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Journal articles on the topic 'Location choice'

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Published: 4 June 2021

Last updated: 20 February 2023

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1

Branikas, Ioannis, Harrison Hong, and Jiangmin Xu. "Location choice, portfolio choice." Journal of Financial Economics 138, no. 1 (October 2020): 74–94. http://dx.doi.org/10.1016/j.jfineco.2019.10.010.

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2

SHEARD, PHILIP. "Choice location." Nursing 27, no. 11 (November 1997): 6–8. http://dx.doi.org/10.1097/00152193-199711000-00003.

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3

Huang, Shengsheng, and John Cantwell. "FDI location choice: the role of locational ambidexterity." Multinational Business Review 25, no. 1 (April 18, 2017): 28–51. http://dx.doi.org/10.1108/mbr-04-2016-0016.

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Purpose This paper proposes locational ambidexterity as a location-specific factor based on an operation flexibility perspective, and explores why and how multinational corporations (MNCs) proactively deal with uncertainty by valuing locational ambidexterity in making location decisions. Design/methodology/approach Location choice data for foreign direct investment (FDI) at a sub-national level in China is used to test the role of locational ambidexterity. Findings We find that FDI generally prefers locations with high ambidexterity. Moreover, investments from a heterogeneous country context are more sensitive to locational ambidexterity than those from a similar country context. However, there is no significant evidence that wholly owned investments favor locational ambidexterity more than do international joint ventures. Research limitations/implications An alternative operationalization of locational ambidexterity may be needed. Future research could explore the sources of locational ambidexterity, identify other firm- and industry-level factors that could alter the value of ambidexterity, investigate how MNCs integrate locational ambidexterity into organization-specific option creation strategies and test the ambidexterity perspective with micro-level location choice data. Practical implications Locational ambidexterity may reduce the overall risk and adjustment cost of future changes. FDI may choose a location with high ambidexterity, i.e. a balanced portfolio of location-specific determinants, under uncertainty about the future. Originality/value Drawing on the notion of location flexibility from Buckley and Casson (1998), this study identifies a new location character, locational ambidexterity, and proposes that MNCs address uncertainty by choosing ambidextrous locations that offer more flexibility for MNCs to change or respond to potential volatility. Selecting locations with high ambidexterity is thus an alternative and complement to the organization-specific flexibility creation strategies suggested by the literature on real option and flexibility.

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4

Schaefer, Donald F. "Locational Choice in the Antebellum South." Journal of Economic History 49, no. 1 (March 1989): 145–65. http://dx.doi.org/10.1017/s0022050700007373.

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This article examines the economic and noneconomic factors that influenced the migration decisions of antebellum Southern households. It appears that nonslaveowners were neither pushed to inferior locations nor did they move independently of the economic consequences. For slaveowners, the observed links between locational choice and the economic characteristics of locations are weaker. The proportion of whites in a location's population was positively associated with the choice of a location for the nonslaveowners. This association was not found for any other group.

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5

Bilal, Adrien, and Esteban Rossi-Hansberg. "Location as an Asset." Econometrica 89, no. 5 (2021): 2459–95. http://dx.doi.org/10.3982/ecta16699.

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The location of individuals determines their job and schooling opportunities, amenities, and housing costs. We conceptualize the location choice of individuals as a decision to invest in a “location asset.” This asset has a current cost equal to the location's rent, and a future payoff through better job and schooling opportunities. As with any asset, savers in the location asset transfer resources into the future by going to expensive locations with high future returns. In contrast, borrowers transfer resources to the present by going to cheap locations that offer few other advantages. Holdings of the location asset depend on its comparison to other assets, with the distinction that the location asset is not subject to borrowing constraints. We propose a dynamic location model and derive an agent's mobility choices after experiencing income shocks. We document the investment dimension of location and confirm the core predictions of our theory using French individual panel data from tax returns.

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6

Ekici, Özgün, and Bugra Caskurlu. "Location Choice under Spillovers." Business and Economics Research Journal 13, no. 1 (January 31, 2022): 1–9. http://dx.doi.org/10.20409/berj.2022.358.

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7

Gupta, Surabhi, Peter Vovsha, and Rebekah Anderson. "Choice of Workplace Location." Transportation Research Record: Journal of the Transportation Research Board 2493, no. 1 (January 2015): 48–57. http://dx.doi.org/10.3141/2493-06.

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8

Bryant, Shannon. "Location, location, location: Anaphor selection in English locative prepositional phrases." Proceedings of the Linguistic Society of America 7, no. 1 (May 5, 2022): 5263. http://dx.doi.org/10.3765/plsa.v7i1.5263.

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This paper presents experimental work on the relative naturalness of subject-oriented reflexives (herself) and pronouns (her) in English locative prepositional phrases (e.g., Michele set a glass next to her/herself). Syntactic approaches to anaphor licensing have tended to focus on the lack of complementarity in such constructions; however, it has long been observed that preferences between forms may depend on verb meaning (change in location vs. perception vs. possession) and spatial relation (+contact vs. -contact), with very strong preferences reported in some cases. This study aims to clarify the extent to which these two factors shape anaphor choice. Results confirm that both play a significant role: reflexives are most natural in the expression of change in location and direct contact, while pronouns pattern oppositely. Importantly, preferences between forms are less stark than those found in constructions where syntactic constraints are assumed to render one form ungrammatical. I suggest that these findings favor a treatment of English anaphora that takes event structure into account.

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9

Vandeviver, Christophe, and Wim Bernasco. "“Location, Location, Location”: Effects of Neighborhood and House Attributes on Burglars’ Target Selection." Journal of Quantitative Criminology 36, no. 4 (October 11, 2019): 779–821. http://dx.doi.org/10.1007/s10940-019-09431-y.

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Abstract Objectives To empirically test whether offenders consider environmental features at multiple spatial scales when selecting a target and examine the simultaneous effect of neighborhood-level and residence-level attributes on residential burglars’ choice of residence to burglarize. Methods We combine data on 679 burglaries by 577 burglars committed between 2005 and 2014 with data on approximately 138,000 residences in 193 residential neighborhoods in Ghent, Belgium. Using a discrete spatial choice approach, we estimate the combined effect of neighborhood-level and residence-level attributes on burglars’ target choice in a conditional logit model. Results Burglars prefer burglarizing residences in neighborhoods with lower residential density. Burglars also favor burglarizing detached residences, residences in single-unit buildings, and renter-occupied residences. Furthermore, burglars are more likely to target residences in neighborhoods that they previously and recently targeted for burglary, and residences nearby their home. We find significant cross-level interactions between neighborhood and residence attributes in burglary target selection. Conclusions Both area-level and target-level attributes are found to affect burglars’ target choices. Our results offer support for theoretical accounts of burglary target selection that characterize it as being informed both by attributes of individual properties and attributes of the environment as well as combinations thereof. This spatial decision-making model implies that environmental information at multiple and increasingly finer scales of spatial resolution informs crime site selection.

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Zhan, Crystal. "SCHOOL CHOICE PROGRAMS AND LOCATION CHOICES OF PRIVATE SCHOOLS." Economic Inquiry 56, no. 3 (February 5, 2018): 1622–45. http://dx.doi.org/10.1111/ecin.12560.

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Konrad, Kai A., Harald Künemund, Kjell Erik Lommerud, and Julio R. Robledo. "Geography of the Family." American Economic Review 92, no. 4 (August 1, 2002): 981–98. http://dx.doi.org/10.1257/00028280260344551.

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We study the residential choice of siblings who are altruistic towards their parents. The firstborn child's location choice influences the behavior of the second-born child and can shift some of the burden of providing care for the parents from one child to the other. These strategic considerations lead to an equilibrium location pattern with firstborn children locating further away from their parents than second-born children. We also analyze the location choices empirically using German data. These data confirm our theoretical predictions.

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12

Wang, Ruoniu. "Tracking “Choice” in the Housing Choice Voucher Program: The Relationship Between Neighborhood Preference and Locational Outcome." Urban Affairs Review 54, no. 2 (April 25, 2016): 302–31. http://dx.doi.org/10.1177/1078087416646205.

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Do residential locations of Housing Choice Voucher (HCV) households reflect tenants’ preferences for neighborhood quality? Study results come from a three-part methodology: (1) survey of voucher holders to find neighborhood preferences and other factors in the consumer decision-making model, (2) geographic information system (GIS) analysis of actual locational outcomes in terms of neighborhood opportunity and transportation accessibility, and (3) quantitative analysis of the strength of preference–outcome relationships. The results reveal that survey participants placed high priority on neighborhoods that were safe and clean, and with quality schools. Despite this, higher priority on quality housing and search barriers affected the housing choice. As such, to a large extent, the residents did not live in places that met their location preferences. The study calls for an expansion of location assessment measures in the current policy framework and the provision of more information about housing and neighborhood options to voucher recipients.

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13

Colombotos, John, Richard L. Ernst, and Donald E. Yett. "Physician Location and Speciality Choice." Contemporary Sociology 17, no. 3 (May 1988): 391. http://dx.doi.org/10.2307/2069679.

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14

Lv, Ping, and Francesca Spigarelli. "The determinants of location choice." International Journal of Emerging Markets 11, no. 3 (July 18, 2016): 333–56. http://dx.doi.org/10.1108/ijoem-09-2014-0137.

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Purpose – The purpose of this paper is to analyze the role of institutional distance and host country attractiveness in location determinants of Chinese Foreign investments in EU in the renewable energy sector, taking into account bilateral political and economic relations. Design/methodology/approach – A firm-level Ministry of Commerce (MofCom) database of greenfield and non-greenfield Chinese investments abroad is used. A six fixed-effects logit analysis is performed. Findings – Chinese firms tend to invest in EU countries with reduced rule of law; market affluence is an attraction factor for them, but they do not seem to be human capital asset-seekers. Countries with politically stable environment are most attractive to sales/services subsidiaries; while countries with good control of corruption, low trade barriers and encouraging foreign ownership are most attractive to manufacturing subsidiaries. A large market is the most attractive factor for R & D subsidiaries, and a rich market is the most attractive factor for manufacturing subsidiaries. Manufacturing subsidiaries are more technological asset-seekers. R & D subsidiaries are the most non-human capital asset-seekers. Research limitations/implications – The study extends the state of the art of the literature by developing a theoretical framework, grounded on the influence of host country institutional factors and on endowment of resources on the location choice of Chinese investors. Further variables should be included in the future (industrial specialization of host country, cultural distance, bilateral ties). Practical implications – Policy implications are relevant. They are related both to outward foreign direct investment attraction policies and to Europe-China cooperation dialogue. With reference to attraction policies, as Chinese green firms are technological asset-seekers, more than human capital asset-seekers, EU countries interested in partnering with Chinese investors should develop specific measures targeting encouraging technology spillover. Even R & D subsidiaries should be tempted with technology-oriented measures. With reference to Europe-China cooperation, the paper findings support suggestions for a more active European position on foreign investments in key European energy sectors. Originality/value – The paper is grounded on an improved theoretical model, tested through a unique Mofcom firm-level database. Originality lies in the fact that the authors provide a sectoral insight. The need for sectoral analysis is fundamental as Chinese industrial development and internationalization path vary extensively across industry, due to policy interventions, supportive measures and prioritized initiatives. Zhang et al. (2011, p. 229) found that – specifically – the energy sector is highly sensitive to host country institutional context, therefore Chinese foreign direct investment are more likely to be exposed to regulatory and competitive pressure compared to other industries.

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Jain, Naveen K., Somnath Lahiri, and Douglas R. Hausknecht. "Emerging market multinationals' location choice." European Business Review 25, no. 3 (April 26, 2013): 263–80. http://dx.doi.org/10.1108/09555341311314816.

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Brekke, Kurt R., and Odd Rune Straume. "Bilateral monopolies and location choice." Regional Science and Urban Economics 34, no. 3 (May 2004): 275–88. http://dx.doi.org/10.1016/s0166-0462(03)00046-2.

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Lin, Yen-Ju, and Kuang-I. Tu. "Vertical Outsourcing and Location Choice." Procedia Economics and Finance 5 (2013): 494–501. http://dx.doi.org/10.1016/s2212-5671(13)00058-0.

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18

Hong, Chang, and Haoyu Wu. "Export spillover and location choice." Journal of the Japanese and International Economies 49 (September 2018): 54–68. http://dx.doi.org/10.1016/j.jjie.2018.04.001.

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LIN, YAN-SHU, JIN-LI HU, and PENG-CHIAO XIA. "LOCATION CHOICE AND PATENT LICENSING*." Manchester School 81, no. 2 (February 26, 2012): 121–42. http://dx.doi.org/10.1111/j.1467-9957.2011.02271.x.

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20

Morain, William D. "Physician Location and Specialty Choice." Plastic and Reconstructive Surgery 79, no. 4 (April 1987): 658. http://dx.doi.org/10.1097/00006534-198704000-00032.

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21

Jayet, Hubert, Glenn Rayp, Ilse Ruyssen, and Nadiya Ukrayinchuk. "Immigrants’ location choice in Belgium." Annals of Regional Science 57, no. 1 (April 19, 2016): 63–89. http://dx.doi.org/10.1007/s00168-016-0761-x.

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22

Kulchina, Elena. "Media coverage and location choice." Strategic Management Journal 35, no. 4 (May 24, 2013): 596–605. http://dx.doi.org/10.1002/smj.2106.

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23

Herger, Nils, and Steve McCorriston. "On discrete location choice models." Economics Letters 120, no. 2 (August 2013): 288–91. http://dx.doi.org/10.1016/j.econlet.2013.04.015.

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24

Turnbull, Geoffrey K. "Revealed Preference and Location Choice." Journal of Urban Economics 41, no. 3 (May 1997): 358–76. http://dx.doi.org/10.1006/juec.1996.2005.

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25

Kopel, Michael, Mario Pezzino, and Anna Ressi. "Location Choice and Contract Bargaining." Managerial and Decision Economics 37, no. 2 (March 27, 2015): 140–48. http://dx.doi.org/10.1002/mde.2732.

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26

Owens, Mark F., and Adam D. Rennhoff. "Motion picture production incentives and filming location decisions: a discrete choice approach." Journal of Economic Geography 20, no. 3 (November 23, 2018): 679–709. http://dx.doi.org/10.1093/jeg/lby054.

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Abstract We use a discrete choice model to study the impact of tax incentives on firm location choices in situations involving heterogeneous geographic characteristics, heterogeneous firm preferences and large choice sets. We apply our model to investigate the impact of movie production incentives on filming location choices for movies produced from 1999 to 2013. We gather the characteristics of filming locations and use a machine-learning technique to define choice sets. We find production incentives can attract movies to a state, but the impact depends on the type of incentive offered, studio characteristics and inherent location geographic characteristics. Mid-sized studios respond to all forms of incentives, major studios respond only to refundable and transferable tax credits, and independent studios are not sensitive to any incentives. We fail to find strong evidence that incentives create a more permanent movie industry in a state. A counterfactual identifies the states most impacted by these policies. We supplement our discrete choice model with a simple cost-benefit analysis, which indicates that movie incentive programs are revenue-negative for states.

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da Silva, Joselma Maria, Djalma Silva Guimarães Júnior, and Carlos Henrique Michels de Sant’Anna. "Location Choice Model for distribution centers: for use in regional economic centers." Revista Gestão da Produção Operações e Sistemas 16, no. 1 (March 14, 2021): 54–71. http://dx.doi.org/10.15675/gepros.v16i1.2418.

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Purpose - This paper aims to propose a location choice model to establish distribution centers using linear programming. Design/methodology/approach - Locational choice models allow decision makers to select between different possible locations, based on the best fit of established criteria. For this, a Mixed-Integer Linear Programming model (MILP) was proposed to identify the most efficient location for a distribution center in the region in the Mata Norte of the State of Pernambuco, Brazil. Findings - The MILP model allowed us to identify the factors that support transport cost minimization, which are significant for the distribution logistics, indicating a location that minimizes these costs and generates greater efficiency in the logistics in a region within the interior of the state, which is a regional economic center. Originality/Value - Most location choice models for distribution centers are built on the logic of densely populated regions and large urban centers, the value of this study lies in its attempt to optimize the efficiency of logistics within inland regions. Keywords - Locational decision. Linear programming. Logistics. Distribution centers. Local economy.

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Krupka, Douglas J. "LOCATION-SPECIFIC HUMAN CAPITAL, LOCATION CHOICE AND AMENITY DEMAND." Journal of Regional Science 49, no. 5 (December 2009): 833–54. http://dx.doi.org/10.1111/j.1467-9787.2009.00614.x.

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Zondag, Barry, and Marits Pieters. "Influence of Accessibility on Residential Location Choice." Transportation Research Record: Journal of the Transportation Research Board 1902, no. 1 (January 2005): 63–70. http://dx.doi.org/10.1177/0361198105190200108.

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There has been substantial discussion among planners about the influence of transport in residential location choices. The purpose of this paper is to analyze the importance of accessibility in explaining residential location choices. The paper addresses this issue by presenting and analyzing findings from the literature and results of a housing market estimation study in the Netherlands. The research findings for the Netherlands illustrate that the transport system influences residential moves at three stages: in move–stay choice, estimation results show that households are less likely to move away from a more accessible location; travel time variables are significant for all household types, and therefore changes in the transport system will affect the size of the housing market and search area of the households; the model estimation results suggest that accessibility of a specific location for many household types is not a significant variable in their location choice. Overall, the empirical results suggest that the role of accessibility is significant but small compared with the effect of demographic factors, neighborhood amenities, and dwelling attributes in explaining residential location choices. The empirical findings are confirmed by findings in the literature; the present results are located at the lower end of findings reported in the literature. An important factor contributing to this result is that accessibility changes among regions in the Netherlands are rather small.

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Peng, Zhongren, Kenneth J. Dueker, and James G. Strathman. "Residential Location, Employment Location, and Commuter Responses to Parking Charges." Transportation Research Record: Journal of the Transportation Research Board 1556, no. 1 (January 1996): 109–18. http://dx.doi.org/10.1177/0361198196155600113.

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The effect of parking prices on mode choice for urban work travel is investigated, controlling for access to transit and residential and employment location. The analysis uses a nested multinomial logit model and is based on travel-activity data from the Portland, Oregon, metropolitan area. Parking prices are estimated to have a significant influence on commuters' mode choices. Parking prices are also found to have divergent impacts on commuters using different modes or living in different areas. Suburban transit users are more responsive to parking price changes than central city transit users. Persons ridesharing are less sensitive to parking prices than those who drive alone. For suburban residents, those driving alone and ridesharing to work are less sensitive to parking prices than are central city residents. Employment location plays an important role in mode choice; those working in suburban areas tend to drive more and use transit less. Increased transit service alone has a fairly small effect on transit use. Increasing parking price and improving transit service at the same time provides an effective means of reducing solo driving and increasing transit use.

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Wang, Yuchen, Jianxiao Ma, Yuhang Liu, Yingjia Bai, and Le Xu. "Optimal exit choice during highway tunnel evacuations based on the fire locations." PLOS ONE 16, no. 8 (August 20, 2021): e0256523. http://dx.doi.org/10.1371/journal.pone.0256523.

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In the case of a fire, the choice of exit in the highway tunnel is strictly limited by fire location, which seriously affects the evacuation time. A spontaneous or disorderly exit choice might result in a decreased evacuation efficiency and utilization rate of exits. In this paper, we propose a strategy to obtain the optimal exit choice based on fire location during highway tunnel evacuations. In our strategy, first, the vehicle distributions and locations of evacuating occupants are determined in the traffic simulation program VISSIM. The evacuation simulation software BuildingEXODUS is employed to obtain the corresponding parameters of the evacuation process and analyze the impacts of different fire locations on the evacuation time. During the analysis, the optimal productivity statistics (OPS) is selected as the evaluation index. Then, the feature points of the crowding occupants are captured by the fuzzy c-means (FCM) cluster algorithm. Next, based on the feature points, the relationship between the location of the fire and boundary of the optimal exit choice under the optimal OPS is obtained through the polynomial regression model. It is found that the R-squared(R2) and sum of squares for error (SSE) of the polynomial regression model, reflecting the accuracy estimation, are 98.02% and 2.79×10−4, respectively. Moreover, different fire locations impact the evacuation time of tunnel entrance and evacuation passageway. This paper shows that the location of the fire and boundary of optimal exit choice have a negative linear correlation. Taking the fire 110 m away from the evacuation passageway as an example, the OPS of our strategy can be decreased by 35.6% when compared with no strategies. Our proposed strategy could be applied to determine the location of variable evacuation signs to help evacuating occupants make optimal exit choices.

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Warsame, Abdisalan Salad. "The Location Choice of Foreign Direct Investment and Economic Development in Africa." International Journal of Economics and Finance 13, no. 10 (September 5, 2021): 69. http://dx.doi.org/10.5539/ijef.v13n10p69.

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Foreign Direct Investment (FDI) inflow to Africa has unevenly distributed investment location choices of multinational enterprises because of some exogenous economic factors associated with the locations, which vary across countries in Africa. The data used in the paper comes from Financial Times, World Bank, African Development Bank. This paper investigated what determines the location choice of FDI inflow to Africa using data on 3,768 firms from 88 countries making location choices in 54 African countries using a multicategory logistic regression. The findings show that: (1) the natural resource seeking enterprises invest more in landlocked countries relative to manufacturing and tertiary sector; (2) the natural resource seeking firms are less concerned about local market size and location’s economic condition comparing to manufacturing and service industries; (3) despite the accusation against the multinational enterprises (MNEs) for exploiting Africa’s natural resources, most of the MNEs choose locations with a large market size and better economic development; (4) the MNEs from developed economies prefer the location with a large market size and a better-developed economy comparing to those from the developing economies.

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Ramos, Miguel A., and J. Myles Shaver. "When individual locations affect the choice of multi-location acquisition targets." Strategic Organization 11, no. 2 (December 24, 2012): 125–55. http://dx.doi.org/10.1177/1476127012466649.

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Çetin, Dilek, Emre Aksoy, and Yalçın Arslantürk. "Tourism Location Choice of Local and Foreign Tourist: A Perspective through Spatial Analysis." World Journal of Applied Economics 8, no. 2 (December 17, 2022): 65–79. http://dx.doi.org/10.22440/wjae.8.2.2.

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The economic outreach of tourism businesses has undoubtedly had a significant contribution to the economic growth of countries and regions. Attracting tourists to the tourist provinces is an important regional growth and development issue. The main aim of this study is to present the factors influencing the tourism location choice of both foreign and domestic tourists. Cross-sectional spatial analysis is applied to Turkish province-level data for 2002-2019, and the time and spatial effects of regional tourism demands are considered. Lisa and Geary’s cluster maps provide the regional clusters. Accordingly, Bitlis, Siirt and Tunceli are the common low-tourist number provinces surrounded by low-ranking provinces (low-low cluster), whereas Burdur is the common low province surrounded by high-ranking provinces (low-high cluster). Both domestic and foreign tourist location choices were strictly influenced by their choice in 2002, i.e., time consistency in location choice is valid. The location choices do not depend on whether the province is on the seaside or inland, which is contrary to our expectations. Foreign tourists’ location choices are influenced by domestic tourists’ location choices three times more than that domestic tourists. Most importantly, according to the spatial autocorrelation results, location choice made by foreign tourists is spatially dependent, but this is not true for domestic tourists.

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Leonardi, G., and Y. Y. Papageorgiou. "Conceptual Foundations of Spatial Choice Models." Environment and Planning A: Economy and Space 24, no. 10 (October 1992): 1393–408. http://dx.doi.org/10.1068/a241393.

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As the location choice of an individual determines his or her feasible consumption set, it can be modelled as a two-stage procedure. First, the individual finds an optimal consumption bundle for each one of the feasible consumption sets that correspond to the locations considered. Second, he or she compares the resulting location-specific optimal utility levels and chooses a location for which the optimal utility level is a maximum. It is imagined that an observer applies costless sampling of the feasible consumption sets involved and records the individual's utility level associated with each trial. As the sample can be arbitrarily large, the asymptotic theory of extremes may be used in order to compute the probability that the consumption bundle associated with the highest overall utility level will correspond to any particular location. The way in which different sampling designs generate different choice probability models either in discrete or in continuous geographical space is explained. The multinomial logit model emerges when perfectly even sampling is applied on a discrete spatial choice set.

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Wartaman, A. S., D. Kusumadewi, A. Ramadhani, and R. D. Andajani. "Locational choice strategy: How FDI’s choice of Indonesia as an investment location towards competitiveness advantage." IOP Conference Series: Earth and Environmental Science 737, no. 1 (April 1, 2021): 012031. http://dx.doi.org/10.1088/1755-1315/737/1/012031.

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Lu, Qing, Mark Goh, Miti Garg, and Robert De Souza. "Remanufacturing in Asia: location choice and outsourcing." International Journal of Logistics Management 25, no. 1 (May 6, 2014): 20–34. http://dx.doi.org/10.1108/ijlm-10-2012-0125.

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Purpose – Remanufacturing is a process whereby value from old products is recovered by replacing and recovering used components to bring such products to a new or like-new state. Today, both original equipment manufacturers (OEMs) and third parties are engaged in remanufacturing activities, investing in many locations throughout Asia. The purpose of this paper is to examine the reasons for initiating remanufacturing activities as well as the location determinants for the remanufacturing sector in Asia. Design/methodology/approach – The authors conduct a multiple case study. Triangulation is applied to gain objective views from interviewing three OEMs, one logistics firm, and three local small enterprises. Real options theory is the theoretical lens used to examine the location choice of the OEMs. Findings – Firms engaged in remanufacturing tend to co-locate facilities with existing manufacturing facilities, and those investing in new sites for remanufacturing view the regulatory environment as the most important factor. OEMs tend to leverage on existing manufacturing facilities or third-party remanufacturers to reduce their cost of commitment when starting remanufacturing at new locations. Research limitations/implications – The sample size is still small for the generalization of the results. Further empirical study is needed to test the propositions from this paper. Practical implications – This paper could assist managers and decision makers in the multinational corporations to design appropriate logistics-related solutions for remanufacturing in Asia. Originality/value – The authors work contributes to the theory on remanufacturing location determinants. It shows that OEMs and third-party remanufacturers can have a collaborative relationship instead of the commonly assumed competitive one, which is currently not found in the literature.

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Burfield, W. B., D. E. Hough, and W. D. Marder. "Location of medical education and choice of location of practice." Academic Medicine 61, no. 7 (July 1986): 545–54. http://dx.doi.org/10.1097/00001888-198607000-00001.

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Abdul Fattah, Hamizah, and Nurwati Badarulzaman. "RESIDENTIAL PREFERENCES IN RESIDENTIAL LOCATION CHOICE." Malaysian Journal of Sustainable Environment 5, no. 2 (December 31, 2018): 41. http://dx.doi.org/10.24191/myse.v5i2.5616.

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Residential mobility attempts to address problems on households' life adjustments or the mismatch between residents' present needs and housing consumption. The desired preferences of each household may be complex to determine, but the trends or preferences in a residential area can be captured. Residential location choice stimulates residential mobility decision on the selection of a particular area. This study aims to identify residential preferences on relocation using a selected sample of 323 households in Penang who intend to move in the near future. Results show that residents prefer to move to other states than Penang. Therefore, determining residential preferences is necessary to develop corresponding housing policies.

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ITAYA, Yuji, and Hiroshi TAKEDA. "Optimal Location Choice of Urban Residents." Transactions of the Society of Instrument and Control Engineers 22, no. 12 (1986): 1340–42. http://dx.doi.org/10.9746/sicetr1965.22.1340.

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Kumar, Anil. "Enterprise Location: Choice of Women Entrepreneurs." SEDME (Small Enterprises Development, Management & Extension Journal): A worldwide window on MSME Studies 31, no. 3 (September 2004): 11–20. http://dx.doi.org/10.1177/0970846420040302.

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Wang, Yong, Yi Tang, Xiaotao Yao, and Shu Yu. "MNE Space and Subnational Location Choice." Academy of Management Proceedings 2020, no. 1 (August 2020): 10029. http://dx.doi.org/10.5465/ambpp.2020.41.

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Y, Nguyen Cao. "Modeling enterprise location choice decision behavior." Journal of Transport and Land Use 14, no. 1 (June 20, 2021): 669–91. http://dx.doi.org/10.5198/jtlu.2021.1743.

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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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Yeoh, Poh‐Lin. "Location choice and the internationalization sequence." International Marketing Review 28, no. 3 (May 31, 2011): 291–312. http://dx.doi.org/10.1108/02651331111132866.

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Letdin, Mariya, and Hyoung S. Shim. "Location choice, life cycle and amenities." Journal of Regional Science 59, no. 3 (April 23, 2019): 567–85. http://dx.doi.org/10.1111/jors.12441.

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Guevara, Cristian Angelo, and Moshe Ben-Akiva. "Endogeneity in Residential Location Choice Models." Transportation Research Record: Journal of the Transportation Research Board 1977, no. 1 (January 2006): 60–66. http://dx.doi.org/10.1177/0361198106197700108.

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Bina, Michelle, Valdemar Warburg, and Kara M. Kockelman. "Location Choice vis-à-vis Transportation." Transportation Research Record: Journal of the Transportation Research Board 1977, no. 1 (January 2006): 93–102. http://dx.doi.org/10.1177/0361198106197700112.

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PEARCE, DOUGLAS G. "Motel Location and Choice in Christchurch." New Zealand Geographer 43, no. 1 (April 1987): 10–17. http://dx.doi.org/10.1111/j.1745-7939.1987.tb01203.x.

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Danalet, Antonin, Loïc Tinguely, Matthieu de Lapparent, and Michel Bierlaire. "Location choice with longitudinal WiFi data." Journal of Choice Modelling 18 (March 2016): 1–17. http://dx.doi.org/10.1016/j.jocm.2016.04.003.

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Cronqvist, Henrik, Florian Münkel, and Stephan Siegel. "Genetics, Homeownership, and Home Location Choice." Journal of Real Estate Finance and Economics 48, no. 1 (May 30, 2012): 79–111. http://dx.doi.org/10.1007/s11146-012-9373-0.

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