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Hydrogen is a relatively new source of sustainable energy resources; presently, its usage ranges from direct energy generation in mixed-cycle thermal power plants to its usage in the internal combustion engine. If the generation of hydrogen is coupled with renewable energy resources, the use of hydrocarbons can be substantially reduced in both energy generation and transportation. In this paper, we conducted a national-level assessment to identify the hydrogen generation capacity of Pakistan. The methodology used in this study is a combination of spatial multi-criteria analysis and density-based clustering in a geographical information systems environment. Based on the analysis, the national clusters capable of producing green hydrogen were identified. The results shows that the hydrogen generation capacity for Pakistan is approximately 7 million tons per year using solar photovoltaic energy. The Surab-Gwadar alignment, N-25 national highway, and Quetta-to-D-I-Khan alignment offer potential hydrogen generation sites with water resources. Most of the identified sites for the production of hydrogen in the country were found to be near the national electricity transmission networks. The Best-Worst Method was further employed to provide policymakers with a road map for prioritizing the development of these capacities based on their proximity to the national networks, their terrain suitability, and their generation capacities. • This paper assesses the suitable sites for solar-based green hydrogen production in Pakistan. • The methodology used involves a combination of spatial multicriteria analysis, clustering, and the best-worst method. • Pakistan's theoretical annual hydrogen generation capacity is around 7 million tons annually. • The Surab-Gwadar alignment presents promising hydrogen generation opportunities. [ABSTRACT FROM AUTHOR]

Context and background: This study argues that government schemes to serve petty traders in Tanzania remain unsustainable mostly due to poor consideration of the impact the socioeconomic linkage has on location determinants. Goal and Objectives: This research aimed to understand how the articulation of petty trading operations with larger traders, directly or indirectly, influences location decisions. Methodology: The core of this research was based on a case study approach that involved surveys of petty traders and interviews with large-scale traders at the Mwenge trading center, along with documents review. Results: Petty traders select locations that maximize functioning as an economic enterprise and moderate survival risks. That is, the location of the trade is selected based on social ties, but the petty traders' success depends on economic links established with larger traders, from whom they get their merchandise, and over which they have very little control. The implications of these findings are: the level of articulation that governs location decisions, drags down the sustainability of government schemes, and gives rise to serious damage to the urban fabric; and two, the analysis of backward linkages combined with other location determinants provides the background against which the petty trading spaces identification, planning and designing could be analyzed. [ABSTRACT FROM AUTHOR]

This study provides a novel methodology at the nexus of Customer Discovery and business analytics for critical location decisions charity retailers with circular supply chains face. It integrates spatial network analysis with Customer Discovery and multicriteria decision-making. Traditional analyses are primarily based on customer location but for donated goods applying Customer Discovery and expert judgment and systematic analysis of data prevails. This integration provides an agile approach to producing optimal alternative locations, which can be applied to Habitat for Humanity ReStore, and Goodwill Industries, and similar organizations globally. This cross-disciplinary approach is practical and cost-effective and can increase efficiency, decrease risks, and strengthen organizational buy-in. It categorizes the drivers affecting location decisions and combines the current business model search techniques and an overall analytical framework to create the Expert Knowledge and Evidence-Based Location Methodology (EKELM). [ABSTRACT FROM AUTHOR]

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

Context and background: This study argues that government schemes to serve petty traders in Tanzania remain unsustainable mostly due to poor consideration of the impact the socio-economic linkage has on location determinants. Goal and Objectives: This research aimed to understand how the articulation of petty trading operations with larger traders, directly or indirectly, influences location decisions. Methodology: The core of this research was based on a case study approach that involved surveys of petty traders and interviews with large-scale traders at the Mwenge trading center, along with documents review. Results: Petty traders select locations that maximize functioning as an economic enterprise and moderate survival risks. That is, the location of the trade is selected based on social ties, but the petty traders’ success depends on economic links established with larger traders, from whom they get their merchandise, and over which they have very little control. The implications of these findings are: the level of articulation that governs location decisions, drags down the sustainability of government schemes, and gives rise to serious damage to the urban fabric; and two, the analysis of backward linkages combined with other location determinants provides the background against which the petty trading spaces identification, planning and designing could be analyzed.

The location of Low-Altitude Flight Service Station (LAFSS) is a comprehensive decision work, and it is also a multi-objective optimization problem (MOOP) with constraints. As a swarm intelligence search algorithm for solving constrained MOOP, the Immune Algorithm (IA) retains the excellent characteristics of genetic algorithm. Using some characteristic information or knowledge of the problem selectively and purposefully, the degradation phenomenon in the optimization process can be suppressed and the global optimum can be achieved. However, due to the large range involved in the low-altitude transition flight, the geographical characteristics, economic level and service requirements among the candidate stations in the corridor are quite different, and the operational safety and service efficiency are interrelated and conflict with each other. And all objectives cannot be optimal. Therefore, this article proposes a Modified Immune Algorithm (MIA) with two-layer response to solve the constrained multi-objective location mathematical model of LAFSS. The first layer uses the demand track as the cell membrane positioning pattern recognition service response distance to trigger the innate immunity to achieve the basic requirements of security service coverage. In the second layer, the expansion and upgrading of adjacent candidate sites are compared to the pathogen's effector, and the adaptive immunity is directly or indirectly triggered again through the cloning, mutation and reproduction between candidate sites to realize the multiobjective equilibrium of the scheme. Taking 486,000 km2 of Sichuan Province as an example, MIA for LAFSS is simulated by the MATLAB platform. Based on the Spring open source application framework of Java platform, the cesiumjs map data is called through easyui, and the visualization of site selection scheme is presented with the terrain data of Map World as the background. The experimental results show that, compared with dynamic programming and ordinary immunization, the immune trigger mode of double response and the improved algorithm of operation parameter combination designed by the Taguchi experiment, the total economic cost of location selection is reduced by 26.4%, the service response time is reduced by 25%, the repeat coverage rate is reduced by 29.5% and the effective service area is increased by 17.5%. The security risk, service efficiency and location cost are balanced. The present work is to provide an effective location method for the layout number and location of local transfer flight service stations. For complex scenes with larger scale of low-altitude flight supply and demand and larger terrain changes in the region, the above research methods can be used to effectively split and reduce the dimension. [ABSTRACT FROM AUTHOR]

The formal institutions of host countries are key to foreign direct investment (FDI) location choices. Most research suggests that formal institutional risks have a negative impact on FDI; however, some empirical findings indicate an insignificant or even positive influence. Multinational enterprises (MNEs) from developed countries consider weak institutions as risks and uncertainty, whereas MNEs from emerging markets (EMNEs) may prefer to invest in countries with risky institutions. Regarding the inconsistent arguments and the incongruent findings, the effect of formal institutional risks on location choice remains a puzzle. This study aims to refine the theory of formal institutions on FDI location choice of EMNEs. We argue that, for EMNEs, formal institutional risks reveal opportunities and limitations simultaneously, resulting in a nonlinear influence on FDI location choice. Using the 1997–2007 location decisions of Taiwanese MNEs, our results show an inverse U-shaped relationship between economic risk and FDI location choice. [ABSTRACT FROM AUTHOR]

This article analyses the competitive priorities underlying manufacturing location initiatives in developed economies. Specifically, building on secondary data, we compare and contrast manufacturing backshoring from China by companies headquartered in developed economies (308 cases) and Chinese foreign direct investment to developed economies (155 cases). Results suggest that both types of initiatives share some common priorities, such as exploiting the 'country of origin' effect and innovation opportunities in developed countries. At the same time, results highlight differences that may be attributed to the home country of the firm. In particular, cost priorities appear to be more important for Chinese companies than for backshoring ones. Findings offer insight into why manufacturing in developed economies may expand as a result of both repatriations and of foreign direct investments from emerging economies such as China, and point to potential areas of policy intervention. [ABSTRACT FROM AUTHOR]

The objective of this paper is to identify and analyse the factors that influence offshore location decisions from an institutional theory perspective. In the years, emerging economies have shown great growth potential and have attracted significant foreign direct investment, especially from companies willing to set up operations. Despite such a seemingly favourable trade environment, not all companies that entered an emerging economy have been successful. Thus, there is a need to understand the factors that influence the success of any offshore location decision. It is also important to understand the relative importance of these factors, in order to develop novel insights useful to practitioners. There is a lack of literature addressing this issue, which this study aims to fill. We conducted a multi-case analysis with examples of European companies entering India. The findings indicate that successful companies employed locally focused business strategies that enabled them to acquire important relationships and knowledge, and also to adapt to formal institutions, including governmental and regulatory procedures. It was found that, irrespective of size, disregarding collaborative strategies was the main reason for exiting India. These findings are highly relevant for managers and policy makers. [ABSTRACT FROM AUTHOR]

Ethiopia's special economic zone (SEZ) development program features fuzzy knowledge about location decision-making and its effect on host urban resident's quality of life (QOL). This study looks into SEZ's location decisions and the effect on the quality of life by considering Bole Lemi-1 (BL-1) and Eastern Industry Zone (EIZ) cases from central Ethiopia. The research anchors on conceptual frameworks of composited industrial location, political economy, and QOL. A household sample survey, in-depth interviews, and scanning of secondary information were employed. The subjective QOL indicators were analyzed using descriptive, exploratory analysis (EFA) and confirmatory factor analysis (CFA) techniques. The BL-1 and EIZ practices portray the SEZ location decisions in the country were largely driven politically with minimal techno-economic rationales, featuring a top-down approach and less participatory. The EFA result depicts that the 'Governance' structure witnessed high factor loadings with the strongest contribution in relative terms that can explain 25.29% of the total variance in QOL indicators. The 'Environment', 'Economic' and 'Sociocultural' factors can explain 16.75%, 14.69%, and 9.31% of the total variance, respectively. The CFA confirms the EFA-identified factors suggesting the influence of the identified variables on the QOL. We argue that there is a close association between a special economic zone location decision and people's QOL residing near zones. Yet, the extent depends on how well the swing balance across political and techno-economic dimensions is justified. We further debate that sub-components of QOL may have varying significance and influences under different geographies, policy environments, and the development status of countries. [ABSTRACT FROM AUTHOR]

Traffic flow is crucial for the efficient and safe operation of transportation systems. Understanding and managing traffic flow can help alleviate congestion, reduce travel time, and enhance transportation safety. In order to better identify traffic flow in a traffic network, we propose a new method that uses roadside units (RSUs) for path flow reconstruction. Roadside units (RSUs) are vital transportation facilities in cooperative vehicle infrastructure systems. They utilize modern communication technologies to exchange information directly with intelligent connected vehicles and their influence on accurate path flow reconstruction and average travel time are respectively analyzed. Considering the path flow uncertainty in traffic networks, a two-stage stochastic model is formulated, which aims to balance RSU deployment cost and value of reduced travel time. On the first stage, we solve a fully path flow reconstruction problem; On the second stage, we calculates the reduction on average travel time under different scenarios. To effectively handle the characteristics of the second stage model, we employ the integer L-shaped algorithm for solution. Numerical experiments suggest that (1) Expanding the size of scenarios has little impact on experimental results, which indicating that this model has good applicability; (2) some links play important roles in path flow reconstruction.

The purpose of this paper is to contribute to the limited research on universities' decision to innovate, using the network and knowledge-based perspectives as our theoretical underpinning. The first conclusion is that universities are more likely to locate their scientific productivity on a standalone campus than in a multi-campus system when the knowledge effect is more favorable. To make a contribution to industry and collaboration, universities are more likely to locate their scientific productivity in a multi-campus system. The second conclusion is that after controlling for endogeneity bias, the mean of academic performance for scientific productivity on a standalone campus is higher than it is on a multi-campus system. The third conclusion is that locating innovation activities in either a standalone or multi-campus system under theoretically appropriate conditions increases academic performance. These findings pose interesting challenges for knowledge management in innovation through a university's location decision. [ABSTRACT FROM AUTHOR]

This paper proposes to explore the existing literature on the impact of transportation infrastructure on firms' location decision. Using three distinct databases (EconLit, International Bibliography of the Social Sciences and Web of Science), the research identifies 338 potential papers, with 52 of them retained for the analysis. The paper presents a complete descriptive analysis of the selected papers, as well as a meta-analysis based on all the reported statistics. From a quantitative perspective, the meta-analysis results suggest a more positive and significant impact of transport infrastructure on finance, insurance, and real estate activities (FIRE). The meta-analysis also highlights the importance of taking into account the spatial and temporal dimensions of location activities when evaluating the impact of transport infrastructure. The omission of one of those dimensions might lead to overestimation of the effect, and therefore bias in the observed results. • The impact of transport on firms' location is studied using a meta-analysis. • In the worst case scenario, no significant impacts of transport are noted on firms' location. • In the better case scenario, results suggest a positive and significant impact. • Results also imply that the omission of spatial or temporal dimensions in the data might lead to biased results. [ABSTRACT FROM AUTHOR]

Since the emergence of new coronaviruses and their variant virus, a large number of medical resources around the world have been put into treatment. In this case, the purpose of this article is to develop a handback intravenous intelligence injection robot, which reduces the direct contact between medical staff and patients and reduces the risk of infection. The core technology of hand back intravenous intelligent robot is a handlet venous vessel detection and segmentation and the position of the needle point position decision. In this paper, an image processing algorithm based on U-Net improvement mechanism (AT-U-Net) is proposed for core technology. It is investigated using a self-built dorsal hand vein database and the results show that it performs well, with an F1-score of 93.91%. After the detection of a dorsal hand vein, this paper proposes a location decision method for the needle entry point based on an improved pruning algorithm (PT-Pruning). The extraction of the trunk line of the dorsal hand vein is realized through this algorithm. Considering the vascular cross-sectional area and bending of each vein injection point area, the optimal injection point of the dorsal hand vein is obtained via a comprehensive decision-making process. Using the self-built dorsal hand vein injection point database, the accuracy of the detection of the effective injection area reaches 96.73%. The accuracy for the detection of the injection area at the optimal needle entry point is 96.50%, which lays a foundation for subsequent mechanical automatic injection.

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

Aiming at the location research blank of the AG600 amphibious aircraft marine rescue base, the location decision index system of the AG600 is established, and the AG600 location decision model based on the interval intuitionistic fuzzy theory and improved TOPSIS method is constructed. Through investigation and statistical analysis, the evaluation system with 10 indices is determined based on applicability, safety, and accessibility, and in the process of quantization of index assignment, a fuzzy conversion method for different indices is proposed. The interval intuitionistic fuzzy number of each index is obtained by combining objective calculation and subjective assignment, and the interval intuitionistic fuzzy decision matrix is constructed. The fuzzy entropy method is used to calculate the index weight, and then the improved Technique for Order of Preference by Similarity (TOPSIS) is used to evaluate and rank the rescue bases, the scientific and reasonable location decision results are obtained. Moreover, STOPSIS and WS are used to analyze and demonstrate the sorting inversion problem, and the value is 0.908, which further proves the effectiveness of the method proposed in this paper. Finally, taking the South China Sea islands as an example, the correctness and reliability of the proposed model is verified by comparison with the calculation results of the score function method and the projection method.

Amid a growing interest in how geographical location functions as a motive for self-initiated expatriate (SIE) academics to choose their next employer, more research is needed to understand how academics select a potential location for their expatriation. With the goal of contributing to the literature on SIE academics, this study explores the cues that drive early career-stage academics to choose a destination—Copenhagen or Amsterdam—when accepting an international job offer. The data reveal that four frames drive SIE academics' meaning-making regarding a potential destination city: positive impression, livable city, familiarity, and political stability and career development expectations. This paper concludes with a discussion of how our findings contribute to the higher education and mobility literature and offers important implications for practice. [ABSTRACT FROM AUTHOR]

Multi-functional rainwater storage space is a practical solution to flood and runoff pollution in high-density built-up areas. This study presents a location decision method to improve the control effect of total runoff volume, runoff peak flow, and runoff pollution. The results show that this method can accurately and quickly screen available locations for multi-functional rainwater storage space and prioritize them as optimum, suitable, less suitable, unsuitable, and not available for construction. In the case of this study, greening the road can achieve a better effect on runoff control. [ABSTRACT FROM AUTHOR]

For tourists in the post-COVID era, it is a popular choice to experience nature and idyllic rural life in fields, gardens, and farms instead of crowding into high-level services in modern tourist destinations. This trend has created a focus on sustainable development within tourism. Agritourism is an alternative tourism experience that demonstrates high potential for the tourism industry while positively impacting agricultural production in rural areas. A suitable location selection process is essential to effectively developing agritourism and sustainability. However, the current literature on this issue is still limited. Therefore, this study introduces a combined decision-making model for optimal agritourism destination identification in the context of sustainable development. This research highlights the use of the spherical fuzzy set (SFSs), in which the spherical fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) determines the criteria's importance in combination with their causal relationship, and the spherical fuzzy Evaluation based on Distance from Average Solution (EDAS) finds the alternative destinations' priority. The model's efficiency is illustrated through an empirical study of Vietnam and by a sensitivity analysis. The resulting research found that decision-makers should consider the factors of local living conditions (ASC10), and local agriculture products (ASC3) when investigating agritourism locations. Consequently, the optimal destination for sustainable agritourism development was found to be Lam Dong (AD9), which can efficiently promote tourism activities while increasing the value of agriculture in the countryside. These findings can assist decision-makers in selecting tourism sites in other regions and other tourism development projects. [ABSTRACT FROM AUTHOR]

For a long time, it was assumed that hard location factors (e.g. workforce, land) were the primary influence on the location decisions of firms. In the course of the tertiarization of the economy and linked increases in the qualification of employees as well as changes in values and timemodels, soft location factors (e.g. image, cultural offerings) are expected to gain in importance. Therefore, this paper examines whether the importance of soft location factors has really increased in comparison to traditional, hard location factors. For this purpose, company surveys conducted by the Chamber of Commerce and Industry Mittlerer Niederrhein (Germany) in 2002 and 2017 are analysed. More than 1,000 firms took part in both surveys and evaluated more than 50 location factors in terms of their importance. The results of the study show that the importance of soft location factors related to quality of life (e.g. safety, image) and the city centre (e.g. parking) increased significantly over this time period. In comparison, the importance of the hard location factors stagnated or even decreased (without including the factor information and communication infrastructure). These results provide indications for the local authorities concerning which site conditions are important for retaining firms or attracting new companies in the future. [ABSTRACT FROM AUTHOR]

This study seeks to investigate the relational structure and factors that influence the locational decision of organizations present in the Biotechnology Local Production Arrangement (APL) in the metropolitan region of Belo Horizonte (RMBH). The data were collected through documentary research and interviews and analyzed through descriptive statistics, content analysis and sociometric analysis. The results indicated the importance of considering both the availability of space and infrastructure, as well as issues of proximity, funding and personal characteristics. It was also noticed that the relationships between the actors are incipient and there is a concentration of companies in the APL, although it is not high. [ABSTRACT FROM AUTHOR]

The fossil resource consumption, which is scarce for the solution of the increasing energy demand problem as the population increases, is replaced by the consumption of renewable energy resources. Solar energy from renewable energy sources is the type of energy with the highest potential on earth. The maximization of the efficiency to be taken from solar energy is possible with the correct selection of the location. The decision to decide on more than one criterion for multiple alternatives is a very difficult problem. Therefore, the problem of choosing a solar power plant is a complex decision problem, and this study aims to solve the problem of the most appropriate location for the Solar Power Plant by using Hesitant Fuzzy AHP. Based on linguistic expressions of three different decision makers, three alternative locations were evaluated by considering four different evaluation criteria.

[Display omitted] • Subjective and objective double weight decision. • Improved TOPSIS model and spatial analysis of road network. • Double sensitivity analysis was used to verify the results. • Two-stage selection of regions and candidate sites to determine the best location. [ABSTRACT FROM AUTHOR]

Warehouses are crucial infrastructures in supply chains. As a strategic task that would potentially impact various long-term agenda, warehouse location selection becomes an important decision-making process. Due to quantitative and qualitative multiple criteria in selecting alternative warehouse locations, the task becomes a multiple criteria decision-making problem. Current literature offers several approaches to addressing the domain problem. However, the number of factors or criteria considered in the previous works is limited and does not reflect real-life decision-making. In addition, such a problem requires a group decision, with decision-makers having different motivations and value systems. Analysing the varying importance of experts comprising the group would provide insights into how these variations influence the final decision regarding the location. Thus, in this work, we adopted the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to address a warehouse location decision problem under a significant number of decision criteria in a group decision-making environment. To elucidate the proposed approach, a case study in a product distribution firm was carried out. Findings show that decision-makers in this industry emphasise criteria that maintain the distribution networks more efficiently at minimum cost. Results also reveal that varying priorities of the decision-makers have little impact on the group decision, which implies that their degree of knowledge and expertise is comparable to a certain extent. With the efficiency and tractability of the required computations, the TOPSIS method, as demonstrated in this work, provides a useful, practical tool for decision-makers with limited technical computational expertise in addressing the warehouse location problem.

For a long time, it was assumed that hard location factors (e.g. workforce, land) were the primary influence on the location decisions of firms. In the course of the tertiarization of the economy and linked increases in the qualification of employees as well as changes in values and timemodels, soft location factors (e.g. image, cultural offerings) are expected to gain in importance. Therefore, this paper examines whether the importance of soft location factors has really increased in comparison to traditional, hard location factors. For this purpose, company surveys conducted by the Chamber of Commerce and Industry Mittlerer Niederrhein (Germany) in 2002 and 2017 are analysed. More than 1,000 firms took part in both surveys and evaluated more than 50 location factors in terms of their importance. The results of the study show that the importance of soft location factors related to quality of life (e.g. safety, image) and the city centre (e.g. parking) increased significantly over this time period. In comparison, the importance of the hard location factors stagnated or even decreased (without including the factor information and communication infrastructure). These results provide indications for the local authorities concerning which site conditions are important for retaining firms or attracting new companies in the future.

In 2017–2018, Seattle-based Tech behemoth Amazon executed a highly publicised location-finding process for a $5 billion investment project, dubbed ‘HQ2’. Owing to the combination of high investment volume and the company’s unique public exposure, the HQ2 process is on course to becoming a basic yardstick for future foreign direct investment (FDI) projects all over the world. This article compiles the company’s previously unpublished site selection criteria and develops an evidence-based system of investment decision arguments which is employed to test the currently dominant approaches in location decision theory—behavioural, neoclassical, and institutional. Our results identify gaps vis-à-vis this emerging ‘Gold Standard’ and we propose the addition of a fourth, project-oriented approach to theory to fill the detected shortcomings. Furthermore, this system equips policymakers with a tool to evaluate their investment attraction strategies based on the decision criteria extracted from the HQ2 process.

The aim of this paper is to capture the changed location decision-making processes and location factors of the automotive industry, resulting from the current challenges brought by electro mobility. From the Taylorist assembly-line production system in the “Fordism” era to the just-in-time focused manufacturing of the Japanese carmakers during “post-Fordism” and at the turn of the millennium with global production and new technologies in the digital age, location analysis has changed massively over time. The same is to be expected for the fourth revolution in the industry. For this reason, the decision-making process of a major German car manufacturer is analysed in a field study conducted over a two-year period. Based on this, a decision process that takes the new framework conditions into account is modelled. The relevant location factors are then examined in a survey of the relevant departments in the BMW Group. Due to the changed production requirements in the course of the electrification, the uncertainty in the technological change and the unstable political trading conditions, the factors: network suitability, risk exposure, optimal sunk cost usage and sustainability play central roles. Before the latest economic crisis, the industry was focused on exploiting opportunities and expanding the production network. This tendency now seems to be transformed by a volatile technological future and by cost pressure. This means that ‘sustainability’ is increasingly important in automobile industry decision-making, but in specific ways.

Multi-functional rainwater storage space is a practical solution to flood and runoff pollution in high-density built-up areas. This study presents a location decision method to improve the control effect of total runoff volume, runoff peak flow, and runoff pollution. The results show that this method can accurately and quickly screen available locations for multi-functional rainwater storage space and prioritize them as optimum, suitable, less suitable, unsuitable, and not available for construction. In the case of this study, greening the road can achieve a better effect on runoff control.

Multi-site selection is a hot research issue for equipment manufacturing enterprises. With the development of smart industry, equipment manufacturing enterprises have entered the era of personalized and small batch manufacturing. Enterprises want to better meet customer needs and win competition, they must carry out scientific factory planning and site selection, so as to ensure quick response to the market. Based on this, this paper proposes a two-stage location selection model. Firstly, the method uses fuzzy numbers to express the demand size of demand points. Secondly, the distance factor is used as a criterion to select the candidate manufacturing bases with sufficient available resources. Next, the location model of enterprise manufacturing base is established which the goal of maximizing service efficiency and the constraints of time, cost and demand. Finally, a random numerical example is used to simulate the model, and lingo is used to solve it. [ABSTRACT FROM AUTHOR]

The construction of the Sichuan-Tibet railway is encountered with some problems such as complicated geological conditions, bad climate, active plate movement, and sensitive ecological environment. Therefore, scientific and reasonable site selection is an essential guarantee for the smooth construction of the Sichuan-Tibet railway. Through constructing weighted scoring function and intuitionistic fuzzy similarity model and researching the dynamic intuitionistic fuzzy multi-attribute decision-making method considering time factor, the location decision of client-supplied goods and materials support center for Sichuan-Tibet railway construction can be complete, and the research theories and methods of location problem worldwide can be analyzed. Given the route direction and engineering construction of the Ya'an-Linzhi section of the Sichuan-Tibet railway, this paper aims to set up seven client-supplied goods and materials support centers as alternative site selection schemes, which integrates six factors (transportation, geological conditions, climate environment, site selection characteristics, engineering construction, and communication conditions) and constructs 12 index systems for client-supplied goods and materials support center location selection. Combining with the index system, the intuitionistic fuzzy decision-making matrices for four periods are established. Besides, using a dynamic intuitionistic multi-attribute decision-making method, the weighted results of similarity decision-making matrices are compared, and the location schemes of client-supplied goods and materials support centers are sequenced. The results demonstrate that Linzhi is the best site selection scheme for the construction client-supplied goods and materials support center of Ya'an to Linzhi section of the Sichuan-Tibet Railway, providing reference significance for supporting the construction of the Sichuan-Tibet Railway Project. [ABSTRACT FROM AUTHOR]

We analyze empirically how firms' characteristics affect the foreign affiliates location decisions of heterogeneous firms in different markets. Using a European firm-level data and estimating the marginal effects for the multinomial logit model, the results corroborate the relevance of firms' characteristics in their investment decisions, particularly the productivity level. [ABSTRACT FROM AUTHOR]

The aim of this paper is to capture the changed location decision-making processes and location factors of the automotive industry, resulting from the current challenges brought by electro mobility. From the Taylorist assembly-line production system in the "Fordism" era to the just-in-time focused manufacturing of the Japanese carmakers during "post-Fordism" and at the turn of the millennium with global production and new technologies in the digital age, location analysis has changed massively over time. The same is to be expected for the fourth revolution in the industry. For this reason, the decision-making process of a major German car manufacturer is analysed in a field study conducted over a two-year period. Based on this, a decision process that takes the new framework conditions into account is modelled. The relevant location factors are then examined in a survey of the relevant departments in the BMW Group. Due to the changed production requirements in the course of the electrification, the uncertainty in the technological change and the unstable political trading conditions, the factors: network suitability, risk exposure, optimal sunk cost usage and sustainability play central roles. Before the latest economic crisis, the industry was focused on exploiting opportunities and expanding the production network. This tendency now seems to be transformed by a volatile technological future and by cost pressure. This means that 'sustainability' is increasingly important in automobile industry decision-making, but in specific ways. [ABSTRACT FROM AUTHOR]

This paper combines evolutionary game theory and input–output analysis to assess firms' strategic location choice. To evaluate the model, firms competed in the automotive sector of Mercosur. To decide where to locate, the following exogenous factors were considered: potential market; local productive interdependence; tax incentive; and macroeconomic stability. Firms assigned weights to these factors in their location decision. It was found that competing in a market where there is tax exemption is not always an ideal location decision, contradicting the common-sense assumption by which there is a direct relationship between government incentives and the attractiveness of regions. [ABSTRACT FROM AUTHOR]