In this article, we present an academic research study exploring how hotel services influence tourist decisions using the push and pull model. This study combines theoretical rigor with practical insights and offer actionable recommendations for stakeholders in the hospitality and tourism industries. While rooted in academic methodology, the findings are tailored to inspire innovative approaches to concept creation that is a core focus of our services.

Overview of the Research

This research explores why tourists choose to visit multiple destinations during one trip and how hotels can influence this decision. It uses a well-known theory called the “Push and Pull Model,” which looks at two factors:

• Push Factors: Internal motivations like wanting to see beautiful places or trying new experiences.
• Pull Factors: External factors like convenient hotel services or attractive facilities.

The study surveyed travelers to understand what motivates them and analyzed how these factors work together to shape travel decisions.

Key Findings

1. Natural Beauty Matters: Tourists are highly motivated to travel to destinations with beautiful scenery. That makes it the most important “push factor.”
2. Flexible Hotel Services Attract: Hotels that offer flexible check-in and check-out times strongly influence tourists’ decisions. That makes it the most significant “pull factor.”
3. Practical Hotel Services Help: Amenities like transportation between destinations and easy logistics (e.g., packing/unpacking assistance) enhance the multi-destination experience.
4. Demographics Don’t Change Much: Motivation factors like natural beauty and flexibility appeal to all groups, regardless of age, gender, or income.

Academic Research: How Do Hotel Services Influence Tourist Decisions Using the Push and Pull Model?

The tourism or leisure travel industry is an important component of the global economy and key to its growth (Wu & Carson, 2008). It is and a significant part of tourism is multi-destination travel, which is defined as when tourists visit multiple places in a single journey or travel. Multi-destination tourism is complex in terms of route choices and has two major constraints, time and space, which determine the significance of multi-destination travel. In addition, tourists have varied motivations that encourage them to engage in tourism. Literature is reviewed to explore tourists’ motives and behaviours during their leisure travels while focusing on multi-destination travel. Hierarchical, rational, behavioural, and motivational theories are also reviewed to determine the most appropriate and suitable theory to be applied to the context of this capstone project. 

The role of hotel services and their influence on tourists’ decisions to engage in multi-destination travel using push and pull model factors is also reviewed in terms of literature. These are considered most appropriate for studying the effect of hotel services on tourist motivation. Understanding those influences amid changing consumer preferences is crucial for developing strategies and services that enhance travellers’ satisfaction. In addition, the paper discusses how tailored and personalised hotel services can influence and encourage travellers to engage in multi-destination travel.

Research Aims

The study aims to analyze the specific segment of multi-destination leisure travel, where tourists visit multiple locations during a single trip and spend at least one overnight stay at two separate locations. The purpose of this research is to analyze the impact of hotel services on tourists’s decision to use multi-destination travel using the push-and-pull model. 

Research Questions

RQ1: Which specific push and pull motivations factors significantly predict tourists’ preferences for multi-destination travel?

RQ2: What is the overall impact of push and pull motivations on tourists’ intentions to engage in multi-destination travel?

RQ3: How do hotel services and tourists’ motivations (push and pull factors) influence tourists’ intentions to engage in multi-destination travel?

RQ4: Is there a significant difference in the likelihood to travel between different demographic factors (gender, age, and income)?

Literature Review

Tourism and Leisure Travel

Tourism and leisure travel is a highly significant industry to national and local economies and is expected to grow to reach $1 trillion by 2030 (WTTC, 2023). Also, it is beneficial in job creation (Wu & Carson, 2008) and attracting high-spending international tourists and foreign investments. Furthermore, the industry attributes its growth to an increase in leisure time and economic conditions (Sohn et al., 2021). Tourism and leisure travel refers to people’s movement or travel from their typical surroundings or home to various locations. It is the set of activities that a person must take during a defined visit to fulfil emotional needs, relax from tension, and escape boredom in another location. Accordingly, travelling to a separate location is an essential part and requirement of tourism, irrespective of the transportation method or the duration of the travel (McKercher & Mak, 2019). 

Researchers have classified only leisure travellers as tourists, while other travellers, such as language students and interns, are not tourists (Yousaf et al., 2018). Understanding tourists’ movements ensures the development of sufficient infrastructure and transportation methods (McKercher & Lew, 2004) as tourists choose their destinations based on the quality of the destination, including hotels, parks, and transportation networks, but still, infrastructure remains crucial for full touristic potential (Rahim et al., 2022). Furthermore, research has posited that time, budget, and other constrained resources are the main factors that affect tourists’ travel plans (Parroco et al., 2012). The facets to tourism, such as size, type, constraints, and destination choice, and all participate in the way tourism is experienced.

In addition, tourism can be experienced and consumed in many ways, such as leisure tourism at hedonic destinations that offer pleasure and fun while, in contrast, practical and functional destinations offer more return in cost-benefit analysis and offer knowledge and self-actualisation (Do et al., 2021). The tourism industry’s size and significance ensure that the capstone project has academic relevance as it investigates how hotel services influence tourist decisions using the push and pull model that will enhance the understanding of tourists’ behaviour and motives regarding tourism while focusing on multi-destination travel. One type of travel that is an increasingly popular trend among leisure travellers and requires further studies is multi-destination travel.

Multi-destination Travel

Multi-destination travel is when travellers visit more than one destination during their travel and spend at least one night at that destination (Cigale, 2020). This form of travel is dynamic and has two significant constraints: time and space, as tourists must move to separate locations at different times. Therefore, tourists whose motivation is to maximise their travel advantage and experience will be inclined to engage in multi-destination travel (Lue et al., 1993) as it enables them to visit many areas, towns, or countries during their travel. Therefore, addressing those constraints is crucial to regulators and developers to ensure that tourists can experience multi-destination travel.

Policymakers and the tourism industry recognise the significance of multi-destination travel. In addition, multi-destination travel offers time and cost-saving advantages, which are influential to tourists’ motivation (Ben-Akiva & Lerman, 1985). These motivations drive tourists towards optimising costs and time and will impact their choice of location, duration, and transportation methods (Ben-Akiva & Lerman, 1985; Wu & Carson, 2008). Multi-destination travel is essential to the tourism industry as it will influence tourists’ motivation to maximise pleasure and experiences during their travels (Lue et al., 1993). Tourists tend to be cost- and time-optimised, and therefore, many tourists practise multi-destination travel. 

Multi-destination Travel Significance

Studies on multi-destination travel significance have been conducted in different regions, and research posited that many tourists engage in multi-destination tourism during their travels (Hwang et al., 2006; Oppermann, 1995; Tideswell & Faulkner, 1999). For instance, research posited that 41.7% of Slovenian travellers’ recent trips were visits to multiple destinations (Cigale, 2020). 

Further academic studies in Sicily reveal that 32% of tourists visit multiple destinations while on the island and that foreign tourists show a higher tendency for multi-destination tourism than Italian nationals (Parroco et al., 2012), and this suggests that travel behaviours are different based on the tourist’s country of origin. However, beyond its economic and cultural significance, other factors influence multi-destination travel, such as temporal and spatial factors, which are discussed in the following section.

Multi-destination Travel Temporal and Spatial Aspects

Travel, in general, has constraints, and the most important constraints are temporal and spatial aspects, which are time and space, and both are extremely influential in motivating multi-destination travel. Specifically, time constraints can impact vacation time and require tourists to allocate resources efficiently as time is finite. Accordingly, tourists allocate more time to sightseeing if their travel duration is more prolonged (McKercher & Lew, 2004). In addition, there is a positive correlation between multi-destination journeys and the duration of stay, and this indicates that tourists extend their travel periods when travelling to more than one destination during their travels (Cigale, 2020; Nagar, 2016). 

Various reasons may lead tourists to engage in multi-destination travel, but research suggests that variety-seeking motives may be the most compelling motives that may lead tourists to visit several destinations at a time (Tideswell & Faulkner, 1999). However, other factors that might affect tourist decisions, including distance between the destinations, means of transport, and cost of travel (Tussyadiah et al., 2006). The temporal aspect is one of the sides of tourists’ constraints, and the second side is space constraints.

In relation to space, spatial factors significantly influence tourists, as a study of 92 source markets posits that 52% of all international departures are to adjacent countries that share borders (McKercher & Mak, 2019). Moreover, research in the USA posited that 80% of international travel is to countries within a 360-mile radius, and people are more likely to engage in multi-destination travel as the travel distance from their homes increases (Hwang & Fesenmaier, 2003). 

Therefore, transportation methods influence tourists to visit multiple destinations, and motor vehicles remain the most efficient and popular facilitators for tourists (Cigale, 2020; Tideswell & Faulkner, 1999) while other researchers posited that the construction of high-speed rails would also increase tourists’ dispersal (Wang et al., 2022; Zhou et al., 2021). Infrastructure and transportation methods heavily affect the spatial factor, and ensuring adequate facilities will increase tourists’ engagement in multi-destination travel. Time and space constraints heavily influence tourists’ decisions during their travels (McKercher & Lew, 2004) and, therefore, can affect travel patterns, as examined in the next section.

Multi-destination Travel Patterns

Tourists can take multiple itineraries during their multi-destination travel. Those travel itineraries range from simple and direct routes to complicated tours to multiple destinations. For instance, academic studies in the USA identified four touring routes among domestic American tourists visiting Yellowstone National Park (Mings & McHugh,1992). Other researchers expanded on multi-destination trip patterns and added more route characteristics and complex patterns (Lau & McKercher, 2006; Zhu et al., 2020), while other researchers focused on international tourists’ routes (Oppermann, 1995). 

Understanding those travel patterns is essential for destination management policymakers and product development (Santos et al., 2011). Current examination has identified a variety of travel patterns among multi-destination tourists, but the impact of hotel services on these patterns requires further examination. Furthermore, understanding these patterns highlights the need to examine the motivational and behavioural factors that influence tourists to engage in multi-destination travel.

Multi-destination Travel Motivation and Behaviour 

Psychological factors are also strong determinants of travel behavior and choice. Several research studies have established that tourists have varying reasons for multi-destination tourism. Specifically, motivation factors like seeking variety, different opinions among the travel group, and trying to minimize the risk will influence the tourist travel decision regarding multi-destination travel (Nagar, 2016), and the same study has also pointed out that young-age tourists are more inclined towards hedonic multi-destination travel (Nagar, 2016). Furthermore, Cigale (2020) explains that a study in Slovenia suggests that tourists’ main impact on multi-destination travel is risk minimization. 

Slovenian tourists prefer to travel with their families to places that they have visited before and are familiar with, so we can see that previous experiences influence Slovenian tourists’ choice of destinations (Cigale, 2020). However, other factors may also affect tourist destinations concerning multi-destination travel, such as the trip’s purpose and length and whether it is an initial visit or a revisit (McKercher & Lew, 2004). The dynamics of tourists’ behavior call for an analysis of the factors that lead to multi-destination travel, as will be discussed in the next section.

Tourist Motivational Theories

Various motivational theories in the tourism literature can be helpful in identifying tourist motivation and destination choice (McKercher et al., 2021; Yousaf et al., 2018). The review is aimed at linking the capstone project with the most suitable and relevant theory for assessing the impact of hotel services. Several behavioral theories can be applied in the evaluation of tourists’ motivation. Some of the theories include Maslow’s hierarchy of needs. The hierarchy of needs is behaviorally motivated by physiological requirements, safety, social affiliation, recognition, and actualization (Maslow, 1943; Yousaf et al., 2018). 

In the case of hotels, Maslow’s theory is useful since it fulfils different needs, including security, self-esteem, and others; however, it does not account for any sequential order or requirements and only addresses internal motives. Another physiological theory is the travel career pattern model. Like the hierarchy of needs by Maslow, the travel career pattern model presupposes a hierarchical travel motivation based on the travel career ladder model (McKercher et al., 2021; Pearce, 2005; Pearce & Lee, 2020).  

Maslow’s Hierarchy of Needs and the Travel Career Pattern Model outline a progression of needs and motives. Maslow’s framework, primarily psychological, emphasises individual development and self-actualisation in travel motivations. Whereas Pearce’s model, which is more tailored to tourism, classifies motivations linked to travel experiences. Therefore, there is a limitation regarding the use of this theory in the context of the capstone project, as it does not address external influences.

Other theories focus on economic value, including Consumer Choice Theory, which posits that the value of the good does not lie in the value of the goods themselves but rather in the utility and attributes derived from it (Lancaster, 1966). Its empirical implications in tourism are that destinations packed together will offer more utility to tourists as there will be diverse experiences while utilising time and space (Do et al., 2021; Santos et al., 2011; Tussyadiah et al., 2006). Similarly, Rational Choice Theory, originally developed by Adam Smith, posits that individuals make decisions based on calculations of the costs and benefits of those decisions. 

Consumer Choice Theory and Rational Choice Theory focus on utility maximisation but have different applications within the tourism context. Consumer choice theory emphasises the combined utility derived from bundled offerings and suggests that destination offerings will have more utility and enhance traveller satisfaction if they are bundled as a package. In contrast, rational choice theory applies a cost-benefit analysis. These differences in theories highlight the ongoing discussion in tourism research about the primary drivers of tourist decision-making and whether tourists are seeking the best overall experience or the most cost-effective solution. 

Both theories address and focus on economic factors and do not focus on external influences and motivations, which is the main theme of this capstone project. One of the theories that focus on such motivations is the Theory of Planned Behaviour. It posits that individual intentions and motivations derive from three elements: 1) Behavioural intentions, 2) Perceived behavioural control, and 3) Social Norms (Ajzen, 1991). In other words, behavioural intentions are the individual’s attitude towards the destination, perceived control deals with whether it is easy or challenging to reach the destination, and social norms would investigate how people would think of the individual if they were to take such travel (Abbasi et al., 2021; Ajzen, 1991). 

However, it does not apply to all contexts as it may not assess distinctive hotel services and their influence, which is the topic of the capstone project. Therefore, a more appropriate motivational theory in the context of the capstone project should address the effect of hotel services on tourists’ motivation, and the push and pull theory is suitable for studying that effect. 

Push and Pull Theory

The push and pull theory is vital to studying what motivates individuals, and according to Dann (1977), the theory addresses two motivational variables: internal motivations, which are (Push) variables that drive individuals to travel and external (pull) variables that attract individuals to a certain destination. Push and pull variables are related to what drives tourists, as they cover internal and external factors (Md et al., 2023). These variables are capable of inducing or affecting travel, holiday taking, or multi-destination travel. Push variables are internal factors like prestige, boredom, and desire for adventure, while pull variables include the physical attractiveness of the destination, weather, and cultural events (Uysal et al., 2008). 

There is a need to focus on external motivators or pull factors, as they help to consider the motives and choices of tourists in advance. In fact, Pektas (2022) studied push and pull factors in Turkey and found that these factors influence tourist behavior: destination awareness and loyalty, perceived quality, and economic value. Further, a cross-sectional study on the tourists visiting Langkawi Island, Malaysia, hypothesizes that both push and pull factors influence satisfaction and cause tourists to revisit the destination (Md et al., 2023). Other studies have also confirmed the fact that there are differences in groups and segments where the motivation towards cultural tourism differs among young UAE nationals (Prayag & Hosany, 2014). In South Africa, a cross-sectional study examined the cultural motives and their effects on tourists’ destination decisions (Douglas et al., 2023). 

In addition, the study of international tourists in Malaysia argues that knowledge and learning are the main motivational factors that compel international tourists to visit Penang, while history and culture are the main motivational attributes that attract tourists to the city (Abdul Hamid et al., 2022). Likewise, Novotna and Kunc (2020) employed a survey study of affluent Czech tourists and, based on the push and pull theory, hypothesized that learning about destinations is the key reason for tourism travel and that destination attractiveness is the most important pull factor.

The push and pull theories offer a broad number of internal and external factors that influence tourists and will reflect the role of hotel services as an external factor to the maximum extent. With regards to the capstone project, the pull variable can be hotels that provide new services that will facilitate multi-destination travel. Also, push factors can be incorporated into the service offerings of hotels in order to suit the needs of their clients.

Research Gap

There exists a gap in research on how hotel services can motivate tourists to engage in multi-destination activities. The capstone project uses the push and pull model to explore how hotel services influence tourist decisions. Particularly, the model pull factors can truly represent innovative hotel services and will enable the independent study of the influence of each hotel service on leisure travellers. This study seeks to fill the gap in research by analysing what motivates tourist selections and investigates hotels’ strategic role in lifting the attractiveness of multi-destination travel. 

This literature review has explored the complexity and dynamics of multi-destination travel. Throughout the review, it is evident that a gap in research remains in understanding how hotel services influence tourists’ decisions to engage in multi-destination travel. In addition, academic studies stress that both push and pull factors are instrumental in motivating tourists to engage in multi-destination travel. This review underlines the importance of linking theoretical frameworks with practical applications to provide actionable insights for hotels to strategically enhance the multi-destination travel experience and introduce services that can act as a pull factor to motivate tourists. This research is intended to be the trigger for further studies into the hotel pull factors and their influence on motivating tourists.

Research Methodology

The capstone project focuses on using quantitative analysis obtained through a survey to study motivations, as it produces statistical results despite the inherent limitations of quantitative research in capturing tourists’ emotional and psychological motivations. Quantitative studies allow for the quantification of relationships between variables and groups and are essential for analysing the impact of hotel services. However, quantitative analysis limits the research in obtaining a detailed understanding of tourists’ motives and emotions. While researchers emphasise the significance of qualitative research methods in revealing tourists’ motivations and behaviours, both quantitative and qualitative research approaches have contributed to understanding tourists’ motives (Zhu et al., 2020). In addition, due to time and budget limitations, quantitative studies permit the researchers to collect more data at a lower cost than qualitative studies.

Survey Design

The survey used a five-point Likert scale ranging from 1= indicates not at all important or influential to 5=indicates extremely important or influential. The survey has three main sections. The first section is designated for collecting the demographics of participants and their travel experience. It includes age, gender, income, leisure spending patterns and participants’ travel frequency. The second section assessed the push factors and internal motivations like culinary or shopping experiences. The third and final section evaluates the pull factors and external motivations that are influenced by hotel services, such as logistics and personalised packages. This approach allows an analysis of both internal and external factors or push and pull motivations separately that influence tourists to engage in multi-destination travel.

Data Collection

The survey was distributed to EHL MBA students by using the university’s mailing list, posted on my personal LinkedIn profile, and shared through my mailing list. This approach was chosen due to its ease of access and practicality, which allows for a timely and cost-effective collection of survey responses. However, there is a limitation in using this sampling strategy as it may not fully represent the broader population of travellers. Efforts were made to ensure a diverse range of travel experiences among respondents to capture varied perspectives on multi-destination travel.

Data Analysis

Microsoft Excel program was used to analyse the data. The data was cleaned and organised to ensure consistency and accuracy. Demographic data was analysed using descriptive statistics, including means and frequencies. Likert scale responses were also analysed using frequencies. Two further types of analysis were used to examine the data:

First, multiple regression analysis was used to assess the impact of multiple independent variables, specifically the push and pull factors, on the dependent variable, which is the likelihood of engaging in multi-destination travel. This analysis was conducted using Excel’s regression analysis tool, evaluating coefficients and p-values to determine the significance and strength of the relationships. Second, an Analysis of Variance (ANOVA) was conducted using Excel’s ANOVA tool to compare differences between groups and determine if there were any significant differences between genders, age, and income level in the likelihood to travel to multi-destinations. A p-value of less than 5% was used to determine significant factors. 

Research Limitations

The capstone limitations include the exclusive use of quantitative methods, geographical biases due to the distribution method, limited survey questions to ease the analysis, and an English-only survey. Additionally, the reliance on distributing the survey to EHL MBA students and through personal networks introduces a selection bias, as this sample may not fully represent the broader population of travellers. 

In addition, it is difficult to capture the full range of tourist motivations in a quantitative survey, possibly limiting the understanding of tourist motivations. However, the survey includes a range of questions that will capture tourists’ motivations to help mitigate the limitations posed by quantitative research. Additionally, efforts will be made through international channels to offset the geographical biases and ensure the survey reaches a diverse audience. Other limitation is the use of basic statistical models in analysis due to the requirements of this capstone project and limited knowledge in advanced statistical methods.

Data Analysis and Discussion

The chapter disucsses and analyzes the results collected from respondents. A total of 155 samples were collected using SurveyMonkey, and due to inconsistencies in two respondents’ answers, the relevant two respondents’ results were omitted from the analysis, resulting in a total of 153 valid survey responses that were analyzed.

Demographic Analysis

The respondent demographic characteristics are summarised in Table 1. The survey respondents’ gender consisted of 54.25% males (n=83) and 45.75% females (n=70). A wide range of respondents age ranging from 18 to 76 years with a mean age of approximately 39.80 years. The distribution of respondents age was dominant by middle aged respondents as 31.37% were between 30-39 years (n=48), 42.48% were between 40-49 years (n=65) (Table 1).

Table 1

Demographic Characteristics

Multiple Destination Leisure Trips

Annual household income of respondents was as follows: 14.38% with an income below $40,000, 18.95% with an income between $40,000 to $59,999, 7.19% with an income between $60,000 to $79,999, 7.19% with an income between $80,000 to $99,999, 12.42% with an income between $100,000 to $119,999 and 39.87% with an income of $120,000 and above. This spread was diverse and had diverse representations of genders, ages, and income groups in the analysis.

Regarding planning and whom they travel with during their leisure travel, the highest responses were 47.71% that travel with their family and children, followed by 26.80% that prefer to travel with a partner or spouse. 46.41% of respondents plan everything themselves and 42.48% share planning responsibilities.

The types of accommodation most preferred by respondents during leisure travel were luxury hotels, 41.18%, 26.14% preferred upscale hotels, and the rest stayed in other accommodations. Preferred mode of travel followed the same theme as 43.79% prefer airline first or business class and 36.60% prefer airline economy class and the rest use other modes of transportation. 

In terms of the budget for a typical 1-week leisure trip, the responses were 31.37% spend between $2,000 to $4,999, 24.84% spend between $5,000 to $9,999, and 16.99% spend $10,000 and above. Respondents were asked about their intentions regarding future trips that will include multiple destinations and how many of their leisure trips in the last two years included multiple destinations: 13.73% had none, 49.67% had 1-2 trips, 28.10% had 3-5 trips and 8.50% had more than five trips. 

When asked that in the next two years how many times they intend to travel to multiple destinations in a single trip, the responses were: 9.80% do not intend to travel to multiple destinations, 56.86% intend to travel 1-2 times, 28.10% intend to travel 3-5 times, and 5.23% intend to travel more than five times.

Table 2

1-week Leisure Trip

Push Factors

Push factors are the intrinsic motivations that drive individuals to seek out new experiences, escape their routine, and fulfil personal desires during travel. The analysis of these factors includes the extent to which respondents’ budgets influence their travel decisions, as well as their preferences for cultural and experiential activities, relaxation, and personal well-being. The detailed analysis of the push factors influencing respondents’ travel decisions is presented in Table 3.

Financial and Planning Constraints

Respondents indicated varying degrees of influence that budget has on their decision to engage in multi-destination travel, with 11.11% stating it is not at all influential, 18.30% slightly influential, 31.37% moderately influential, 29.41% very influential, and 9.80% extremely influential. On average, the influence of budget on travel decisions was moderate (M = 3.08; see Table 3).

Cultural and Experiential Motivations

The influence of cultural experiences such as visiting museums and historical sites was rated as not at all influential by 11.11%, slightly influential by 22.22%, moderately influential by 26.80%, very influential by 26.80%, and extremely influential by 13.07%. On average, cultural experiences had a moderate influence (M = 3.08; see Table 3). Adventure activities like hiking and bungee jumping were considered not at all influential by 17.65%, slightly influential by 21.57%, moderately influential by 21.57%, very influential by 20.92%, and extremely influential by 18.30%. On average, the influence of adventure activities was moderate (M = 3.02).

Culinary experiences, including food tours and wine tasting, were rated not at all influential by 7.84%, slightly influential by 10.46%, moderately influential by 26.80%, very influential by 30.07%, and extremely influential by 24.84%. On average, culinary experiences had a high influence (M = 3.54). Social interactions were seen as not at all influential by 20.92%, slightly influential by 21.57%, moderately influential by 24.84%, very influential by 16.34%, and extremely influential by 16.34%. On average, social interactions had a moderate influence (M = 2.86).

Relaxation and Personal Well-being

The need for relaxation and escaping from routine was rated as not at all influential by 2.61%, slightly influential by 7.19%, moderately influential by 17.65%, very influential by 36.60%, and extremely influential by 35.95%. On average, the influence of relaxation and escape from routine was high (M = 3.96). The importance of shopping experiences was rated not at all influential by 18.30%, slightly influential by 14.38%, moderately influential by 25.49%, very influential by 23.53%, and extremely influential by 18.30%. On average, shopping experiences had a moderate influence (M= 3.09).

Historical and Cultural Discovery

The influence of exploring historical sites was rated not at all influential by 7.84%, slightly influential by 20.92%, moderately influential by 24.18%, very influential by 31.37% (n = 49), and extremely influential by 15.03%. On average, exploring historical sites had a moderate influence (M = 3.25).

Attending local events, festivals, or celebrations was rated not at all influential by 8.50%, slightly influential by 20.26%, moderately influential by 29.41%, very influential by 26.80%, and extremely influential by 15.03%. On average, attending local events had a moderate influence (M = 3.20). The desire to discover unique places not visited by friends was rated not at all influential by 10.46%, slightly influential by 9.80%, moderately influential by 23.53%, very influential by 31.37%, and extremely influential by 24.84%. On average, discovering unique places had a high influence (M = 3.50).

Appreciation of Natural Beauty

Enjoying the natural beauty of destinations was rated not at all influential by 3.27%, slightly influential by 7.19%, moderately influential by 18.95%, very influential by 30.07%, and extremely influential by 40.52%. On average, enjoying the destination’s natural beauty had a high influence (M = 3.97).

Table 3

Push Factors

Pull Factors

Pull factors are the external influences and services offered by hotels and destinations that attract individuals to travel. The analysis of these factors includes the availability of amenities and logistical conveniences that enhance the travel experience. The detailed analysis of the pull factors influencing respondents’ travel decisions is presented in Table 4.

Amenities and Services

The presence of amenities like spas, swimming pools, and fitness centres was rated not at all influential by 10.46%, slightly influential by 20.26%, moderately influential by 24.18%, very influential by 26.80%, and extremely influential by 18.30%. On average, the influence of spa and fitness centres was moderate (M = 3.22).

Guided and Customized Experiences

The influence of guided access to local attractions and travel experience programs was rated not at all influential by 15.69%, slightly influential by 18.30%, moderately influential by 23.53%, very influential by 27.45%, and extremely influential by 15.03%. On average, the influence of guided access programs was moderate (M = 3.08).

Customised travel packages tailored to personal interests were rated not at all influential by 13.73%, slightly influential by 18.30%, moderately influential by 26.14%, very influential by 27.45%, and extremely influential by 14.38%. On average, the influence of customised travel packages was moderate (M = 3.10).

Logistical Conveniences

The importance of simplified logistics such as packing and unpacking was rated not at all influential by 10.46%, slightly influential by 22.88%, moderately influential by 18.95%, very influential by 30.07%, and extremely influential by 17.65%. On average, the influence of simplified logistics was moderate (M = 3.22).

Flexible check-in and check-out times were rated not at all influential by 3.92%, slightly influential by 11.11%, moderately influential by 18.30%, very influential by 38.56%, and extremely influential by 28.10%. On average, the influence of flexible check-in and check-out times was high (M = 3.76).

The availability of hotel-provided transportation between destinations was rated not at all influential by 10.46%, slightly influential by 12.42%, moderately influential by 27.45%, very influential by 28.76%, and extremely influential by 20.92%. On average, the influence of hotel-provided transportation was moderate (M = 3.37).

Technological Enhancements

The importance of digital and contactless services was rated not at all influential by 11.76%, slightly influential by 20.92%, moderately influential by 22.88%, very influential by 29.41%, and extremely influential by 15.03%. On average, the influence of digital and contactless services was moderate (M = 3.15).

Table 4

Pull Factors

The descriptive statistics presented above offer valuable insights into the demographics and motivations of the survey respondents. Two types of further advanced statistical analyses was used to understand the impact of various push and pull factors on the likelihood of engaging in multi-destination travel and differences among groups, multiple regression analysis and Analysis of Variance (ANOVA).

Multiple Regression and Analysis of Variance

These analyses will help us assess the significance and strength of the relationships between the independent variables (push and pull factors) and the dependent variable (likelihood of engaging in multi-destination travel) and examine differences between demographic groups based on these factors.

Multiple Regression Analysis

The multiple regression analysis will quantify the influence of various push and pull factors on the likelihood of engaging in multi-destination travel. This analysis evaluates the coefficients and p-values of each independent variable to determine the strength and significance of their impact.

Push Factors Regression Analysis

The regression analysis of push factors on the likelihood of engaging in multi-destination travel revealed that the overall model was significant, explaining 34.6% of the variance in travel likelihood. The F-statistic value of 6.78 suggests that the variance explained by the model is substantially greater than the variance not explained by the model, with a p-value less than 0.01, indicating strong statistical significance. 

The natural beauty of destinations had a significant positive impact on the likelihood of engaging in multi-destination travel. Respondents who rated natural beauty highly were more likely to engage in multi-destination travel and had a p-value of 0.016, indicating strong statistical significance. 

Other factors were not found to have significant impacts on the likelihood of engaging in multi-destination travel. While these factors had varying coefficients, none of them showed a statistically significant relationship with the dependent variable in this analysis. Only the natural beauty of destinations significantly influenced the likelihood of engaging in multi-destination travel (see Table 5).

The regression analysis of push factors on the likelihood of engaging in multi-destination travel revealed that the overall model was significant, explaining 34.6% of the variance in travel likelihood. The F-statistic value of 6.78 suggests that the variance explained by the model is substantially greater than the variance not explained by the model, with a p-value less than 0.01, indicating strong statistical significance. 

The natural beauty of destinations had a significant positive impact on the likelihood of engaging in multi-destination travel. Respondents who rated natural beauty highly were more likely to engage in multi-destination travel and had a p-value of 0.016, indicating strong statistical significance. 

Other factors were not found to have significant impacts on the likelihood of engaging in multi-destination travel. While these factors had varying coefficients, none of them showed a statistically significant relationship with the dependent variable in this analysis. Only the natural beauty of destinations significantly influenced the likelihood of engaging in multi-destination travel (see Table 5).

Table 5

Regression Analysis of Push Factors Influencing Likelihood of Engaging in Multi-Destination Travel

Pull Factors Regression Analysis

The regression analysis of pull factors on the likelihood of engaging in multi-destination travel showed that the overall model was significant, explaining 27.36% of the variance in travel likelihood. The F-statistic value of 7.80 suggests that the variance explained by the model is substantially greater than the variance not explained by the model, with a p-value less than 0.01, indicating strong statistical significance.

Among the pull factors, flexible check-in and check-out time had a significant positive impact on the likelihood of engaging in multi-destination travel. Respondents who valued flexible check-in and check-out times were more likely to engage in multi-destination travel, with a p-value of 0.0009, indicating very strong statistical significance.

Other factors were not found to have significant impacts on the likelihood of engaging in multi-destination travel. Although these factors had varying coefficients, none showed a statistically significant relationship with the dependent variable in this analysis.

In summary, among the pull factors, only the timing of travel significantly influenced the likelihood of engaging in multi-destination travel. The overall model was effective in explaining a notable portion of the variance in travel likelihood, indicating that the predictors used in this analysis offer meaningful insights into travel behaviour (see Table 6).

Table 6

Regression Analysis of Pull Factors Influencing Likelihood of Engaging in Multi-Destination Travel

Combined Push and Pull Factors Regression Analysis

Due to the limitations of Microsoft Excel, which restricts the number of variables in regression analysis to 16, variables were selected based on their p-value significance from the earlier push factors regression analysis. For the pull factors, all variables were included since our primary focus is to study the impact of pull factors and hotel services on travel behaviour. The combined regression analysis of key push and pull factors on the likelihood of engaging in multi-destination travel revealed that the overall model was significant, explaining 41.9% of the variance in travel likelihood. The F-statistic value of 6.13 suggests that the variance explained by the model is substantially greater than the variance not explained by the model, with a p-value less than 0.01, indicating strong statistical significance.

Among the factors analysed, only the natural beauty of destinations and flexible check-in and check-out times had significant positive impacts on the likelihood of engaging in multi-destination travel. Respondents who rated natural beauty highly were more likely to engage in multi-destination travel, with a p-value of 0.0057, indicating strong statistical significance. Similarly, flexible check-in and check-out times significantly influenced travel likelihood, with a p-value of 0.0017.

Other factors were not found to have significant impacts on the likelihood of engaging in multi-destination travel. While these factors had varying coefficients, none of them showed a statistically significant relationship with the dependent variable in this analysis (see Table 7).

Table 7

Combined Regression Analysis of Push and Pull Factors Influencing Likelihood of Engaging in Multi-Destination Travel

Analysis of variance (ANOVA)

The ANOVA is used to compare the differences between groups based on the likelihood of engaging in multi-destination travel. By examining the p-values and group means, it can be determined if there are statistically significant differences in the motivations for multi-destination travel among different respondent groups.

Gender And Likelihood to Travel

A one-way ANOVA was conducted to compare the effect of gender on the likelihood of travelling. There was no significant effect of gender on the likelihood of travel as the p-value was 0.679, which is more than 5% (see Table 8).

Table 8

ANOVA Single Factor for Gender

Age and likelihood to travel

A one-way ANOVA was conducted to compare the effect of age groups on the likelihood of travel. There was no significant effect of age groups on the likelihood of travel as the p-value was 0.255, which is more than 5% (see Table 9).

Table 9

ANOVA Single Factor for Age

Income Levels and Likelihood to Travel

A one-way ANOVA was conducted to compare the effect of income levels on the likelihood of travel. There was no significant effect of income levels on the likelihood of travel as the p-value was 0.127, which is more than 5% (see Table 10).

Table 10

ANOVA Single factor for Income Levels

Furthermore, motivational factors that are significant, such as natural beauty and flexibility, have been chosen for further analysis due to their significance in predicting tourists’ likelihood to travel based on their significant impact in the initial regression models.

Gender and Natural Beauty Motivation

A one-way ANOVA was conducted to compare the effect of gender on the influence of natural beauty. There was no significant effect of gender on the influence of natural beauty as the p-value was 0.244, which is higher than 5% (see Table 11).

Table 11

ANOVA Single Factor for Gender

Gender and Flexibility in Check-In/Check-Out

A one-way ANOVA was conducted to compare the effect of gender on the influence of the flexible check-in and check-out feature. There was no significant effect of gender on the influence of the flexible check-in and check-out feature as the p-value was 0.456, which is higher than 5% (See Table 12).

Table 12

ANOVA Single Factor for Gender

Discussion

The purpose of this study was to examine the influence of push and pull factors on tourists’ decisions to engage in multi-destination travel using the push and pull model. Furthermore, the research focused on understanding how various push and pull factors represented by hotel services can impact tourists’ motivations and intentions to engage in multi-destination travel.

Discussion on Push Factors

The regression analysis showed that the natural beauty of destinations was a significant push factor influencing tourists’ likelihood to engage in multi-destination travel. This aligns with existing literature emphasising the importance of scenic and aesthetic appeal in motivating travel decisions (Uysal et al., 2008). Natural beauty had a statistically significant positive impact, suggesting that destinations with beautiful landscapes can be more attractive for tourists to engage in multi-destination travel. Overall, the model represents 34.59% of the total variances. 

We can reject the idea that all push motivations are equal and that there is a specific significant push factor, which, in our case, is natural beauty. Besides, we were able to reject the idea that push motivations are not a significant predictor of engaging in multi-destination and that the model can predict 34.59% of the total variances. Another factor that was rated highly but had no significance in predicting tourists’ behaviours is relaxation and escape from routine, which had the highest mean at 3.97 but did not show significant impacts in the regression analysis.

Discussion on Pull factors

Among the pull factors, flexible check-in and check-out times significantly influenced the likelihood of engaging in multi-destination travel, and it also has the highest mean among all pull factors. This indicates that flexibility, when offered by hotels, will play a crucial role in tourists’ travel decisions. We can reject the idea that all pull factors are equal and that flexibility is a significant predicting factor. Finally, the model represents 27.36% of the total variances and therefore we reject that pull motivations is not a predictor of tourists intentions to engage in multi-destination travel.

Discussion on Combined Push and Pull Factors

The combined regression analysis revealed that both natural beauty (push factor) and flexible check-in and check-out times (pull factor) significantly influenced the likelihood of engaging in multi-destination travel. This underscores the importance of both internal motivations and external services in shaping travel behaviour. This finding is supported by the literature, which emphasises that both internal motivations and external factors play crucial roles in travel decisions (Dann, 1977; Uysal et al., 2008). The push and pull theory, as discussed in the literature, addresses the internal desires that drive individuals to travel (push factors) and the external attributes that attract them to specific destinations (pull factors), highlighting how both dimensions are essential in understanding tourist behaviour (Md et al., 2023). 

Overall, the combined factors model represents 41.88% of the total variances, and this showed an improvement from the individual factor’s regression, and this further supports the existing studies (Md et al., 2023) that both internal and external factors are important in influencing tourist decisions. Besides, we can accept that both push and pull factors are influential motivations to tourists.

Demographic Differences

The ANOVA results indicated no significant differences in the likelihood of travelling based on gender, age, or income level. This suggests that the motivations and likelihood to engage in multi-destination travel are relatively consistent across different demographic groups. Based on the discussion, it is revealed that there are no significant differences among the demographics studied in determining the likelihood of travelling to multiple destinations.

Conclusion

This study contributes to the understanding of how hotel services influence tourists’ decisions to engage in multi-destination travel. The findings highlight the importance of both natural beauty and flexible hotel services in motivating multi-destination travel. This provides actionable insights for the hospitality industry. As push and pull factors are the basis of the research; therefore, conclusion revolves around them.

Push Factors

The most important motivational push factors based on survey results are natural beauty, relaxation and escape from routine, and seeking culinary experiences. Natural beauty was the highest, with an average score of 3.97. Respondents rated this factor highly, indicating that scenic landscapes, picturesque views, and overall aesthetic appeal significantly motivate them to explore multiple destinations. This suggests that destinations known for their natural beauty can attract more tourists who are looking for visually appealing and relaxing environments. The need for relaxation and the desire to escape from routine was rated second with an average score of 3.96. 

This factor indicates that tourists prioritise destinations that offer opportunities for unwinding and de-stressing, which can be fulfilled by visiting various relaxing locations within a single trip. Culinary experiences was ranked third with an average score of 3.54. Culinary experiences, such as food tours and wine tasting, are another significant push factor motivating tourists to engage in multi-destination travel. Tourists who enjoy exploring different cuisines and food cultures are likely to plan trips that include multiple destinations known for their unique culinary offerings.

Pull Factors

The most important motivational pull factors, according to the survey, are the possibility of checking in and checking out early or late, the hotel’s amenities, and transportation between hotels. The most preferred services were flexible check-in and check-out, which were given a mean score of 3.76. This service enables tourists to coordinate their travel timetables and is therefore useful and versatile for multi-destination travelers. Second to this was transportation from one destination to another facilitated by the hotel, which received a mean rating of 3.37. 

Another pull factor is the availability of transport by the hotels between the various places of interest. This service eliminates the need for transport and ensures that tourists can easily move from one place to another without any hustle. Hotel facilities and amenities and easy access facilities were ranked as the third most critical factor, with a mean score of 3.22. Facilities like spas, swimming pools, fitness centers, etc. are some of the reasons that make tourists visit hotels and specific destinations. These services complement the entire travel experience by providing leisure and entertainment, which are key attractions to multi-destination travel. On the other hand, some of the logistical solutions, like packing and unpacking, will help the tourists save time and improve their travel experience.

Recommendations for Action

The following are the suggestions that can be made to hotel managers, destination marketers, tour operators, and policymakers from the findings of this study to improve the attractiveness and satisfaction of multi-destination travel for tourists. These recommendations are intended to build on the extensive push and pull factors highlighted in the research to deliver better travel experiences.

Emphasize Natural Beauty in Marketing

Tourism boards and destination marketers should ensure that the natural scenery of the places is well captured and displayed in the advertisements. Beautiful, interesting, and engaging visuals and virtual tours of specific natural or aesthetically appealing sights would appeal to beauty-seeking tourists. Cooperate with local authorities and various environmentalist agencies to maintain and even improve the existing natural sights. This may involve preserving parks, beaches, and natural reserves as eye-catching places to visit for tourists.

Offer Flexible Check-in and Check-out Services

Check-in and check-out procedures must also be more relaxed to suit the general tourist timetable. This could involve offering early check-in and late check-out options for a small fee or as part of loyalty programs. Utilise technology to streamline the check-in and check-out process, such as mobile check-in/check-out apps, digital room keys, and automated systems that reduce wait times and enhance convenience.

Develop Comprehensive Travel Packages

Hotels should focus on creating and promoting customised travel packages. Such packages should include flexible timing options for check-in and check-out, focusing on culinary experiences, natural beauty and transportation between multiple destinations. These packages can cater to tourists looking for a seamless and hassle-free travel experience while focusing on culinary experiences.

Improve Infrastructure and Transportation

Local authorities to improve transportation infrastructure, making it easier for tourists to travel between multiple destinations. This includes enhancing public transport options, developing shuttle services, and improving road connectivity. Equally important is to promote seamless travel experiences by coordinating with other hotels, transport providers, and tour operators to offer integrated travel solutions that simplify the logistics of multi-destination travel.

Offer Hassle-free Packages

Hotels and tour operators can offer hassle-free packages that focus on seamless travel with flexibility in timings, transportation services between locations, and assistance in packing and unpacking and luggage transfers. Those services, coupled with locations that are known for natural beauty and culinary offerings such as food and wine tours, will be highly appreciated by tourists. In addition, hotels with facilities can have a competitive edge as they will offer the relaxation that is much sought after by tourists.

By implementing these recommendations, the tourism and hospitality industry can better meet the needs and preferences of tourists. It will also encourage more multi-destination travel and assist in dispersing tourist to more destinations and avoid over-tourism in certain areas. These actions will not only improve the travel experience but also contribute to the sustainable growth and development of the tourism sector.

Implications for the Hospitality Industry

Hotels can enhance their attractiveness to multi-destination travellers by offering flexible check-in and check-out times. This logistical convenience can significantly increase the likelihood of tourists choosing multi-destination travel. Destinations should emphasise their natural beauty in marketing campaigns to attract tourists interested in multi-destination travel. Scenic landscapes and aesthetic appeal are powerful motivators for tourists. While other hotel services, such as amenities and personalised packages, are important, they may not be primary drivers of multi-destination travel. However, offering a comprehensive package that includes these services can enhance overall tourist satisfaction.

Research Limitations

The study relied on a sample of MBA students and personal networks, which may not fully represent the broader population of travellers. Future research should include a more diverse and representative sample to validate the findings. The exclusive use of quantitative methods limits the depth of understanding regarding the emotional and psychological motivations of tourists. Future studies should incorporate qualitative methods to capture these aspects more comprehensively. The survey did not cover the entire spectrum of push and pull motivational factors as it will result in a more complicated study that is beyond the scope of the capstone project.

Future Research Directions

The need to understand the influences of hotel services in shaping tourists’ decisions is an area worth further research. Other potential push and pull factors that may influence multi-destination travel, such as social media influence, cultural tourism offering and environmental sustainability, are worth studying due to their reach and popularity. Apart from that, an exploration of the impact of hotel services on specific segments of tourists is worth researching. Solo travellers, families, and business travellers research will provide more targeted insights into the hospitality industry.