Abstract

Kenya’s tourism continues to rely heavily on wildlife. Of the approximately 922,000 annual international arrivals during the peak season between June and October, nearly 738,000 head for the Maasai Mara National Game Reserve to witness the seventh wonder of the world, the annual wildebeest migration. Several studies have been conducted based on construal level theory to establish the effect of temporal distance using various factors that determine travel decisions. However, to date, no study has been carried out to establish the effect of temporal distance on destination choice decision-making. As tourism consumption involves making a purchase decision now for a future point in time, this study evaluated the effects of temporal distance on the destination choice decision-making based on the construal level theory framework. The study adopted the survey approach based on a confirmatory research design. Using a sample of 144 drawn from a population of 230 tourists, data was collected and analyzed using correlation, ANOVA, and regression methods. The findings revealed that temporal distance has a positive and significant effect on decision-making regarding destination choice based on levels of construal measured through R=0.324; R2=0.105; β = 0.295; t= 3.024 > +2; F=9.145; and p=0.003<0.05. The study revealed that temporal distance has a significant effect on the decision process of choosing a destination. In conclusion, therefore, marketing communications targeted at tourists should be intensified well in advance of the season envisioned for traveling to increase the desirability of the destination and thus, influence more tourists to choose the destination. The study also contributes valuably to the literature on tourists’ destination choosing decisions based on temporal distance in the construal level theory framework.

Keywords: Temporal distance, Destination choice, International arrivals, Tourism, Construal level theory, Decision-making.

Received: 4 February 2021 / Revised: 14 June 2021 / Accepted:6 August 2021/ Published: 10 September 2021

Contribution/ Originality

The study contributes to the existing literature on tourists’ choice of a destination by taking into consideration the effect of temporal distance by adopting the Construal Level Theory (CLT), which has not yet been adopted in service industries such as tourism. And more so in a developing country like Kenya.

1. INTRODUCTION

Kenya ranks highly in the business environment and travel and tourism prioritization indices in comparison with other destinations within its league. Tourism has been identified as one of the focus areas for achieving double-digit economic growth and development in ‘Vision 2030,’ which is Kenya’s current blueprint for development (Vision, 2030). It has been further noted that tourism contains the capacity to positively contribute to the “Big Four” agenda (which is also a national development goal), the sustainable development goals, and ‘Agenda Africa 2063.’

However, one challenge with tourism is that the present-day tourist demands travel that is experiential (Tourism Strategic Plan 2018-2022). To maximize the experience, the tourist must be exposed to useful information targeted to them that will enable them to optimize their experience from the choice of destination. Tourist decision-making, therefore, will always be central to the tourism industry. Most studies involving tourist decision-making have been adopted from the consumer decision process established for goods. But it has also been observed that tourists form images of, and evaluate destinations based on the information they receive about the same, together with their personal goals (Bajs, 2015; Shih & Do, 2016). It is therefore vital to capture this aspect of information that informs image formation and the effect it has on the tourist’s decision-making process.

1.1. Destination Choosing Process

The conventional consumer behavior model shows that a consumer goes through five stages when deciding to purchase, namely need recognition, evaluation of alternatives, selection of the best alternative, purchase of the best alternative, and post-purchase evaluation. Studies on tourists’ decision-making also indicate that this decision-making process is further influenced by other aspects such as the determinants of tourists’ behaviors and tourist motivators. Individual determinants of tourist behavior include individual circumstances, knowledge of the destination and products, attitudes and perceptions, and past experiences. On the other hand, motivators include social status, culture, emotions, personal development, and physical engagements like exercise. In addition, tourism being a business, it is important that the right kind of customers be attracted, and this can be achieved through segmenting the market and identifying appropriate tourists, marketing promotion activities, and facilitating the visit (Sri Lanka Tourism Development Strategic Plan 2011-2016). To attract the right tourists, it is imperative that their decision-making processes be understood with respect to choosing travel destinations (Smallman & Moore, 2010).

Traditionally, tourism consumer behavior research has been influenced by research outside tourism, notably the classical buyer behavior school of thought (Decrop & Snelders, 2004; Sirakaya & Woodside, 2005). The offspring of this school of thought, whether the grand models of consumer behavior (Engel, Kollat, & Blackwell, 1968) or tourism consumer behavior models, view consumers as rational decision-makers. Consumer behavior research in tourism continues to be marked by studies underpinned by the assumption of rational decision-making. These studies explore causal relationships by means of ‘variance’ analysis, which estimates how much of an outcome (or dependent variable) is explained by relevance (or independent variable) (Smallman & Moore, 2010). The theories of reasoned action and planned behavior, which are based on the expectancy-value model of attitudes (Fishbein, 1963), are examples of sequential theories which continue to be used (Decrop & Snelders, 2004; Decrop, 2010; Hyde & Lawson, 2003) without considering that some of the decisions are made prior to arrival, while others are made while at the destination (Choi & Choi, 2019).

The complexity of the tourist decision-making process is also increased by the fact that many travel decisions are highly influenced by situational factors (Decrop & Snelders, 2004). It has also been argued that such levels of complexity can only be fully captured through a focus on the process of tourist decision-making. Yet, research on tourist decision-making continues to focus little on aspects of the process.

According to the Construal Level Theory (CLT), events in the near future are represented in concrete terms, whereas events in the distant future are represented as abstractions. Liberman and Trope (1998) tested the temporal distance by studying the roles of feasibility and desirability when considering proximal and distal decisions and discovered that distant future events are construed at a high level using central and abstract features. However, the application of CLT and the psychological distance from the process of choosing a tourist destination is just beginning to be explored. Nenkov (2012) conducted an experiment on the effect of psychological distance on persuasive messages and found that the effect of messages could be maximized by framing them to match the specific stage that the consumer was at in the decision-making process. Lee, Liu, and Tzeng (2012) performed a case study on motivations and travel distance with temporal advance and established that motivations to travel to a destination remain unchanged over time. Kim and Ritchie (2014) carried out experiments on the application of CLT on promotional strategies in the hotel industry and established that temporal distance had a significant impact on the evaluations involving different descriptions of hotel information.

Basoglu and Yoo (2015) conducted another experiment on the effect of temporal distance on hedonic and utilitarian travel decisions and concluded that temporal distance was a significant evaluation input criterion in hedonic travel decisions. Kastenholz (2010) researched temporal distance in travel intention behavior and concluded that longer temporal distances raised desirability, while longer spatial distances tended to act as impediments to traveling. From the studies reviewed, it is evident that the effect of temporal distance on the process of choosing a tourist destination has not been carried investigated. Besides, Smallman and Moore (2010), after reviewing the process studies of tourists’ decision-making, argue for the development of process studies involving the narrations and activities of individuals as important additions to the existing body of knowledge. This study is, therefore, a contribution since it was carried out on tourists in one of the world’s most popular tourist destinations, the Maasai Mara National Game Reserve in Kenya.
The variables of the study were conceptualized, as shown in Figure 1.

Figure-1. Model of conceptual framework.

2. METHODOLOGY

This paper employed a mixed-method inquiry design, adopting the quantitative design embedded in the positivism paradigm. The target population consisted of tourists who visited the Maasai Mara Game Reserve between the periods of January and March 2020 from seven different countries. For this study, eight hotels and four camps, constituting 10% of the target population, were sampled from the estimated 118 hotels and camps in the Maasai Mara Game Reserve. Convenient sampling was used in selecting the 144 tourists out of the target population of 230 from seven different countries distributed as follows: 1) Chinese—11, 2) American—31, 3) Indian—8, 4) Japanese—11, 5) European—26, 6) Moroccan—11, and 7) Mexicans—16. These had the highest number of bookings at Maasai Mara Game Reserve. The study sample size was obtained using the sample size formula developed by Krejcie and Morgan (1970), as shown below:

The data was collected through a self-administered questionnaire survey. A five-point Likert scale was adopted and used to collect data from the respondents. The independent variable was the perceived temporal distance, and different items including decisions concerning timing of the trip, information about destination attractions, information to help with preparations, and personal objectives for taking the trip were used to measure this variable. The respondents were asked to provide their socio-demographic characteristics and respond to specific statement items as provided in the Likert Scale. The Statistical Package for Social Sciences version 23 was used to facilitate the data processing. The data collected was analyzed quantitatively where descriptive statistics of frequency, percentages, and mean and standard deviation helped to describe the characteristics of the data and inferential statistics of correlation, while ANOVA and regression analysis were used to assess the relationship between the variables. The hypothesis was tested at a 5% level of confidence.

3. FINDINGS

A total of 144 questionnaires were distributed to the tourists. The study recorded a response rate of 89.6%, which was 129 of the total number of tourists considered for the study, and this was appropriate for the analysis.

The validity of the instrument was determined using the factor analysis where the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was used, and from the analysis, it was noted to be 0.5, which was acceptable, as shown in Table 1. According to a KMO, a value above 0.4 is considered an appropriate measure of the validity of a research instrument.

Table-1. KMO and Bartlett's test.

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.500
Bartlett's Test of Sphericity	Approx. Chi-Square	11.854
	df	1
	Sig.	0.001

The reliability was computed using the alpha reliability coefficient, and the results indicated a coefficient value of 0.780, as shown in Table 2. This was considered appropriate given that the expected threshold, according to Kothari (2004), is 0.7 and above. The instrument was therefore considered appropriate.

Table-2. Cronbach’s Alpha Test for Reliability.

	Cronbach's Alpha	N of Items
Study variables	0.780	15

3.1. Descriptive Data Analysis

The study sought to discover the distribution of the respondents in terms of their gender, age, education level, occupation, income level, and the purpose of their visit to the Maasai Mara Game reserve. The results are presented in Table 3.

The results in Table 3 show the majority of visitors who were willing to participate in the study were male at 67%, while only 33% were female. Regarding the age bracket, the results indicated that of the respondents, 32% were aged from 36-45 years, 25% were aged from 46-55 years, and 22% were aged above 55 years. Only a total of 21% were aged below 35 years. This implies that most visitors were above 35 years. The occupation levels of the respondents indicated that of them, 34% were businesspeople, 32% were retirees, 23% were in full-time employment, and the rest, 11%, were students.

Table-3. Demographic characteristics.

Gender	Percentage
Male	67%
Female	33%
Age bracket
15-25 years	6%
26-35 years	15%
36-45 years	32%
46-55 years	25%
More than 55 years	23%
Education
Lower than college education	4%
College education	20%
Graduate degree and above	52%
Occupation level
Formal employment	23%
Businessperson	34%
Retired	32%
Students	11%
Income level
Less than $1,000	6%
From $1,000-$4,000	21%
From $4,001-$6,000	23%
From $6,001-$8,000	29%
More than $8,000	21%
Purpose of visit:
Leisure / holiday	47%
Work related trip	32%
Education	21%

The study also revealed that of the respondents, 29% were in the income bracket between $6,001 and $8,000, and 23% were in the bracket between $4,001 and $6,000. Only 21% had an income of more than $8,000. This implies that 50% of the respondents earned an income of more than $6,000. Regarding the purpose of the visit, the study established that of the respondents, 47% indicated that they had visited for leisure/ holiday, 32% had visited for work-related assignments, while the rest, 21%, had visited for academic purposes. This section was significant because it helps to create a clear picture for the policymakers about the characteristics of tourists who visit the country. This becomes an important planning tool for marketers and other strategic planners in providing information for future planning.

3.2. Information Sources and Making a Final Destination Choice

It was important for the researcher to identify the various sources of information available to tourists and how this information influences the final decision on the choice of the destination. The respondents were required to rate various information sources, viz personal experience, friends/ colleagues/ relatives, print media, number of visits, television, internet, and travel agents/ marketers by how effective they were in the final destination choice. The results are presented in Figure 2.

The results presented indicate that information gathered out of personal experience was rated as being very important at 92%, followed by information provided by friends, colleagues, and relatives at 80%, then the number of visits the tourist has made to various destinations 78% was rated as being very important in a choice of destination by tourists. This implies that word of mouth and personal experiences play a very significant role in enhancing decision-making for a tourist’s destination choice. The other sources, though important, were rated lower. Tour agents and marketers were rated as being least important at 36%, indicating that tourists do not fully trust the information provided on these platforms.

Figure-2. Information sources and destination choice.

This could be because they are seen as advancing public relations activities rather than providing actual, useful information. The internet, television, and print media were considered important, with ratings of above 60%, meaning the information provided could be relied upon by tourists. The results support the findings of Jeuring (2016), Pike and Page (2014), and Gren and Huijbens (2015), who indicated that the experience of people reinforced by various marketing information, which is more of a push and pull strategy that provides an imbalance in the information provided, affects the tourist’s decision-making process in the choice of a destination.

3.3. Understanding Temporal Distance

The study sought to assess tourists’ understanding of the implication of temporal distance regarding their choice of a destination. The study established that the majority of the respondents from India and Morocco with (M= 4.201 and M=4.301 respectively) indicates that there is a high consideration for temporal distance in the choice of a destination. This was followed by Chinese (M=3.325), Mexican (M=3.264), American (M=3.173), and European (M=2.509). This indicates that temporal distance plays a significant role among tourists from the East and Asian areas as compared to those from the western world. This is true, given that international tourists make travel decisions some months before the actual time of travel, and therefore make decisions based on construal formed because of the information they receive from various sources. The results are in support of Kastenholz (2010), who also noted that the choice of a destination by tourists is determined by the distance that is not just physical but also cultural. The results are shown in Table 4.

Table-4. Understanding temporal distance.

	SA	A	U	D	SD	Mean	Std. Dev.
	%	%	%	%	%
Chinese	20.5	8.5	2.5	13.5	55.0	3.325	0.734
Americans	26.5	7.5	4.5	9.0	52.5	3.173	0.701
Indians	69.5	12.0	2.0	10.0	6.5	4.201	0.928
Japanese	28.5	11.5	2.5	4.5	53.0	3.204	0.708
Europeans	30.5	10.5	4.5	13.0	41.5	2.509	0.554
Moroccans	61.5	20.0	2.0	7.0	9.5	4.301	0.825
Mexicans	18.5	41.5	2.5	4.5	33.0	3.264	0.718

3.4. Correlation Analysis

The study sought to establish whether there was a statistical correlation between the variables that can help to justify that temporal distance influences consumer behavior and thus affects the choice of a destination by tourists. The results are presented in Table 5.

Table-5. Test for Correlation.

	Temporal distance
Pearson Correlation	0.615**
Sig. (2-tailed)	0.002
N	144

Note: **. Correlation is significant at the 0.01 level (2-tailed).

The results in Table 5 show that the correlation between temporal distance as an independent variable and consumer behavior as a dependent variable is strong and significant (R= 0.615; P = 0.002<0.05). This shows that temporal distance is an important construal factor that influences tourists’ decision-making process while choosing a destination, which helps us to understand how tourists make their choices of a destination they intend to visit. The correlation value is strong and positive, indicating that the choice of a destination by a tourist depends on the temporal distance assumed by that tourist.

3.5. Regression Analysis

The regression model was computed to establish the expected percentage change in a tourist’s choice of a destination given a percentage change in the temporal distance. The results are presented in Table 6.

Table-6. Regression analysis model summary.

Model	R	R Square	Adjusted R Square	Change Statistics
Model	R	R Square	Adjusted R Square	F Change	df1	df2	Sig. F Change
1	0.615a	0.379	0.245	16.759	1	143	0.002

The results in Table 6 show that the model is highly significant, given that p = 0.002 < 0.05. The R square of 0.379 indicates that the choice of a destination by a tourist intending to travel improves by 37.9% with a change in the understanding of temporal distance on the basis of construal, as a factor in the tourists’ decision-making process.

Further analysis using the analysis of variance model also indicated that the regression model is a perfect predictor of the effect of temporal distance on the decision-making process among tourists. The results are presented in Table 7.

Table-7. ANOVAa.

Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	4.796	1	4.796	16.759	0.002b
	Residual	40.896	143	0.286
	Total	45.592	144

The results in Table 7 show that the model is a good predictor of the relationship that exists between the variables under test, given that the F value=16.759 > the critical F value of 3.95. This model is statistically significant since the p-value = 0.002 < 0.05. This model can therefore be used confidently to reject the null hypothesis that temporal distance factors have no effect on a tourist’s decision-making process, and hence the choice of a destination by a tourist. The results of the regression coefficients used to model the relationship between the variables are presented in Table 8.

Table-8. Regression coefficients.

Model		Unstandardized Coefficients		Standardized Coefficients	T	Sig.
Model		B	Std. Error	Beta	T	Sig.
1	(Constant)	2.437	0.566		4.304	0.000
1	Temporal distance	0.295	0.097	0.324	3.024	0.002

The results in Table 8 show that temporal distance influences a tourists’ decision-making process by 29.5%, which implies that a unit change in the tourist decision-making model is influenced by a 29.5% change in temporal distance factors. The model is statistically significant given that the T statistic value = 3.024, which is higher than the +2 threshold.

The linear mode can be developed as follows:
Tourists’ destination choice = 2.437 + 0.295X1+ 0.324

Accordingly, it was noted that construal factors tend to influence consumer decision-making, and hence social distance is noted to have a positive effect on the consumer decision-making process. This implies that temporal distance influences the consumer decision-making process. This contributes to the indication that the relationship between distance and purchase decision-making is quite complex and calls for further analysis in future studies.

3.6. Summary

The purpose of the paper was to assess the effect of temporal distance on tourists’ choice of a destination. The paper focused on assessing the age, gender, education level, occupation, income level, sources of information, and tourists’ understanding of temporal distance and how it affects their decision-making process. The results established that most of the tourists who participated in the study were aged above 45 years, the majority were male with an education level above college, and the income level for most of the tourists was $6,000 and above. The main source of information was personal experiences and word of mouth from friends and family members. The results further noted that there was a significant correlation between temporal distance and a tourist’s choice of destination.

3.7. Conclusion

The study sought to assess the influence of integrating the dimension of temporal distance on the tourist consumer decision-making model for a tourist’s choice of a destination. The study considered temporal distance as a significant factor in consumer behavior influencing the tourist’s choice of a destination. It is concluded that temporal distance plays a critical role in a tourist’s destination decision-making process.

3.8. Recommendations

Based on the findings presented in this paper, there are implications for theory, practice, and further research.

3.8.1. Implications for Theory

The findings of this study reveal that temporal distance based on the construal level theory has a significant effect on the decision-making process that a tourist engages when choosing a destination. This adds to the extant literature in tourism research, especially that which concerns destination choice.

3.8.2. Implications for Practice

Based on the findings of this study, it is recommended that those who operate tourism businesses and those in charge of tourism destination marketing must consider the integration of psychological distance and construal levels, particularly temporal distance, in designing and communicating with source markets. These findings not only advance the understanding of the role of temporal distance in a tourist’s decision-making process but also offer implications regarding strategies that can be employed by policymakers to enhance their policies on how to market tourist destinations. For instance, with the knowledge that tourists form construal based on the information that they receive about the destination and that travel decisions are made months prior to actualization, tourism business owners and marketers will design the communication in such a way that the construal formed therefrom are effective enough to result in the destination being chosen. Also equipped with the knowledge that desirability increases with temporal distance, information will be sent out well in advance to further increase the chances of the destination being chosen.

3.8.3. Limitations of the Study

The study focused on international tourists visiting the Maasai Mara National Reserve in Kenya. The study also confined the investigation to only the effects of temporal distance on the tourist decision-making process in choosing a destination. Furthermore, the study was limited by the methodology of the sampling method, convenient sampling, which is less ideal in a study with a large population. There is a need for future studies to consider using a larger sample size and more probability sampling methods to ensure representation and improve the generalizability of the findings.

Funding: This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

Acknowledgement: All authors contributed equally to the conception and design of the study.

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