e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 1 Taemane Phoofolo University of KwaZulu Natal Joram Ndlovu University of KwaZulu-Natal The effect of risks on tourists’ travel decision choices in Durban, South Africa Tourism is an important economic sector in many countries worldwide. Many governments are placing a higher priority on tourism development because it leads to increased foreign exchange income and creates employment opportunities. However, the tourism sector is prone to both natural and human-made crises and risks, which invariably affect the functionality, sustainability, and competitiveness of a destination. The purpose of this paper is to provide an empirical analysis of the tourists' perceptions of crises and risks affecting the tourism sector in Durban. The paper used a mixed-method through the use of surveys and direct interviews with a sample of local, regional, and international tourists and key informants in the tourism sector within Durban. The results show that the level of risks in the city is perceived to be high and was found to have a significant impact on destination decision- choices. First-time visitors might be discouraged by mediatised risks. However, repeat visitors were likely to visit Durban since they were more conversant with the local conditions. Domestic tourists were likely to visit the destination since they have various mechanisms at their disposal to deal with perceived risks than first-time visitors. Furthermore, the results indicated that tourists are resilient to negative media coverage of risks. The study concludes that several factors influence the image of a destination, so tourist visitation cannot be affected by crises and risks alone. The study recommends a multi-pronged strategy to mitigate the impact of crises and risks on the destinations. Keywords: Risks, Destination sustainability, Destination Competitiveness Dr Taemane Phoofolo Lecturer: Cultural and Heritage Tourism University of KwaZulu-Natal School of Social Sciences Durban, South Africa, 4001 Phone: +27312602404 Email: Phoofolot@ukzn.ac.za Prof. Joram Ndlovu Programme Coordinator: Cultural and Heritage Tourism University of KwaZulu-Natal School of Social Sciences Durban, South Africa, 4001 Phone: +27312607503 Email: Ndlovuj1@ukzn.ac.za http://ertr.tamu.edu/ mailto:Phoofolot@ukzn.ac.za mailto:Ndlovuj1@ukzn.ac.za e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 2 Taemane Phoofolo is Lecturer in the Cultural and Heritage Tourism programme. He has vast experience in teaching Tourism policy and law, Tourism, planning and development, Tourism Events and Representation of Culture and Heritage in Tourism. He completed his PhD at the University of KwaZulu-Natal. He has taught Tourism for a number of years. His research interests are on Disasters and Risks, Sustainable tourism and Conservation. Joram Ndlovu is an Associate Professor in Tourism Management and Coordinator for the Cultural and Heritage Tourism programme at the University of KwaZulu-Natal in the School of Social Sciences. Professor Ndlovu has over two decades of teaching Tourism in different Universities in Southern Africa. He completed his PhD at the University of Pretoria in the Faculty of Economic and Management Sciences. His research interests are on Eco-tourism, Sustainable tourism development, and Tourism marketing. Introduction Tourism is an important industry in many countries worldwide. Many governments prioritise tourism development because it increases foreign exchange income and creates job opportunities (Croucamp and Hind, 2013). Tourism development has an effect on gross domestic product and advances economic growth. However, the tourism sector is vulnerable to many crises, which invariably threaten the sustainability and competitiveness of destinations sought after by travelers. Even though the number of visitors coming to South Africa has been steadily increasing since 2010, serious concerns have been raised about the level of risks affecting the country (Moyo et al., 2013). The study was anchored around literature review and empirical research to unpack the risk situation in the country's eastern coastal city of Durban in KwaZulu-Natal. To conceptualise the study, the protection motivation, mobility, and the model of international tourism decision-making process were used to examine the dynamics of the risk situation in and around the city. The aim of the paper is to discuss the sensitivity of the tourism industry to risks and disasters and the recovery thereof in the aftermath of catastrophes. The study sought to assess the perceptions of the local, regional and international tourists on risks affecting the tourism sector in South Africa, their http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 3 concomitant impacts on their travel decision-making choices, and potential countermeasures against them. Surprisingly, little is known about the nature of 'disaster tourism' and the motivations of tourists to visit a destination during and or in the immediate aftermath of a disaster (Neef & Grayman 2018). There is a paucity of research dealing with risks, crises, and disasters in coastal cities, particularly in South Africa. Therefore this study sought to close the gap through unpacking potential crises and direct research foci in Durban. A lack of comprehensive reviews is not only due to the extensive breadth of the topic area, but also because travel behaviour is generally considered a continuous process that includes varied yet inter-correlated stages and concepts that cannot always be analysed separately (Cohen, Prayag & Moital 2014). Hence this study sought to examine tourist consumer behavior in light of other factors that affect travel consumption decisions, such as disasters and risks. Literature Review The current crisis research is aware of an almost infinite number of possible causes of the crisis, and there are almost as many approaches to categorize them (Uğur & Akbıyık, 2020). There are various classifications and categories of the causes of risks. However, more recently, it has been argued that natural hazards turn into catastrophic events because of a lack of preparedness or inept management. Examples include the 2005 Hurricane Katrina in the Gulf of Mexico, where levees were insufficient to protect New Orleans from flooding, and the 2011 East Japan Earthquake and Tsunami, which caused an enormous loss of human life, destroyed infrastructure on a massive scale, and triggered a long-term nuclear crisis (Neef & Grayman 2018). For instance, the recent pandemic outbreak erupted most likely in Wuhan, China, at the end of 2019. The origin of the novel coronavirus, later labeled COVID-19, is obscure (Bae & Chang, 2020). As a result, COVID- http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 4 19 triggered epidemics and pandemics. The fear of COVID-19 led to significant uncertainty and chaotic conditions in many industries (Uğur & Akbıyık, 2020). Consequently, the pandemic severely affected the tourism industry, resulting in declining revenues. The impact of the pandemic has demonstrated that the tourism industry is extremely vulnerable to numerous factors, such as natural disasters, pandemics, terrorism, uprising, etc. Therefore, tourism-related organisations need to be well prepared in countering and recovery strategies (Shih-Shuo, 2020). The increasing number of people who travel to exotic and distant destinations is influenced by the continually evolving travel behavior of tourists. Individual travel motives are the key elements that represent travel decisions. Due to the increase in the number of destinations, the decision to travel to a particular destination is influenced by factors such as safety and security preferences at the destination. There are two main risk factors that the study considers, namely, dangers associated with the individual's travel itinerary and activities and the epidemics that spread fast and easily due to international tourism. Therefore, it has been argued that tourists are particularly vulnerable to disasters and conflicts because they travel in unfamiliar environments, face language barriers, and are difficult to account for, as they have insufficient connectedness with local communities and information channels (Neef & Grayman 2018). Health risks become an essential element that influences tourists’ perceptions. Tourists who perceive certain risks are likely to be more cautious and minimise health risks associated with certain travel behaviours. Studies have shown that the impacts of 9/11 and Hawaii disaster resulted in a decline in international travel, which was easily offset by domestic tourism. Similarly, a study that The Asian Development Bank conducted in 2015 found that tourism shifted from Vanuatu to http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 5 Fiji following the 2015 Cyclone Pam, while a reverse trend was observed in the aftermath of 2016 Cyclone Winston that devastated parts of the Fiji Islands (Neef & Grayman, 2018). Natural disasters tend to invoke greater public understanding, empathy, and tolerance among potential tourists, while terrorist attacks may have a more intimidating effect (Kaushala & Srivastava, 2021). On the contrary, disasters such as earthquakes, hurricanes, or even nuclear accidents can lead to serious public health implications and environmental impacts, which can scare tourists for a very long time. For instance, after the volcanic eruption in Hokkaido in Japan, tourism operators and government officials used previous experiences to preserve volcanic debris as 'disaster heritage,' which was used as the basis for harnessing the international geopark movement to build social capital and develop new management and marketing approaches. In the wake of tourism disasters, some scholars claim that marketing campaigns can foster recovery and restore the destination's positive image (Ferreira, 1999; Ferreira et al., 2000). However, the challenge is aligning effective marketing strategies with restoring tourists' confidence and security. For instance, a study by Rittichainuwat in 2013 on risk perceptions of foreign tourists in southern Thailand found that perceived beach safety hinged upon the availability of a tsunami evacuation system and crisis management plans (Bae & Chang, 2020). Ferreira (1999) argues that tourism requires a critical partnership with safety so that it can succeed and be sustainable. This is informed by the fact that leisure travelers, in particular, undertake travelling willingly and are not prepared to spend their hard-earned money in destinations with low levels of safety. The same applies equally well to business tourists. Ferreira (1999) contends that the country, therefore, has a 'herculean' task in terms of addressing these risks. Factors that lead to crime in the country are political intolerance (various ethnic groups, different http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 6 languages, and religions); the legacy of apartheid (which stirs up emotions and resentment amongst many people); the proliferation of firearms; high unemployment; socio-political instability and the prevailing culture of solving problems violently (ibid, 1999; Ferreira et al., 2000). Image is the most important element of a tourist attraction. It influences the destination's marketing initiatives when looked at through the lens of a visitor's buying behavior. Crime is a key concern for the South African government. It is notable for the level of violence associated with personal/property crime, as criminals do not hesitate to use lethal weapons, and the occurrence of crimes across all metropolitan areas regardless of the socioeconomic status of a particular neighborhood. Crime has various manifestations. Perry et al. (2013) and South African Cities Network (2016) highlight the following forms of crime as more prevalent in the country: petty muggings, ATM scams, armed residential home invasions, and murder, and violent crimes such as robberies, burglaries, car hijackings, street muggings, smash- and-grabs, organised attacks on commercial centers (shopping malls and outlets), and attacks on cash-in-transit vehicles/personnel (armoured car/personnel). Another serious form of crime is rape, and both the locals and foreigners fall victim to it. Financial and identity theft crimes are common in the country (South African Cities Network, 2016), and they comprise, inter alia, debit/credit card, and advance-fee scams. Many businesses (restaurants, petrol stations) have portable credit card facilities that allow customers to swipe their cards when making purchases. These cards are frequently cloned, giving rise to fraudulent transactions despite some built-in safeguards mechanisms. Some Automated Teller Machines (ATMs) are also fitted with skimming devices or have at their disposal what looks like a “helpful person” who offers to assist those in need of help. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 7 Criminals are also adept at bombing ATMs during the early morning hours in remote areas (ibid, 2016). While there is probably no controversy around the argument that tourism flourishes in a peaceful environment, it is hard to prove a direct causal relationship between a successful tourism sector and peaceful conditions in a country (Neef & Grayman 2018). Hence, there is debate on whether communication and learning processes can take place at an intensity that can overcome political, socioeconomic, and cultural differences and build bridges between and within countries. However, there is agreement among scholars that most tourists avoid destinations that are prone to conflict and are politically unstable (Lone & Ahmad, 2020). Tourists do not want to be caught in a crossfire or missile attack in a civil war or cannot risk being kidnapped by a separatist rebel group. A small segment of tourists are interested in vacationing in danger zones, such as solidarity tourists who partake in a conflict, activist tourists, or intrigued tourists. Dealing with crises is not uncommon for companies in the tourism industry since almost every tourism company is faced with extraordinary events over time, but the occurrence of tourist crises often leads to a loss of safety consequences (Uğur & Akbıyık, 2020). Hence crises have serious impacts on individual traveler’s behaviour and the whole travel behaviour process. The Decision-Making Behavior of Tourists Tourists follow a certain pattern in making destination choices. The tourists’ decision-making behavior is influenced by their behavior. The behavior is related to four stages namely, tourist http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 8 motives, information collection, analysis, the final decision, and evaluation. The diagram below shows the model for the tourist decision-making process. Source: Nuraenia, S., Arrub, P.B., and Novanic, S. 2014. The above diagram shows that the decision to visit a particular destination starts with personal features and preferences. Tourist motivation is the internal demand, and external stimulation influence the tourist motives. The travel information source, information cost, and information technology are applied to tourism information gathering analysis and then affect travel decisions. The psychological expectation before travel is a subjective desire of tourists and requirements, which has a very important influence on travel decisions (Cohen, Prayag & Moital 2014). The tourism literature indicates that travel motivations underlie travellers’ decision-making processes and are key triggers of purchasing behaviours (Seyidov & Adomaitienė, 2016; Chavez, Ruiz, Curras, and Hernandez, 2020). However, while travel motivations have emerged as an influential factor that affect tourists' post-purchase behaviours, their impact is not homogenous, given the http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 9 diversity of tourism activities and destinations. The IRMSA Risk Report (2015) contends that travelers’ perception of risks is shaped by a wide range of factors such as actual victimisation and first-hand experiences of crime and violence; impressions and opinions of the city environment; interaction with colleagues, friends, and family; perceptions about the government's ability to provide safety; and the extent to which the tourists feel helpless against risks. Methodology A mixed-method approach was used to unpack several issues concerning the tourists' perspectives on risks and their perception of Durban as a tourism destination. A qualitative approach was used to unpack the subject matter on the disaster, crises, and the risk-fear nexus and how the tourists perceive Durban as a tourism destination. The data collection tools were constructed based on the collection of textual data sets referred to as the basic text mining process. At this point, structured or semi-structured texts were obtained from sources such as documents, web pages, social media, and user/consumer comments (Uğur & Akbıyık, 2020). The next stage was the data transformation phase where text was filtered in a structured way. In this way, words in the text set were analysed in terms of frequency and occurrence. The last stage was the data conversion process; topics and contents within the scope of information extraction were determined. A Likert scale type of questionnaire was then drafted. It carried a number of statements dealing with a common theme, and the research subjects were asked to show their degree of either agreement or disagreement on a five-point scale. Semi-structured interviews augmented the approach. A pilot study was conducted to determine if the survey, key informant interview guide, or observation tools would work in the "real world" by trying it out first on a few people. Similarly, http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 10 to conduct this study, the researcher adopted a style largely allied to the recommendations of other tourism research scholars in respect of conducting this type of interview. The questions asked were standardised, and probes were provided to ensure that the correct material was covered. The purpose was to ensure that everyone in the sample understood the questions the same way. Data collection The data was collected mainly by using a Likert scale questionnaire which carried some statements dealing with certain specific themes. It enabled the interviewees to express their degree of agreement or disagreement on a five-point scale, which ranged from extremely low risk (represented by 1) to extremely high risk (represented by 5). The questionnaires were administered to tourism experts and the tourist themselves. The study involved five tourism experts in Durban. The snowballing technique was used to select the participants. The study was worth undertaking as it enabled the researcher to identify some ambiguous questions and those which were correctly phrased and well understood. Therefore, those which were not clear were corrected henceforth. The pilot study, therefore, assisted in defining the research question and testing the reliability and validity of the study design. Sampling The sample comprised 399 tourists who visited Phezulu Cultural Village, Cabana Beach Resort, and Botanical Gardens in Durban. It drew samples that were accessible and willing to participate in a study. The technique proved useful when randomization was impossible due to a large population and when the researcher had limited resources, time, and workforce (Etikan et al., 2016; Teddlie et al., 2007; Farrokhi et al., 2012). The specified number of tourists was obtained from http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 11 each specified tourist site but with no randomization of unit selection. Researchers collected a quarter of the data telephonically from the management of the above sites. The sites were chosen because of their popularity and geographical proximity. They tend to attract many tourists per week in KwaZulu-Natal. Their responses were cross-checked and validated against those derived from the tourism experts to attain refinement and ensure reliability. The use of a mixed-method design ensured that data collection became complete, balanced, and trustworthy. Since some researchers consider a sample size of 15 to 20 interviews as appropriate for saturation to be reached (Given, 2008) when using a qualitative approach, for this study, researchers reached a saturation level after interviewing 15 key informants in Durban. Data analysis Questionnaires were completed by senior managers in the tourism sector in Durban and the tourists. The study evaluated tourists' social perspectives on crime, which affects Durban, and the subsequent countermeasures that could be adopted to deal with criminality. It included risks such as financial, psychological, time costs, health, crime, injury, and death. The tourists' personal, social, and commercial cues were also investigated. The main reason why the variables listed above were investigated was, as advanced by Sonmez and Graefe (1998), that risks, in general, have received little research attention because they have been treated as facilitators versus inhibitors or constraints. A pilot study was conducted to determine the feasibility of the study. The data collected was analysed using the Statistical Packages for Social Sciences (SPSS) to replicate and speed up some of the more mechanical aspects of the manual processes (Veal, 2011; Sofaer, 2002; Cramer, 2005). Findings http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 12 Demographic characteristics of the tourists The research respondents’ demographic characteristics had a direct bearing on the subsequent tests done depicting the risk factors influencing travelling in Durban. Therefore, the presentation of demographic factors can assist in the understanding of relationships between the variables probed and enhance clarity and conciseness. The following table shows the demographic characteristics of respondents. Table 1: Demographic characteristics of respondents. Characteristics Category Frequency Percentage % (N=399) Gender Male 160 40.10 Female 239 59.90 Total 399 100.00 Age under 20 years 53 13.28 20-39 years 239 59.90 40-49 years 58 14.54 50-59 years 42 10.53 60-69 years 6 1.50 above 69 years 1 0.25 Total 399 100.00 Marital Status Married 76 19.05 Single 288 72.18 Divorced 15 3.76 Widowed 12 3.01 Other 8 2.01 Total 399 100.00 Level of education No schooling 24 6.02 Primary 16 4.01 Secondary 110 27.57 Tertiary 249 62.41 Total 399 100.00 Country of origin Local 266 66.67 Regional (including the rest of Africa) 90 22.56 International 43 10.78 Total 399 100.00 Occupation General worker 81 20.40 Retired/Pensioner 13 3.27 Self-employed 57 14.36 Unemployed 194 48.87 Other 51 12.85 Missing 3 0.25 Total 399 100.00 http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 13 The 399 specified number of tourists were obtained from different sites without randomization of unit selection. The majority questionnaires were administered to tourists who were females (59, 90%) and males (40, 10%). The uneven number of participants was influenced by samples that were accessible and willing to participate in the study. Hence the technique proved useful when randomization was impossible due to a large population, particularly when the researchers had limited resources, time, and workforce. The age of participants ranged from 20 to 69 years. The dominant age group was those who were between 20 to 39 years (59, 60%). As far as their marital status was concerned, most of the respondents were single (72, 18%). A high proportion of the travelers had a secondary (27, 57%) and a tertiary qualification (62, 41%). In terms of their country of origin, the majority were locals (66, 67%), followed up by the regional tourists who included those from the rest of Africa (22, 56%) and international visitors (10, 78%). Perceived common risk factors in Durban It depicted the frequency of occurrences of values within a particular group or interval. The tourists were asked to rate risks (socioeconomic /environmental/political and personal) on a 1-5-point Likert scale for the prevalence of the risks associated with travelling in Durban. Table 2 (Percentages for common risk factors by tourists visiting Durban destinations), therefore summarised how the values in the population sample were distributed. Table 2: Percentages for common risk factors by tourists visiting Durban destinations Risk factor N Extremely low risk (%) Low risk (%) Moderate Risk (%) High risk (%) Extremely high risk (%) Socioeconomic/environmental/political risk factors Xenophobia 399 15.29 12.78 25.81 23.56 22.56 War 390 25.38 21.79 26.41 16.92 9.49 Terror 381 29.40 19.95 25.98 15.75 8.92 http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 14 Poor infrastructure 393 19.08 14.25 29.52 22.90 14.25 Security 393 11.96 23.92 27.74 20.61 15.78 Poor service delivery protests 399 12.28 13.53 21.30 26.07 26.32 Airport safety 389 22.22 20.71 28.54 17.93 10.61 Port safety 389 18.25 5.58 12.18 23.35 50.51 Crime 394 8.38 5.58 12.18 23.35 50.51 Pollution 392 9.44 11.73 21.43 27.30 30.10 Health systems 393 7.38 11.96 28.50 26.21 25.95 Political instability 388 6.44 5.67 21.39 28.09 38.40 Earthquakes 395 34.18 21.01 26.84 10.63 7.34 Poverty 396 6.82 6.82 15.15 25.00 46.21 Unemployment 396 5.30 5.30 10.61 23.74 55.05 Decaying municipal infrastructure 391 10.74 13.30 29.92 27.88 18.16 Floods 397 20.40 14.86 20.40 28.21 16.12 Drought 398 14.82 12.56 26.88 26.63 19.10 Diseases 396 11.87 7.83 19.19 22.22 38.89 Economic risk factors High transport costs 397 35.52 19.14 22.17 11.34 11.84 High commodity prices 395 32.91 23.54 25.57 9.62 8.35 Negative exchange rate 396 19.19 34.09 29.04 10.10 7.58 Low economic growth 395 31.65 29.37 21.27 10.89 6.84 Export leakages 392 21.17 22.96 38.27 11.48 6.12 Import leakages 396 27.27 23.74 31.82 11.11 6.06 Stiff competition 394 26.65 26.90 29.19 11.68 5.58 Lack of funding 395 37.47 26.33 18.48 8.86 8.86 Economic dependence of locals on tourism 396 25.25 28.03 27.78 13.13 5.81 High taxes 394 36.04 23.86 24.87 8.88 6.35 Theft 397 48.61 18.14 16.12 7.05 10.08 Labour instability and strikes 395 43.80 22.78 16.71 9.11 7.59 Corruption 397 65.24 19.40 8.06 3.02 4.28 Personal risk factors Death 399 28.57 16.54 23.81 19.55 11.53 Personal injury 395 20.25 31.14 25.82 17.72 5.06 Assault 396 35.35 26.77 18.43 11.87 7.58 Loss of personal belongings 396 28.28 30.30 22.22 12.12 7.07 Housebreaking/robbery 397 34.01 28.46 19.65 9.32 8.56 Street robbery 398 37.69 29.65 18.34 6.53 7.79 Car hijacking 397 36.02 28.97 18.89 7.81 8.31 Rape 399 34.09 24.56 19.30 13.78 8.27 Socioeconomic/environmental/political risks The perceptions and the ratings of the regional and international travelers were in line with mobility theory as postulated by Cohen and Cohen (2012), which regarded safety and security as key prerequisites to sustainable tourism. The theory asserts that tourists' perplexity can be sparked http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 15 by the prevalence of human-made disasters such as xenophobia, terrorism, and natural disasters. Socio/environmental/political risks that were considered to be extremely low included war (25.38%) and terror (29.40%). Those that constituted moderate risk included xenophobia (25.81%), poor infrastructure (29.52%), security (27.74%), airport safety (28.54%), health systems (28.50%), earthquakes (26.84%), decaying municipal infrastructure (29.92) and drought (26.88%). Floods (28.21%) were seen as a high-risk factor. This problem is exacerbated by the tropical cyclones originating in the warm Mozambique Channel. They pose a threat to the port as they unleash violent storms and rain along the coast. The cruise ships, as well as the beach users, are most likely going to be affected by this scenario. Factors that were perceived to be high risk included poor service delivery protests (26.32%), port safety (50.51%), crime (50.51%), pollution (30.10%), and diseases (38.89%). The study reinforced the assertion of Adeleke et al. (2011), who maintain that most tourists consider safety when choosing a vacation destination. An unsafe destination invariably acts as a push factor that repels them. The opposite holds for a safe destination, which attracts more tourists. Among the local and regional tourists, crime elicited a mode response of 5, which amounted to extremely high risk. The following realities could inform the tourists' ratings: Firstly, local and regional travelers could have become actual victims of crime in the country. Secondly, the tourists could have first-hand experiences of crime and violence and the ability of the government to provide safety and security. Therefore, if tourists perceive a particular destination to be crime-infested and unsafe, then they will avoid visiting it. Other extremely high factors included political instability (38.40%), poverty (46.21%), and decaying infrastructure (55.05%). Political instability is another variable that deserved attention in Durban's disaster, crises, and risk- fear nexus. There is a high level of political instability which characterises the political landscape http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 16 in the city. Unfavorable policies of the government may force risk-averse tourists to undertake their travelling elsewhere. Several factors may lead to an unfavorable political rating by the tourists. The classic examples include inter-party political rivalry; the “greed for power and economic wealth” (South African Cities Network, 2016); high unemployment; escalating food and commodity prices; inequalities between the rich and poor; disenfranchisement with the rule of the local government; political corruption and low social cohesion (IRMSA Risk Report, 2015). Economic risks Regarding the economic factors, the tourists' reactions vacillated mainly between extremely low risk and moderate risk. The main examples of these extremely low-risk economic factors included high transport costs (35.52%), high commodity prices (32.91%), and lack of funding (37.47%). Negative exchange rates (34.09%), low economic growth (29.37%), and economic dependence of locals on tourism constituted low risk (28.03%). Export leakages (38.27%), import leakages (31.82%), and stiff competition (29.19%) constituted a moderate economic risk. The findings indicated that, conversely, the travelers were less likely to be deterred from travelling to Durban by economic factors. Personal risks In so far as the personal risk factors were concerned, there were no statistically significant responses offered by the tourists. The results could be ascribed, but not limited, to the following practical rationales: firstly, the tourists did feel that issues like death (28.57%), injury, assault (35.35%), housebreaking/robbery (34.01%), street robbery (37.69%), car hijacking (36.02%) and rape (34.09%) were difficult to avoid. Secondly, personal injury (31.14%) and loss of belongings http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 17 (30.30%) can affect anyone at any given time. Therefore, tourists felt that one could just learn how to be resilient to risks. The results corroborated the assertion of Saha et al. (2014), who argued that tourists might adopt what is called "inward-oriented rationalization," a strategy whereby tourists reduce the perceived risks prevailing in any destination by emphasising the provision of security and safety, or an "outward-oriented rationalization," whereby they stress that risks occur anywhere and anyone can be a potential victim. To sum up, the tourists' responses seemed to be statistically insignificant as they felt that the personal risk factors were unavoidable. The Kruskal-Wallist test for risk factors The Kruskal-Wallist test is a rank-based nonparametric test that can determine if there are statistically significant differences between two or more groups of an independent variable on a continuous or ordinal dependent variable (statistics.laerd.com). This study used this test to compute, quantify, and compare the mean responses of tourists by their country of origin to assess the null hypothesis. H0: There was no statistically significant difference between the mean responses on risk factors by local, regional, and international travelers in Durban. The results were captured as illustrated by the table below: Table 3: Kruskal-Wallis Test for risk factors Risk factor Observations Rank Sum Chi-square H-Statistic with 2 df Probability Socio/environmental/political risk factors Xenophobia South African 266 53063.00 Regional 90 17993.00 0.505 0.7639 International 43 7912.00 War South African 259 49718.50 Regional 89 17888.00 0.808 0.6675 International 42 8638.50 Terror South African 254 46972.00 Regional 85 17174.50 2.341 0.3103 http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 18 International 42 8624.50 Poor infrastructure South African 262 50543 Regional 88 17931 1.286 0.5257 International 43 9036 Security South African 260 51476 Regional 90 17871 0.322 0.815 International 43 8073 Poor service delivery South African 265 50666.00 Regional 90 19301.00 3.691 0.1580 International 42 9036.00 Airport Safety South African 265 51392 Regional 88 17506 3.786 0.1506 South African 43 99707 Port Safety South African 259 47677 Regional 88 17983 10.618 0.004*** International 42 10194 Crime South African 263 53523 Regional 89 16607 2.233 0.1506 International 42 7684 Pollution South African 260 50616.00 Regional 89 16289.00 2.233 0.3274 International 43 10123.00 Health Systems South African 263 50851.00 Regional 89 17700.50 1.483 0.4764 International 41 8869.50 Political Instability South African 261 49599 Regional 87 17503 1.401 0.4964 International 40 8364 Earthquakes South African 263 48122.50 Regional 89 19696.00 14.551 0.0007*** International 43 10391.50 Poverty South African 263 50698 Regional 90 18231 3.086 0.2137 International 43 9677 Unemployment South African 264 53320 Regional 89 16546 1.436 0.4877 International 43 8539 Decaying municipal infrastructure South African 261 50391 Regional 88 18093 0.823 0.6628 South African 42 8151 Floods http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 19 South African 266 52351.50 Regional 88 17512.50 0.695 0.7064 International 43 9.139.00 Drought South African 265 53328 Regional 90 16826 1.921 0.3826 International 43 9248 Diseases South African 264 53391 Regional 89 17661 1.994 0.3690 International 43 7553 Economic Risk factors High Transport Costs South African 264 52170 Regional 90 18296 0.165 0.9208 International 43 8537 High commodity prices South African 262 53583 Regional 90 16763 2.536 0.2814 International 43 7594 Increased infrastructure cost South African 262 51872 Regional 90 17838 0.001 0.9997 International 43 8499 Negative exchange rate South African 265 53463.50 Regional 89 17345.00 0.831 0.6600 International 42 7797.50 Low economic growth South African 263 54645.50 Regional 89 16368.00 6.381 0.04*** International 43 7196.50 Export leakages South African 263 53790.00 Regional 87 15210.50 4.595 0.08 International 42 8027.50 Import leakages South African 265 52755 Regional 90 17602 0.008 0.9570 International 41 8248 Stiff competition South African 263 51428 Regional 90 18024 0.263 0.8709 International 41 8362 Lack of funding South African 264 51096 Regional 89 19344 3.502 0.1736 International 42 7770 Economic dependence of locals on tourism South African 263 54250 Regional 90 16763 3.821 0.1480 International 43 7592 High taxes South African 264 53667 http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 20 Regional 89 17124 2.250 0.3246 International 42 7418 Theft South African 265 52435.50 Regional 89 18309.50 0.489 0.7830 International 43 8258.00 Labour instability and strikes South African 263 53024 Regional 90 18006 2.652 0.2655 International 42 7179 Corruption South African 264 53588 Regional 90 17102 0.974 0.6143 International 43 8313 Personal risk factors Death South African 266 53813.50 Regional 90 17367.00 0.442 0.8018 International 43 8619.50 Injury South African 263 54864.00 Regional 90 15766.00 6.856 0.03*** International 42 7580.00 Assault South African 264 54763.50 Regional 89 15595.00 5.437 0.05*** International 43 8247.50 Hypothesis test H0: There was no statistically significant difference between the mean responses on risk factors by local, regional, and international travelers in Durban. In short, the null hypothesis stated that the population medians were all equal. In this Kruskal-Wallis test, we computed and compared means responses of tourists by origin (i.e., with p-values significant at 95% significance level) to assess the null hypothesis. As a default setting, a significance level (denoted as α or alpha) of 0.05 indicated a 5% risk of concluding that a difference existed when there was no actual difference. If the H-statistic was below 0.05, we rejected the null hypothesis and concluded that there was 95% chance that at least tourists had statistically significant differences in their perceptions of risks. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 21 The results in table 4 present the H-statistic with a subsequent chi-square distribution with k-1=3-1=2 df (degrees of freedom). Thus, we can reject the null hypothesis at the .05 level and state that South African, regional, and international tourists are significantly different in their opinion of key risk factors to consider when travelling to Durban. For instance, there is a significant difference in regard to personal risk factors (i.e., assault (H=5.437), 2 df, p=0.05 and injury (H=6.856), 2 df, p=0.03 among tourists as well as socio/environmental/political risk factors, such as low economic growth (H=6.381) 2 df, p=0.04, port safety (H=10.618), 2 df, p=0.004 and earthquakes (H=14.551), 2 df,p=0.0007, respectively. Table 4: Pearson Chi-square statistics for the association between source of information and origin of tourist Source of Information South African Regional International Degrees of freedom with 2 df X2 Pearson’s Chi-Square Statistic Probability Media 215 72 36 4 0.7912 0.940 Travel agents 148 51 21 4 1.4521 0.835 Tour Operator 151 53 21 4 2.6739 0.614 Forecast 133 43 29 2 4.9089 0.08 Friends and relatives 216 76 40 2 3.2686 0.195 Law enforcement agencies 186 57 30 2 1.3987 0.497 Crime statistics 177 59 24 4 2.5930 0.628 Tourists 163 57 25 4 0.7539 0.945 Complains 158 50 20 2 1.9175 0.383 In loco 136 43 19 2 0.7204 0.698 Home affairs 165 46 43 2 3.6736 0.159 Embassies 139 50 28 2 2.4079 0.300 Department of Trade and Industry 152 45 21 2 1.8940 0.388 IGP 189 56 29 2 1.7568 0.415 South African Police Service 203 68 36 2 1.0797 0.583 National Department of Tourism 184 63 28 2 0.4388 0.803 Word of mouth 221 72 33 2 1.0827 0.582 The results in the Table above showed no statistically significant relationship between the type of preferred source of travel information to Durban and the origin of tourists. However, there is a http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 22 clear trend towards significance in the relationship between the origin of the tourist and relying on political and economic forecasts for information regarding risks in Durban (chi-square with 2 degrees of freedom = 4.9089, p = 0.08). Discussion and implications In line with the Model of International Tourism Decision-Making Process, which Sӧnmez and Graefe postulated in 1998, tourists' ability to gauge the safety of a destination is influenced by variables such as past travel experience, perception of risk, and many demographic factors. For instance, those tourism destinations perceived to be risky may be substituted with those perceived to be safer. The model maintains that the tourists' perceptions of what constitutes a safe destination can be influenced by various factors, which can impact visitation to a destination. In Durban, crime was perceived to be extremely high. These perceptions could affect mostly the first-time visitors who are sensitised by the media with regard to its prevalence in the city. The study revealed that repeat visitors are more resilient to crime as they devise their mechanisms to deal with criminal activities and are well conversant with the local conditions. The study further revealed that many factors influence tourists' destination choices, so their visitation cannot be affected by crime alone. According to Korstanje (2011), the Risk Perception Theory supports how tourists determine risk, for instance, tourists' nationality and their psychological personality, and those with a higher sensation (sensation seeking) tend to experience fewer risks and travel more than those with a lower degree of sensation seeking. Risk perception has been discussed as an essential component http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 23 in predicting health behaviours; individuals who perceive a particular risk are assumed to engage in more preventive health behaviours to avoid or minimize health risks (Bae & Chang, 2020). The theory presumes that tourists face their own risks when selecting the destination for their holidays and transport modes. For instance, findings by Christopher, Craig, Ma, and Karabas (2021) suggest that camping consideration due to COVID-19 is significantly related to an understanding of time and distance of travel and is dependent on the pandemic scale. Thus, the theory deals with issues of fear, anxiety, and tourists' expectations. Risks manifest themselves in the form of terrorism, crime, natural disasters, road accidents, diseases, or delays in flights (Floyd and Pennington-Gray and Thapa, 2004; Hall, 2002; Banyai, 2009). According to Buys (2005), the local strategies for communicating and making the general public aware of disasters, crises, and risks and available risk reductions options are in most cases very poor, even in the presence of advanced technological devices, which expedite the extreme accurate prediction, forecasting, and monitoring of severe weather conditions in Durban. For instance, Tempelhoff et al. (2009) argued that the vulnerability of the tourism sector is exacerbated by a lack of the following variables: sufficient early warning systems; proper infrastructure maintenance; local institutions to deal with disasters, [crises and risks]; and a comprehensive understanding of the disaster risk profile of the area in question. There are several categories of risks in Durban, namely, socioeconomic, environmental, political, and personal. According to Austin (2008), droughts are endemic in Durban. They are a product of a complex array of biophysical and socioeconomic variables. These factors http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 24 cumulatively heighten the risk-fear factor amongst the tourists and yield diverse impacts, which include but are not limited to death, destruction of property and tourism infrastructure, human displacement and suffering, low economic growth, the proliferation of arms, cross-border flow of illegal goods and services (Bae & Chang, 2020). Perry et al. (2013) concur that actual crime, as well as the perception thereof, adversely impacts the well-being of the vast majority of South Africans and naturally impacts major economic sectors such as tourism. George (2010:577) substantiates the author's opinion by the following remarks: "Although crime against tourists is not a new phenomenon, the researchers had difficulty linking crime to the demand for tourism" and adds that "the collection of valid and accurate data to measure crime is near impossible and prevents researchers from providing substantial evidence that directly links crime rates to tourism demand." South African Cities Network (2016) argues that even though there are many important social, economic, and political changes that have occurred in the country since the advent of formal democracy in 1994, there is a myriad of significant factors that continue to cause political violence in South Africa, and they are, the effects of colonialism and institutionalised apartheid. Croucamp et al. (2014) argue that globally terrorist attacks surely hurt tourism, maintaining that, more often than not, it is the frequency rather than the severity of the terrorist act which impacts the tourists' decisions to visit that specific area. Crises and high-risk factors can potentially destroy the country's social and cultural image, tourism functionality, sustainability, and the destination's competitiveness. The study shows that negative tourists' perceptions of a destination can adversely affect their decisions to visit Durban. Soyombo (2011) holds that xenophobia can http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 25 be shown in various ways, that is, verbally, by inciting speeches and discussions, or it can be exhibited when some people leave their place of abode or communities as soon as they notice the foreigners moving in that community. This points to a need to devise multi-pronged marketing strategies to arrest the impact of risks on the destination. More ongoing research needs to be conducted to redefine the tourists' perceptions of the city and the multiplicity of factors affecting tourists' movement in the country. Conclusion There are several categories of risks in Durban, namely, socioeconomic, environmental, political, economic, and personal. The results showed that port safety, crime, and political instability were extremely high risks, while personal risk factors such as loss of personal belongings and street robbery elicited low ratings. Furthermore, crime and its various manifestations, which comprise, among other things, hijackings, murder, violence, home invasions, and cash-in-transit heists, were perceived as high risk, followed by political instability. Xenophobia can be exhibited in various ways, that is, verbally, by inciting speeches and discussions, or it can be exhibited when some people leave their place of abode or community as soon as they notice the foreigners moving into that community. These factors cumulatively heighten the risk-fear factor amongst the tourists and yield diverse impacts, including but not limited to death, destruction of property and tourism infrastructure, human displacement and suffering, low economic growth, the proliferation of arms, and cross-border flow of illegal goods and services. Crises and high-risk factors can potentially destroy the city's social and cultural image, tourism functionality, sustainability, and the destination's competitiveness. The study shows that negative tourists' perceptions of a destination can adversely affect their decisions to visit Durban. However, repeat visitors and domestic tourists http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 19, No. 1, 2022 http://ertr.tamu.edu 26 were likely to visit Durban since they were more conversant with the local conditions and have various mechanisms at their disposal to deal with perceived risks than first-time visitors. However, the results indicated that tourists are resilient to negative media coverage of risks and that many factors influence the image of a destination. Hence observations showed that perceptions are not cast in stone but evolve over time. The study recommends a multi-pronged strategy to mitigate the impact of crises and risks on the destinations. Considering that tourist decision-making process in disaster-risk discourses is a complex issue, further studies should focus on conducting multiple studies that consider diverse tourists' exposure and vast experiences with disasters, crises, and risks. References Adeleke, B.O., Amitola, A.A. & Olukole, T.O. 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