity in prioritizing criteria and allowed for a fully automated analysis process. Among the factors analyzed, land use emerged as the most significant, followed by the normalized difference vegetation index (NDVI) and proximity to surface water. The results indicated that 16% of the area was deemed highly suitable for urban park development, while 15% was considered unsuitable. One-at-a-time (OAT) sensitivity analysis, based on changes in the weight of the land-use factor, revealed that a 75% reduction in weight resulted in a nearly 57.2% decrease in unsuitable areas, while a 75% increase in weight led to a 40% expansion of the most suitable locations. The potential park locations were compared with a heat map of urban activity in the city. The developed method contributes to the discourse on the transparency of location decisions and the validity of the criteria used, to promote sustainable urban development that provides residents with access to active recreation.

How Could Higher Education System Help Attract International Organisations? Differences Between China, the U.S., Switzerland, and the Netherlands

ABSTRACTAs more regions seek to attract international organisations (IOs) to improve their lack of voice in the global community, researchers have increasingly examined the factors that influence the IO location decisions. While these studies inform policy development, most focus on external factors such as international relations, with limited attention to a city's internal qualities. We reviewed the existing literature systematically to identify the factors that influence the location selection of IOs and deeply discussed the neglected factors as well as how to improve them. We especially explored “talents gathering” factor and analysed what could the higher education system contribute to it. We found out three main influencing factors: economy, government action, and talent gathering, among which the third is the most pivotal one. Specifically, even economically robust regions might lose IOs if political instability or other issues hinder timely payment of dues. Government policies should foster networks to prevent competition between different levels of governance. Additionally, IO tends to have less mobile talent pools compared to other industries, making it harder for these organisations to establish a talent base in new locations. Furthermore, an interesting finding is that higher education may greatly foster building the IO ecosystem within a city. We found that, compared to Western models, Chinese universities lack specialised programs to train professionals for IOs, offer insufficient practical resources, and are unaware of the need to establish employment support systems. These observations highlight the need for decision‐makers of higher education institutions (HEIs) and governments to maximise resources to build the local IO ecosystem and IO employment support system.

Performance below Aspirations and FDI Location Decisions of MNEs: The Moderating Role of Strategic Orientations

Performance below Aspirations and FDI Location Decisions of MNEs: The Moderating Role of Strategic Orientations

The impact of speed limits on labour sheds in the mountain west United States

Many state-level policies impact the location decisions of both employees and employers. As most jobs require some form of commute, one such state-level policy impacting location choices are speed limits. We consider the effect of speed limits on the size of the labour sheds in the mountain west United States. Our analysis leverages the natural experiment of changing speed limits in the 281 counties of Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming over the years 2004–2018. Utilizing the revealed commuting behaviour in the origin-destination data available through the Longitudinal Employer-Household Dynamics program we measure the geographic labour shed size as the radius of containment of commuters. Employing spatial panel methods to evaluate the significance of speed limits on the radius of containment we find evidence in favor of the hypothesis that higher speed limits correspond to larger labour sheds.

Regional specialization: From the geography of industries to the geography of jobs

AbstractOur analysis begins with an empirical investigation of how employment concentration in industries and occupations across regions of the United States has changed over time and how regional specialization has changed. Results show that industry concentration and specialization indices have fallen, while occupation concentration and specialization indices have risen. Using this background as motivation, we develop a model in which the comparative advantage of regions lies in their productivity of supplying functions such as law, finance, advertising and engineering, to multiple sectors. Productivity differences specific to region functions shape the location decisions of industries that use multiple functions and hence determine patterns of regional specialization both in functions and in sectors. A key parameter is the cost of sourcing functions from a different region (fragmentation costs), and we show that a fall in this cost mimics the data: sector concentration and regional specialization fall and function concentration and specialization rise. At high fragmentation costs, regional comparative advantage in sectors determines general equilibrium analogous to a Heckscher–Ohlin model (HO). At low fragmentation costs, comparative advantage in functions drives an equilibrium that has little resemblance to a HO world.

Practice makes perfect: Using the total cost of ownership to teach global locational decision making

In this paper we introduce a three-stage Total Cost of Ownership (TCO) experiential learning exercise. Using data collected from 199 students across eight different semesters, we offer hypotheses grounded in the eclectic theory of international production and in behavioral decision making (System 1 and System 2 thinking) to make recommendations for educators and managers. In part one of the exercise, using System 1 thinking, we asked students to select far-shoring (e.g., China) or near-shoring (e.g., Mexico) as a manufacturing location and provide rationale to support their decision. We found that students selecting far-shoring used resource- and efficiency-seeking criteria while students selecting near-shoring used strategic- and market-based criteria. In addition, we found that students were prone to possible availability bias. We identified demographic factors impacting the decision-making process, and highlighted important variables not utilized by students enabling us to recommend changes in college curriculums. In the second and third parts of the exercise, we asked students to reanalyze their decisions using Total Cost of Ownership (System 2 thinking) and then reflect on their pre and post TCO decisions. Interestingly, though unexpectedly, it was encouraging to see a considerable number of students either willing to change their perspective or provide citations or scholarly support as part of the reflection. Such an experiential learning intervention including reflection and documentation is an important exercise to build current and future supply chain managers who can adapt to a dynamic, complex, and global environment. Our study adds to the literature by demonstrating the role of bias in global sourcing decision making and ways to mitigate for it.

Tabu Search Algorithm for Solving a Location-Routing-Inventory Problem

Location decisions, inventory control, and vehicle routing are interrelated decisions. Inventory control decisions, such as order lot size and order frequency, affect both inventory and transportation costs. Failure to take inventory and transportation costs into consideration when determining location decisions can lead to suboptimality since they have a large impact on inventory and transportation costs. Therefore, how to decide locations, determine vehicle routing, and control inventory optimally, or location-routing-inventory problem (LRIP), becomes an important issue to design logistics systems. The objective of this paper is to develop a heuristic method base on Tabu Search (TS) to solve a LRIP. The contribution of this paper which is the heuristic method based on TS to solve a LRIP has never been developed before. TS is a type of metaheuristic. The success of TS is due to its ability to direct the search process so as not to get trapped in the local optimum, in large part, like many other metaheuristics. TS has been widely used to solve complex combinatorial optimization problems. The result of the computational comparison show that the heuristic method can provide a relatively small average gap of 3.20% compared to the optimal method. Application of the proposed heuristic is done in DKI Jakarta.

In-migration for transforming peripheral locations through a real-world experiment? Experiment insights on location decisions in the medium-sized city of Görlitz, Germany

A real-world experiment was implemented in the city of Görlitz to gain knowledge about the requirements for, and the opportunities of, in-migration to revitalize urban areas and increase local capacities for sustainability transformation.Many cities, in particular those in peripheral locations, are dependent on in-migration to compensate for the negative population development often experienced due to demographic and economic change. In addition, the necessary transformation towards urban sustainability requires appropriate know-how and innovation potential. A real-world experiment to stimulate the revitalization of existing urban areas and to enhance the local potential for sustainability transformation through targeted in-migration was implemented in the city of Görlitz, Germany. The aim of this article is to reflect upon the impact of such an experiment with special regard to learning effects for individuals, municipalities, and transdisciplinary collaborations. It explains that there is great value for the future development of a city in the long-term consideration and co-productive work of various stakeholders, but this is also associated with challenges.

Firms’ location decisions, supply chain disruptions and government subsidies: A dynamic game

This paper develops a dynamic game to study the interaction between firms’ production location decisions and a government subsidy policy. On the one hand, firms consider the cost of shielding their production capacity from (potential) supply chain disruptions. On the other hand, the government is interested in curbing production offshoring to increase domestic tax revenues. The location decision of each firm is affected by the government subsidy policy and the location choices of other firms, while the share of firms producing domestically influences the government’s decision on whether and to what extent to provide subsidies to firms. We show that government subsidy policy must target a sufficiently large number of firms to encourage production reshoring and achieve the Pareto-efficient equilibrium. However, a subsidy policy providing a high number of low subsidies is likely to be ineffective in increasing domestic production, highlighting the importance of careful fine-tuning of the policy. Finally, in some scenarios, industrial policy becomes crucial to increase the resilience of domestic supply chains and foster reshoring.

Census Tract and Neighborhood Racial Change and the Locational Decisions of Financial Services in Metro Detroit

Scholarship on the geography of US retail financial services consistently finds racialized patterns in the locations of traditional (e.g. banks, credit unions) and higher-cost or alternative (e.g. payday lenders, check cashers) financial services. While scholars tend to offer explanations based on spatial void and market segmentation hypotheses, we theorize these racialized patterns as consistent with a social reproduction of investment and divestment. We use a novel, longitudinal dataset that follows census tract- and neighborhood-level changes in racial demographics and financial services in Detroit during the pre- and post-Recession periods. Changes in the locations of financial services follow changes in racial demographics, which occur in addition to the well-documented practice of targeting or avoiding tracts and neighborhoods based on their racial majority. These racialized patterns are heightened in the post-Great Recession period.

Data-Driven Shelf Stocking: Robustness and Vertical-Location Effect

In this article, we study a shelf-stock allocation problem in a data-driven setting where the demand distribution is unknown. The retailer needs to decide which commodities to place on each level of the shelf (location decision), and determine the stock level for each selected commodity at the shelf (stock decision) that can be adjusted based on updated demand prediction, under constraints on allocation and capacity, so as to maximize total expected profit. Key issues of the problem include demand endogeneity on vertical-location effect and the demand ambiguity that may arise from the ever shorter life cycles of commodities and other complicated determinants. We address the problem in a rolling-horizon fashion and develop a two-phase data-driven robust optimization model leveraging a decision-dependent Wasserstein metric that incorporates time-series demand forecasts and captures vertical-location effect under demand ambiguity. We derive tractable solution schemes for the model, in which the phase-I model determines the optimal location decision by solving one instance of mixed-integer linear program, while the phase-II model admits an analytical solution for updating the optimal stock. Furthermore, we discuss the sensitivity implications on how the ambiguity aversion impacts the optimal stock, and prove the consistency of the model solution under regularity condition on the underlying demand process that well justifies the asymptotic performance of the proposed data-driven approach. Finally, we extend our model to incorporate substitution effect, and conduct sufficient numerical experiments with real-life data that demonstrate the performance of our model.

Review on road congestion pricing: a long-term land use effect perspective

Road congestion pricing (RCP) is an important way of controlling traffic congestion from the perspective of traffic demand management. This paper introduces the concept and four main types of applications of RCP, summarises the development of RCP theory, reveals the first- and second-order effects of RCP on transportation systems and land use, and analyses the long-term impact of RCP on the spatial location structure of land use. Relevant research progress considering land use effects is systematically and comprehensively reviewed from three research perspectives: demand modelling (pre-RCP), monitoring and analysis (post-RCP) and modelling methods (integration models and other models). The results showed that RCP will affect residents’ travel behaviour in the short term and will lead to changes in spatial location decisions in the long run, thus creating new travel demands and travel modes, affecting the transportation system and urban spatial patterns again. Implementing cordon charges has an agglomeration effect on the population in city centres. Cordon charges also have a significant negative impact on businesses in the toll area and a dispersive effect on jobs. Combined with appropriate strategies for shared autonomous vehicles, RCP can simultaneously improve transportation efficiency and regional accessibility.

Does prior success influence risk‐taking in foreign location decisions? A prospect theory perspective

AbstractResearch SummaryResearch suggests that foreign direct investment decisions can be biased and deviate from economic theory. This study deploys prospect theory to analyze the impact of the success of previous investments on risk‐taking in subsequent investment decisions. Our theorizing suggests that prior success influences foreign investors' decisions to take host‐country risk, and that this moderating influence on the risk‐investment relation is specific to the type of risk. The results of an event‐history study of 1259 location decisions support the notion that the success of previous investments encourages investors to enter host countries with high negative or positive risk, whereas it discourages them from entering locations with high mixed risk. The effects are stronger for investment locations that are similar than for those that are dissimilar.Managerial SummaryRegarding the varying risks that investors face in foreign countries, investment decisions may sometimes appear rather confident and sometimes rather cautious. Our study relates these decisions to the success that investors had with similar investments in the past, since research suggests that experiencing gains or losses can influence decision behavior. The results suggest that prior success affects risk‐taking in foreign direct investment decisions and comes in contrary forms, depending on the type of risk: prior success leads to overconfident investment decisions in the case of negative and positive risk, whereas it induces overcautious investment decisions in the case of mixed risk. Being aware of these behavioral tendencies can prevent managers from making biased investment decisions.

Identifying an optimal cancer risk threshold for resection of pancreatic intraductal papillary mucinous neoplasms

BackgroundIPMN consensus guidelines make implicit judgments on what cancer risk level should prompt surgery. We used decision modeling to estimate this cancer risk threshold (CRT) for BD-IPMN patients. MethodsWe created a decision model to compare quality-adjusted life years (QALYs) following surgery or surveillance for BD-IPMNs. We simulated treatment decisions for hypothetical patients, varying age, comorbidities and lesion location (pancreatic head/tail). The base case was a 60-year-old patient with mild comorbidities and pancreatic head IPMN. Probabilities, life expectancies, and utilities were incorporated from literature/public datasets. CRT was defined as the level of cancer risk at which the expected value of QALYs for surgery first exceeded that of surveillance. ResultsIn the base case, surgery was preferred over surveillance, yielding 21.90 vs. 21.88 QALYs. The optimal CRT for a BD-IPMN patient depended on age, comorbidities, and location. CRT in the base case was 20 % and 3 % for an IPMN in the head and tail of the pancreas, respectively. Other drivers of preferred treatment were age and likelihood of postoperative mortality. ConclusionFor BD-IPMNs, the optimal CRT varies depending on patient age and risk of surgical complications. Personalized risk threshold values could guide treatment decisions and inform future treatment consensus guidelines.

Perceived impact of abortion access on quality of cancer care and on future practice location decisions among oncology fellow physicians: An ASCO State of Cancer Care in America study.

43 Background: The Supreme Court decision in Dobbs v. Jackson Women’s Health Organization (2022) allows states to ban or limit abortion without health exceptions for pregnant persons. Notably, about 1 out of every 1000 pregnant persons has cancer and abortion is utilized in up to 28% of pregnant patients with cancer. To investigate the impact of this court decision on oncology practice, we studied perceptions among oncology fellows of the effect of abortion restrictions on quality care and whether they anticipate care implications to influence their decisions on future practice location. Methods: Fellows who took the 2024 ASCO Medical Oncology In-Training Exam (ITE) were invited to take an optional post-ITE survey assessing perceived (1) effect of abortion policies on ability to provide 9 key aspects of quality cancer care, including care access and delays, trust, and professional well-being and (2) impact of abortion restrictions on quality care in decisions of future practice location. Agreement (Agree, Strongly Agree) and impact on future practice location (Somewhat likely, Very likely) were compared by respondent gender and abortion policies (banned/under legal contention vs legal) in their own or neighboring state using chi-squared analysis. Results: Of 1884 US medical oncology fellows who took the ITE, 1254 (67%, inc. 49% male, 46% female) participated in this survey; 34% trained in states with bans, 44% in states adjacent to states with bans, and 22% in and adjacent to states where abortion is legal. Overall, 33% of fellows report that abortion restrictions affected their ability to deliver at least one aspect of quality care, including 22% reporting limited availability/delays of drugs and 28% reporting poorer job satisfaction. For all 9 aspect of quality care, agreement was strongly associated with local abortion status (p<0.001). For example, 37% of fellows in abortion-restricted states report reduced patient trust and relationship quality vs. 20% among those in states adjacent to bans vs. 18% among those in and adjacent to legal states (p<0.001). Over half (51%) of fellows report that they are likely to consider the impact of local abortion policies on quality care when deciding future practice location (28% were neutral, 21% unlikely to consider). More fellows training in states where abortion is legal report being likely to consider the impact of local abortion policies on care in future practice location decisions (55%) than those training in abortion-restricted states (45%) (p<0.001). More women (58%) than men (45%) report being likely to consider the impact of local abortion policies on quality care in future practice location (p<0.001). Conclusions: Findings provide early insights into the impact of abortion restrictions both on key aspects of quality care as well as the geographic distribution of future oncologists.

Robust cooperative hub location optimization considering demand uncertainty and hub disruptions

Amidst the rise of economic globalization and increased commodity trading, the logistics industry is experiencing rapid growth, encountering intricate transportation demands and fierce market competition. Simultaneously, it faces challenges related to infrastructure development and resource allocation efficiency. To enhance the adaptability and robustness of transportation networks when facing uncertain demands and potential hub disruptions, this paper proposes a two-stage robust optimization model for cooperative hub location problem. The model utilizes a hybrid algorithm that effectively combines the global search capability of genetic algorithms with the step-by-step optimization efficiency of Benders decomposition. Case study analyses demonstrate that, irrespective of the uncertainty environment, the cooperative model maintains lower total costs. Particularly in the case of large demand fluctuations, its cost advantages over non-cooperative models become notably prominent, showcasing remarkable performance in meeting service demands and enhancing resource utilization. Additionally, in cooperative networks, hub disruptions have a more significant impact on hub location decisions, with penalty and supplementary costs further exacerbating this influence. These research findings offer crucial insights for management practices: in uncertain market environments, adopting cooperative and robust planning strategies is pivotal for mitigating operational risks. When making decisions on cooperative hub location selection, carriers should comprehensively consider the interaction between uncertainty and economic benefits to achieve an optimal balance between risk and cost, ensuring the sustained economic feasibility of cooperative ventures.

Correlations between an Urban Three-Dimensional Pedestrian Network and Service Industry Layouts Based on Graph Convolutional Neural Networks: A Case Study of Xinjiekou, Nanjing

Urban high-density development has led to the emergence of complex three-dimensional pedestrian networks. As a crucial component of city centers, these networks significantly influence the spatial distribution of service industries. Understanding the correlation between pedestrian networks and service industry layouts is vital for effective planning and development. This study proposes a technical framework for analyzing the relationship between three-dimensional pedestrian networks and service industry layouts. Using the Xinjiekou central area in Nanjing as a case study, we constructed a three-dimensional pedestrian network model using the sDNA method. Focusing on catering formats, we introduced a method to study the spatial distribution characteristics of service industries in three-dimensional spaces and employed a graph convolutional network model to systematically analyze the correlation between pedestrian network closeness and betweenness with catering formats. The results indicate that pedestrian network closeness is significantly positively correlated with the number and average spending of catering formats, while betweenness shows almost no correlation. High-closeness areas, due to their traffic convenience and walkability, are more conducive to the concentration of catering formats and higher spending levels. Our findings provide valuable insights for catering format location decisions and the optimization of three-dimensional pedestrian networks, contributing to sustainable urban development.

The Fiscal Capitalization of Public Spending: Does Municipal Operating and Capital Spending Increase Property Values?

This study investigates the impact of local public spending on property values. The theory of fiscal capitalization, first proposed by Charles Tiebout and Wallace Oates, holds that a positive relationship exists between local public spending and property values. The theory posits that individuals and businesses make locational decisions based on their preferences for a community’s mix of taxes and spending on services. Although an extensive literature exists supporting fiscal capitalization, studies rarely investigate the separate effects of operating versus capital expenditures. Furthermore, few studies have investigated whether a distinct capitalization effect exists between the signal created by ongoing capital expenditures and a longer term amenity effect realized once projects are completed. This article extends the fiscal capitalization theory by assessing these distinctive effects on property values. The study uses a border discontinuity research design, limiting the sample to residential properties near municipal boundaries. The results show capital and operating expenditures have different effects on property values. In addition, the spending on capital improvements has short-term and long-term effects in the property market. The findings provide local policymakers with guidance on the relative benefits of operating versus capital spending when balancing the two choices.

Design of a reverse logistics network for medical waste considering location and routing decisions

Medical waste generated in healthcare facilities is categorized as hazardous due to its infectious, toxic, or radioactive properties, posing substantial risks to human health and the environment. This research proposes a bi-objective Mixed-Integer Linear Programming model for designing reverse logistics networks that enable both economical and safe medical waste management. Said model determines optimal quantity, depot locations, and routes for transporting waste from its generating points (hospitals) to the treatment and disposal sites (depots).This research addresses a bi-objective location routing problem, with multiple depots, time windows, capacity constraints, and variated waste types, across a multi-period horizon. It is innovative because no previous works have successfully dealt with such a combination of pragmatic features. The Location Routing Problem is an already well-known NP-Hard problem, with the additional aforementioned features further adding to its complexity. Thus, a genetic algorithm to solve large-sized realistic instances within reasonable computing times had been developed.Numerical experiments considered 20 random instances contrasting exact and approximate solution approaches. Also, a medical waste collection case study of a public hospital network in Atlántico Department, Colombia, delivering a Pareto frontier solution set, was introduced. The results demonstrated the efficacy of the proposed genetic algorithm in successfully addressing small instances of the problem, delivering outcomes comparable to the Mixed-Integer Linear Programming model. Furthermore, it yields good-quality solutions in a reduced computational time for larger instances deemed unfeasible for the Mixed-Integer Linear Programming model.This article contributes to both scientific literature and practitioners by presenting a decision-making tool designed to address the medical waste reverse logistics challenge under realistic scenarios. It approaches the issue from a bi-objective standpoint, jointly considering economic factors and biomedical safety. Additionally, the article introduces realistic and pertinent assumptions that have not been explored in previous literature.