1. Introduction
Climate changes characterized by flood, cyclone, sea-level rise, and so on are having serious impacts on many countries around the world. Bangladesh is one of the most vulnerable countries in the world threatened by floods and cyclones due to its geographical location and setting. As a country with a high population density, 10% of the Bengalese live along the coastal areas [
1]. Floodplains of its three large rivers cover about 80% of the country’s land where three-quarters of the total population lives [
2], and only 10% of Bangladesh is 1 meter above the global mean sea level and one-third is under tidal influence [
3]. On average, 6000 people die from flooding and storms each year [
4]. People’s everyday lives and daily travel are undergoing great challenges from flooding and cyclone impacts. Serious impacts have also been being placed on the transportation infrastructure and system in the country.
Research work focusing on climate change impacts are usually addressed from two aspects—mitigation and adaptation. Comparing with climate change mitigation efforts, however, climate change adaptation may be more urgent to prepare the society in aspects such as infrastructure systems and people’s travel behavior to adapt to the increasing impacts. As a result, climate change adaptation receives much more attention in terms of system performance analysis [
5,
6,
7] and adaptation decision making [
8,
9,
10,
11]. Among all these impacts, climate change is also expected to have an impact on people’s activity behavior especially in seriously affected countries like Bangladesh. People’s behavior such as travel behavior and job and residence location choice behavior may also change with the climate, especially with the increase in intensity and frequency of climate change events.
Until recently, travel behavior adaptation to climate change attracts attention from scholars addressing behavioral changes to adapt to the impacts of climate change, especially adverse weather events in people’s daily travel [
12,
13,
14,
15]. It is important to understand people’s travel behavior changes under climate change impacts because transportation network performance is largely dependent on how travellers respond to traffic conditions [
16]. The residence and job location change choice behavior under climate change is as important as travel behavior change, which changes the traffic generation and distribution and then the transportation network performance. In the network performance analysis literature, great contributions have been made to explore improved analysis methods under climate change disasters [
17,
18] or develop more efficient calculation techniques in the application [
19,
20]. However, people’s residence and job location choice behavior should be addressed in these network performance analyses, neglecting which might lead to inaccurate evaluation results. Residence and job locations might be changed because of frequent or serious flood or cyclone impacts, and thus the traffic demand and volume will change with the choice of residence and job locations. Actually, climate significantly enters into and is shown to be a direct determinant of location choice decisions [
21]. As a result, it is of great importance to better understand people’s residence and job location change behavior under climate change impacts and include these behavioral changes in the transportation network performance analysis and adaptation decision making.
The residence or job location choice behavior is usually addressed with its relationship with public transport accessibility, travel costs, travel modes and departure time, and so on [
22,
23,
24]. The influences of physiological factors and gender on residence location choice are also investigated in the literature [
25,
26,
27]. The balance of residence and job location choices is found to be associated with the population pattern of a city and traditional residence and job location policy [
28,
29]. Arentze and Timmermans [
30] find a less significant impact of congestion pricing on residence or job location change than travel behavior change. Mortreux and Barnett [
31] conclude factors influencing residence or job location choice into three groups which are factors at the point of origin including environment, economic factors, and government policies, factors at the destination involving social network, economic factors, and government policies, and intervening obstacle factors such as distance and institutional constraints. These factors are proposed for normal location change decisions and may not be directly attributable to changes under climate change. Mcleman gives a review of the linkage between climate change and migration, confirms the relationship between climate variability and human migration pattern, and identifies developments in the modeling and datasets of climate change and migration [
32]. With an agent-based simulation model, Kniveton
et al. [
33] find that the migration or residence location change is obviously affected by the environment, that is, dry or wet environment. They also suggest that rainfall’s impact on location change choice is expressed via its influence on other drivers such as differential employment opportunities, limited access to natural resources, national policies and incentives, ecological vulnerability, political instability, and infrastructure. With the same methodology, Hassani-Mahnooei and Parris explored people’s internal migration under climate change in Bangladesh [
34]. After a review of empirical research on migration and climate change, Klaiber confirms that household location change arises due to changes in economic opportunities and climate amenities resulting from climate change [
21]. Saldana-Zorrilla and Sandberg [
35] find that declining incomes, higher educated individuals and increasing numbers of natural disasters lead to higher levels of out-migration under climate-related disasters in Mexico. Other studies also investigate factors or reasons affecting the migration or location change decision under climate change impacts, and the identified factors include lack of education, strong attachments to land, age, family size, the availability of transport infrastructure, and so on [
31,
36,
37,
38]. With evidence from two communities in Canada, Wolf
et al. argue that values such as tradition, freedom, harmony, safety, and unity shape different interpretations and meaning of climate change impacts, and as a result lead to distinct adaptation decision including migration or location change choice [
39]. Iqbal and Roy focus on the temperature and rainfall impact migration through agriculture, and predict that the net out-migration rate will be about 22% higher in 2030 than in 1990 as a result of changes in climate variables in Bangladesh [
40]. Although factors influencing the residence or job location choice decision may vary among countries or observation, there is almost no doubt that people’s location choice behavior is affected by climate change impacts.
Most of the above literature focuses on the household or residence location choice under climate change scenarios. However, not only residence location choice but also job location choice will have impacts on the traffic distribution and transportation network performance. Furthermore, people may gradually consider changing the job location first and then the residence location under climate change impacts. It is agreed that because of the diversities of climate change regimes and culture/habituation in different countries people’s travel behavior and residence and job location choices behavior under climate change are different [
13,
15,
41]. Thus, understanding people’s residence and job location choice behavior under climate change in different countries of the world is of great importance especially those developing countries which are more diverse in terms of people’s education, income, and family structure and becoming more vulnerable under the impacts of climate change. Given the uncertainties of climate change, people’s residence and job location change choice decision may also be different under different climate change scenarios and types such as rainfall, river or coastal flooding, and cyclone. These research gaps should be addressed with detailed investigation of people’s preference of location choices under different climate change and impact scenarios together with factors describing the household characteristics.
To address the above research gaps, this paper aims to identify flooding and cyclone factors such as frequency and intensity and impact factors that explain the joint choice of residence and job location while including personal and family socio-economic factors and previous experiences at the origin in Bangladesh. Particularly, residence and job location change behavior comparison is evaluated under flooding and cyclone impacts as well as coastal and inland areas of Bangladesh respectively. People may consider changing job or residence locations under long-lasted impacts, and thus the focus of this work will be on the gradual impacts from flood and cyclone. The design of the research including data collection and methodology development are presented in the next section.
4. Conclusions
Efforts of this work were made on investigating significant factors influencing people’s location choice behavior at the origin in coastal and inland areas of Bangladesh, and exploring the joint choice behavior among residence, job locations, and house reinforcement through a proposed CNL model structure. Results of this study confirm the serious impacts that floods and cyclones are imposing on Bengalese people, and more than 80 percent of the respondents would like to make changes to their houses or jobs. Flooding and cyclone attributes such as frequency and intensity turn out to be the most significant factors affecting people’s choice behavior, and income, number of family members, and amount of land owned also show significant effects on the location change choice, which confirms the results of previous studies. Different from coastal observations, the inland people may be less affected by floods, and thus previous experiences such as QOL shows insignificant influences. Road connections play an important and significant role when people choose to change residence locations in coastal areas. The CNL model shows better model fitting results than the MNL model and could give more insights on people’s location choice behavior. Under flooding or cyclone impacts, people would like to change their job locations and then residence locations. It is also found that if there are changes in flooding impacts, the inland people will consider changing their job locations, while the coastal people would consider both job and residence location changes.
Results of this work add to the understanding of location change choice behavior adapting to flood and cyclone impacts in a developing and seriously affected country. As disclosed by the study, there is an obvious change of residence or job location in both coastal and inland areas under flooding and cyclone scenarios. This location change behavior should be addressed in transportation network performance analysis, and failing to include these changes might neglect the differences in travel demand, travel attraction, and route choice resulting in inaccurate analysis results. The study also sheds light on policy suggestions for local governments and families adapting to flooding and cyclone impacts. People with high income, less land, and fewer family members are encouraged to migrate to safety places, and coastal households are suggested to go to shelters or change job and residence locations under cyclone threats, since reinforcing the house is not a significant factor in the analysis. It is important to guarantee accessible road infrastructure under flooding or cyclone failing of which might significantly lead to people’s residence location change. The above conclusions could be learnt by the government to be included in migration and land use planning policies, shelter planning and construction, transportation infrastructure investment, and so on, so as to help people safely evacuate or avoid being affected in flooding and cyclone events.
However, this research is not without its limitations. Factors at the job or residence locations to be moved, socio-economic connections with the target locations, and the moving costs are not included in the model. It is incomplete to only address the mentioned flooding/cyclone scenarios and factors, and more flooding and cyclone scenarios, socio-economic factors, family attributes, and choice alternatives such as going to shelters are expected to be addressed. More detailed and accurate behavioral characteristics of people’s choice behaviors should be explored under climate change. People’s behavioral changes are not only affected by flooding and cyclone impacts, combined impacts resulted from heavy rainfall, extremely hot or cold weather, and sea-level rise, together with floods and cyclones are not addressed in this work. Finally, findings and conclusions of this research may better fit situations in Bangladesh, and comparative analyses of people’s residence and job location change choice behavior response between regions or nations with different climates, flooding and cyclone impacts, living traditions, and adaptive capacity are also preferable.