Abstract
Despite the impact of urban flooding on businesses, the choice of microentrepreneurs continuing to stay in flood hazard areas runs counterintuitive to the principles of profitability and sustainability albeit both are the most vulnerable aspects of the business sectors. Existing literature has provided substantial knowledge on the factors affecting an entrepreneur’s choice of operating location but does not go deeper into why entrepreneurs decide to remain and operate in frequently flooded urban areas. A multi-stage cluster sampling technique was used in this study to establish an adequate representation of microentrepreneurs in flood-prone areas of Marikina City in Metro Manila, Philippines, using various statistical tools to evaluate decision factors. The research revealed that component factors such as economic considerations, the microentrepreneur’s socio-spatial relations, and experiences and perception of resilience influence the decision to remain in urban flood-prone areas. Moreover, specific sub-factors under each component factor were identified, which can be grouped into ‘pre-existing’ and ‘learned’ categories, introducing a new location decision model attuned to the dynamics that exists between microentrepreneurs and a natural disaster such as urban flooding. The findings of the study may guide policymakers and urban planners in designing targeted intervention measures that translate to more micro enterprise-responsive disaster risk reduction and management plans. Moreover, by treating microenterprises as separate from the traditional occupations, communities might appreciate the crafting of local land use plans which would successfully improve the overall resilience of this sector in urban flood-prone areas.
Introduction
Numerous studies have documented the significance and criticality of micro, small, and medium enterprises (MSMEs) in the development and prosperity of the Philippine economy, highlighting their specific role as drivers of the country’s GDP. One critical element influencing a firm’s ability to propel growth is its location, which allows it to thrive at the highest possible level. Alfred Weber postulates that location should enable cost minimization (Church, 2023). Losch (1954) suggests, however, that the location depends not only on cost but on the potential maximization of net profit. Meanwhile, Alfred Marshall observed the concentration of firms (Figure 1) in specific locations as being a significant factor (Belussi & Caldari, 2008).
However, location choice theorists and scholars have not gone deeply into the phenomenon of why firms decide to locate in dangerous or vulnerable areas (Figure 2) as site selection literature has often overlooked natural hazards (Grames et al., 2019). Analyzing the impact of extreme weather events has led several scholars to acknowledge flooding as the most frequent and devastating natural disaster, especially in monsoon Asia (Gupta & Chakrabarti, 2009). Flooding has been observed to be primarily aggravated by uncontrolled building, informal settlements, lack of appropriate building codes and enforcement of regulations, encroachments onto river rights-of-way, indiscriminate disposal of solid waste, sedimentation, and the lack of maintenance of watercourses (Navarro, 2014). All of these are present or experienced in urban areas.
Of all the Metro Manila cities flooded by Typhoon Ondoy (Typhoon Ketsana) in 2009, Marikina City was considered to have been the most severely impacted, with floodwaters reaching heights ranging from knee-deep to neck-deep to roof-top deep (NDCC, 2009), affecting the majority of the city’s barangays (neighbourhood). Of its total 16 barangays, there are at least 10, as shown in the flood hazard map (Figure 3), which are considered flood-prone in most of their areas. These are Nangka, Tumana, Concepcion Uno, Malanday, Sto. Niño, Jesus Dela Peña, Tañong, Sta. Elena, Calumpang, and San Roque.
In another event, Typhoon Ulysses (Typhoon Vamco) in 2020 wreaked havoc on at least 41,000 individuals, flooded 30,000 houses in Barangay Nangka, in places reaching the roofline. It also inundated the city hall of Marikina with its offices rendered unusable (Citizen’s Disaster Response Center [CDRC], 2020).
At the firm level, mostly reported by MSMEs in the Philippines (iPrepare Business Facility, 2017) flooding impacts included employees’ inability to go to work, failure to deliver products to the market, damages to facilities and equipment, damage to raw materials, and more than three months of stoppage in operations due to disruption. Evidence shows that compared to larger companies, MSMEs, specifically microenterprises, are more vulnerable to natural hazards. Most have been observed to be worse off in the aftermath of disasters, experiencing a loss of assets, supplies, customers, and personnel, given their limited access to risk-management mechanisms (United Nations Development Program [UNDP] Crisis Prevention and Recovery, 2013). The basic question is: how does a microentrepreneur reconcile with the principles of cost minimization and net profit maximization if flooding is arguably the most damaging and devastating natural disaster, given its long-term and repetitive effects (Pornasdoro et al., 2014).
This study aims to answer the main research question: What factors influence the decision of microentrepreneurs to remain in flood-prone areas? Specifically, it seeks to uncover the economic and non-economic influencing factors that drive these decisions to stay in high-risk areas.
This article is organized to begin with a brief introduction. The second section presents the literature review discussing recent findings on location choice in various contexts, studies on the impact of urban flooding and how enterprises cope with the effects, and the socio-spatial relationships, including their development and cultivation over time. The third section discusses the framework of the analysis which guided the researchers in structuring the proposed research problems and designing a practical approach and perspective to ensure the appropriate focus. The fourth section explains the research methodology used and the objectivity of the population, sample size, and the sampling technique used to accurately represent the respondents, and includes various statistical tools used to establish evidence of the relationship among the variables. The fifth section highlights the results of the data analysis, providing the answers to the research problem guided by the study’s framework. Finally, the conclusions and recommendations for further research are presented.
Literature Review
The MSME Profile: Focusing on Microenterprises
The Philippine government classified the MSME sector according to asset size and number of employees. Microenterprises have up to Php 3,000,000.00 worth of assets and up to nine personnel employed. Most of the MSME sector, specifically 89%, comprises microenterprises (Figure 4).
According to the Department of Trade and Industry (DTI) (2021), most of the MSME sector comprised Wholesale and Retail Trade (46.2%). This denotes that most of these enterprises were engaged in the direct sales of various goods or commodities. The next largest sectors were Accommodation and Food Services (14.4%) and Manufacturing (11.5%).
Moreover, most of the MSMEs, especially the microenterprises, were concentrated in regions with high urbanization, starting in the National Capital Region (NCR) with 202,011 (20.2%) firms. This is followed by the provinces of Cavite, Laguna, Batangas, Rizal and Quezon, collectively known as the CALABARZON Region and Central Luzon Region with 148,017 (14.8%) and 115,877 (11.6%) firms, respectively (DTI, 2021).
In terms of employment absorption, DTI (2021) reported in 2019 that microenterprises accounted for 29.8% of the total employment while small enterprises contributed approximately 25%.
Enterprise Resilience to Urban Flooding
The iPrepare Business Facility (2017) defined resiliency as the ‘ability of a system and its parts to anticipate, absorb, accommodate, or recover from the effects of a hazardous event in a timely and efficient manner, including ensuring the preservation, restoration, or improvement of its essential basic structures and functions’ (p. viii). In the same vein, coping capacity refers to the ‘ability of people, organizations, and systems to face up to and manage adverse conditions, emergencies, or disasters using available skills and resources’ (p. vii).
At the firm level, the business continuity concept focuses on a firm’s operations and how it can restart immediately after a disaster event (Ballesteros & Domingo, 2015). For instance, some SMEs often rely on overseas worker remittances and loans from family members and informal moneylenders to fund post-disaster recovery, while others eventually stop their business operations (Ballesteros & Domingo, 2015). In India, small businesses have had to cover the immediate expenses of cleaning their premises, restarting operations, or temporarily relocating production (Patankar, 2019). In the Philippines, after typhoons Ondoy, Pepeng and Sendong caused havoc, smaller firms mainly relied on remittances and private loans (Ballesteros & Domingo, 2015). In India, either none of the MSMEs received government compensation for their losses, or the perception of government assistance as a relief measure was deemed insufficient to facilitate the sector’s recovery (Patankar, 2019; Prakash & Krishnarani, 2020).
Regarding the resumption of operations, enterprises near Marikina River, where approximately 85% of the city was inundated during the height of Typhoon Ondoy, it took an average of one and a half months to resume normal operations (Tuaño et al., 2016). Meanwhile, in India, where SMEs were without power, water, and other essential services for 10–15 days, the recovery times varied across areas and sectors—enterprises in Mumbai took an average of three to four days, with some taking one to two weeks, while in Chennai, where waterlogging affected many areas for a long time, businesses began staggered operations after one to two weeks (Patankar, 2019).
Location Decision of Firms
Ultimately, a location decision is the outcome of a trade-off based on: (a) minimizing production costs (including transportation costs); (b) minimizing the distance cost to the markets; (c) maximizing the potential scale of economies and agglomeration economies; and (d) minimizing rent, which refers to the price paid for a location (Dube et al., 2016). However, variations exist when studying decision factors across different industry sectors and countries. For example, Portuguese companies engaged in knowledge-intensive business services (KIBS) tend to prefer locating in urban areas (Ferreira et al., 2016), while in Canada, KIBS which include Retail Trade, Accommodation & Foods, and Finance, Insurance, & Real Estate (FIRE) industries are strongly influenced by overall economies of agglomeration rather than solely the distance from urban areas (Dube et al., 2016). These findings are further exemplified in Portugal, where the location decisions of firms have been found to depend on the sector of activity, type of area (urban vs. rural), and the characteristics of its founder (Ferreira et al., 2016).
To understand these variations and differences, Ferreira et al. (2016) used Hayter’s approaches to location decisions, which include the following: (a) Neoclassical: cost minimization and profit maximization; (b) Institutional: how companies select locations appropriate to the institutional surroundings for meetings (clients, suppliers, commercial associations, regional systems, the government as well as other companies); and (c) Behavioural: influenced by non-economic factors, including the entrepreneur’s personality characteristics. The behavioural approach encompasses factors such as proximity to the founder’s residence, the founder having been born in the community, and the local community’s attitude to business, to name a few.
A combination of similar factors, including location-specific, personal, and community factors, may also influence location choice. Personal factors such as proximity to residence, acquaintance with local people and location, ability to arrange capital, and concern for family and children are often prioritized over other factors in the selection process (Rahman & Kabir, 2019).
The concept of agglomeration, first observed by Alfred Marshall in industrial districts, has remained relevant (Belussi & Caldari, 2008). In India, for example, it has been found that large firms, or those with higher levels of working capital, operating profits, fixed assets, material costs, and higher sales values, tend to prefer locating in large cities. This is advantageous for firms as it provides them with more consumers, higher real wages (since consumers tend to be located closer to their suppliers, reducing transportation costs), and higher demand (Tripathi & Kumar, 2017). Similarly, in Canada, economies of agglomeration, as measured by the size of nearby establishments, are an essential factor in location sorting across service industries. The most substantial effects have been observed in the Retail Trade, Accommodation & Foods, FIRE, and KIBS industries (Dube et al., 2016).
In the Philippines, there are more MSMEs in and around municipalities where large firms are present compared to municipalities that do not have large firms (Abrigo & Francisco, 2013). Similar findings were uncovered in Chennai, India, where small businesses’ locational choices were driven by factors such as the accessibility of workers, the presence of specific large industries, and ease of logistics, including proximity to clients, business potential, and continuity (Patankar, 2019). Likewise, in Germany, it has been revealed that agglomeration economies play a significant role for small firms due to the positive externalities they generate (Krenz, 2016).
However, when firms produce goods for export and foreign demand, they tend to locate in smaller cities to take advantage of low-cost production due to lower land rent and wages (Tripathi & Kumar, 2017). Regarding firms’ localization, the low cost of space was a crucial force (Rahman & Kabir, 2019).
Overall, the principal focus of recent scholars has been on how entrepreneurs choose locations based on economic and non-economic factors. They have not addressed the decision of entrepreneurs to remain in flood-prone areas even after experiencing a devastating event. In summary, recent location choice factors studied could potentially serve as a starting point for proposing sub-factors related to the decision to remain in flood-prone areas.
Socio-spatial Relationship Factor
From the perspective of residents or entrepreneurs, moving away from their current location is not simply a matter of realizing the physical and emotional impact and cost of disasters. There may be other considerations beyond purely economic factors that are equally significant.
Jessop et al. (2008) described the concept of human attachment to one’s surroundings using structural homologies of spatial forms with social relations. Specific spatial forms and social relations initially shape socio-spatial relationships. For instance, distance (spatial form) and face-to-face relations (social relations) will lead to familiarity with people in the community (socio-spatial relationship).
People describe their cognitive, affective, and conative relationship with a place and others through a non-mathematical experience of the place (Erfani, 2022). Furthermore, at the community level, a sense of place is formed through the collective intersection of people’s subjectivities over time and space (or inter-subjectivity), potentially creating a sense of trust and familiarity that distinguishes one community from another (Erfani, 2022).
Concerning place and time (or time-space), the persistent character of places is related to the continuity of the individual’s experience of change and the nature of change itself, reinforcing a sense of association and attachment to those places (Relph, 1976). For example, as one becomes accustomed to a place or the changes it undergoes, the meaning or significance of that place may diminish.
Framework of Analysis
A corollary to the literature culled for this study is the framework of analysis, which grounded the research problem and guided the in-depth investigation. Relevant theories on firm location choice were discussed, primarily focusing on economic factors such as cost, profits, and agglomeration. The limitations of these theories in explaining why microentrepreneurs choose to remain in flood-prone areas were also discussed. In response to the inadequacy of the said theories, the researcher proposed a conceptual framework integrating economic and non-economic considerations to enhance the understanding of location decisions following the impacts of urban flooding.
Theoretical Framework
Belussi and Caldari (2008) investigated the origins and evolution of Marshall’s industrial districts model, which sought to explain the concentration of firms in specific locations. Marshall observed that this development required the accumulation of time for a substantial number of firms to establish themselves before availing the eventual benefits of agglomeration, or the created ‘atmosphere’. Clustering in industrial districts offered advantages such as access to skilled labour, new knowledge, and a thriving supply chain through the growth of smaller firms that complement existing manufacturers. Regarding the tendency to cluster, key factors for an area included the abundance of raw materials that could be processed into a final product, the presence of high-income residents who would consume these products, and the existence of towns or large cities.
In Weber’s theory of the location of industries (refer Church, 2023), the central idea was to address the need to serve one or more places of consumption of a product with raw materials that are only available at specific locations. The first step in this theory was to determine the optimal location based on the market area and the origin of raw materials, taking into account transportation costs at a certain point and then incorporating labour costs into the analysis, aiming to find the optimal combination of labour and transport costs at the identified location options. Overall, the optimal location should be where labour and transportation costs are minimal.
Losch (1954), however, had a more radical view on location choice as he opposed the one-sided approach, which tended to be biased on cost drivers specifically as in Weber’s model. He argued that the correct location of an enterprise should be where net profit is greatest. For this to work, the market area needs to be incorporated into the equation, recognizing that areas with higher demand have the potential for higher profits. Losch also emphasized that the most effective way to determine such a location is through empirical analysis rather than relying solely on theoretical models since different areas have unique contexts regarding both cost and demand. He also acknowledged that subjective considerations could influence an entrepreneur’s decision-making process.
However, these three prominent theories of firm location fell short of fully explaining location decisions to account for natural disasters, for instance, how does such a location remain optimal for continued operation after experiencing the impact of urban flooding. While Losch (1954) mentioned the inclination of entrepreneurs towards subjective considerations, the discussion on this aspect was limited in terms of choosing a location.
Conceptual Framework
Studies have suggested that firm location choices are driven by the potential to generate maximum sales and achieve cost efficiency, considering factors such as low labour, raw materials, and transport costs. Agglomeration is believed to play a significant role in location decisions, as the benefits experienced by smaller firms resulted in cost efficiency including infrastructure support and supply chain systems that evolve as firms grow.
Other scholars have argued that non-economic factors, such as socio-spatial relationships play a significant role in the initial selection and continued operation in a location. For example, the personal preference of entrepreneurs, influenced by factors such as being born in the area or an appreciation for community values, can shape their location choices. Additionally, proximity or distance to relatives may be regarded as necessary in times of disaster due to ease of access to possible financial, social, emotional, or physical support. Frequent exposure to flooding can strengthen socio-spatial relationships within a community. The shared experience of surviving floods and the common trauma associated with such events can foster camaraderie and support groups among community members. As studies have noted, the familiarity with flood incidents and the perception of being able to handle and mitigate flooding may have shaped how entrepreneurs weigh their location decisions. The positive memories and experiences a person associates with their surroundings may hold more value over the other opportunities presented by safer locations.
Resiliency, for the study’s purpose and as guided by literature, refers to the ability of an enterprise to anticipate, absorb, accommodate, and recover from the impact of flooding in a timely and efficient manner. Entrepreneurs have demonstrated resilience in various ways, such as participating in community preparation activities, borrowing funds for recovery, seeking employment elsewhere, and changing their means of livelihood. Their initiative to cope, along with the support mechanisms provided by the local government in terms of policies and projects, contribute to their chances of survival.
This study attempts to explain how entrepreneurs decided to remain in flood-prone areas by framing the factors considered in their decision process. The framework (Figure 5) suggests that microentrepreneurs’ choice of location is based on economic and socio-spatial relationship factors. But when urban flooding occurs it produces negative impacts that disrupt business operations, destroy assets, and cause emotional, physical, and mental concerns, affecting the profitability of the enterprise.
Conceptual Framework for Microentrepreneurs’ to Remain Located in Urban Flood-prone Areas.
Positive impacts may strengthen socio-spatial relationships due to the common goal of the community to survive and recover. There are both negative and positive impacts, which are treated separately by the entrepreneur. Negative impacts should be managed through resilience strategies facilitated by the entrepreneur and the local government unit (LGU). On the contrary, positive impacts are used to motivate and fortify the resolve of the entrepreneur to survive and recover. In the end, as long as microentrepreneurs can anticipate, respond, absorb, recover from, and adapt to the negative impacts of flooding, regardless of the cost and time involved, and the presence of socio-spatial relationships in the area is perceived as valuable or important, they will conclude that remaining in flood-prone areas is still the most viable choice.
Research Methodology
A multi-stage cluster sampling technique was employed in this study to select a representative sample of microenterprises. The sampling process involved narrowing the sample step by step, considering the population’s characteristics (microentrepreneurs in Marikina City). The selected barangays were chosen based on their homogeneity in terms of location (all of them are flood-prone based on the flood hazard map), the experience of Typhoon Ondoy (as indicated on the Typhoon Ondoy map) and Typhoon Ulysses, and the presence of all types of enterprises in the said barangays. By leveraging the homogeneity or similarities within the specified areas, the study adopted a cost-effective and efficient sampling procedure considering the size and dispersion of the population.
A total of 485 microentrepreneurs currently operating in flood-prone areas were surveyed, resulting in a 95% confidence level and a 5% margin of error. These respondents were drawn from the 2021 list of establishments, focusing on the barangays within Marikina City determined as flood-prone by the city’s flood hazard map. The barangays identified through the multi-stage cluster sampling were as follows: Malanday, Tumana, Concepcion Uno, Tañong, Sta. Elena and San Roque.
Moreover, these enterprises were in the business of sari-sari stores (smaller retail shops found in every neighbourhood), retailers (food and non-food shops), essential stores (shops for basic household needs), eateries (food services), contractors (non-food services), and manufacturing. These types of businesses in Marikina City were chosen according to the top sectors of the total Philippine industry sectors of microenterprises.
A survey questionnaire was designed to gather primary data that would be used to measure and analyze the variables presented in the conceptual framework. The focus group discussion (FGD) was also facilitated with enterprise associations and groups. At the same time, a key informant interview (KII) was conducted at the local government level, specifically with the Marikina City Planning Office. The responses obtained from these pre-tests further validated the results of the survey.
Finally, the relationship between specific variables was examined using the following statistical tools:
Mann–Whitney U test: for testing averages between two populations (e.g. economic factors and length of stay). Spearman rank correlation test: to check whether the continuous variable was correlated with the ordinal random variable (e.g. cost of damage vs. socio-spatial relationship factors). Kendall Tau correlation test: to test the relationship between two ordinal random variables, especially for cases with only a few categories (e.g. assessment of the cost of damage (only three categories) vs. socio-spatial relationship factors). Chi-square test of independence: to test categorical variables (e.g. length of stay and economic factors).
Discussion
The initial response of microenterprises to the open-ended question of why they remain in flood-prone areas reveals a tendency towards gross sales orientation rather than cost orientation, specifically, the guarantee of profit due to an already established enterprise and location having a high footfall and sales (39%). When respondents were categorized according to their nature of business, the retailers, essential services providers, and contractors recorded high responses relating to high footfall and sales. Only the sari-sari stores reported the highest response for ownership of space, while manufacturing was the only sector to lean the most on agglomeration-related reasons.
To investigate further into the decision to remain in a flood-prone location, sub-factors were developed for each component (influencing) factor based on the literature review. These were provided for respondents to review and choose which are valid for them or already in existence. Among the top factors considered by entrepreneurs were: a stable customer base, familiarity with flooding and people, friendship with people, feeling of safety in the area, precious memories of the area/city, pride in belonging to Marikina City. In terms of resilience, the overwhelming majority perceived their preparation, emergency response, and recovery strategies as effective.
To establish evidence of a relationship, these sub-factors were measured with the respondents’ enterprise characteristics (nature of business, type of ownership of space, asset size, and barangay location), length of stay in the barangay/location, and experiences of worst flooding (height of flood and cost of damage) through the application of various statistical tools. The study discovered that economic, socio-spatial, and resilience factors influence the decision of microentrepreneurs to remain in flood-prone barangays in Marikina City. Sub-factors under each component factor were also identified (Table 1).
List of Influencing Sub-factors Tested with Significant Relationship.
Economic factors were found to be directly related to operational costs and sales. The socio-spatial relationship encompassed factors that were related to experiences of community culture and values before and after the flooding event. Resilience factors emerged as key influencers in the decision to stay, with most entrepreneurs perceiving themselves as resilient based on their continuous survival.
This was also validated during the conduct of FGD, where participants acknowledged the interconnectedness of these factors. However, correlation results showed that not all sub-factors of the component factors demonstrated a significant relationship. In summary, 23 out of 33 sub-factors were found to have considerable influence on the decision of entrepreneurs to remain (Table 1).
Moreover, there were specific sub-factors (out of the 23) which recurred the most during the conduct of relationship testing. This means that regardless of the respondents’ differences (i.e. nature of business, asset size, location, cost of damages, etc.) sub-factors, namely, net profit/loss only during worst flooding, ownership of space, feasibility of rental fee, stable customer base, value for moral support within the community, familiarity with flooding, pride in being resident, investments made to improve resilience, and perceived assessment on preparation and emergency response strategies appeared more frequently than the others (three times or more).
The study also confirmed that even in the context of urban flooding, such variations existed when evaluating location decision factors by industry and country (Dube et al., 2016; Ferreira et al., 2016; Patankar, 2019; Rahman & Kabir, 2019). For instance, most of the entrepreneurs in the eatery sector considered the fact that they only experienced net profit/loss in the worst flooding instances and their stable customer base aided their eventual recovery. Ownership of space was considered mainly by the manufacturing sector, while the feasibility of rental fees was related primarily to the essential services and goods sector.
Regarding socio-spatial relationship factors, familiarity with flooding, proximity of relatives, and pride in one’s location proved to be significant. All sectors gave high regard to the factor of having pride in Marikina City.
Remarkably, Losch’s (1954) theory remained relevant in location decisions to stay in flood-prone areas, as net profit/losses were only experienced during normal/serious flooding events. Stable customers in the area proved essential for business recovery as purchasing power would eventually return after the flooding event. Though it may initially seem contradictory to Losch’s belief that a one-sided approach to location decisions is incorrect, further in-depth investigation revealed the influence of socio-spatial relationships and resilience factors, thus aligning with the preferred multi-dimensional approach.
Weber’s cost-oriented theory additionally demonstrated its applicability, but only in rental expense. Conversely, the recurring sub-factor of ownership of space indicated that entrepreneurs were better off staying in their current locations than paying rent in flood-safe areas.
In terms of the influence of the benefits of agglomeration, only the manufacturing sector valued the abundance of skilled workers and input suppliers, as revealed during the FGD. Moreover, Marshall’s agglomeration theory may have been expounded upon by the results of the study, accounting for the non-economic aspect (or socio-spatial relationship), which also grew or was cultivated over time. However, this should not be confused with the agglomeration concept, which can pull enterprises due to better profitability but makes the decision to remain justifiable due to the socio-spatial relationship nurtured by agglomeration over time. Moreover, such relationship factors became more robust with the recurrence of flooding and the community’s collective efforts to continuously survive, as revealed in the FGD.
The study also identified two perspectives on socio-spatial relationship factors. First, these factors had already existed before the flooding events (e.g. being born and raised in the city, pride in being a resident of Marikina). Second, there are factors such as moral and physical support networks which they discovered or learned to offer in their community amidst the flooding events. This strengthened the appreciation of enterprise owners for their community, as their members showed them the unity, camaraderie, and support needed to overcome a common challenge. The FGD results confirmed that individuals were rooting for each other’s success and willing to do everything to help others survive. Another socio-spatial relationship factor, which was fostered through time emerged during the FGD. This was on how entrepreneurs witnessed their area grow, improve, and become well-known for what it offered.
Furthermore, resilience was an important factor influencing the decision to remain in flood-prone barangays. This, along with the fact that the enterprises have already survived the worst flooding events, arguably provided them with a rationale and conviction to continue operating in the vulnerable barangays of Marikina City. The respondents also validated this sentiment during the FGD, saying that their confidence in their eventual recovery grew with each year of surviving the floods and improving their resilience strategies. Moreover, it could be argued that the intensification of Marikina City’s flood control projects (i.e. daily dredging of Marikina River) including their effective clearing operations after flooding contributed to the perception of the respondents.
To better explain the decision of microentrepreneurs to remain in flood-prone areas, a location decision model should employ a multivariate approach (Figure 6). Two important discoveries were made due to the FGD during the modelling process. First, some sub-factors already existed and were neither dependent on nor induced by the flooding event. These sub-factors will be referred to as ‘pre-existing influencing factors’. The other component was the ‘learned influencing factors’. Sub-factors under this category would not have been experienced if not for the occurrence of urban flooding.
Location Decision Model of Micro Enterprises in Urban Flood-prone Areas.
The pre-existing influencing factors were economic and socio-spatial relationships, driving the entrepreneurs’ decisions to remain due to the proven reality attested by experiences. Such factors, which resulted in a statistically significant P value are detailed below:
Economic
Ownership of property/space Affordability of rental fee Stable customer base or high sales/footfall in the area Socio-Spatial Relationship
Friendship with people in the area Feeling of safety and security in the area Beauty of surroundings Born/raised in the area/city Precious memories of the area/city Proud resident of Marikina City Branding of Marikina City
The learned influencing factors were similar to the above but also incorporated the resilience component. Learned factors are particularly vital as they potentially diminish the negative impact of flooding, which could explain why entrepreneurs were willing to go through the challenge and recovery process repeatedly. The following sub-factors with statistically significant P values were identified as follows:
Economic
Net profit/loss only during normal/worst flooding Stable customer base in the area, which almost guarantees recovery after flooding. Socio-Spatial Relationship
Moral and physical support of the community during flooding Familiarity with flooding Proximity of relatives for immediate support during flooding Resilience
Investments made to improve resilience Capability to improve management of flooding impacts Cost of damage was manageable. Perceived effectiveness of managing impacts Perceived effectiveness of preparation, response, and recovery strategies
Overall, the new model suggests that when faced with the decision to remain in flood-prone areas, microentrepreneurs are influenced by the inextricably linked components of pre-existing and learned factors.
Conclusion and Recommendations
The worsening effects of global warming contribute to the vulnerability of the MSME sector. Numerous studies have documented the struggle, especially of microenterprises to survive the impacts of natural disasters such as urban flooding. Despite such incidents, it was evident that microenterprises continued to operate in flood-prone areas and justifiably accepted the risk of another catastrophic event. The results of the study established that influencing factors in the form of economic, socio-spatial relationships, and perception of resilience have driven microentrepreneurs to remain in flood-prone areas.
This uncovering could complement with foundational firm location choice theories focusing only on the economic aspect (i.e. cost minimization and net profit maximization). It has further given depth to other studies on firm location choices with results relating to differences in choice factors in specific business sectors, trade-offs, and drivers such as costs, customer access, agglomeration, and spatial and social relationships, including the sense of place and its variety of measurements, but here it is related to the phenomenon of urban flooding.
The LGU can effectively conceptualize impactful resilience programmes by understanding how microentrepreneurs behave. However, challenges persist. For one, these entrepreneurs were not inclined to relocate. Second, recurring flooding significantly hinders productivity as some enterprises may still be in the process of recovering. This would be crucial also in terms of sustaining the level of LGU funds, since on the one hand, tax relief and cash assistance were provided for these enterprises. On the contrary, LGUs must also sustain the funding of flood control projects, an example of which is the daily dredging of the Marikina River. Lastly, if the potential growth in the number of enterprises in flood-prone areas is not effectively planned and prepared, it may increase the city’s exposure and vulnerability.
The value of this study lies in showing that there are specific differences within the microenterprise sector, especially in the understanding and appreciation of socio-spatial relationships and developmental requirements, among others. However, these nuances can also be advantageous for designing resilience strategies that promote efficient allocation of support/development funds and encourage microenterprise engagement, especially if such strategies effectively incorporate the existing community values and their socio-spatial relationships as part of the design principle.
The results of the study are complementary to foundational firm location choice theories, which have traditionally focused solely on economic aspects such as cost minimization and net profit maximization. By expanding the concept of optimal location to include the decision to choose to remain, the study provided a comprehensive elaboration of the rationale of entrepreneurs to locate in flood-prone areas, given how the impacts of urban flooding are often devastating and repetitive.
The furtherance of this study could hinge on at least three aspects:
First, conduct a thorough exploration of the MSME sector, including small and medium-sized enterprises. This would allow researchers to check and compare differences among enterprise sizes. Uncovering consequent vital information in this regard may greatly assist planners in developing intervention measures that promote functional relationships anchored on promoting resilience among micro, small, and medium-sized enterprises within specific industries and contexts.
Second, expand the analysis of socio-spatial relationship factors to include enterprises relocated to flood-safe areas. Now that the study has revealed that socio-spatial relationship factors strongly influence location decisions in flood-prone areas, it would be practical to make structured comparisons between two entrepreneurs with different decisions, one choosing to move away from the flooded area and the other choosing to remain. How do their socio-spatial relationship contexts differ? What other related factors were considered or were not valued?
Lastly, contextualize the proposed location decision in similar urban areas facing different hazards, such as earthquakes. Would entrepreneurs still be influenced by economic, socio-spatial relationships, and resilience factors in these scenarios?
By addressing these aspects, future research extends the discussion of firm location decisions to encompass the element of ‘choosing to remain’ in a given hazardous location. This would consequently beget a more nuanced understanding of location choices, the holistic knowledge of which would significantly contribute toward promoting a resilient urban environment, especially in the context of risks brought about by natural hazards.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
This study is part of the dissertation in partial fulfilment of the doctorate degree at the University of the Philippines School of Urban and Regional Planning (UP SURP). The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Office of the Chancellor of the University of the Philippines Diliman (UPD) through the Office of the Vice Chancellor for Research and Development, through the Thesis and Dissertation Grant program.