Attitudes and Behaviour towards More Sustainable Travel Options in the Kingdom of Saudi Arabia: An Emerging Social Change?

Abstract

The Kingdom of Saudi Arabia (KSA) is known for its high car ownership and usage and its high GDP per capita. This, combined with a low provision of public transportation (PT) systems, has resulted in perceptual attitudes of high dependency on private car travel. The level of awareness of the benefits of reducing car use and increasing travel by more sustainable options has a great impact on social change and behaviour. The Kingdom is currently progressing towards a new phase of “national reform” through implementation of strategic sustainable programs. Riyadh city is constructing a massive metro-system, which is nearing completion and operation. The public is aware of the national agenda, the construction of transportation projects, and of the social changes needed to realize the new vision of the country. This paper aims to assess travel behaviours and attitudes of Saudi nationals towards public transportation. A discrete choice model of the intent to use public transportation is calibrated as a function of social and attitudinal factors, using online survey data. The analysis was carried out using an ordered logit model (OLR) which is derived from the theory of random utility. The results show that, overall, a higher support for public transportation modes was stated by young females, lower income groups, and university graduates. The level of awareness of the national agenda appears to be increasing the level of support for public transportation. The paper is the first investigation of willingness to use public transportation in Riyadh, at a crucial time of national reform; the choice of mode of travel appears to be determined by the travellers’ social and economic characteristics and the level of awareness of the country’s agenda.

1. Introduction

Travel attitudes in the Kingdom of Saudi Arabia (KSA) have become centred on the private car. This is a result of the very high car ownership and use in the country, the high GDP per capita, and the low or non-provision of public transportation options. There are very limited bus services in most KSA cities, and they are mostly used by the very low-income classes of expatriates. In addition, in most Saudi cities, riding public transportation is culturally not adequate, while car travel has become the normal travel option. Even low-income Saudi families, who do not own private cars, rely on contracted drivers or taxis for their travel rather than using public transportation. This is a major phenomenon that needs further consideration, given the KSA’s population, size, and the national vision 2030.

With the new national vision 2030, the city of Riyadh is constructing several public transportation options including a substantial metro system, costing a massive $22.5 billion, to encourage more sustainable travel patterns. The local population are aware of the newly constructed public transportation options through witnessing the construction work and traffic delays. They are also aware of the proposed routes and conscious about the possibilities of their use.

Such developments are expected to not only result in changes in the KSA’s social travel behaviours and attitudes towards the use of public transportation systems, but also to result in enhancing tourist activities, meeting the international environmental targets, and achieving sustainable societies.

Transportation is an important component in encouraging mobility, societal progression, and tourism, which is one of the main components of the global economy. There are very clear, multifaceted, and matching associations between transport and tourism, in both productive and destructive ways. An increase in tourism would lead to increasing traffic congestion, which will correspondingly have negative impacts on safety and the environment of the urban areas. On the other hand, transport is a crucial component in the tourism industry that is accelerating and constraining the development of tourism [1]. A good transportation system significantly facilitates tourists’ travel activities from one location to another. Therefore, encouraging more sustainable and efficient transportation systems can contribute to easing some of their negative effects. Impacts of transportation enhancement on tourism industries have been observed and contemplated in the enrichment of tourism activities [2]. They support the idea that the transportation systems of a place have impacts on the tourism experience that can affect the choice of the tourist destinations and the duration of visits. The dynamics of transport and tourism relationships have been assessed and presented [3]. For example, in the absence of public transportation options, tourists will have no choice but to use private transport. In a country that has just started to encourage tourism such as the Kingdom of Saudi Arabia, supporting the construction and use of public transportation options is a very important obligation and a success factor for achieving more efficient mobility, tourism, and sustainability.

Whilst public transportation options were neither adequate nor acceptable in the past by the Saudi nationals, it is hoped that, in the new era, things will improve and a shift towards more sustainable options of travel will be encouraged. Without a real social change, the newly constructed systems will deteriorate, the level of service will decline, and the newly built transportation systems will become redundant, an infrastructure burden, and a waste of investment.

Social change occurs because of changes in population volumes, population composition, culture and technology, awareness about benefits or disbenefits, and environmental and natural changes. In the case of Saudi Arabia, social change is happening because of advancements in industrial and environmental technologies, higher awareness of the population of the benefits of the more sustainable options, and the growing population exposure to other societies and communities. In this paper, we attempt to assess the overall impact of changes in attitudes and behaviours towards travel choices in the city of Riyadh.

The paper is structured as follows. Section 2 provides an overview of relevant previous literature on modal choice models, travel choice studies, previous studies on travel behaviours, and attitudes in Riyadh and other neighbouring cities/countries. The methodology is presented in Section 3, including the experimental design and the ordered logit model. Analysis of the survey results is presented in Section 4. The results of the ordered logit model are discussed in Section 5. Discussions of the results and conclusions are presented in Section 6 and Section 7. The limitations of the study are discussed in Section 8.

2. Previous Literature

2.1. Modal Choice and Travel Behaviour Studies

Modal choice modelling and choices between public transport and private transport are very relevant and influential parts for the understanding and prediction of future travel behaviours [4,5,6]. Theories of social science have also been developed and used heavily to understand and assess travel behaviours [7,8,9,10]. There are many studies in transportation planning processes that have applied both travel behavioural and social science theories [7,8,9,10,11,12,13,14,15,16,17].

In traditional modal split studies, the market would be divided mainly between private and public modes of travel. These models are presented as S-shaped curves, and appear to characterise the relationship between the cost difference and the proportion of trips made by each option that were essentially functions of one or two characteristics of the trips such as vehicle travel time or cost [18,19,20,21,22]. The components of the cost difference between the two options have been developed since to include qualitative and quantitative level of service, social, attitudinal, and behavioural factors.

Travellers assess the available travel options based on their cost functions and select the option that maximises their utilities [23,24]. There are the captive travellers, however, who are either those captives to public transportation (where they do not have access to a car) or those who are captive to the car. The captives to the car are those travellers who do have access to private cars but not to public transportation options because they live far from them for example or do not perceive public transportation as a feasible option of travel, as is the case in most of Riyadh’s residences. On the other hand, in most low-level of income countries, there are more “captives” to public transportation options than to private cars.

2.2. Modal Choice and Travel Behaviour Studies in High Income Countries

In higher income cities and countries that have specific cultures, captivity to the private car is experienced. For example, in the city of Riyadh and most cities in the KSA, almost all travellers are captives or confined to their private cars rather than being choosers between the private and public options of travel. This is a result of the relatively high-income levels in the country, very high level of car ownership, and the very low level of provision of public transportation or, in some cases, the complete lack of it. This, in addition to the cultural norms of not accepting riding on public modes of travel, makes it a big challenge to expect travellers in these cities to use public transport.

The Kingdom of Saudi Arabia is working towards achieving more sustainable travel behaviours and attitudes by constructing very high level of service public transportation options including a state-of-the-art metro system, which is very near completion and operation. The local travellers, therefore, are aware of such options and aware of the need to shift some of their travel activities towards such options [25,26,27,28]. Moreover, a large proportion of the population have travelled abroad and in the neighbouring countries and acquired different travel experience and awareness of the public modes of transportation. All these factors are expected to lead to changing travel behaviours and attitudes towards public transportation systems.

There are very few available publications on the modal choice and use of travel options in countries such as the KSA and other similar oil-rich countries. Relevant studies on these focusses include [29], who claim that high income and economic factors have contributed to shaping the lifestyle in Saudi Arabia that resulted in the high dependency on private cars [30]. A study reported on a stated preference investigation that assessed potential commuters’ perception towards the proposed metro system in Riyadh, as a function of socio-economic as well as level of service variables [25,26,27,28]. Other studies include an investigation of public perception on public transportation system in Dammam [30]. There is a lack of studies, however, that investigate the public acceptability of public transportation systems in these countries.

Dubai is a neighbouring city to the KSA that was the first Arabic Gulf city to introduce integrated transport planning, implement travel demand management, and build a metro system to achieve shifting car traffic to public transport traffic. The aim was also to reduce negative traffic impacts and achieve sustainability goals. Such shift of demand for public service entails not only market motivations to bring down private vehicle ownership and improve the public transport services, but also an understanding of how much people are willing to use and pay for improved public transport services. As well as building public transportation systems, Dubai has introduced financial incentives and disincentives, legislative measures, and raising awareness programs to facilitate the shift. This approach has resulted in success in shifting some of the car trips to public transportation, walking, and cycling as well as increasing the acceptability of such options [31,32].

Oman is another Middle Eastern country that has identified the importance of public transportation modes of travel. In a public opinion study that was carried out in Oman, it was reported that public transport facilities in the city are minimal and do not meet the demand, and that the private car is still the main dominant mode of travel in the city [33]. Marketing of public transport services is constrained by certain issues, including the socio-cultural and physical environments. The study produced recommendations to policy makers in Oman including establishing viable options to public transport solutions. Doha city in Qatar attempted to address the rapid-growing demand on transportation in the city to reduce traffic congestion on the roads by building a new metro system with four lines, an overall length of approximately 340 km, and 98 stations [34].

2.3. Travel Behaviour Studies

Future setups for the transport sector are increasingly motivated by behavioural changes towards sustainable travel prospects. It is very important therefore to increase the understanding and facilitate the management of travel behaviour. Considering individual social and psychological parameters, some research adopts attitudes towards particular travel options to assess different mobility systems [35,36]. Some research assessed mobility orientations as five diverse mobility types: traditional domestics, reckless car fans, status-oriented automobilists, traditional nature lovers, and ecologically resolute [36]. They evaluated travel behaviour arrangements associated with each group and demonstrated the extensive differences between them. Other research assessed motivations and constraints for behavioural changes that are associated with different lifestyle approaches [35]. Their analysis showed six groups: “malcontented motorists”, “complacent car addicts”, “die hard drivers”, “aspiring environmentalists”, “car-less crusaders”, and “reluctant riders”. The analysis demonstrated that there are some awareness and considerations of sustainability and environmental concerns that were apparent in all groups in the sample.

In terms of behavioural changes, a few studies have assessed sustainable travel behaviours, concentrating on car use and the use of alternative means of transport including public transport, bicycle use, or walking [37,38]. In general, a simplified assessment of sustainable versus non-sustainable behaviour and assessing their impacts on certain travel choices, such as mode choice or the frequency and distance of holiday air travel, increases the understanding and management of travel behaviour. Hence, we centre our analysis on assessing the level of willingness to use public transportation options in relation to several socio-economic factors. Impacts of social economic factors on travel behaviours and their influence on modal choices are evident in the literature. Several studies reported some gender differences in terms of accessibility and travel experiences in a case study of Sofia, Bulgaria, and Germany [35,39,40]. They report that women have less accessibility in comparison with men who use identical travel options. Another study investigated significant differences in the social implications of using different types of public transportation, including metro and buses, in South Asia [41]. Three studies looked at the impact of gender and income, levels of education, age, employment status, and car ownership on travel behaviours and choices, with a specific interest in Saudi women [12,41,42]. An investigation of mobility patterns and their impacts on culture and the structure of the household and relation to the transport patterns in terms of gender differences in Dublin has been reported [15]. The study concluded on the variables’ impact on the choices of modes of travel in relation to employment destinations. Commuters’ perceptions on employment decentralization and impacts on their mode choices in China has been reported in [12].

Swedish women’s attitudes towards sustainability have been investigated and reported [43]. The outcome of the study shows that Swedish women are more affirmative towards sustainability and are more likely to reduce their car travel in comparison with men. A study reported on recent UK research that young women tend to travel more than young men. The authors also concluded that young men travelled substantially less than their counterpart young men in previous generations, which could indicate that different generations face different socio-economic contexts which impact on mobility trends [6].

Household structure and patterns of mobility on modal choices in Paris have been investigated and reported [16]. The impact of position in the family on work trip behaviours and travel in Oslo has been assessed and stated [17]. In a comparative assessment, the lower-income categories of women and their levels of accessibility to public transportation in China and India have been assessed [18].

A study on demographic variables in Libya [44], such as age and gender, has shown a significant contribution to explaining mode choice behaviours. In addition, the study showed that men were less likely than women to shift to public transport [44]. They also found that women tend to travel by car more often as passengers, while men tend to be the drivers. A study found that, for students in Beirut, gender is one of the main factors affecting mode choice and, compared to females, males were more likely to use the bus [12]. A study investigated the travel characteristics of female college students in Saudi Arabia. They found that 57% travelled as car (or van) passengers and 39% travelled by bus, and over half (53%) were captives to their current mode of transport [13].

There has also been significant research on gender differences and travel patterns in the West, with less research conducted in other parts of the world, including the Middle East, where cultural and background factors are significantly different to those in the West, which could have impacts on travel behaviours [37,38,39]. There are few studies, however, that have attempted to examine gendered differences in travel behaviours in the Arab world [14,17,18,44,45].

In countries such as the KSA, women’s travel attitudes and behaviours are affected by economic and geographical factors, as well as other social and cultural differences and restrictions. Internationally, gender is decreasingly being viewed as a binary classification of female and male. Frequently, surveys are required to include options like “others” or “preferred not to say”. However, the KSA may have different interpretations on this issue due to the local culture. Therefore, the analysis in this study has been focused only on gender as a binary classification due to the KSA’s social norm and culture.

From the review of previous research, there has been a lot of research on travel behaviours and attitudes towards public transportation in the West. However, in countries such as the Kingdom of Saudi Arabia, the available reported research is minimal. There are, therefore, many gaps in the literature on the assessment of attitudes, travel behaviours, role of public transportation, and its acceptability in countries such as the KSA and other similar countries. This research attempts to fill some of these research gaps.

3. Methodology

3.1. Case Study

Riyadh city is situated in the centre of the Eastern part of the Najd hill and is the largest city of Saudi Arabia. There are 13 municipalities that house 209 districts that are accommodated within a 40-mile radius of Riyadh [1]. Riyadh’s population increased rapidly from 40,000 inhabitants in 1935 to 83,000 in 1949 to a total of 7.6 million inhabitant in the year 2019, making it the most-populated city in the KSA [25,26]. Of the current population, about 64.19% are Saudis, while expatriates account for 35.81%. The female population accounts for over 43% of the total population, with a population density of 2379 inhabitants per square kilometre (ADA 2015). About 85% of the eight million daily trips are carried out in private cars, whereas just 2% of the trips are undertaken via buses [26,27,28]. Between 1996 and 2018, private vehicle ownership increased by over 200%. Until recently, the vast majority of Riyadh’s population had never used public transportation; instead, they completely relied on private cars in all their travel. Any world city of that size, population, and volume of travel would most likely be operating a mass transit system; however, Riyadh city does not yet. The current Riyadh public transportation system consists of buses that are operated by the Saudi Public Transport authorities [26,27,28]. These started operation in 1979, aiming to run high-level bus services locally and across neighbouring countries such as the Arab Gulf countries, Jordan, Turkey, and Syria.

Compared to other neighbouring cities such as Dubai, Doha, or Kuwait, where there are more people supporting and using the public transportation systems that are in operation, the KSA is still behind. Although public transportation systems in those countries are also largely used by expatriates who are familiar with and accustomed to using them, this is not a major issue there as the majority of the population are expatriates and there is a good use of the public transportation system. The KSA is a much bigger country, however, with a much larger population and a much larger Saudi percentage of the population (e.g., about 65% of the city of Riyadh’s population are Saudi nationals). It is very important, therefore, to encourage Saudi nationals to accept the public transportation options and use them. It is, hence, very important to evaluate the willingness of the Saudi nationals to use public transportation systems and to assess their level of support.

3.2. Data Collection and Methodology Framework

As discussed above, the main aim of this research is to investigate attitudes and anticipated behaviours towards public transportation system in the city of Riyadh in the KSA in an era of national reform. The methodology is summarised under the following stages:

• Design and implement a questionnaire survey to assess travellers’ attitudes, perception, and behaviours towards public transportation options.
• Carry out a general analysis of the results using R software (version 4.2.3). These general results show the main factors that affect choice behaviours and choice of modes of travel.
• Identify relevant important factors that affect choice behaviours.
• Exploit these identified factors in an ordered logit model to assess the impact of the socio-economic factors on the stated attitudes and intended behaviours towards public transportation usage.
• Assess the model’s performance and discuss the results.

3.3. Experiment Design

An online questionnaire survey has been designed and piloted on a sample of 19 participants from the Princess Nourah bint Abdulrahman University (PNU) to test the clarity of the questions, the length of the questionnaire, and the practicality and worth of each of the questions. The questionnaire was then finalised, administered, and sent online to participants including both males and females using social media and Saudi universities through the research team and other colleagues at the PNU University in Riyadh. The questionnaire link was accessed by over 2000 potential Saudi national participants. Finally, 399 completed questionnaires were received. The survey was conducted between August and November 2022. The final version of the questionnaire included questions to collect data on the following factors:

• Modes of travel (frequently used modes, less frequently used modes, non-used modes, departure times, etc.);
• Travel characteristics (travel time, travel costs, waiting time, walking time, number of times to fuel your car weekly, cost of fuelling, etc.);
• Personal socio-economic characteristics (age, gender, position in the family, income);
• Household (HH) socio-economic characteristics (HH structure, number of driving licenses in the HH, number of private drivers);
• Education and employment;
• Attitudinal questions towards level of awareness of the new transportation systems in Riyadh;
• Attitudinal questions towards the importance of factors related to the transportation system (safety, reliability, delays, congestion, etc.);
• Attitudinal questions towards possible travel demand management measures (TDM) to include (pricing, parking, public transportation, access control, etc.);
• Questions on reported intent to use public transportation modes when they become available. The respondents were asked to report on their future intent to use public transportation modes as they become available, and to report these intentions on a three-point Likert scale: {will definitely shift to PT, I might do, and definitely will not shift to PT.};
• General questions on the experience with the questionnaire (time, clarity of questions, any further comments, etc.).

In this paper, information gathered from questions 1–6 and 9 above has been analysed and will be discussed. An initial assessment of the data that was collected was carried out to assess and finalise the selected factors/variables in the final analysis as follows:

• The socio-economic characteristics that are selected as independent variables are suggested from previous literature to be relevant to mode choice analysis considering the specific context.
• A correlation analysis between each independent variable and the dependent variable was carried out to select the factors that are relevant for this research.
• A correlation analysis between the independent variables to eliminate any highly correlated variables.

The list of the selected variables and their general statistics are presented in

Table 1. General statistics of the survey’s socio-economic information.

Variable	Surveyed	%
Dependent Variable
Intention to use PT
Will definitely shift to PT	159	39.8%
I might do	162	40.6%
Definitely will not shift to PT	75	18.8%
Independent variables
Gender
Male	183	45.86%
Female	216	54.14%
Position in the household (HH)
Son	84	21.1%
Daughter	162	40.6%
Husband	99	24.8%
Wife	54	13.5%
Driving License
Yes	267	66.92%
No	132	33.08%
Level of Education
PG	67	18.05%
UG	169	67.67%
Others	158	14.29%
No. of persons/HH
1–4/HH	91	22.56%
5–7/HH	211	52.63%
7–9/HH	91	22.56%
>9	6	01.50%
Income (individual income per month)
High (>20 K SR/m)	144	36.09%
Medium (12–20 K SR/m)	99	24.81%
Low (5–12 K SR/m)	117	29.32%
V Low (<5 K SR/m)	39	9.77%
Level of awareness of the new PT systems in Riyadh
Aware	299	75%
Not aware	100	25%

below.

3.4. Ordered Logit Model

Logistic regression analysis is an extensively utilised analysis tool used to analyse relationships between a dependent and a number of independent variables using the concept of random utility. In regression analysis, the dependent variable is often discrete, with one or more possible options, and is considered binary or multiple classes. This type of analysis uses linear regression estimation and results in a logit function that best describes the function form between the dependent and independent variables. While the multinomial logit models allow for more than two categories of the dependent variable, the binary logit models allow only for two categories. The calibration of a binary or multinomial logit model (with dependent variable classes) involves the calibration of the independent coefficients that predict the probability of the outcome of interest. The probabilities of a binary logit model are given by the following expression in Equation (1) below [46,47]:

ln (prob.(an event occurring))/(1 − prob.(an event occurring))
= α + β₁ X₁ +…+ β_k X_k

(1)

The coefficients in the logit model give information as to how much the logit changes depending on the independent variable values. The term on the left-hand side refers to the log of the odds that an event occurs. The logit models (binary or multiple) estimate the values of the parameters of an assumed probability distribution, given some observed data [23].

Where the dependent variable is ordinal, the logistic regression analysis is referred to as ordinal logistic regression or ordinal logit model (OLR). When there is a systematic order in the dependent variable classes or categories, the ordinal logit model can be used to predict the dependent variable as a function of independent variables. To calibrate the coefficients of an ordinal logit model, the levels of the dependent variable must be defined [23,24,25]. The mathematical formula of the odds of proportional of the OLR can then be written as in Equation (2):

logit [P(Y ≤ d)] = α_d − ΣβiXi

(2)

In this research, the outcome (or dependent) variable of the model is the intention to use public transportation expressed on a three-point Likert scale to represent levels of willingness to use the metro system. The independent variables are socio-economic and attitudinal factors that were proved relevant from the general statistics part of the analysis. D is the total number of levels of the dependent variable (in this case D = 3) and I is the number of independent variables (I = 6) as seen in

Table 2. Mode choice statistics with socio-economic characteristics.

	Private Car	Public Transport	Carsharing	Walking	Work/Bus. Driver	Private Driver	Motor Bike
Gender
Male	165	0	39	15	18	36	15
Female	123	3	75	18	6	51	15
Position in family
Son	72	0	24	6	3	15	15
Daughter	87	0	66	15	6	48	12
Husband	93	0	12	9	15	9	0
Wife	36	3	12	3	0	15	3
Driving license
Yes	216	0	57	18	18	33	18
No	72	3	57	15	6	54	12
Income
<5000 SR	27	0	18	6	0	3	0
>5000–<12,000	75	0	33	12	9	30	15
>12,000–<20,000	69	3	39	0	3	18	9
>20,000	117	0	24	15	12	36	6

. In this case, d = 1 refers to ‘will definitely shift to PT’, d = 2 refers to ‘I might do’, and d = 3 refers to ‘will definitely not ‘shift to PT’. In addition, when i = 1 refers to ‘gender’ i = 2 refers to ‘position in the HH’, i = 3 refers to ‘possession of driving license’, i = 4 refers to ‘education’, i = 5 refers to ‘number of people in the HH’, and i = 6 refers to ‘individual monthly income’. The coefficients of the ordinal logit model were calibrated based on responses received from the survey. The analysis was carried out using R software [48]. The coefficients’ estimates of the independent variables, the odd ratios, and goodness of fit statistics of the OLR model are presented in

Table 3. Coefficient estimates of the OLR model, the odd ratios and the t-statistical significance values. coefficient’s estimates and their exponential values.

Parameters	Coefficient Estimates	Odd Ratios	Std. Error	t-Values
Gender
Male	0.775	2.171	0.127	6.102
Position in the HH
Son	0.501	1.665	0.3319	1.536
Daughter	1.274	3.575	0.332	3.837
Husband	0.895	2.447	1.477	0.6059
Driving License
Yes	2.809	16.593	1.882	1.493
Level of Education
G	1.989	7.308	0.452	4.4.400
UG	3.213	24.853	0.682	4.711
No. of persons/HH
1–4/HH	3.800	44.701	1.028	3.696
5–7/HH	3.943	51.573	1.371	2.876
7–9/HH	3.01	20.287	0.896	3.359
Income (individual income per month)
High (>20 K SR/m)	−1.443	0.236	0.397	−3.634
Medium (12–20 K SR/m)	2.633	13.915	1.301	2.024
Low (5–12 K SR/m)	1.90	6.686	0.415	4.578
Intercepts (intent levels)
Level 1	3.002	28.933	0.597	5.636
Level 2	5.365	20.126	1.152	2.606
Level of awareness of new PT in Riyadh
Yes	2.611	13.626	1.782	1.465
Sample size		399
−2 Loglikelihood with zero coefficient	289.143
Final model	258.964
R2	0.399
p-values < 0.05

below.

The definitions of the ordinal logit model are that all the coefficients of the dependent variable across all categories have equal slope. This is tested using the parallel line test or the Brant test. In this investigation, a comparison of the ordinal model with one set of coefficient estimates for all categories of each of the independent variables (i.e., null hypothesis of the ordered model) is compared with a model that has a separate set of coefficients for each category (referred to here as the “general model”), and the assumptions of the ordered model have been accepted. The objective behind using OLR is to predict the dependent variable (D) as a function of the five independent parameters that are presented in Table 3.

In this research, we utilize logistic regression analysis to calibrate models to assess the travel behaviours and attitudes of Saudi nationals towards public transportation in an era where the new sustainability projects are observed and witnessed. A discrete choice model of the intent to use public transportation is calibrated as a function of the relevant social and attitudinal factors.

4. Analysis of Survey Data

4.1. General Statistics of the Analysis

The analysis of the outcome of the survey that was carried out with 399 participants is presented in this section. The number of those surveyed categorised by each socio-economic group, and overall percentages within each category are presented in Table 1 and Figure 1a–f.

The general characteristics of the participants show that 54.14% of participants were female and 45.86% were male. The age question was not included in the survey, since this the kind of question that might be considered private information in this case. It was also thought that there are other questions in the survey that would be a sufficient indicator of the participant’s age. The participants were also asked to report on their position in the family. The results indicated that “daughter” is the majority reported position in the sample (40.60%); this is followed by husband (24.81%), son (21.05%), then lastly wife (13.53%). It is interesting to note that female drivers in the sample are still much lower in numbers than male drivers. One possible reason for this is that women only started driving in the KSA five years ago, and therefore they still rely on “others” for their travel. In this sample, more than 72% of the female participants reported to have a private driver, while only 27% of the male participants reported having a private driver. Other socio-economic characteristics include possession of a driving license. About 67% of the participants reported that they possess a driving license, while 33% do not. The majority of those who do not possess a driving license are the daughters and wives. Over 70% of those who do not possess a driving license in Riyadh are daughters and over 20% are wives. Sons and husbands are minorities in this category. It should be noted here that although Saudi women only started driving five years ago, the numbers of female drivers have been increasing constantly. In terms of education, three levels are defined: PG holders represent 18.05% of the sample, the university graduates represent 67.67%, while other education levels combined represent 14.29% of the sample.

The total number and percentages of participants falling in four categories of number of persons in the household (HH) show that the category of 5–7 persons per household is the largest category in the sample in terms of number of participants (52.63%). Two categories (1–4 persons/HH and 7–9 persons/HH) are equal and each category represents about 22.5%, with the category >9 persons/HH being the lowest category, with a percentage of 1.5% only. It is well documented in the literature that, in Saudi Arabia, there are extended families and that the families generally include a larger number of persons than is the case in the West.

The general statistics also show the distribution of the participants to the four income groups. Just over 36% of the sample fall in the monthly income category of >20,000 SR (>$5300). The second largest category with just over 29% of participants is the category of 5000–12,000 SR ($1330–3200), while about 24% fall in the category of 12,000–20,000 SR ($3200–5300), and the final category, representing only 9% of participants, is monthly income < SR 5000.

4.2. Travel Characteristics of Participants

Participants were also asked to report on their travel experience and on their most frequently used modes of travel over the previous month. The information on mode of travel was coded to include “always” and “almost always” categories. This is because most participants in the survey and in the Kingdom mostly use private cars (>70%). Table 2 and Figure 2 provides a summary of the mode choice statistics of the participants against some socio-economic characteristics. From Table 2, it appears that the private car is the most dominant mode of transportation in Riyadh. It also appears that public transportation is the most unused mode of travel in the city (<0.8%). When participants were asked about how often they use public modes of transportation, which is currently only the bus system, only three working females reported that they use it always. Those three females are of the lowest income group, do not own a private car, and they are all in the category of 5–7 persons in the household. In another question in the survey, the participants were asked to report on their level of awareness of the new public transportation systems that are currently being constructed in Riyadh. About 25% of the participants said that they are not aware of the newly introduced public transportation options while 75% said they are aware of the new options of travel including the metro. This is an important piece of information, as the level of awareness could have an impact on the level of acceptability.

Sustainability is a big issue in the Kingdom of Saudi Arabia at the current time, and the decision makers are very keen to implement measures to encourage more walking activities. While walking is a very important mode of travel in particular for short journeys, as well as one of the sustainable modes of travel in most world cities, in Riyadh, walking is not a popular option. On walking trips to work, only about 8% reported that they always go to work on foot; these were all journeys of less than 30 min. This, of course, is expected, since Saudi Arabia is a hot country on the whole and not many people would be observed to be making their daily trips to work on foot. About 60% of participants reported that they never walk to work, and the rest reported that they sometimes they walk to work. The reported journey times for over 70% of this latest category are also less than 30 min, while, for the other 30% of them, the journey time is between 30–60 min.

5. Ordered Logit Model Results

Figure 3 shows the frequency distribution of independent variables against the response variable. From the graph, it appears that there is an overall positive intention towards using the public transportation systems when they start operation. In terms of position in the family, the daughter showed the highest interest in using public transportation over the other members of the family. University graduates showed more interest in public transportation modes than participants with other qualifications. Previous literature suggest that women are more supportive of public transportation modes than men [36,37]. Participants who possess a driving license seem to have higher intent to use public transportation than those who do not. Assessing the impact of income on the intent of using public transportation shows that participants with the highest income groups indicated the highest percentage of rejecting the use of PT, which might be expected and supported by the previous literature.

The results are dedicated to the intent to use public transportation services, once they become available, to achieve sustainability and improve overall travel efficiencies.

Table 3 shows the coefficient estimates of the OLR model, the odd ratios, the t-statistical significance values, and the coefficient’s estimates and their exponential values. From the Table 3, it is evident that the proportional odds model shows the positive effects of all coefficients, which are statistically significant (p < 0.05) according to the Wald test. The results presented in Table 3 present the ordered log-odds (logit) coefficients of regression. The standard interpretation of the ordered logit coefficient is that for a one unit increase in the independent variable, the dependent variable level is expected to change by its respective regression coefficient, while all other variables in the model are held constant. Furthermore, the proportional odds ratio of the ordered logit model is obtained by exponentiating the ordered logit coefficients.

From the results, for a one unit increase in the “male” group, we expect a 0.775 increase in the log odds of being at a higher likelihood to use future public transportation, given all other variables in the model are held constant. Furthermore, for a one unit increase in the “male” gender group, the odds of being at the highest level of using public transportation versus the combined two other levels are 2.171 greater, given that all the other variables in the model are held constant. For a one unit increase in the “son” position category, we expect a 0.501 increase in the log odds of being at a higher level of using future public transportation, given all the other variables in the model are held constant. Furthermore, for a one unit increase in the “son” position category, the odds of being at the highest level of using public transportation versus the combined two other levels are 1.6665 greater, given that all the other variables in the model are held constant. On the other hand, for a one unit increase in the “daughter” position category, we expect a 1.274 increase in the log odds of being at a higher level of using future public transportation, given all the other variables in the model are held constant. Also, for a one unit increase in the “daughter” position category, the odds of being at the highest level of using public transportation versus the combined two other levels are 3.575 greater, given that all the other variables in the model are held constant.

For a one unit increase in the “yes” category of the driving license variable, we expect a 2.809 increase in the log odds of being at a higher likelihood to use future public transportation, given all the other variables in the model are held constant. Furthermore, for a one unit increase in the “yes” category of driving license, the odds of being at the highest level of using public transportation versus the combined two other levels are 16.593 greater, given that all the other variables in the model are held constant. For a one unit increase in the “university graduates” category of level of education variable, we expect a 3.213 increase in the log odds of being at a higher likelihood to use future public transportation, given all the other variables in the model are held constant. In addition, for a one unit increase in the “university graduates” category of level of education, the odds of being at the highest level of using public transportation versus the combined two other levels are 24.853 greater, given that all the other variables in the model are held constant.

For a one unit increase in the “income > 20 K” category of the income variable, we expect a −1.443 reduction in the log odds of being at a higher likelihood to use future public transportation, given all the other variables in the model are held constant. Moreover, for a one unit increase in the “university graduates” category of level of education, the odds of being at the highest level of using public transportation versus the combined two other levels are 0.236 greater, given that all the other variables in the model are held constant. The cut points shown at the bottom of the coefficient estimates indicate where the latent variable is cut to make the three levels that we observe in the data. Table 3 also provides evidence for the model’s goodness of fit and its ability to predict the outcome variable. The loglikelihood values of the model with zero coefficients are compared with those of the final model with all independent variables, which demonstrates the improvement in the goodness of fit of the model. The p-values show the level of significance of the models. The results of the test of parallel lines show evidence for the appropriateness of the ordinal logit model and its estimates (null hypothesis of the ordered logit model), being superior to a model with a separate set of coefficients for each category, which is the general model.

A factor that could affect social change is the level of awareness of the new PT systems in Riyadh. For a one unit increase in the “yes” category of level of awareness variable, we expect a 2.611 increase in the log odds of being at a higher likelihood to use future public transportation, given all of the other variables in the model are held constant. Furthermore, for a one unit increase in the “yes” category of level of awareness, the odds of being at the highest level of using public transportation versus the combined two other levels are 13.626 greater, given that all the other variables in the model are held constant.

6. Discussion of Results

Sustainability and the role of public transportation to modal choices have been discussed very widely in the literature. Factors that affect the choice of mode of travel have been categorised into quantitative and qualitative [49,50,51,52,53]. The quantitative factors, such as travel time, travel cost, waiting time, and walking time, have been heavily investigated in the literature, not only because they are measurable but also because they have been proved to be effective and influential on the choice of mode of travel [54,55,56,57,58]. Recent studies, however, have suggested that the qualitative factors are as effective as the quantitative ones and maybe even more so [52,53] in convincing and influencing the use of public transportation options. The list of the qualitative factors has evolved over the past few decades to include many social modes’ characteristics including knowledge, awareness, and attitudinal factors [18,19,20,21].

It is observed that raising awareness of the travellers about the relevance of using public transportation travel to sustainability has a positive impact on their behaviours, and in particular, the behaviours of the younger generation [52]. It is of note that there has been evidence of a long-term trend away from car dependency, not only due to economic breakdown. It is the younger population in particular who are driving the new trends for several reasons, including changes in the generations’ values and preferences [54]. In many cases, females are showing high support for public transportation use [11,12,15,48]. The situation in the KSA is not very far from the current trends. The KSA is a wealthy country with very high car ownership and use. However, from the results of the study, it appears that the younger generations, mainly females, are the most supportive of public transportation options.

The social acceptability of public transportation is also a very important factor that affects travellers’ choice of public transportation. In countries such as the Kingdom of Saudi Arabia, culture and other social factors impact travel decisions and the acceptability of public modes of travel. The Kingdom is going through a national change where the citizens are very supportive and proud of the transformations and there is a real desire to be at the forefront in terms of sustainability, including sustainable travel. The recently constructed metro system in the city of Riyadh is aiming to increase public transportation travel. It is very important, therefore, to investigate the level of support and the willingness to use it in the Kingdom. There seems to be a high level of awareness about the metro system, which has a positive impact on the level of willingness to use public transportation (about 75% of participants reported that they are aware of the newly constructed metro system). The model’s results show that over 80% of respondents expressed willingness to use the metro system, with just under 20% reporting that they would not shift to public transportation options. Results in Table 3 shows that if the “yes” value of level of awareness category increases by one unit, the odds of being at the highest level of using public transportation versus the combined two other levels is 13.626 greater, given that all the other variables in the model are held constant. These statistics show a much-improved anticipated market share for public transportation than the current situation, which shows that only about 2% of the population are using public transportation.

While there has been significant research on gender differences and travel patterns in the West, less research has been carried out in other parts of the world, including the Middle East, where cultural and communal factors are significantly different [15,16,43]. The results of this research show that, for example, if the “son” category increases by one unit, the ordered log-odds of being in a higher likelihood to use public transportation category will increase by 0.501, while all the other variables in the model are held constant. Furthermore, the proportional odds ratio for a one unit increase in the son category, the odds of “will definitely shift to PT” versus the combined two other categories, “I might shift” and “definitely will not shift to PT’, are 1.6665 greater, given that all the other variables in the model are held constant. On the other hand, if the “daughter” category increases by one unit, the ordered log-odds of being in a higher likelihood to use public transportation category will increase by 1.274, while all the other variables in the model are held constant. Furthermore, for a one unit increase in the daughter category, the odds of “will definitely shift to PT” versus the combined two other categories, “I might shift” and “definitely will not shift to PT’, are 3.575 greater, given that all the other variables in the model are held constant. These results show that the younger females were more supportive of using the public transportation systems than the sons, although both of them showed positive support. This seems to be anticipated, as the females who have just recently gained access to driving their private cars in the country are becoming increasingly inspired to further augment their participation and support sustainable options.

Other results from this research include that participants in highest income groups were less keen to use public transportation, and they were expressing more preference towards “definitely not going to use PT” than other income groups. The model’s results show that if the “income > 20 K” category increases by one unit, the ordered log-odds of being in a higher likelihood to use public transportation category will decrease by 1.443, while all the other variables in the model are held constant. This is an expected finding, since higher income individuals often sustain higher values of time and are less keen to use public transportation options [23]. This is particularly relevant in cultures of high car dependency and high income.

The two constants of the model, in this case, represent cut points used to differentiate the adjacent levels of the response variable. A threshold can then be defined that results in the different observed values on the levels of the dependent variable, which is used to identify the three ordered regions of the dependent variable. In this case, the two constant values from Table 3 are 5.365 and 3.002. This indicates that participants who score 5.365 or more on the dependent variable will be classified as “will definitely shift to PT”. Participants who score 3.002 or less on the dependent variable will be classified as “will definitely not shift to PT”.

The paper adds value to the literature by offering a first investigation of willingness to use public transportation in the city of Riyadh, at a very apt time where there is abundant knowledge and experience of the new metro system that is being constructed and will be operating in the city soon. The paper suggests that the choice of mode of travel is determined by the travellers’ social and economic characteristics, as well as the level of awareness of the available services. The relevance of the level of awareness has been evident in the literature in the context of public acceptability of street lighting and its importance in increasing the provision of information and awareness [27,28,29,49,50,51,52,53].

7. Conclusions and Recommendations

The paper investigates the anticipated behaviours towards the newly constructed metro system in Riyadh city. This is a very significant contribution; if social change is emerging and modal shift to public transportation is achieved, that would provide a momentous shift towards achieving sustainability in the Kingdom of Saudi Arabia. Currently, over 98% of the trips in the city of Riyadh are carried out in private cars, while the Kingdom is aiming at reversing this pattern and progressing towards sustainable travel behaviours. The country is constructing a massive metro system, which is near completion and operation. The new metro system is being recognised and witnessed by all residents of the city during the construction phases, and so it is hoped that this will encourage positive attitudes of the residents to becoming more sustainable. It is very timely and critical, therefore, to investigate and assess the potential intent to use this system.

The study involves an online questionnaire survey that was designed, piloted, finalised, and administered between August and November 2022, and sent online to participants, including both males and females, using social media. In this paper, individual and HH socio-economic data, education, income, and attitudinal statements towards the transportation system in Riyadh were exploited and analysed.

The model’s results show that over 80% of respondents expressed willingness to use the metro system, with just under 20% reporting that they would not shift to public transportation options. This shows a much-improved market share for public transportation than the current situation, which shows only about 2% using public transportation.

The results show that females are keener to support sustainability and public transportation options than males, which is compatible with previous research results. This is an interesting finding from the point of view that the current era in the KSA is characterized by empowering women; this will be added to other evidence that reflect women’s achievements in the country [11]. Participants in the highest income groups were less keen to use public transportation and expressed greater preferences towards “definitely not going to use PT” than other income groups, which is an expected finding. This is particularly relevant in cultures of high car dependency and high income.

The results also suggest that the higher the level of public awareness of sustainability and sustainable transport projects, the higher the level of acceptability of such options. These are very significant findings that would provide policy makers with important knowledge to improve the public acceptability of sustainable projects.

The paper adds value to the literature by offering a first investigation of willingness to use public transportation in the city of Riyadh, at a suitable time where there is abundant knowledge and experience of the new metro system that is being constructed. The paper suggests that the choice of mode of travel is determined by the travellers’ social and economic characteristics, as well as the level of awareness of the available services.

Social studies are very expedient for the understanding of attitudes and behaviours, and for supporting the design and planning of appropriate travel services and programs that would support the national vision. The local transportation authority in Riyadh is about to start operating the new metro system, and the findings from this study can provide recommendations to help better the understanding of Riyadh’s population’s travel attitudes and preferences. Carrying out this type of research could also be a possible means of raising awareness and informing the travellers, the industry, and academia of the available transport options and resources to gain the public support that is very critical for the success of public transportation projects.

8. Limitations

This is an original and pioneering research into travel behaviours and attitudes. There are, however, various limitations of the research, as discussed in this section. The survey was distributed and administered using online means, with more than 2000 people accessing the link. Only 399 completed surveys, however, were received. While this number is tolerable for this analysis, a larger quantity of feedback would no doubt provide more representative results. The initial target group of the survey was meant to be representative of the Saudi population. However, the survey was posted through social media, and, therefore, most of those who accessed it were younger participants (over 65%), while only 35% were older participants. Furthermore, in this paper, the pilot study was conducted at PNU with only female participants. In future studies, it would be useful to expand the pilot sample to include both genders. The online survey might have affected the types of respondents; not all populations are able to access online surveys. This is particularly true for the older population. Ordered logit models were used to analyse the willingness to use public transportation. Other types of models could have also been employed, including logit regression and linear and continuous models. The results presented in this research are limited to one city, which is Riyadh. It would be very beneficial to extend the study to other cities in the Kingdom. Further research needs to be carried out involving local authorities and transport planners, so that actual measures and programs can be built in the design of the surveying methodology. The current research includes seven independent variables. Other variables could also be included in future research including age, level of employment, attitudinal opinions, stated preferences surveys, and other methodological approaches.