Relocation Decisions Research Articles

The role of social networks in relocation induced by climate-related hazards: an empirical investigation in China

ABSTRACT Relocation is an adaptive strategy applied to prevent the threats of climate-related hazards. Thus, understanding the determinants of rural households’ adaptation decisions is crucial when informing policy interventions. This study explores the role of social networks (or peer groups) in geohazard-induced relocation using survey data (N = 516) from Chongqing, China. This study applies an instrument variable (IV) method and a series of robustness checks to confirm the findings. The results indicate that (1) social networks’ willingness to relocate (WTR) increases one’s relocation intention; and (2) people imitate their peers’ mobility choices by consciously observing and learning when facing uncertain climate-related hazard risks. Our findings contribute to comprehending whether and why social networks prompt population relocation decisions and help policymakers exploit the role of peer groups when implementing relocation-related policies in geohazard-prone regions.

Dynamic Relocations in Car-Sharing Networks

We propose a novel dynamic car relocation policy for a car-sharing network with centralized control and uncertain, unbalanced demand. The policy is derived from a reformulation of the linear programming fluid model approximation of the dynamic problem. We project the full-dimensional fluid approximation onto the lower-dimensional space of relocation decisions only. This projection results in a characterization of the problem as n+1 linear programs, where n is the number of nodes in the network. The reformulation uncovers structural properties that are interpretable using absorbing Markov chain concepts and allows us to write the gradient with respect to the relocation decisions in closed form. Our policy exploits these gradients to make dynamic car relocation decisions. We provide extensive numerical results where our dynamic car relocation policy consistently outperforms the standard static policy in realistic instances from the literature. In fact, it reduces the static policy's optimality gap by more than 13% in all of these instances and up to 35% in some.

Precious Neighbors: The Value of Co-locating with the Government

I analyze the firm value of co-locating with the government. Since neither firms nor gov- ernments move randomly, this value is normally hard to identify. I solve this problem by examining a unique event - the decision to relocate the German federal government from Bonn to Berlin in 1991. Following reunification, there was a free vote in the German parliament on the future location of the government. Berlin won by a narrow margin, an event that could not be anticipated even days before and that is free from confounding fac- tors. Firms with corporate headquarters in Berlin experience abnormal equity returns of about 3.5 percent following the relocation decision. These value effects are predominantly realized by firms in lobbying-intensive industries.

Modelling firm relocation decision behaviour in the Tokyo metropolitan region, through discrete choice theory

Modelling firm relocation decision behaviour in the Tokyo metropolitan region, through discrete choice theory

Making the Most of Your Regret: Workers’ Relocation Decisions in On-Demand Platforms

Problem definition : We have witnessed a rapid rise of on-demand platforms, such as Uber, in the past few years. Although these platforms allow workers to choose their own working hours, they have limited leverage in maintaining availability of workers within a region. As such, platforms often implement various policies, including offering financial incentives and/or communicating customer demand to workers in order to direct more workers to regions with shortage in supply. This research examines how behavioral biases such as regret aversion may influence workers’ relocation decisions and ultimately the system performance. Academic/practical relevance : Studies on on-demand platforms often assume that workers are rational agents who make optimal decisions. Our research investigates workers’ relocation decisions from a behavioral perspective. A deeper understanding of workers’ behavioral biases and their causes will help on-demand platforms design appropriate policies to increase their own profit, worker surplus, and the overall efficiency of matching supply with demand. Methodology : We use a combination of behavioral modeling and controlled laboratory experiments. We develop analytical models that incorporate regret aversion to produce theoretical predictions, which are then tested and verified via a series of controlled laboratory experiments. Results : We find that regret aversion plays an important role in workers’ relocation decisions. Regret-averse workers are more willing to relocate to the supply-shortage zone than rational workers. This increased relocation behavior, however, is not sufficient to translate to a better system performance. Platform interventions, such as demand information sharing and dynamic wage bonus, can help further improve the system. We find that workers’ regret-aversion behavior may lead to an increased profit for the platform, a higher surplus for the workers, and an improved demand-supply matching efficiency, thus benefiting the entire on-demand system. Managerial implications : Our research emphasizes the importance and necessity of incorporating workers’ behavioral biases such as regret aversion into the policy design of on-demand platforms. Policies without considering the behavioral aspect of workers’ decision may lead to lost profit for the platform and reduced welfare for workers and customers, which may ultimately hurt the on-demand business.

Looking for a change in scene: analyzing the mobility of crowdfunding entrepreneurs

As the platform economy expands, little is known about entrepreneurial mobility for those creating new ventures using online platforms. Few studies have focused on entrepreneurs’ decisions to relocate. Entrepreneurs using crowdfunding platforms, especially those in the arts and creative industries, present an interesting opportunity to investigate factors influencing relocation decisions. Our analysis sheds light on why crowdfunding creators relocate their projects, the factors that explain their destination choice, and how those factors differ by the type of crowdfunding venture. To understand entrepreneurs’ relocation decisions, we build a pseudo-panel dataset to track creator relocations on the largest reward-based crowdfunding platform (Kickstarter). The final dataset consists of over 25,000 instances where entrepreneurs within the USA made relocation decisions. Taken together, the Kickstarter data on thousands of creators over time, some of whom opted to move, reveals interesting patterns about who moved and where they went. We model their relocation decisions in two stages. First, we analyzed the decision to stay or relocate. Then, for those who relocate, we estimate a destination choice model that identifies the factors that influence which destination regions are selected. Even though these entrepreneurs utilize a platform-based tool for fundraising, they are strongly tied to their local geography. The results confirm that decisions to “change scenery” follow regional conditions relevant to local market size and their networks. The particular factors attracting these entrepreneurs depend on the sort of creative activity (e.g., music, film), as these creators exhibit tendencies to cluster in metros with well-developed crowdfunding communities.

Voting with One's Neighbors: Evidence from Migration within Mexico

We study how proximate neighbors affect one’s propensity to vote using data on 12 million registered voters in Mexico. To identify this effect, we exploit idiosyncratic variation at the neighborhood block level resulting from approximately one million relocation decisions. We find that when individuals move to blocks where people vote more (less) they themselves start voting more (less). We show that this finding is not the result of selection into neighborhoods or of place-based factors that determine turnout, but rather peer effects. Consistent with this claim, we find a contagion effect for non-movers and show that neighbors from the same block are much more likely to perform an electoral procedure on the same exact day as neighbors who live on different blocks within a neighborhood.

Role of Spatial Effect in Postdisaster Housing Recovery: Case Study of Hurricane Katrina

This study examines the influence of spatial effect and demographic characteristics on postdisaster households’ relocations at the block group level. Data for 479 block groups were collected in the city of New Orleans following Hurricane Katrina. The explanatory variables were transformed into five uncorrelated principal components using principal component analysis and spatial autocorrelation of the relocation decision of households tested using Moran’s I index. The results indicate households’ decisions exhibit significant spatial clustering. A better statistical fit was found for spatial lag regression than standard linear regression and other spatial models. Four statistically significant components influencing the block group level percentage of relocated households were identified. Specifically, places characterized by a greater proportion of the population with higher income population and out-of-county employment are more likely to experience high rates of relocation. In addition, family ties and place attachment had significant negative effects on the rate of block group-level relocation.

Charging for Higher Education: Estimating the Impact on Inequality and Student Outcomes

Abstract Over the last two decades, undergraduate university education in England moved from being state-funded and free for students, to costing all students substantial amounts in tuition fees. In this paper, using detailed administrative longitudinal microdata that follow all students attending state schools in England (approximately 95% of student population), we causally show that, despite the substantial reforms, enrollment fell only by 0.5 percentage points, where the effect is largely borne by those in wealthier groups, reducing the enrolment gap across socio-economic groups. Since tuition fees were introduced in conjunction with the government offering generous means-tested maintenance (cash) grants, as well as loans, our results highlight the importance of reducing financing constraints. Beyond enrollment, we find that the reforms have limited impact on students’ higher education choices, such as relocation decisions, university choice, and field of study. Finally, by tracking the students after graduation, we show similarly small effects on labor market outcomes.

Land costs, government intervention, and migration of firms: The case of China

By using unique firm relocation data in China, we first document the relocation behavior of Chinese firms and show that less government intervention (relative to market forces) can improve economic efficiency by facilitating industrial relocation which saves on costs. Ever since China joined the World Trade Organization (WTO) in 2001, investments have poured into the coastal region, which in turn, have almost tripled land costs in the major coastal cities. We exploit this land cost shock in the early 2000s to identify its effect on the relocation behavior of firms. Specifically, we instrument land price growth with the access of a city to foreign markets (approximated by distance to Shanghai), and then estimate the differential impact of land costs on firms regarding land reliance. Our major findings are as follows: (1) the migration rate of Chinese firms in China is on average 3.2%, (2) Rising land costs drive firms to migrate, and firms that use more land-intensive technology are more compelled to migrate, and (3) in regions where the local government intervention is stronger (the market is less developed), the relocation decision of Chinese firms is distorted in the sense that firms are less likely to relocate despite surging land prices due to government intervention.

The end of travel time matrices: Individual travel times in integrated land use/transport models

To reduce inaccuracies due to insufficient spatial resolution of models, it has been suggested to use smaller raster cells instead of larger zones. Increasing the number of zones, however, increases the size of a matrix to store travel times, called skim tables in transport modeling. Those become difficult to create, to store and to read, while most of the origin-destination pairs are calculated and stored but never used. At the same time, such approaches do not solve inaccuracies due to lack of temporal resolution. This paper analyzes the use of personalized travel times at the finest spatial resolution possible (at x/y coordinates) and a detailed temporal resolution for synthetic agents. The approach is tested in the context of an existing integrated land use/transport model (ILUT) where travel times affect, among others, household relocation decisions. In this paper, person-level individual travel times are compared to traditional skim-based travel times to identify the extent of errors caused by spatial and temporal aggregation and how they affect relocation decisions in the model. It was shown that skim-based travel times fail to capture the spatial and temporal variations of travel times available at a microscopic scale of an agent-based ILUT model. Skims may provide acceptable averages for car travel times if a dense network and small zones are used. Transit travel times, however, suffer from temporal and spatial aggregation of skims. When analyzing travel-time-dependent relocation decisions in the land use model, transit captive households tend to react more sensitively to the transit level of service when individual travel times are used. The findings add to the existing literature a quantification of spatial biases in ILUT models and present a novel approach to overcome them. The presented methodology eliminates the impact of the chosen zone system on model results, and thereby, avoids biases caused by the modifiable spatial unit problem.

Robust facility location decisions for resilient sustainable supply chain performance in the face of disruptions

PurposeFacility location and re-location decisions are critical managerial decisions in modern supply chains. Such decisions are difficult in this environment as managers encounter uncertainty and risks. The study investigates establishing or moving distribution facilities in the global supply chain by considering costs, fulfilment, trade uncertainties, risks under environmental trade-offs and disruptive technologies.Design/methodology/approachThis paper combines the possibilities and probabilistic scenarios for a supply chain network by proposing the novel Robust Optimisation and Mixed Integer Linear Programming (ROMILP) method developed under the potential uncertainty of demand while considering the costs associated with a four-tier supply chain network. ROMILP has been solved in a real-time logistics environment by applying a case study approach.FindingsThe solution is obtained using an exact solution approach and provides optimality in all tested market scenarios along the proposed global logistics corridor. A sensitivity analysis examines potential facility location scenarios in a global supply chain context.Research limitations/implicationsLogistics managers can apply the ROMILP model to test the cost-benefit trade-offs against their facility location and relocation decisions while operating under uncertainty. Future research is proposed to extend the literature by applying data from the OBOR logistics corridor.Originality/valueThis study is the first to examine sustainable dimensions along the global logistics corridor and investigate the global container traffic perspective. The study also adds value to the Middle East logistics corridor regarding facility location decisions.

Heterogeneous preferences and the individual change to alternative electricity contracts

Abstract Based on data from a large-scale computer-based survey among more than 3700 citizens in Germany, this paper empirically disentangles the determinants of the general change of electricity contracts and the specific change from any green or non-green to current green electricity contracts within the last ten years. Our econometric analysis reveals a strong relevance of behavioral factors and individual values and norms. For example, patience (which was measured by an incentivized experiment included in the survey) has a significantly positive effect on both general switches to alternative electricity contracts and specific switches to green electricity contracts. Furthermore, trust and (less robust) social preferences (also measured by an incentivized experiment) have additional significantly positive effects on the specific change to green electricity contracts. Our estimation results also imply an important role of political identification, i.e. an ecological policy orientation is strongly significantly positively correlated with the change to green electricity contracts. Furthermore, several household specific factors like relocation decisions as well as socio-demographic and socio-economic variables like household income are also relevant. The empirical analysis thus provides new explanation patterns for the phenomenon that relatively few households regularly change their electricity contracts and specifically switch to green electricity contracts, although they have high stated preferences for such changes. Our insights suggest several directions for policy and electricity suppliers to increase these switching rates. For example, the high importance of trust for the change to green electricity contracts suggests transparency initiatives of electricity suppliers to decrease concerns against renewable energies.

To move against the odds: A portrait of socio-spiritual underpinnings of residential mobility decisions in pro-poor housing systems of Tamale, Ghana

Housing mobility is an overlooked aspect of pro-poor housing policy debates despite the growing complexities of downstream housing sectors in cities of the global South. Stable housing regimes confer multiple socio-economic advantages on households and the incidence of housing relocation, especially involving very poor families, foists a considerably disruptive consequence. In the mainstream academic literature, residential mobility of the poor is believed to be firmly rooted in the agency of households and the associated housing outcomes arguably reflect their considered choices. Scholars have contended that residential mobility is a progressive practice in which people seek improvement in housing outcomes in terms of unit price, quality and tenure. This notion led to the suggestion that poor households are unlikely to move housing due to resource constraints. These perspectives may have overlooked the complex matrix of spiritual beliefs and practices which condition housing consumption and residential mobility decisions in the pro-poor housing sector. This paper analyses the sociocultural and spiritual enablers of housing mobility decisions in the pro-poor housing system of Tamale, Ghana, using data from in-depth interviews with selected survey participants. The analysis suggests that mistrust and socio-cultural practices in which people seek alternative interpretations to life events and misfortunes in the spiritual realm, deepens the sense of dissatisfaction with respect to safety and security of the homes they live in. We argue that spiritual interpretations of life circumstances create and sustain anxiety in the pro-poor housing sector and mark the subject on which housing relocation decisions are predicated. Housing policy debates ought to be broadened beyond the objective aspects of housing and environmental services to include the socio-cultural contexts shaping housing practices in the pro-poor sector.

Drivers of post-disaster relocations: The case of Moore and Hattiesburg tornados

Post-disaster relocation may occur in the aftermath of major disasters, either unplanned or through buyout programs. There is an extensive research on recovery of affected population. However, research on the factors which cause the households to decide in favor of relocation or reconstruction is still in its infancy. This paper suggests a framework for classification and prediction of households' recovery decisions based on their attributes. To achieve this objective, data was collected through a telephone survey of residents affected by the 2013 Moore, Oklahoma and Hattiesburg, Mississippi tornados. The analysis was implemented using conditional inference trees and revealed the significance of level of damage, pre- and post-disaster homeownership, and housing type on the households' relocation decisions. The model can help with devising data-driven recovery policies tailored to a community's characteristics.

SALTy Citizens: Which State and Local Taxes Contribute to State-to-State Migration?

ABSTRACTState and local governments depend heavily on revenue generated from state and local taxes (SALTs). Migration between states occurs for many non-tax reasons, but prior research suggests tax-related factors may play an important role. Even so, the specific SALTs motivating state-to-state migration remain unclear given mixed and inconclusive results of prior studies. This study examines state and local tax variables individually and then jointly, and controls for important economic and noneconomic factors to determine which SALTs matter to residents when making relocation decisions. Using data collected from multiple sources for 2008 to 2015, results indicate overall state and local tax burden, individual income taxes, select sales taxes, and property taxes are all significantly and negatively associated with taxpayer migration. Further, select sales taxes and property taxes seem to be most significantly associated with migration. We also provide some intuition related to the economic impact associated with net migration.

Exploring the effects of congestion charge on relocation decisions under non-capital functions relieving strategy in Beijing

A common problem with rapid urbanization is the associated infrastructure lag that fails to keep pace with an increasingly growing population. Lawmakers try to minimize this lag by implementing policies that can ameliorate the challenges faced by rapid urbanization. The Beijing government has implemented a “non-capital functions relieving strategy” to incentivize specific industries to relocate. Unfortunately, the willingness of business owners to relocate was too low, and the reasons remain unclear. Moreover, limited studies explored the long-term effects of a congestion charge, especially when combined with a government relocation strategy. The purpose of this research is to achieve a deeper understanding of the urban population's attitudes towards strategies that aim to mitigate the effects of over-populated cities. To accomplish this research, face-to-face surveys were conducted in six wholesale markets in four categories. The ordered logit model revealed there were seven types of influential factors that had a significant effect on the respondents' willingness to relocate. The results indicate that the relocation effect of a congestion charge may be weakened under such an urban strategy. This study empirically informs market managers and policymakers on how to incentivize merchants into resettling into areas outside of megacities to mitigate the adverse effects of overpopulation.

Business Climate in the Eye of the Employer

What constitutes a “good business climate” is often couched in monolithic and diametrically opposed terms of low taxes versus high public services. However, there is likely considerable heterogeneity across firms in their preferences for the trade-off between higher taxes and the public services they provide. Using a novel primary data set of firm expansion and relocation decisions, this analysis investigates how firms in relatively high-paying sectors express their preferences for a variety of local “business climate” attributes relative to firms in lower-paying sectors. The findings show evidence that firms in low-wage sectors view a “good business climate” differently than firms in high-wage sectors.

Older adults who move to independent living units: A regional Australian study

ObjectiveThe purpose of this study was to ask older adults in a regional area of Australia how they made the decision to move into an independent living unit (ILU) within a three‐tier residential complex that provides varying services and care to older adults.MethodFocus groups were used to enable the gathering of rich data and to enable the voices of older adults. A deductive qualitative analysis (Gilgun, Qualitative research in social work, 2nd ed., pp. 107–135, 2013) was deployed using the factors for a successful later‐life transition to an aged‐care facility identified in the researchers’ earlier systematic review.ResultsFeelings of autonomy and control over the decision to move were important to all respondents. Any sense of loss of day‐to‐day autonomy, privacy and purpose, was compensated for by increased feelings of safety and security. Selected items brought from the old home to the new were a significant source of comfort.ConclusionsThis study provides the views and experiences of 19 older adults from regional Australia about moving into ILUs in a three‐tier complex. The values and missions of the complex were important in the relocation decision‐making. Further, if the choice is between living near friends or family, participants recommended choosing friends. The strategic choice of an ILU in a three‐tier complex was seen as providing appropriate care into an unknown future. This study highlights the importance for older adults, their families and health‐care professionals of making timely relocation decisions and the importance for older adults to retain autonomy and control over the relocation decision.

Global auto industry and product standards

Global auto industry and product standards