Firm Relocation and Accessibility of Locations

Bok, Michiel de; Sanders, Frank H.

doi:10.1177/0361198105190200105

Cited by 16 publications

(3 citation statements)

References 20 publications

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“…While the topics of company location decisions and freight transportation mode choice are widely studied in research, their interrelationship, in contrast, has been barely studied, as illustrated by Table 1. A closer look reveals that most of the literature on distance determination of infrastructures to companies refers to passenger transport rather than freight transport [54][55][56]. Ref.…”

Section: Proximity Of Business Locations and Transport Infrastructurementioning

confidence: 99%

Economic Risk Potential of Infrastructure Failure Considering In-Land Waterways

Wehrle

Wiens

Neff

et al. 2022

Water

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Purpose—Unreliable transport infrastructure can cause negative externalities for industries. In this article, we analyze how the private sector is affected by infrastructure failure of public transport infrastructure, using waterways as an example. Methodology—To investigate the affectedness of riparian industries, we chose two complementary parallel approaches: A proximity analysis via GIS, and a concluding survey among the identified waterway-dependent industries. An exemplary application is validated by stakeholders. Findings—We identify a predominance of location preferences in dependence on waterways for mining, chemical, and metal industries. Their risk tolerance exhibits potentially severe impacts on industries if reliable transport cannot be ensured via waterways, as our paper provides essential insights into the relationship between infrastructure failure and company decisions. Most importantly, we reveal that a lack of alternatives due to missing capacities of other transport modes causes realistic threats to business locations. Practical implications—include that a regional focus is crucial for the empirical risk assessment of transport infrastructure. Hence, the data collection should relate to the regional focus groups, particularly the directly affected industries. In addition, infrastructure maintenance should integrate a risk focus and consider the short and long-run impacts on industries.

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Section: Proximity Of Business Locations and Transport Infrastructurementioning

confidence: 99%

Economic Risk Potential of Infrastructure Failure Considering In-Land Waterways

Wehrle

Wiens

Neff

et al. 2022

Water

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show abstract

“…In general, all approaches of the empirical research have in common that they represent the firm as an active decision-making agent: a firm chooses a location from a number of alternatives. By doing so, it takes economic and or non-economic factors into account (de Bok & Sanders, 2005).…”

Section: Conceptual Framework Of Location Choice Modelsmentioning

confidence: 99%

Modeling enterprise location choice decision behavior

2021

JTLU

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This study presents a location choice model that incorporates urban spatial effects for enterprises. A modeling framework is developed to analyze decisions regarding location choice for enterprises using a series of discrete choice models including multinomial logit without any urban spatial effects, multinomial logit incorporating urban spatial effects, and mixed logit incorporating urban spatial effects. In this framework, urban spatial effects, such as the urban spatial correlation among enterprises in deterministic terms and the urban spatial correlation among zones in the error term, are captured by mixed logit models in particular and discrete choice models in general. The results indicate that the urban spatial effects and the land prices in a given zone strongly affect the decision-making process of all the enterprises in the Tokyo metropolitan area. Moreover, the important role of urban spatial effects in the proposed model will be clarification through comparing the three above models. This comparison will be implemented on the basis of three types of indicators such as the log likelihood ratio, Akaike information indicator, and hit ratio of each model.

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“…The organizations must predominantly deal with making the location decisions by the time of new investments, or relocation (De Bok and Sanders, 2005). The most common facility types to be located are industrial, retail, warehousing, residential and leisure units.…”

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confidence: 99%

A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era

Mosallaeipour

Shavarani

Steens

et al. 2019

JCRE

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Purpose This paper aims to introduce a practical expert decision support system (EDSS) for performing location analysis and making real estate location decisions in the organization’s facility and real estate management (FREM) department in presence of several decision criteria, under risk and uncertainty. This tool is particularly useful for making strategic decisions in facility planning, portfolio management, investment appraisal, development project evaluations and deciding on usage possibilities in an unbiased, objective manner. Design/methodology/approach The proposed EDSS uses fuzzy logic and uncertainty theory as two of the most useful tools to deal with uncertainties involved in the problem environment. The system performs an unbiased mathematical analysis on the input data provided by the decision-maker, using a combination of Analytical Hierarchy Process (AHP) and Global Criterion Method; determines a suitable compromise level between the objectives; and delivers a set of locations that complies best with the outlined desires of the management as the final solution. The application of the system is tested on a real case and has delivered satisfactory results. Findings The proposed EDSS took the defined objectives, the list of alternative locations, and their attributes as the required input for problem-solving, and used a combination of AHP, Possibilistic approach, and global criterion method to solve the problem. The delivered outcome was a set of proper locations with the right attributes to meet all objectives of the organization at a satisfactory level, confirmed by the problem owners. Originality/value The application of such a system with such a degree of preciseness and complexity has been very limited in the literature. The system designed in this study is an Industry 4.0 decision making tool. For designing this system several body of knowledge are used. The present study is particularly useful for making strategic decisions in the domains of portfolio management, investment appraisal, project development evaluations and deciding on property usage possibilities. The proposed EDSS takes the information provided by the experts in the field (through qualitative and quantitative data collecting) as the inputs and operates as an objective decision-making tool using several bodies of knowledge considering the trends and developments in the world of FREM. The strong scientific method used in the core of the proposed EDSS guarantees a highly accurate result.

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Firm Relocation and Accessibility of Locations

Cited by 16 publications

References 20 publications

Economic Risk Potential of Infrastructure Failure Considering In-Land Waterways

Economic Risk Potential of Infrastructure Failure Considering In-Land Waterways

Modeling enterprise location choice decision behavior

A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era

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