Making Location Decisions Research Articles

Selected issues in contemporary housing design for seniors – Poland in the European context

Concern for the residential environment for the elderly is increasingly evident in theory in numerous academic studies and in practice reflected in contemporary realisations. Residential centers for seniors are becoming increasingly popular, and their form and function are becoming more complex and dedicated to specific needs. The authors presented the results of a study of a dozen of different case studies of residential and commercial complexes with a healthcare function for the elderly realised after 2005. The authors hypothesise that contemporary realised complexes for seniors are characterised by a varied morphology, i.e., in some cases they replicate the structure of the urban fabric, while in others they clearly break away from it and create individualised forms. The qualitative assessment considers the advantages and disadvantages associated with the morphology of the complexes. The authors also presented their individual design as an experiment of implementing current trends in an established location (research by design). The presented research shows that both the form and function of housing for seniors evolve depending on the needs. Functional programs and the facilities themselves are usually quite extensive and result in complex functional-spatial systems that fill most of the plots on which they were designed. Conclusions from the research can be valuable in studying other senior centres, especially when making location decisions for similar functions.

The influence coverage optimization problem

We introduce the Influence Coverage Optimization Problem (ICOP), which is an influence maximization problem where the activation of nodes also depends on their location on the plane. Specifically, the ICOP assumes that there is a network where nodes become active (i.e., influenced) either by the influence they receive from interactions with active in-neighbors or by entering the coverage area of a physical ad or a Geo-fence. The objective is to locate a fixed number of ads or Geo-fences and modify the network influence rates to minimize the network activation time. Assuming a Markovian influence model, we prove that the ICOP is NP -hard, and then we present mixed-integer programming formulations for three different types of coverage modes. A reformulation of the non-linear “big-M” constraints, two types of valid cuts, and a fast heuristic based on the k-means algorithm are used as enhancements that facilitate solving the ICOP via an Iterative Decomposition Branch-and-Cut (IDBC) algorithm. In addition, we present an alternative discrete formulation of the ICOP using critical intersection points. Several experiments under various parameter configurations across instances with more than a hundred nodes and thousand arcs are conducted, showing the IDBC’s capability to provide optimal solutions within seconds or minutes for most instances. Moreover, the experiments reveal that the ICOP can significantly outperform a Geo-fence coverage model that does not consider network interactions to make location decisions.

Urban hotel location determinants: Evidence from Ankara's hotel geography

This paper argues that urban hotels have different characteristics and make location decisions based on this differentiation, which in turn affect to the urban spatial structure. To this end, the study examines the determinants of location choices of hotels and their spatial distribution in Ankara. A sample of 75 hotels operating in Ankara was selected through criterion sampling method and applied a questionnaire to identify their location determinants. Findings suggest that hotels with differentiated characteristics show variations in making their location choice, which leads to a shift in gravity of the city and promotes spatial segregation among the central districts of the city. The overall assessment provides evidence on the increasing importance of the new development districts in hotel locations and the decreasing role of old town in the market competition which necessitates the development of local policies targeting the improvement of central district with the lens of hotel geography. Verification of the hypothesis by the case study will fill the gap in literature that has not yet been addressed in Turkey's cities context in the framework of the planning discipline.

Evaluating Location Alternatives for a New Manufacturing Plant using Weighted Sum Model Method

This study uses the Weighted Sum Model to analyze location possibilities for a new manufacturing plant based on six variables, including transportation cost, labor cost, taxes, utilities cost, closeness to suppliers, and proximity to customers. The data was collected and normalized using the min-max method, and weight values were assigned to each criterion based on their relative importance. The Weighted Sum Model formula was then used to determine the weighted sum for each alternative location, and City B was identified as the best location for the new manufacturing plant, followed by City A and lastly City C. The Weighted Sum Model provides an objective and systematic approach to evaluating location alternatives, allowing decision-makers to weigh the importance of each criterion and consider multiple factors in making informed decisions. The strategy is versatile and can be modified to numerous decision-making scenarios, making it a helpful tool for firms wishing to make location decisions based on data-driven approaches. In conclusion, the Weighted Sum Model is a useful tool for analyzing location possibilities for a new manufacturing plant and can help firms make informed and data-driven decisions regarding the optimum location for their operations

Join the Club: Club Goods, Residential Development, and Transportation

A good and sustainable city requires compatibility between the various functions and services that it provides its residents. This study examined the relations between the development of new residential neighborhoods and transportation infrastructure by applying Tiebout’s model of club goods. Thus, we introduced the spatial dimension into the theory of club goods by referring to neighborhoods as clubs and their residents as the club’s members, who make location decisions. Specifically, we explored how residents behave spatially in response to the problematic transportation infrastructure of the neighborhoods. That is, to consider the socioeconomic implications of inadequate transportation infrastructure, we used data from newly developed neighborhoods in Israel to examine the extent to which an increase in traffic congestion can reduce a neighborhood’s size. Our findings show a negative correlation between increases in travel time and the number of housing transactions undertaken in a given neighborhood, thus confirming Tiebout’s assumption that people vote with their feet: When traffic congestion increases, residents prefer to leave the neighborhood and move, in all likelihood, to a place with less congestion. The paper also discusses the results with respect to the social consequences of these trends and warns against the expected socioeconomic consequences, namely that those who can afford to do so will leave in favor of a club with better conditions. The key lessons derived from this study of the Israeli experience are considered relevant to many other countries experiencing similar situations.

Investment Suitability Assessment Based on B&R Symbiotic System Theory: Location Choice of China’s OFDI

Achieving mutualistic symbiosis is the core concept of China’s promotion of the Belt and Road Initiative (BRI). Therefore, how to guide China’s OFDI location decision-making in the Belt and Road (B&R) countries from the perspective of mutualistic symbiosis is of great significance. This paper constructs the B&R symbiotic system based on symbiotic system theory, to establish the investment suitability index from three dimensions: stability, coordination, and sustainability, then uses the entropy weight, TOPSIS, and GIS method to assess and analyze the investment suitability index of 60 major countries in B&R’s six economic corridors. The findings indicate that Russia, India, Indonesia, Thailand, Singapore, Vietnam, and Malaysia have the highest investment suitability and are China’s most favorable OFDI destinations for achieving mutualistic symbiosis. Conversely, Syria, Lebanon, Jordon, and Yemen have the lowest investment suitability. Based on these results, policymakers can formulate more scientific and reasonable policies to guide China’s OFDI to make location decisions in B&R countries with high investment suitability, so as to promote the high-quality and sustainable development of B&R construction. However, due to data acquisition and technical reasons, this study does not analyze investment suitability from time trends. The analysis of investment suitability from more B&R countries or different types of industries is an important direction for further research in the future.

Kentsel Dönüşüm Alanlarının Analitik Hiyerarşi Süreci Yöntemi ile Belirlenmesi

Kentsel dönüşüm, yapısal düzenleme, sürdürülebilir çevresel performans ve sosyo-ekonomik bütünleşme dengesinin gözetildiği bir düzendir. Yapı-çevre-insan ilişkisinin yeniden kurulmasında öngörülen hedeflere ulaşılabilmesi için göstergelerin tanımlanması ve sürdürülebilirliğin sağlanması önemlidir. Çalışmada, kentsel dönüşümde gösterge temelli önceliklendirme yaklaşımı kurgulanarak yer seçim kararlarının alınma süreçlerinde karar destek sürecini besleyen analitik hiyerarşi süreci yöntemi kullanılmıştır. Göstergelerin ölçülebilir, değerlendirmeye açık ve denetlenebilir olması sürdürülebilir yerleşim alanları oluşturulması için bir fırsattır. Kentsel dönüşüm projelerinin olumlu sonuçlarını artırabilmek için yapısal, çevresel ve sosyo-ekonomik bileşenleri kapsayan kriterler tanımlanmıştır. Uzman görüşleriyle kriterler ağırlıklandırılarak kentsel dönüşüm alanlarının belirlenmesinde dikkate alınması gerekebilecek bileşenlerin öncelik sıraları ortaya konmuştur. Önerilen yaklaşım ile kentsel dönüşüm projelerinin öncelikli olarak hangi alandan başlanması ve planlanması gerekliliği tespit edilmiştir.

Reconfiguring a multi-period facility model—An empirical test in a dynamic setting

Facility location is an important problem faced by companies in many industries. Finding an optimal location for facilities and determining their size involves the consideration of many factors, including proximity to customers and suppliers, availability of skilled employees and support services, and cost-related factors, for example, construction or leasing costs, utility costs, taxes, availability of support services, and others. The demand of the surrounding region plays an important role in location decisions. A high population density may not necessarily cause a proportional demand for products or services. The demography of a region could dictate the demand for products, and this, in turn, affects a facility’s size and location. The location of a company’s competitors also affects the location of that company’s facilities. Another important aspect in facility location modeling is that many models focus on current demand and do not adequately consider future demand. However, while making location decisions in an industry in decline, carefully and accurately considering future demand is especially important, and the question in focus is whether to shrink or close down certain facilities with the objective of keeping a certain market share or maximizing profit, especially in a competitive environment. This paper develops a model which enables companies to select sites for their businesses according to their strategy. The model analyzes the strategic position of the company and forms a guideline for the decision. It investigates which facilities should be closed, (re)opened, shrunk, or expanded. If facilities are to shrink or expand, the model also determines their new capacities. It depicts the impact on market share and accounts for the costs of closure and reopening. A number of papers deal with location theory and its applications, but few have been written for modeling a competitive environment in the case of declining demand. Existing papers in this area of research are mostly static in nature, do not offer multi-period approaches, nor do they incorporate the behavior of competitors in the market. To demonstrate the validity of the model, it is first solved using a small problem set–three facilities, three demand locations, and three periods–in LINGO solver. To get a better understanding of the model’s behavior, several additional scenarios were constructed. First, the number of demand locations was extended to 10. Our findings show that the model presented provides an extension of existing facility location models that can be applied to a variety of location problems in commercial and industry sectors that need to make their decisions considering future periods and competitors. The developed heuristic shows multiple options for solving the problem, including their advantages and disadvantages, respectively. The Java code and LINGO fragments thus developed can be used to provide easy access to related problems.

The p-efficient problem in location analytics: Definitions, formulations, applications, and future research directions

This paper aims to demonstrate the need for more extensive collaboration between two broad research areas: location analytics and performance analytics. We present a concise but comprehensive overview of the location analytics fundamental and its evolution, including a historical perspective, early challenges, seminal contributions, and a classification of the problems. The p-efficient problem in location analytics is introduced, where the primary objective is improving the overall efficiency of the network of facilities. We exemplify how performance analytics methods could be used in location analytics. Theoretical discussions are supported with real-world examples in healthcare. The perspective and techniques in this paper can enhance our ability to make location decisions more efficient and effective and give rise to new research questions and methodological approaches in both location and performance analytics.

Changing Population Exposure to Pollution in China’s Special Economic Zones

Martin and Zhang (2020) show that the increase in manufacturing output in China's special economic zones significantly increased air pollution. In this complementary paper, we document that widespread migration into these industrial clusters between 2000 and 2010 did little to change overall population exposure to pollution. We show using satellite air pollution data that there is much heterogeneity across zones and that most population growth occurred in relatively cleaner zones, supporting recent literature that documents local willingness to make location decisions based on environmental quality (Chen et al. 2019, Khanna et al. 2020).

The obnoxious facilities planar p-median problem

In this paper, we propose the planar obnoxious facilities p-median problem. In the p-median problem the objective is to find p locations for facilities that minimize the weighted sum of distances between communities and their closest facility. In the obnoxious version, we add constraints that each facility must be located at least a certain distance from a partial set of communities because they generate nuisance affecting these communities. The resulting problem is extremely non-convex and traditional nonlinear solvers such as SNOPT are not efficient. An efficient solution method based on Voronoi diagrams is proposed and tested. We also constructed the efficient frontiers of the test problems, showing the trade-off between the required distance and the p-median objective, to assist the planers in making location decisions.

Geopolitical disruptions and the manufacturing location decision in multinational company supply chains: a Delphi study on Brexit

PurposeThis study investigates the impact of geopolitical disruptions on the manufacturing supply chain (SC) location decision of managers in UK multinational firms. The context of study is the UK manufacturing sector and its response to the UK's decision to leave the European Union (EU), or Brexit.Design/methodology/approachThe study adopts an abductive, theory elaboration approach and expands on Dunning's eclectic paradigm of international production. A Delphi study over four iterative rounds is conducted to gather and assess insights into manufacturing SC location issues related to Brexit. The panel consisted of 30 experts and managers from a range of key industries, consultancies, governmental organisations, and academia. The Delphi findings are triangulated using a focus group with 38 participants.FindingsThe findings indicate that the majority of companies planned or have relocated production facilities from the UK to the EU, and distribution centres (DCs) from the EU to the UK. This was because of market-seeking advantages (being close to major centres of demand, ease of access to local and international markets) and efficiency-seeking advantages (costs related to expected delays at ports, tariff and non-tariff barriers). Ownership and internalisation advantages, also suggested by the eclectic paradigm, did not play a role in the location decision.Originality/valueThe study elaborates on the OLI framework by showing that policy-related uncertainty is a primary influencing factor in the manufacturing location decision, outweighing the importance of uncertainty as an influencer of governance mode choices. The authors find that during geopolitical disruptions managers make location decisions in tight time-frames with incomplete and imperfect information, in situations of high perceived uncertainty. The study elaborates on the eclectic paradigm by explaining how managerial cognition and bounded rationality influence the manufacturing location decision-making process.

Does internet security matter for foreign direct investment? A spatial econometric analysis

This paper examines the impact of the Internet security environment on Chinese outward foreign direct investment (FDI) using a merged cross-country data set over 2010–2017 with a dynamic spatial model. The results show that Internet security is a crucial determinant for Chinese firms to make location decisions overseas. Particularly, a secure Internet significantly promotes Chinese outward FDI to a host country. In contrast, Internet security in surrounding countries yields negative spatial location spillovers that hinder Chinese firms from investing in the host country. This phenomenon can be regarded as a national competition for Internet security to attract FDI. Mechanism tests show that Internet security promotes FDI in host countries through four channels: operating cost reductions, transaction cost-cutting, information asymmetry decreases, and confidentiality protection. Further heterogeneous analyses show that the impact of Internet security is more significant as time passes and the host country becomes an Internet society. In contrast, specific international cooperation frameworks led by China weaken the location effect of Internet security for Chinese outward FDI. These results are robust after controlling for potential endogeneity and to different specifications. Therefore, the host authorities should endeavor to create a high-quality Internet security environment to attract FDI.

Reconfiguring a Multi-period Facility Model – An Empirical Test in a Dynamic Setting

Facility location is an important problem faced by companies in many industries. Finding an optimal location for facilities and determining their size involves the consideration of many factors, including proximity to customers and suppliers, availability of skilled employees and support services, and cost-related factors, for example, construction or leasing costs, utility costs, taxes, availability of support services, and others. The demand of the surrounding region plays an important role in location decisions. A high population density may not necessarily cause a proportional demand for products or services. The demography of a region could dictate the demand for products, and this, in turn, affects a facility’s size and location. The location of a company’s competitors also affects the location of that company’s facilities. Another important aspect in facility location modeling is that many models focus on current demand and do not adequately consider future demand. However, while making location decisions in an industry in decline, carefully and accurately considering future demand is especially important, and the question in focus is whether to shrink or close down certain facilities with the objective of keeping a certain market share or maximizing profit, especially in a competitive environment.<br /> This paper develops a model which enables companies to select sites for their businesses according to their strategy. The model analyzes the strategic position of the company and forms a guideline for the decision. It investigates which facilities should be closed, (re)opened, shrunk, or expanded. If facilities are to shrink or expand, the model also determines their new capacities. It depicts the impact on market share and accounts for the costs of closure and reopening. A number of papers deal with location theory and its applications, but few have been written for modeling a competitive environment in the case of declining demand. Existing papers in this area of research are mostly static in nature, do not offer multi-period approaches, nor do they incorporate the behavior of competitors in the market. To demonstrate the validity of the model, it is first solved using a small problem set – three facilities, three demand locations, and three periods – in LINGO solver. To get a better understanding of the model’s behavior, several additional scenarios were constructed. First, the number of demand locations was extended to 10. Our findings show that the model presented provides an extension of existing facility location models that can be applied to a variety of location problems in commercial and industry sectors that need to make their decisions considering future periods and competitors. The developed heuristic shows multiple options for solving the problem, including their advantages and disadvantages, respectively. The Java code and LINGO fragments thus developed can be used to provide easy access to related problems.

Changing Population Exposure to Pollution in China’s Special Economic Zones

Martin and Zhang (2020) shows that the increase in manufacturing output in China’s Special Economic Zones significantly increased air pollution. In this complementary paper, we document that widespread migration into these industrial clusters between 2000-2010 did little to change overall population exposure to pollution. We show using satellite air pollution data that there is much heterogeneity across zones and that most population growth occurred in relatively cleaner zones, supporting recent literature that documents local willingness to make location decisions based on environmental quality (Chen et al. 2019, Khanna et al., 2020).

Hotel pricing at tourist destinations – A comparison across emerging and developed markets

The application of price hedonic theory in the hotel pricing domain has relatively ignored the destination and country-level differences. We compare hotel rents across tourist and non-tourist destinations for an emerging (India) and a developed (USA) market. Utilizing multiple regression on a combined dataset of 21,904 data points spread over 2458 unique hotels, we show that the nature of destination and market moderates the association between hotel attributes and rents. Further, the results show that hotels at tourist destinations enjoy a rent premium across markets. However, this rent premium is positively associated with star rating, only in emerging markets, and is stable in developed markets. We contribute to price hedonic theory by proposing destination and market variables as moderators. Globalization and industry concentration make location decisions recurring and flexible. The study aims to help hotel managers by providing a contextual framework for making these strategic investment decisions.

Behavioral Factors in Hotel Location: a Study of Hotels from Opole Province in Poland

The choice of location is one of the key economic decisions for hotel owners. In modern economics traditional premises are increasingly questioned, and assumptions are often made involving imperfect competition, limited rationality of behavior, and the incomplete scope of information or the inability to use it effectively. This is also reflected in the theory of location within which a behavioral trend has been developed assuming the occurrence of non-economic, subjective factors in making location decisions. The aim of the paper is to identify behavioral factors in hotel location in Opolskie Province in Poland. The paper uses four main research methods: literature review, documentation, diagnostic survey and individual case studies. The study results confirm the importance of the behavioral approach in the process of selecting a location for independent hotels in Opolskie Province, involving the choice of secondary or primary locations. In the latter case, the decision-making process is based entirely on behavioral factors or is supplemented by them in situations where an objective approach is not connected with decision-making certainty. Behavioral factors such as intuition, emulation, experience, place of origin and residence, individual cases and the influence of others should be regarded as highly significant.

Do rising rents lead to longer commutes? A gravity model of commuting flows in Ireland

The classical monocentric city model suggests that property prices decrease and transport costs rise with distance to the urban centre, implying that employees face a trade-off between long commutes and high housing costs when making location decisions. Accordingly, some commuters might be forced to take on longer commutes due to rising rents in central locations. In this study, we investigate empirically whether the rental differential between employment centres and residential areas predicts changes in average commuting times. To this end, we consider a gravity model of commuting flows for Ireland over 2011–2016. We present results for Ireland and the metropolitan area of Dublin, which constitutes the largest commuting region in Ireland. The results imply that a 10% rise in rents in employment centres is associated with an up to 0.6 minute rise in one-way daily average commuting times nationally (about 2.2% of the average commute duration).

An agent-based learning-embedded model (ABM-learning) for urban land use planning: A case study of residential land growth simulation in Shenzhen, China

A forward-looking urban land use plan is crucial to a city’s sustainability, which requires a deep understanding of human-environment interactions between different domains, and modelling them soundly. One of the key challenges of modelling these interactions is to understand and model how human individuals make and develop their location decisions by learning that then shape urban land-use patterns. To investigate this issue, we have constructed an extended experience-weighted attraction learning model to represent the human agents’ learning when they make location decisions. Consequently, we propose and have developed an agent-based learning-embedded model (ABM-learning) for residential land growth simulation that incorporates a learning model, a decision-making model, a land use conversion model and the constraint of urban land use master plan. The proposed model was used for a simulation of the residential land growth in Shenzhen city, China. By validating the model against empirical data, the results showed that the site-specific accuracy of the model has been improved when embedding learning model. The analysis on the simulation accuracies has proved the argument that modelling individual-level learning matters in the agent’s decision model and the agent-based models. We also applied the model to predict residential land growth in Shenzhen from 2015 to 2035, and the result can be a reference for land-use allocation in detailed planning of Shenzhen. The ABM-learning is applicable to studying the past urban growth trajectory, aiding in the formulation of detailed residential land and public service facility planning and assessing the land use planning effectiveness.

German tax consolidation regimes in an international comparison

The tax climate of a jurisdiction may encourage or discourage potential investors. There are many tax factors taken into account by multinational enterprises when making location decisions. One of those factors is the possibility of creating a group for tax purposes. Consolidation allows two or more companies to be potentially considered as a single entity for tax purposes. The European Union and OECD member states offer tax grouping regimes on different conditions. This article reviews the German tax consolidation model and discusses requirements and options for that consolidation. Moreover, it compares German consolidation rules with the ones implemented in selected countries. The methodology of this article is determined by the research objectives and the research topic. The requirements for tax consolidation are specified in the law implemented in European countries. Hence, this article includes a legislative analysis of the regulations comprised in selected national acts. It also reviews the literature on the topic analysed, along with the statistical data collected by the German Federal Ministry of Finance in regard to the tax groups and their functioning.