Perceived risk of public transport travel during flooding events in Metro Manila, Philippines

Transportation Research Interdisciplinary Perspectives 2 (2019) 100051

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Perceived risk of public transport travel during flooding events in Metro Manila, Philippines ⁎

Raymund Paolo B. Abad , Alexis M. Fillone Civil Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila, Philippines

A R T I C L E

I N F O

Article history: Received 20 April 2019 Received in revised form 19 August 2019 Accepted 1 September 2019 Available online xxxx Keywords: Public transport Risks Travel Flooding Beliefs

A B S T R A C T

Understanding the risks associated with traveling is essential to finding solutions for strengthening transport services, especially during adverse weather conditions. The current study performed an analysis of the perceived risk of public transportation users of Metro Manila travelers during a flood event. Questionnaire data collected among transit users demonstrated that travelers generally perceive low risks (no risk to somewhat not risky) in using public transportation services during a flood event. Furthermore, bivariate analyses and linear regression models revealed that perceived risks primarily depend on the respondent's characteristics and their typical travel situation. Prior travel experience during a flood and beliefs about changes over time in the frequency of flood events also played a role but were less associated with the perceived risk of public transport use during a flood. Recommendations for authorities were derived from the analyses so that public transport users may benefit from a resilient transit system that is prepared for any flood event.

1. Introduction Changes in climate and weather patterns combined with fast development and population growth increase flood exposure of cities, thereby threatening the lives of its inhabitants. As such, cities are considered the most vulnerable human habitats (Intergovernmental Panel on Climate Change (IPCC), 2007; Stern, 2006). Notably, many Asian coastal cities have high flood risks because of frequent typhoons and rainstorms that occur in their region (Webster et al., 2005). The Philippines is one of the countries significantly affected by climate change-induced variability of rainfall (R. V. Cruz et al., 2007). In the capital region of Metro Manila, municipalities in the Pasig-Marikina River basin (Manila City, Mandaluyong City, and Marikina City) and CAMANAVA areas (cities of Caloocan, Malabon, and Navotas) are at high risk from flooding due to extreme weather events by 2050 (R. V. O. Cruz et al., 2017). Recurrent flooding has been troublesome even for an urban area like Metro Manila. The region topographically acts as a catch basin between Laguna Lake and Manila Bay. Aside from topographic conditions, the unregulated commercial and residential developments, inadequate flood control measures, and poor solid waste management make it difficult for the metropolis to cope with recurring flood events often caused by severe weather disturbances. ⁎ Corresponding author at: Civil Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila City, Philippines. E-mail address: [email protected]. (R.P.B. Abad).

Frequent flooding events in Metro Manila may influence the perceived risks among its inhabitants. Understanding people's risk perception and factors influencing such are critical in improving risk communications and creating effective policies on mitigation (Kellens et al., 2011; Liu et al., 2018). Moreover, it allows authorities to understand the level of preparation and possible behavioral response of the population in any event (Lechowska, 2018; Siegrist and Gutscher, 2006). Thus, decisionmakers would have the necessary information about people's willingness to take protective behavior (Kellens et al., 2011), which would guide the formulation of strategies in motivating people in endangered areas to take mitigating actions (Lechowska, 2018). In the field of transportation and tourism, studies usually center on the role of perceived risks on the intention to travel, driving a car, or using public transport. Work along these lines typically determines how users think about the associated risk (Moen, 2007) and how they will likely support policies to improve the public transportation sector especially in urban areas (Lund et al., 2016). However, studies about the perceived risk of travel during a disruptive event (e.g., a flood) are scarce. This study aims to fill the research gap by determining factors affecting the perceived risks of individuals using public transport during a flood event. Because of more frequent extreme weather disturbances, the need for understanding the perceived risks to travel is imperative. The study focuses on transit users because their travel options are limited to the services that operators provide. This limitation sets users of public transport apart from private car users because the latter enjoy the flexibility of using alternate routes when needed.

http://dx.doi.org/10.1016/j.trip.2019.100051 2590-1982/©2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4. 0/).

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Transportation Research Interdisciplinary Perspectives 2 (2019) 100051

2015) or they were not subjected to an adverse outcome (Halpern-Felsher et al., 2001; Lindell and Hwang, 2008). Travel experiences influence risk perceptions and affect certain decisions like choosing safer destinations (Sonmez and Graefe, 1998). This paper explores the possibility that previous flood experiences influence people's perceived risk of transit travel during a flood. Furthermore, it investigates if travel experiences, during normal and flood-disrupted conditions, influence people's perceived risk of travel during a flood. It aims to reveal the role of transportation services in effectively managing the perceived risks of public transport travel during unfavorable weather conditions. Filipinos are familiar with the frequent occurrence of different disasters (Morin et al., 2016) through personal experience or second-hand reports (vicarious) (Macapangal and Patron, 2017). The repeated occurrences have led them to adapt to these disasters such that it has become instilled in their cultural practices (Bankoff, 2007). The current study explores people's formed beliefs regarding the frequency of flooding events in recent years. It is hypothesized that a person's formed beliefs from frequent flood events are associated with their perceived risk of travel. The remainder of the paper continues with a description of the data collection methods, the method of analysis, followed by the presentation of results. A discussion of relevant statistics and formulated models is provided in the latter portion. The last section concludes the paper and provides some recommendations.

The research uses data from a questionnaire survey collected from public transport users all over the region. The analysis below seeks to identify which socio-demographic factors, travel characteristics of the respondent, and features of the last flood event they experienced correlate with the perceived risk of travel during a flood. It also looks at how beliefs about changes in the frequency of flooding over time affect their perceived risk in travel during a flood. Beliefs may act as proxies for the respondent's awareness, exposure, and experiences with flooding and may contribute to the explanation of their risk perception. 2. Related literature Risk is often quantified as the product of two parts: (1) the probability for an event to occur (subjective probability assessment), and (2) the resulting consequences once the event occurs (severity of consequences) (Becker et al., 2014; Berdica, 2002; Bubeck et al., 2012; Lechowska, 2018; Noland, 1995; Raaijmakers et al., 2008; Roche-Cerasi et al., 2013; Rundmo et al., 2010). Usually, the perceived risk generates the degree of caution people apply to their behavior and may result to changes in their behavior due to their health and safety (de Oña et al., 2014). Risk analyses are often applied in accident perception and their influence in mode use. For instance, risk- and accident-related factors are believed to be associated with the likelihood to use public or private transportation (Rundmo et al., 2010). Roche-Cerasi et al. (2013) show that perceptions of high likelihoods of an accident to occur influence people's shifting to other modes of transport. Noland (1995), on the other hand, studied the reduction of transit modal shares when people viewed transit travel as riskier. Fyhri and Backer-Grondahl (2012) added that private car users fear road crashes and may induce them to travel at a different time. In tourism, risk perception is fundamental to the travel decisionmaking process (Sonmez and Graefe, 1998). For instance, travelers who find a destination risky may change their intention to travel (PenningtonGray et al., 2011). Individual socio-demographic factors play an essential role in forming the risk perception of natural hazards (Kellens et al., 2011). Females are usually positively correlated with risk perception (Kellens et al., 2011; Roche-Cerasi et al., 2013; Zhu and Levinson, 2012) as their vulnerable mental and physical characteristics result to an overstating of their risk (Liu et al., 2018). Older people are typically more risk-averse (Cyders and Smith, 2008; Machin and Sankey, 2008; Rhodes and Pivik, 2011) and younger people tend to undertake risky behaviors such as driving through flooded roads (Drobot et al., 2007). The educational attainment of the respondent resulted in varied results. In one case, being highly educated makes people more aware of environmental hazards which result in higher risk perception (Qasim et al., 2015). It may also give them a degree of controllability over the disaster which allows them to perceive risks lower (Liu et al., 2018). Likewise, higher-income earners tend to worry less about the consequences of a flood (Lechowska, 2018; Liu et al., 2018). This paper evaluates if socio-demographic characteristics influence the perceived threat of traveling using public transport during a flood. Spatial factors were also found to influence people's perceived risk. Lechowska (2018) inferred that a person who resides in an area where flooding risks are high tend to be aware of risks and have higher risk perceptions. Whereas, Drobot et al. (2007) argued that people who believed that their residence is safe from flooding would likely engage in risky behavior like driving through flooded roads. People are also inclined to downplay the risk of traveling when going to important destinations. It was found that time-sensitive trips like work trips make people more willing to assume the risk of driving (Noland, 1995; Strawderman et al., 2018; Watling, 2006). First-hand experiences with disasters also contribute to people's awareness of flood risks. Direct experiences with floods often have a positive influence to people's perceived risks (Bradford et al., 2012; Lindell and Hwang, 2008; Messner and Meyer, 2006; Qasim et al., 2015). In contrast, persons may have low risk perceptions either because they experienced the disaster a long time ago (Grothmann and Reusswig, 2006; Su et al.,

3. Methodology 3.1. Data collection A questionnaire survey was conducted from September to October 2017 through random convenience sampling of public transport users and whose trips had been previously disrupted by flooding in Metro Manila. The survey instrument was administered in 10 various locations around and within Metro Manila that have large concentrations of passenger movements (Department of Transportation and Communications (DoTC), 2014) which are typically near malls, residential areas, business districts, or provincial bus terminals. A target of 1000 respondents was set, but only a total of 881 complete and valid responses were considered for the study. All respondents were asked about the details of the most recent flood they experienced, typical daily trip characteristics, socio-demographic characteristics, beliefs regarding the frequency of flood events, and their general perceived risks when traveling during flood events. Initially, respondents were asked about their belief regarding the frequency of flood events over the last ten years. Next, respondents were asked to describe the previous flood event they experienced. Specific information included the depth of the flood in relation to the respondent's body parts (ankle, knee, waist, chest levels), the location, and the duration of the flood. Respondents were also asked about normal travel conditions they typically go through, such as their usual travel time and travel fare. Queues and traffic condition that best describes what respondents usually experience in a typical day were determined using a picture set. Respondents were then asked if they have an alternate way of traveling for their usual trip. Finally, they were asked about the duration of their travel during flooded conditions to compare the changes in traffic conditions caused by the flood. The questionnaire then elicited responses about the respondent's perceived risk of travel during flooding events (‘How risky it is to travel during flooded conditions?’). Respondents were asked to describe the perceived risk using a Likert Scale (1 = not risky at all, 5 = extremely risky). Finally, the socio-demographic characteristics of the respondents were then collected. 3.2. Sample characteristics The summary statistics of the 881 respondents comprising the sample is shown in Table 1. The sample has 526 male respondents resulting in a (male-female) sex ratio of 1.48. Most respondents are aged between 21 2

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Table 1 Cross-tabulation of socio-demographic factors and perceived risk of travel. Variable

Age Below 20 21–30 31–40 41–50 51–60 Above 60 Gender Female Male Civil status Single Married Employment type Part-time Full-time Business/self-employed Unemployed/student Possession of driving license Yes No Residence located in Metro Manila Yes No

Risk perception of travel during a flood Not risky at all

Somewhat not risky

With some risk

Total

22 (35.5%) 105 (29.4%) 84 (29.1%) 38 (27.9%) 8 (22.9%) 0

26 (41.9%) 135 (37.8%) 117 (40.5%) 47 (34.6%) 14 (40.0%) 1 (50.0%)

14 (22.6) 117 (32.8%) 88 (30.4%) 51 (37.5%) 13 (37.1%) 1 (50.0%)

62 (7%) 357 (40.5%) 289 (32.8%) 136 (15.4%) 35 (4%) 2 (0.2%)

100 (28.2%) 157 (29.8%)

139 (39.2%) 201 (38.2%)

116 (32.7%) 168 (31.9%)

355 (40.3%) 526 (59.7%)

161 (35.9%) 96 (22.2%)

163 (36.3%) 177 (41.0%)

125 (27.8%) 159 (36.8%)

449 (51.0%) 432 (49.0%)

17 (11.6%) 208 (33.3%) 11 (34.4%) 21 (27.3%)

70 (47.6%) 230 (36.8%) 9 (28.1%) 31 (40.3%)

60 (40.8%) 187 (29.9%) 12 (37.5%) 25 (32.5%)

147 (16.7%) 625 (70.9%) 32 (3.6%) 77 (8.7%)

78 (30.2%) 179 (28.7%)

103 (39.9%) 237 (38.0%)

77 (29.8%) 207 (33.2%)

258 (29.3%) 623 (70.7%)

232 (30.2%) 25 (22.3%)

305 (39.7%) 35 (31.2%)

232 (30.2%) 52 (46.4%)

769 (87.3%) 112 (12.7%)

χ2 (p-value)

Cramer's V

6.887 (0.736)

0.063

0.289 (0.865)

0.018

20.76 (0.000)

0.154

28.89 (0.000)

0.128

0.95 (0.620)

0.033

11.87 (0.003)

0.116

in multicollinearity (Bryman and Cramer, 1997; Grothmann and Reusswig, 2006). Tests of independence were also carried out to confirm relationships between the variables and the perceived level of risk when traveling using public transport during flood events. Cramer's V was used to provide acceptable measures in the strength of association between the variables.

and 30 years old (40.5%), and less than half are married (49.0%). More than 60% have completed at least tertiary-level education, about 71% are employed full-time, and about 34% are employed under the services and sales sector. Less than a third of the respondents possess a driving license and no more than one-fourth of the respondents own a vehicle. About 42% of the respondents reported that no senior citizens are living with them, but some 52% have at least one child in the household. Lastly, the average monthly individual and household incomes are ₱ 21,915.44 and ₱ 64,721.91, respectively. The sample could not be verified as representative of the entire traveling population in Metro Manila since the survey specifically targeted people whose previous travels on public transportation were affected by a flood. This limitation resulted in deviations from regional statistics. First, reported individual incomes were higher than national or regional averages and per capita poverty thresholds (Philippine Statistics Authority (PSA), 2015b). Since employees from Metro Manila tend to earn higher wages and the surveys were conducted in areas near business districts, respondents comprising the sample may have higher incomes. Finally, sample statistics regarding vehicle ownership and possession of a driving license differ from Metro Manila's statistics (Japan International Cooperation Agency (JICA), 2015; Nielsen Holdings, 2014; PSA, 2015a). Nonetheless, there were some similarities between the sample and regional statistics. Regional statistics suggest a larger share of the population is younger than 30 years old, a majority of the working population have a college degree (about 40%), and most individuals are employed under the services sector (JICA, 2015; PSA, 2018). The sample sex-ratio of 1.48 and substantial representation of higher-educated individuals are similar to the characteristics of commuters that mainly use public transportation in Metro Manila (JICA, 2015).

4. Perceived risk of public transport travel during a flood The results in Table 2 shows that no >70% of the respondents perceived that flood events pose little to no risk in traveling during flood events. Since only about a third of the respondents believed there is some risk in traveling during flood events, the subsequent risk perceptions were regrouped into three: not risky at all, somewhat not risky, and with some risk. Tests of independence in Table 1 indicate that individuals who are married, not full-time employees, and living outside Metro Manila see some risk when traveling during a flood event. There were more respondents aged 40 years old and above who saw traveling riskier when there is a flood than younger respondents. However, as with gender and possession of a driving license, both Chi-Square statistic and Cramer's V indicate no association between age and the perceived risk of travel. Finally, respondents who live outside Metro Manila have higher risk perceptions than those residing within Metro Manila. The result may indicate some spatial effect with risk perception, but the strength of association between the two variables is very weak (Cramer's V = 0.116). Normal travel conditions experienced by the respondent during normal weather conditions did not show any effect on their perceived risk in travel under flooding conditions. It is shown in Table 3 that there were more

3.3. Analysis

Table 2 Respondents' perceived risk of travel using public transport in flooded conditions.

Hierarchical multiple linear regression analyses were used to determine the significant variables that affect the perceived risk of travel during flood conditions. The variables used in the study were grouped into (1) sociodemographic characteristics, (2) normal travel conditions experienced by the respondent, (3) details of the last experienced flood event, and (4) the belief about the frequency of flood events. All variables used in the study are dichotomous except for age, household size, and the number of transfers during the trip. Variables whose correlation coefficients are higher than 0.70 were not included as inputs in the same model to avoid issues 3

Perceived risk of travel

Count (percentage)

(1) Not risky at all (2) Somewhat not risky (≥3) With some risk (3) Moderately risky (4) Risky (5) Extremely risky Total

257 (29.2%) 340 (38.6%) 284 (32.2%) 230 (26.1%) 39 (4.4%) 15 (1.7%) 881 (100.0%)

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Transportation Research Interdisciplinary Perspectives 2 (2019) 100051

Table 3 Cross-tabulation of travel characteristics and perceived risk of travel. Variable

With alternate route Yes No Usual traffic condition experienced Light Moderate Heavy

Risk perception of travel during a flood Not risky at all

Somewhat not risky

With some risk

Total

85 (30.6%) 172 (28.5%)

104 (37.4%) 236 (39.1%)

89 (32.0%) 195 (32.3%)

278 (31.6%) 603 (68.4%)

91 (26.5%) 135 (29.0%) 31 (43.7%)

147 (42.7%) 176 (37.8%) 17 (23.9%)

106 (30.8%) 155 (33.3%) 23 (32.4%)

344 (39.0%) 466 (52.9%) 71 (8.1%)

χ2 (p-value)

Cramer's V

0.428 (0.807)

0.022

11.91 (0.018)

0.116

flood-disrupted public transport travel. A possible explanation is that respondents did not experience adverse outcomes despite the repeated flooding events over time (Halpern-Felsher et al., 2001; Siegrist and Gutscher, 2006). It is also likely that people who experienced frequent flooding have gotten used to the situation despite the risks. Overall, tests of independence indicate a moderate association (Cramer's V = 0.233) between respondent beliefs and their perceived risk.

respondents who did not have an alternate way of traveling. Among those who did not have an alternate route of travel, about 34.2% believed that their current route is the most convenient1 while 36.7% believed that it is the only route available to them (36.7%). It is also possible that route that respondents typically use is the best way for traveling and that other available routes may not provide the optimal travel outcome. Table 3 also shows that more respondents saw no risk at all traveling while it is flooded when an alternate route is available to them. Tests of independence, however, indicate that it is independent and very weakly associated with the perceived risk of travel. Finally, the traffic conditions travelers often face during normal weather suggest some association with the perceived risk of travel during a flood, albeit very weakly. Interestingly, travelers who are used to heavy traffic conditions had the highest proportion that saw no risk when traveling under flooding conditions. It is likely that they suppose that traffic conditions during a flood would be no different from the sever traffic conditions they typically go through. The characteristics of the previous flood respondents experienced also influenced their perceptions of risk. Results in Table 4 show that majority of the respondents have experienced flood heights not reaching above their ankles. Also, the floods (71%) were mostly short in duration (less than an hour), and only about 1% exceeded 5 h. The data suggest that these floods were mainly localized and were partly caused by blocked or poorly functioning drainage systems. Despite the relatively shallow floods, the resulting impact to traffic conditions was evident. Majority of respondents have reported that they spent about 30 min to an hour while some 6%, were stuck in traffic for at least 2 h. Findings showed that people who experienced deeper floods also viewed public transport travel during a flood with some degree of risk. Likewise, people who got caught in traffic congestion at prolonged periods also saw transit travel during a flood riskier. Both experienced flood depths and the time spent in traffic congestion influenced the perceived risk of travel. However, the latter had a stronger association (Cramer's V = 0.257) than the experienced flood height. More than half of the respondents used the bus (51.3%) as their primary mode of travel. This was followed by the jeepney (33.5%), the Asian Utility Vehicle (AUVs/FX) (11%), and the rail modes (LRT1, LRT2, MRT3) (4.2%). The results in Table 4 showed that AUVs/FX and rail transit users have the highest shares who saw flood-disrupted travel risk-free. Naturally, rail users viewed their travel with lower risk because the rail system operates abovegrade, thereby avoiding flooded areas. AUVs, on the other hand, are not bound by fixed routes and operate as point-to-point/express services. Further, these services offer travelers some degree of flexibility because drivers may choose roads that are not flooded. Moreover, among road-based public transit modes, AUVs/FX drivers share relevant information like current traffic situation (Matias, 2017), which may be crucial during a disruption. Overall, tests of independence suggest a very weak association between the transport mode used and the perceived risk. In Table 5, there were more respondents who believed that flood events have decreased in Metro Manila over the past years. Around 80% of the respondents who believed flood events have decreased saw some risk when traveling using public transit during a flood. The results may imply that repeated experiences or exposures to flood events lower the perceived risk of

5. Regression analysis: Explaining the perceived risk of travel Hierarchical linear regression models using different sets of variables derived from the survey data attempted to explain the perceived risk of travel of transit users during a flood. The first model (Model 1) included the socio-demographic characteristics of the respondents. Subsequent models were generated by adding transportation or travel characteristics of the respondent (Model 2), details of the previous flood experience (Model 3), and beliefs on the frequency of flood events (Model 4). The modeling results and the corresponding goodness-of-fit measures are tabulated in Table 6. 5.1. The effect of socio-demographic characteristics Model 1 results show that females tend to evaluate risks higher than men (Fyhri and Backer-Grondahl, 2012; Kellens et al., 2011; Roche-Cerasi et al., 2013; Strawderman et al., 2018; Zhu and Levinson, 2012). Next, the effect of age is small and insignificant to the perceived risk of travel thereby validating results in other researches (Armas et al., 2015; Qasim et al., 2015). A positive correlation was observed for respondents who completed at least tertiary education. The result confirms previous researches that noted highly-educated people have higher levels of perceived risk (Kellens et al., 2011; Liu et al., 2018; Qasim et al., 2015; Roche-Cerasi et al., 2013). It was also found that students and those who do not have full-time jobs perceived higher risks in flood-disrupted public transport travel. Single respondents tend to perceive lower risks in travel because they may be less concerned with the possibility of not meeting filial commitments when their travels are disrupted. Respondents from larger households also tend to view lower risks (Houts et al., 1984; Qasim et al., 2015). The findings suggest that travelers who are married but with a small family size perceive risks to be higher than those who are single and with large family sizes. Income and vehicle ownership were positively related to public transport travel risk perception. Respondents earning below ₱30,000 reported higher risk perception implying that higher-income earners worry less about flooding and its potential (Lechowska, 2018; Liu et al., 2018). It is also likely that higher-income earners are more flexible to adapt their travels because of their higher spending capacity. The positive coefficient in vehicle ownership and possession of driver's license may reflect situations wherein these individuals think of the risks associated with driving their own vehicle to inundated areas. Lastly, people who reside outside Metro Manila perceive higher risks of flood-disrupted transit trips. The outcome hints that those residing outside the metropolitan region (i.e., suburban areas, provinces) may be experiencing worse issues with flooding and its corresponding impacts to travel.

1 The term ‘convenient’ was described to the respondent as a situation wherein many transit operators serve the route they usually take.

4

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Transportation Research Interdisciplinary Perspectives 2 (2019) 100051

Table 4 Cross-tabulation of previous flood characteristics and perceived risk of travel. Variable

Flood height Ankle-level Knee-level Waist-level Time spent in traffic during the last flood <30 min 30 min–1 h 1 h–2 h >2 h The main mode of transport used Jeepney Bus Rail AUV/FX

Risk perception of travel during a flood Not risky at all

Somewhat not risky

With some risk

Total

192 (28.2%) 63 (35.0%) 2 (14.3%)

275 (40.3%) 59 (32.8%) 6 (31.6%)

315 (31.5%) 58 (32.2%) 11 (57.9%)

682 (77.4%) 180 (20.4%) 19 (2.2%)

123 (40.3%) 113 (32.0%) 18 (10.5%) 3 (5.9%)

138 (45.2%) 105 (29.7%) 68 (39.5%) 29 (56.9%)

44 (14.4%) 135 (38.2%) 86 (50.0%) 19 (37.3%)

305 (34.6%) 353 (40.1%) 172 (19.5%) 51 (5.8%)

89 (30.2%) 116 (25.7%) 14 (37.8%) 38 (39.2%)

109 (36.9%) 186 (41.2%) 17 (45.9%) 28 (38.9%)

97 (32.9%) 150 (33.2%) 6 (16.2%) 31 (32.0%)

295 (33.5%) 452 (51.3%) 37 (4.2%) 97 (11%)

χ2 (p-value)

Cramer's V

10.94 (0.027)

0.111

110.4 (0.000)

0.250

17.24 (0.069)

0.096

χ2 (p-value)

Cramer's V

96.07 (0.000)

0.233

Table 5 Cross-tabulation of beliefs about flood event frequency and perceived risk of travel. Variable

The belief of the frequency of flood events Not changed Increased Decreased

Risk perception of travel during a flood Not risky at all

Somewhat not risky

With some risk

Total

150 (38.9%) 15 (57.7%) 92 (19.6%)

171 (44.3%) 5 (19.2%) 164 (35.0%)

65 (16.8%) 6 (23.1%) 213 (45.4%)

386 (43.8%) 26 (3%) 469 (53.2%)

Table 6 Results of multiple regression models. Variable Constant Age Female (1 = yes, 0 = Male) Married (1 = yes, 0 = Single/Widowed) Tertiary education (1 = yes, 0 = no) Respondent is not employed full-time (1 = yes, 0 = no) Respondent is currently a student (1 = yes, 0 = no) Household size Income below ₱30,000 (1 = yes, 0 = above ₱30,000) Vehicles owned Possess driving license (1 = yes, 0 = no) Not residing in Metro Manila (1 = yes, 0 = inside MM) Respondent has no alternate route; the current route is only available route (1 = yes, 0 = no) Respondent has no alternate route; the current route is the most convenient route (1 = yes, 0 = no) Number of transfers for usual travel The primary mode of travel: Bus (1 = yes, 0 = no) The primary mode of travel: AUV/FX (1 = yes, 0 = no) The primary mode of travel: Jeepney (1 = yes, 0 = no) Usual traffic conditions (normal): light Usual traffic conditions (normal): moderate Usual travel time (normal): 1 to 3 h Usual travel time (normal): 3 to 5 h Usual travel time (normal): >5 h Last flood event: Knee-level (1 = yes, 0 = no) Last flood event: Waist-level and up (1 = yes, 0 = no) Time in heavy traffic: 30 min to an hour Time in heavy traffic: 1 to 2 h Time in heavy traffic: >2 h The belief of flood event frequency: Decreasing R R2 Adjusted R2 Change in R2

₱1 (1 Philippine Peso) ≈ US $ 0.02. ⁎ p < 0.1. ⁎⁎ p < 0.05. ⁎⁎⁎ p < 0.01. 5

Model 1

Model 2

Model 3

Model 4

1.36⁎⁎⁎ 0.007⁎ 0.1⁎ 0.551⁎⁎⁎ 0.22⁎⁎⁎ 0.388⁎⁎⁎ 0.233⁎⁎ −0.176⁎⁎⁎ 0.158⁎⁎ 0.368⁎⁎⁎ 0.238⁎⁎⁎ 0.259⁎⁎⁎

0.687⁎⁎ 0.004 0.083⁎ 0.414⁎⁎⁎ 0.208⁎⁎⁎ 0.392⁎⁎⁎ 0.174⁎ −0.12⁎⁎⁎ 0.148⁎⁎ 0.355⁎⁎⁎ 0.327⁎⁎⁎ 0.225⁎⁎⁎ −0.37⁎⁎⁎ 0.264⁎⁎⁎ 0.071⁎⁎ 0.347⁎⁎ 0.265⁎⁎ 0.345⁎⁎ 0.162⁎

0.61⁎⁎ 0.003 0.089⁎ 0.425⁎⁎⁎ 0.211⁎⁎⁎ 0.434⁎⁎⁎

0.544⁎⁎ 0.003 0.097⁎⁎ 0.334⁎⁎⁎ 0.211⁎⁎⁎ 0.409⁎⁎⁎ 0.185⁎ −0.085⁎⁎⁎ 0.123⁎ 0.252⁎⁎⁎ 0.272⁎⁎⁎ 0.241⁎⁎⁎ −0.241⁎⁎⁎ 0.211⁎⁎⁎

0.086 0.245⁎⁎⁎

0.452 0.205 0.195 0.205

0.156 −0.111⁎⁎⁎ 0.118⁎ 0.327⁎⁎⁎ 0.336⁎⁎⁎ 0.226⁎⁎⁎ −0.305⁎⁎⁎ 0.187⁎⁎ 0.037 0.169 0.144 0.247⁎⁎ 0.242⁎⁎ 0.146⁎ 0.19⁎⁎

0.042 0.191⁎ 0.143 0.242⁎⁎ 0.207⁎⁎ 0.094 0.221⁎⁎⁎

0.143 0.345

0.073 0.171 −0.116⁎ 0.36⁎⁎ 0.214⁎⁎⁎ 0.458⁎⁎⁎ 0.418⁎⁎⁎

0.156 0.23 −0.115⁎ 0.282⁎ 0.168⁎⁎ 0.444⁎⁎⁎ 0.46⁎⁎⁎ 0.295⁎⁎⁎

0.569 0.324 0.306 0.119

0.601 0.361 0.341 0.037

0.621 0.386 0.366 0.025

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the belief variable only explained about 2% of the variance. It is likely that the impacts of the flood to travel conditions were more influential on people's risk perception than its repeated occurrence.

5.2. The effect of transport-related characteristics The second model identifies which transport-related characteristics are significant to the respondent's risk perception. The model used ten different variables representing the importance of the route to the respondent, the respondent's primary mode and typical travel characteristics. Availability of alternate transportation routes was significant to the perceived risk of travel during a flood disruption. Travelers who thought they only have a single way of travel perceived lower risks against flooding. It is presumed that these people have lower perceived risks because they are resigned to any change in travel conditions caused by disruptions. However, when served by many operators (defined as ‘convenient’ in this study), travelers perceived higher risks. The higher risk perception may reflect people's concerns that disruptions will lead to a decline in operating characteristics for the services they take. The transport mode typically used by respondents and the number of transfers they make on a trip increase the perceived risk of flood-affected travel. Specifically, people who primarily use the bus and jeepney have higher perceived risks than patrons of AUVs/UV Express. Since buses and jeepneys operate on fixed routes, these services may be severely affected when a portion of their routes is flooded. The results suggest that services that avoid flooded areas (like rail modes) or adapt to changes in traffic conditions (like AUVs or UV Express) reduce the risks associated with disrupted travel. Meanwhile, trips with transfers increase the perceived risk because severe weather conditions hinder smooth transfers between services especially when facilities are lacking or need to be improved (de Oña et al., 2014; Sunga et al., 2017). Common issues with transport terminals, stops, or stations include inadequate waiting facilities and poor outside access (ALMEC Corporation, 1999). The findings may indicate the need for improvements in transit interchange facilities (JICA, 2014). Finally, transit users who are used to trips lasting between 1 and 3 h and light traffic conditions, perceived higher travel risks during a flood. The result implies that people who regularly experience favorable travel conditions would find traveling during a flood riskier. The increase in perceived risk may be attributed to their sensitivity to the changes in travel time caused by floods.

6. Conclusions This paper explored different factors which affect risk perception of travel using public transportation during a flood in Metro Manila. Two main conclusions can be formed from the study. First, it was determined that, in the context of Metro Manila, there seems to be a low perception of risk when traveling using public transport during a flood. At least among the recruited sample, respondents who view using public transportation during a flood as risky or extremely risky were uncommon. Second, the models and its findings were consistent in showing that the perceived risk in public transport travel during a flood is mainly shaped by socio-demographic factors and typical travel experiences of the respondent. Females and those who may have filial commitments (married or lives at large households) tend to perceive higher travel risks during flooding. Other socio-demographic factors like educational attainment, income, possession of a vehicle, or a driving license, also influence the risk perception of public transport travel during a flood. Lastly, residents outside Metro Manila perceived risks during flooding higher which highlights potential disparities between living within and outside the metropolitan region. Travel and transit conditions during normal and undisrupted conditions also shape the travel risk perception during a flood. Results demonstrate that travelers who are used to short (less than an hour), fast (light to moderate traffic conditions), and convenient (served by many operators) trips perceive risks higher because they may be sensitive to the substantial changes in travel conditions due to flooding. Furthermore, users of rail and AUV/UV express perceived flood-disrupted transit travel with the lowest risk since operating characteristics of modes provide travelers the ability to bypass areas inundated by floods. Finally, transfers in between legs of the trip increase the risk of transit travel during a flood because they may be exposed to floodwaters when accessing their next transit mode. Transit facilities, therefore, are crucial in facilitating the interchange of passengers during flood events. Previous experiences with flood and respondent's formed beliefs on the frequency of flood events also influenced but only explained about 6% of the variation of risk perception. Analyses showed that past floods reaching waist-level or deeper and floods that resulted in extended periods in heavy traffic conditions increase people's perceived risk. However, when people believe that flood events are decreasing, they tend to believe that traveling using public transport during a flood is risky. Although a decrease in the frequency of flooding events may be beneficial, people may perceive risks higher because they may lack the ability to assess a flooding situation and its potential consequences. Models of Kellens et al. (2011) accounted for a relatively low percentage of the variance despite the number of variables tested. This may suggest instances wherein there could be noise or variation when examining risk perception. Regardless, the current study provided valuable insights into public transport users' perception of travel risks during flooded conditions. Several recommendations are provided based on the insights gained from the study. It was determined that increasing people's awareness may influence their perception of risk. Dissemination of information designed to make travelers aware of the flooding situation is suggested to minimize the impacts of floods on their travels and to aid them in making informed decisions. Providing timely information that includes flooded areas and affected transit services will also benefit those who experienced flood events few and far between. Second, the reliability of transport services is one of the main concerns of respondents that influenced their perceived risk of travels. The models indicate that the travel conditions that people go through on an average day dictate their perception of travel risk in case of a disruptive event. Hence, it is recommended to improve the reliability and robustness of transit services for people with trips and activities that are arrival time-sensitive. Third, as transfer points are critical during

5.3. Previous flood-affected travel experience and beliefs on the frequency of flood events Prior experiences with flood influence people's perceived risks. Despite the test of independence result in Table 5, Model 3 showed that respondents who previously experienced above waist-level floods observed higher levels of risk. Naturally, those who have experienced deeper floods view flood-disrupted transit trips as riskier. The model revealed that people who experienced floods that reached knee-level have lower perceived risk in travel. It may be that their previous experience and its corresponding travel conditions were still acceptable and satisfactory. Respondents who were stranded in poor traffic conditions for prolonged periods had higher levels of risk in flood-disrupted transit travel. Negative experiences heighten travelers risk perception because they anticipate the effect of floods on their travel times. The result validates previous research findings that relate direct experiences to the perception of risks (Kellens et al., 2011; Lindell and Hwang, 2008; Paton et al., 2000; Qasim et al., 2015). However, previous flood experience only contributed to 3.7% of the variance. Beliefs about flood events impact the travel risk perception of individuals. Model 4 determined that respondents who believe that flood events have decreased, perceived higher risks for transit travel during a flood. Filipinos who regarded flooding events have remained or increased in frequency may be used to flooding such that it has been incorporated into their daily lives effectively allowing the “normalization of threat” (Bankoff, 2007). It is also possible that despite the recurrent flooding events, the time elapsed between each event may have been long enough for it not to influence their current risk perception (Grothmann and Reusswig, 2006; Su et al., 2015). Despite its significance, the inclusion of 6

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severe weather disturbances, interchange facilities should be evaluated and assessed if these are enough to protect travelers from weather elements. Continuing studies could be pursued by understanding the level of risk of flood-disrupted travel of private car users and those with no previous experience of traveling during a flood. By this, it may offer readers a broader view of perceptions of travel risk during severe weather disturbances. The use of other modeling approaches is also recommended.

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