Demographic factors and travel motivation among leisure tourists in Tanzania

Abstract

Purpose

To examine demographic factors and travel motivations among leisure tourists in Tanzania. Specifically by examining the influence of demographic factors on travel motivation among local and international leisure tourists in Tanzania.

Design/methodology/approach

Approach is quantitative and applied descriptive statistics, independent t-test and ANOVA.

Findings

The findings showed that age, gender and family size as demographic factors significantly influenced travel motivation among local and international leisure tourists.

Research limitations/implications

Future studies to consider different approaches including collection of data during the peak season, use qualitative method and conduct studies in other parts of the country to explore demographic factors and travel motivations of tourists.

Practical implications

To assist tourism stakeholders in their design of promotional tools to market tourism products/services to different tourists as opposed to homogeneous marketing campaigns.

Originality/value

Examined the influence of demographic factors and travel motivation among local and international leisure tourists in the context of Tanzania.

Citation

Kara, N.S. and Mkwizu, K.H. (2020), "Demographic factors and travel motivation among leisure tourists in Tanzania", International Hospitality Review, Vol. 34 No. 1, pp. 81-103. https://doi.org/10.1108/IHR-01-2020-0002

Introduction

Travel motivation is commonly acknowledged as a crucial concept to most tourism professionals and theorists (Lam and Hsu, 2006). Travel motivation has been known as a driving force behind understanding behavior (Venkatesh, 2006). The concept of travel motivation is not new (Pearce and Caltabiano, 1983). Researchers around the globe have applied travel motivation to determine individual's satisfaction level (Snepenger et al., 2006; Lemmetynen et al., 2016; Celik and Dedeoglu, 2019; Preko et al., 2019), predict leisure participation levels (Yan and Halpenny, 2019), identify travel patterns (Pearce, 1987; Cavagnaro and Staffieri, 2015), understand tourists’ travel decisions and consumption behavior (Chang et al., 2015) as well as to develop more effective strategies and policies to increase demand for tourism (Heung et al., 2001; Papatheodorou, 2006). The complex nature of this concept has pushed many researchers to come up with different travel motives. However, the central themes behind it revolved around push and pull factors/motives. Push and pull factors have been extensively employed to assess tourists' travel motivations (Kanagaraj and Bindu, 2013; Michael et al., 2017; Wijaya et al., 2018).

In Tanzania, tourism plays a significant role in the country's economy and one among the crucial sectors in generating foreign exchange (Tanzania Tourism Sector Survey, 2018). The sector indirectly offered 1,452,000 jobs in 2017 from 1,389,000 jobs offered in 2016 (WTTC, 2017). Tourism in Tanzania generates about 17.5% of the total country's GDP and 25% of total foreign currency earnings (Tanzania Tourism Sector Report, 2017). Tanzania is famously known for tourist attractions and home to the famous Roof of Africa, the Mount Kilimanjaro. Following these attractions, Tanzania has pulled thousands of international visitors from different parts of the world, thereby making the country be known as one of the competitive tourist destinations in sub-Saharan Africa (Mkumbo, 2010). The WTTC (2017) projects a rising trend by 6.8% in 2027 of 2,267,000 international tourists to Tanzania.

On the other hand, the arrivals of domestic tourists to various tourist attractions in the country are not in the same pace as international travel market. Factors such as limited promotion, awareness, low income, inadequate information, media usage, marketing and service quality challenges such as infrastructure and trained staff have been reported to be among the factors affecting the performance of domestic tourism in Tanzania (Wade et al., 2001; Mariki et al., 2011; Mkwizu, 2018a; 2019; Mkwizu et al., 2018). Some of the initiatives were done by the government to boost the travel market including setting preferential rates, establishment of the tourism training college for training purposes and introduction of intensive marketing campaigns to create awareness of tourism attractions. Despite all these efforts, there are more international tourists than locals visiting national parks. In 2018–2019, there were 731,351 international tourists compared to 464,933 locals that visited national parks (Tanzania National Parks, 2019). The differences in tourist numbers can be attributed to the fact that Tanzania is the only country in the world that has allocated 25% of her land for wildlife and game-controlled reserves (Tanzania Tourism Sector Survey, 2018). On the other hand, domestic tourists have been seen traveling mainly to visit their friends or relatives and sometimes they travel for leisure (Mariki et al., 2011). Therefore, there is need for more studies on whether the importance of travel motivations differs among the two groups.

Literature on consumer behavior acknowledges that travel motivation and needs are related (Goodall, 1988), and this means that tourists may decide to take a vacation to satisfy their physiological needs such as food, health and learning. However, the decision of choosing a given destination to visit has been closely linked with sociodemographic characteristics. Woodside and Lysonski (1989), Um and Crompton (1990) and Moscardo et al. (1996) are among the earliest studies that examined the role of demographic factors on tourists' destination choice with findings showing a link between demographic factors and visitors’ participation in tourism activities. For instance, increasing free time and disposable income have provided people with an opportunity to take part in outdoor activities (Ibrahim and Cordes, 1993). Factors such as age and family structure have an impact on the decision of an individual to participate in leisure activities (Foot, 2004).

Demand for leisure is also affected by individuals' age and gender (Mieczkowski, 1990; Collin and Tisdell, 2002). Collin and Tisdell (2002) found that demographic factors have a role to play in influencing visitors' participation in tourism activities as well as the selection of vacation destination. What is not known is the role that demographic factors such as age, gender and family size play in influencing tourists’ travel motivation in Tanzania. Studies that examined the influence of demographic factors on travel motivation in Tanzania are limited. Existing literature in Tanzania has mainly examined demographic factors in relation to nature-based tourism and media such as Mariki et al. (2011) and Mkwizu (2018a). Therefore, this study intends to uncover the missing gap by examining demographic factors and travel motivation among local and international leisure tourists in Tanzania.

Furthermore, this study is important in providing insight information on various demographic factors such as age, gender and marital status in influencing tourists’ travel motivation particularly for Tanzania. The information from this study can help tourism stakeholders to segment tourists based on their demographic traits.

Literature review

Travel motivation

Travel motivation is viewed as an internal force that arouses and pushes an individual from choosing a particular destination with the intention of getting the desired benefits and satisfaction (Pyo et al., 1989; Yoon and Uysal, 2005). Motivation is viewed as a sociopsychological factor that pushes an individual to a new destination and take part in leisure activities (Iso-Ahola, 1982; Beard and Ragheb, 1983). This study defines travel motivation as an internal motive that drives a particular tourist to take a leisure trip in Tanzania.

The complex nature of travel motivation has caused many researchers to come up with different travel motives. However, a good number of them focused on push and pull factors. These dimensions have been used extensively in most of motivation studies (Kim and Lehto, 2013). Due to the importance of these two factors, researchers such as Dann (1977), Crompton (1979), Iso-Ahola (1982) and Epperson (1983) developed different motivation dimensions based on the idea of push and pull travel motives.

Demographic factors

Mazilu and Mitroi (2010) defined demographic factors as descriptive segmentation technique, whereby sociodemographic factors are directly involved. Examples of sociodemographic factors commonly used by tourism experts (Ma et al., 2018; Mkwizu, 2018a, 2018b) include age, gender, family life cycle, education, income and nationality. These variables are believed to be accurate in describing tourism market and predicting travel behavior patterns (Weaver and Oppermann, 2000).

Age is considered to be a crucial demographic factor by tourism stakeholders because leisure demand can effectively be predicted through visitors' age (Mieczkowski, 1990). Age is reported to have positive influence on individual's desire for relaxation and nature exploration (Ma et al., 2018). According to Spence (2002), the probability of an individual to participate in wildlife activities varies with age, meaning that the probability of activity participation increases when an individual is young and decreases as that individual grows old.

Gender is one of the major factors influencing travel demand (Collin and Tisdell, 2002). The travel patterns between men and women vary based on their travel motivation. According to Collin and Tisdell (2002), men travel more than women. Men travel for business-related activities while women do travel mainly for visiting friends and relatives and prefer taking shorter-distance trips compared to men (Moriarty and Honnery, 2005). Females are reported to be highly involved in shopping and are more affected by intrapersonal or structural constraints than men (Josiam et al., 2005; Andronikidis et al., 2008). Cost, time and family commitments are among limitations for women to be active in travel activities (Scott, 2005; Alexandris and Carrol, 1997). As a result, women have been seen participating more in shopping, dining and cultural activities than outdoor activities such as skiing while men are more likely to participate in adventure activities (Xie et al., 2008).

Marital status is one of the factors that affect vacation decisions (Kattiyapornpong and Miller, 2008). It is important for marketers to have such information because they can use such details to predict one's travel patterns. For instance, Lee and Bhargava (2004) found that married couples spend less time enjoying leisure than singles. This is due to the fact that married couples have social and family obligations that limit their time to undertake holiday vacation or participate in sports activities (Henderson, 1990; Downward and Rasciute, 2010). Singles prefer shorter but frequent trips (Biearnat and Lubowiecki-Vikuk, 2012). Singles are assumed to have more free time to engage in various activities compared to those with a family, for example, more time playing musical instruments, singing, dancing, watching TV and traveling for social activities (Lee and Bhargava, 2004). The literature further highlights that Passias et al. (2017) found that never-married mothers have more time to spend on leisure than married mothers. In contrast, Vernon (2010) suggests that married women have more time to engage in leisure than single mothers. For the purpose of this study, age, gender and marital status were included in the analysis. The reason for these factors is due to the fact that there is limited information regarding the roles they play in influencing travel motivation of tourists in the context of Tanzania.

The Beard and Ragheb travel motivation theory

Beard and Ragheb (1983) developed the leisure motivation variables based on the idea from the work of Maslow (1970). The leisure motivation theory contains four major travel motives, which determine satisfaction that a visitor may gain from taking part in leisure activities. The travel factors identified were: “Intellectual” – these include items such as learning and exploring; “social” – covers the desire for developing friendship and esteem of others; “competence-mastery” – involves issues such as health and fitness and lastly “stimulus avoidance” – which simply describes the desire to relax and escape the routine life. This study employs the Beard and Ragheb theory for the purpose of assessing tourist travel motivation. Beard and Ragheb's theory was chosen because since its establishment in 1983, many researchers (Mohsin et al., 2017; Albayrak and Caber, 2018; Jia et al., 2018) have employed and validated it.

In 1983, Beard and Ragheb also noted that using leisure motivation scale (LMS) to study travel motivation is reliable due to the 32 items measuring Cronbach's alpha ranging from 0.89 to 0.91. Past scholars such as Yusof and Shah (2008) and Chen et al. (2018) have used LMS by Beard and Raghed (1983) to study motivation in tourism. For example, Chen et al. (2018) explored travel motivation for Chinese residents using LMS of 32 items to measure motivation due to its reliability and validity. Chen et al. (2018) found that there were significant differences of gender, marital status and education in leisure behaviors. This study not only used the Beard and Ragheb theory but also applied LMS by Beard and Ragheb (1983) due to its reliability and validity.

Demographic factors and travel motivation

Several researchers have examined travel motivation in relation to demographic factors. Some of these works include a work by Saayman and Saayman (2009). Researchers examined the relationship between sociodemographic, behavioral and motivational factors for tourists that visited Addo Elephant National Park. The findings of this study revealed that tourists were motivated to travel to the national park because of the need for nature, activities, escape, attractions, photography, family and socialization. It was further pointed out that both sociodemographic and motivational factors influence visitors’ spending decisions.

Differences in travel motivation are noted in past studies such as You et al. (2000), Kozak (2002), Jönsson and Deonish (2008), Kim and Prideaux (2005), Fan et al. (2015), Gu et al. (2015), Albayrak and Caber (2018) and Marques et al. (2018). The findings of these studies concluded that travel motives differ among travelers from different countries (You et al., 2000; Kim and Prideaux, 2005), among students from different countries (Marques et al., 2018), across various destinations and nationalities (Kozak, 2002), among tourists participated in white water rafting activity (Albayrak and Caber, 2018), across different forms of tourism (Gu et al., 2015) as well as those from different countries visiting the same destination (Jönsson and Deonish, 2008).

Yung-Kun et al. (2015) explored factors related to tourists' motivation to visit Taiwan as well as the demographic segmentation of these foreign tourists. The results indicated that push motivation factors such as enlightenment, freedom, shopping, diverse attractions, culture connections, sport facilities and wildlife play a crucial role in the motivation of foreign tourists. These tourists were later clustered into five main motivation groups to include scenery/knowledge seekers, accessibility/expenditure seekers, relaxation/relation seekers, novelty/experience seekers, sport/service seekers based on five demographic traits (gender, age, marital status, nationality and income).

Additionally, Fan et al. (2015) compared motivation and intention of cruise passengers from different demographic profiles in China. They found that travelers from different demographic caliber differ in terms of their travel motivation. For example, singles had higher mean values for travel motivations such as discovering and exploring nature than those who were married. Researchers believed that singles have ample time and freedom to try new and exciting things compared to married travelers. Furthermore, Ma et al. (2018) examined the relationship among tourists' sociodemographic characteristics, motivation and satisfaction as a way of predicting their visitation patterns and travel behaviors to forest nature reserves in Guangdong. The findings from multiple regression analysis revealed that some of the sociodemographic factors had a role to play in influencing travel motivation. For example, age was positively correlated with travel motivation called sense of relaxation and nature exploration. However, education level negatively influenced social travel motivation.

Older people or senior travelers are motivated by the desire for novelty (Jönsson and Deonish, 2008). However, a study by Luo and Deng (2008) found age negatively influenced travel motivation and that younger tourists prefer seeking for novelty compared to older travelers. A study by Mohsin (2008) was done to examine the impact of sociodemographic variables on Mainland Chinese holidaymakers who traveled to New Zealand. The overall findings of one-way ANOVA revealed that there is a significant relationship between travel motivation and demographic factors such age and educational level. The findings are supported by previous studies of Park and Mok (1998) that travel motivation varies with age. Irimias et al. (2016) conducted a study aimed at exploring demographic characteristics in influencing religious tourism behavior among 345 Hungarians who traveled for pilgrimage. It was found that their travel motives differ with age; senior travelers see educational purposes and feelings of national identity related to sacred sites as crucial travel motives while young tourists did not picture that to be of any value to their travel motives. Njagi et al. (2017) conducted a study to provide an in-depth understanding of the factors affecting travel motivation of youth travelers in Kenya. The study revealed that push factors are more crucial in influencing youth travelers in Kenya than the pull travel motives.

The overall findings from the previous studies confirmed that sociodemographic factors have a role to play in influencing tourists’ travel motivation. However, these studies focused more on push and pull factors among youth travelers in Kenya (Njagi et al., 2017) and among travelers who traveled to Taiwan (Yung-Kun et al., 2015). Furthermore, the existing studies also looked at the relationships between sociodemographic factors and travel motivation among cruise passengers who traveled to China (Fan et al., 2015), those who traveled to national parks (Saayman and Saayman 2009) and those who traveled to sacred places for religious purposes (Irimias et al., 2016). From the reviewed literature, it is evident that sociodemographic factors are crucial in predicting travel patterns of tourists.

However, there are still inconclusive remarks regarding the influence of sociodemographic factors on travel motivation. For example, age was reported to be among the key factors affecting travel motivation (Irimias et al., 2016; Ma et al., 2018). On the other hand, age was reported to have a negative effect on travel motivation (Luo and Deng, 2008). Other demographic factors such as education were also reported to have a negative effect on travel motivation (Ma et al., 2018) while marital status was seen to be a significant factor in influencing travel motivation among cruise passengers (Fan et al., 2015). Furthermore, the existing studies such as Baniya and Paudel (2016) have examined the effects of demographic factors on travel motivation using push and pull items. Other studies in Tanzania (Wade et al., 2001; Mariki et al., 2011; Mkwizu, 2018a; 2018b; 2019; Mkwizu et al., 2018) have focused on nature-based tourism, history, market analysis and media. Therefore, this study specifically intended to examine the extent to which demographic factors such as age, gender and marital status influenced travel motivation among local and international leisure tourists guided by the motivation theory and scale items developed by Beard and Ragheb (1983).

Methodology

Research instrument

The research questionnaire was divided into two major parts. The first part covered general information about the respondents. Demographic information such as age, gender, marital status and family size. This section composed of six questions. The second part comprised information related to tourists' travel motivation. Respondents were asked to rank the list of travel motivation statements according to their level of importance, indicating whether those statements describe their travel motivation on a Likert scale of 1 (Not important at all) to 7 (Extremely important). Examples of travel motivation items were to learn things around me, to challenge my abilities and to relax mentally. This study employed Likert scale developed by Kozak (2002), who highlighted that Likert scale is appropriate to be used in tourist-based studies. This study adopted the shortest version of LMS, which consists of 32 items to measure different travel motives because of its Cronbach's alpha reliability ranging from 0.89 to 0.91 as pointed out by Beard and Ragheb (1983). The shortest version is appropriate to be used in a research constrained by time and can be applied within less time compared to 48 items from the original scale (Beard and Ragheb, 1983).

Sampling design

A convenience sampling technique was adopted to get the appropriate sample for the study. Ferber (1977) noted that convenience sampling as one form of nonprobability sampling can reduce the impact of nonrandom convenience sampling by making sure that the generated findings are a true representative of the population. Additionally, convenience sampling is one among the appropriate sampling techniques to be used when collecting data from the actual tourist settings (Madrigal and Kahle, 1994).

Data collection

This study used a quantitative approach and survey strategy as the research design. Before collection of data, the survey instrument was pretested by distributing the questionnaires to 50 international tourists found on the beaches of Zanzibar and Pemba islands. Respondents were randomly and conveniently selected to take part in the study. The pretesting exercise was done to assess the survey suitability, readability, eliminate any vague items and determine the response rate. Data was collected from January 2017 to May 2017. A self-administered open-ended questionnaire was employed to 300 local and international tourists who traveled to and within Tanzania for leisure. Tourists at the Julius Nyerere International Airport lounges and those on the beaches of the islands of Zanzibar and Pemba were conveniently approached and asked to take part in the study. The decision to take part in the study was left entirely to tourists. Those who agreed to participate in the study were given a survey questionnaire to fill in.

Data analysis

The collected data was analyzed using the aid of a Social Science Statistical Package (SPSS) version 20. This study selected SPSS, which has descriptive statistics such as frequencies and percentages in order to avail demographic characteristics of the respondents. In addition, the independent sample t-test was used to test the differences in travel motivation among local and international tourists. ANOVA assisted this study to test the effect of the independent variable (demographic factors) on the dependent variable (travel motivation). Data was cleaned first to check whether there was missing data, outliers and determine the data distribution pattern before analysis. Cronbach's alpha coefficients were employed for purposes of examining internal data consistency. Content, construct, convergent and discriminant validities were tested using CFA.

Results

Respondents' demographic characteristics

Out of 300 surveys from each group, only 250 from each group were recognized as a useable survey, representing a token useable return rate of 83%. The overall descriptive statistics from Table 1 shows that most tourists from each group were between the ages of 18 and 30 (45.6% for internationals and 49.2% for locals), and less than 10% were covered by the senior tourists (4.4% for internationals and 6% for locals). The gender distribution showed that majority of international tourists were males (61.2%) and also for local tourists most were males (61.8%). Over 50% of all tourists had a university education and employed in different fields. On marital status, 53.2% of all the international tourists were married while 49% of all locals were married.

The findings in Table 1 further indicate that 47% of internationals and 51.2% of all locals were singles. On family size distribution, the majority of international tourists have three children and above while 40% of all locals proved to have less than three children. This suggests that the sampled respondents were mostly young educated male tourists who are employed. In addition, the differences between the international and local tourists are noted in marital status.

Furthermore, Table 2 indicates that the largest group of international tourists was from South Africa (10%) followed by Australia (8.8%) and Kenya (8%). There were very few international tourists from countries such as Bangladesh, Brazil, Cameroon and Zurich. These results suggest that the young educated male international tourists were mostly from South Africa.

Reliability results

The alpha coefficient for the total scale was 0.933 and the alpha values for each of the subscales ranged from 0.880 to 0.907, which are above the acceptable threshold (0.70) as suggested by Hair et al. (1998). The summary of the results is presented in Table 3.

Validity results

All 32 travel motivation items were subjected to CFA for validity testing as it is presented in Table 4. Content validity for the observed items was tested for consistency, easy of understanding and appropriateness by members of the academic staff together with tourist experts. Construct validity was examined using composite reliability (CR) and average variance explained (AVE). The overall findings indicate that CR and AVE surpassed the threshold values of 0.70 and 0.50, respectively (Yap and Khong, 2006). Therefore, it can be concluded that the indicators for all constructs met the reliability thresholds and thus qualified for further analyses. Convergent validity indicated that the standardized factor loadings for all the items were above the acceptable range of 0.5 as indicated by Tabachnick and Fidell (2007). In this study, all the CR and AVE were above the recommended value of 0.7 and 0.5 respectively. Discriminant validity was assessed using Fornell and Larcker’s approach of 1981. In order to achieve discriminant validity, AVE of each construct was compared with the shared variance between two constructs. For all the items, the AVE was higher than the shared variance (MSV). The results indicated that all the constructs had acceptable discriminant validity as presented in Table 4.

Assumptions guiding independent t-test

Data normality

Before testing for the differences in travel motivation among the tourists, data normality was performed using descriptive statistics. Skewness and kurtosis values were used to determine data normality. Meyers et al. (2006) highlighted that if the values of skewness and kurtosis range within ± 1.00, these are evidence of data normality. Pallant (2011) advised that when one is dealing with large enough sample sizes (e.g. 30+), the violation of normality assumption may not cause any significant problems. For this study, the skewness and kurtosis values were within the cutoff points as was highlighted by Meyers et al. (2006) and Pallant (2011).

Differences in the importance of travel motivation among international and local leisure tourists

An independent sample t-test was conducted to test whether the importance of travel motivation differs among international and local tourists. This meant comparing travel motivation mean scores for international and local tourists. First of all Levene's test was performed to see whether there was equal variance in the data set. The overall results show that this assumption was met in eight travel motivation items (p ≥ 0.005) while for the rest of the travel motivation items, the assumption was violated as it is presented in Table 5, Table 6, Table 7 and Table 8. The results in Table 5, Table 6, Table 7 and Table 8 indicate that there was significant difference in scores for travel motivation among international and local leisure tourists. In Table 5, the findings show that local tourists had higher mean values than international tourists for travel motivation (intellectual motivation) such as to learn about myself (M = 5.67, SD = 1.288), to explore new ideas (M = 5.73, SD = 1.294), to expand my knowledge (M = 6.05, SD = 1.136), to be creative (M = 5.68, SD = 1.494), to use my imagination (M = 5.22, SD = 1.757) and to satisfy my curiosity (M = 5.81, SD = 1.265).

In Table 6, the findings show that local tourists had higher mean values compared to international tourists for travel motivation (social motivation) such as to build friendship with others (M = 5.70, SD = 1.353), to interact with others (M = 5.66, SD = 1.428), to develop close friendships (M = 5.47, SD = 1.573), to reveal my thoughts (M = 5.11, SD = 1.657), to be socially competent and skillful (M = 5.66, SD = 1.425), to gain a feeling of belonging (M = 5.62, SD = 1.387) and to gain others' respect (M = 5.24, SD = 1.827).

Table 7 indicates that local tourists had higher mean values than international tourists for travel motivation (mastery competency motivation) such as to be active (M = 5.76, SD = 1.296), to develop physical skills and abilities (M = 5.59, SD = 1.375), to keep in shape physically (M = 5.39, SD = 1.702), to use my physical abilities (M = 5.28) and to develop physical fitness (M = 5.21, SD = 1.685). The remaining mastery competency motives had no significant differences.

Table 8 reveals that local tourists had higher mean values for travel motivation (stimulus avoidance motivation) such as to calm down (M = 4.89, SD = 1.674), to be alone (M = 3.32, SD = 2.064), to relax physically (M = 5.39, SD = 1.499), to relax mentally (M = 5.63, SD = 1.426), to rest (M = 5.53, SD = 1.508), to relieve stress and tension (M = 5.48, SD = 1.506) as well as to unstructure my time (M = 5.48, SD = 1.506) compared to international tourists. The remaining stimulus avoidance motives had no significant differences.

Differences in travel motivation among tourists by age, gender and family size

Univariate ANOVA tests the interaction between each dependent variable with an independent variable; in short, ANOVA explains changes in the dependent variable, which are caused by the interaction between the independent variables. First, multivariate tests were performed to assess whether there is a significant effect between independent and dependent variables. Second, univariate ANOVA was applied to examine the effect of independent variables on specific dependent variable. Previous scholars have also used ANOVA in examining demographic factors with motivation such as Urosevic et al. (2016). Using Pillai's trace results in Table 9 indicated that there was significant effect between travel motivation across age F (96.000) = 1.396, p = 0.008, across gender F (32.000) = 2.005, p = 0.001, across family size F (32.000) = 2.610, p = 0.000, across the interaction between age and family F (96.000) = 1.154, p = 0.023 as well as the interaction between age, gender and family size F (96.000) = 1.514, p = 0.001.

A separate ANOVA shown in Table 10 was performed to each travel motivation at alpha level of 0.005, and it was found that there were significant differences among age groups on the need to develop physical skills and abilities F (312.594) = 4.972, p = 0.002 while for males and females results show the desire to explore new ideas among age groups F (18.906) = 4.451, p = 0.035 and the desire to discover new things F (16.081) = 3.899, p = 0.049.

Furthermore, the results indicated that desire to develop physical skills and abilities was significantly different among tourists who have small and large family size F (156.811) = 22.428, p = 0.000. Other differences were reflected on travel motivation such as the desire to develop physical fitness F (167.625) = 18.772, p = 0.000 as well as to unstructure my time F (150.424) = 14.955, p = 0.000.

This study also examined the contribution of the interaction effects of the independent variables on the dependent variable. Table 10 shows that the interaction between age and family size was significant to travel motivation such as to relieve stress and tension F (319.051) = 6.112, p = 0.000, to develop physical fitness F (320.517) = 5.695, p = 0.001, ŋ² = 0.034, to unstructure my time F (318.159) = 5.386, p = 0.001, as well as to use my physical abilities F (311.260) = 3.322, p = 0.020. Additionally, the interaction effect between age, gender and family size was significant to travel motivation such as to satisfy my curiosity F (35.223) = 2.693, p = 0.046, as well as to develop close friendships with others F (38.729) = 2.634, p = 0.049.

Discussions of findings

This study reveals that leisure tourists from Australia, Kenya, South Africa, Germany, France, the United Kingdom and United States were motivated to travel to the country with the intention of discovering and learning new things. Furthermore, similar groups of tourists were extremely motivated to visit Tanzania for the sake of relaxing mentally, revealing stress and tensions of their daily routine activities. The results imply that leisure tourists may have more than a single travel motive when visiting a particular destination. These findings support the idea developed by Crompton (1979) that tourists' motivations are multiple and because of that they may have different reasons of taking either domestic or international trips (Mayo and Jarvis, 1981). Researchers also add that some people take trips not only to fulfill their physiological desires (food, climate and health) but also to satisfy their psychological needs.

Furthermore, the study also found that tourists from the United Kingdom and United States had strong views that they were motivated to visit the country for social reasons such as building friendship with others. This can be explained by differences in tourists' culture. It has been identified that there are motivational differences between nationalities (Kozak, 2002). Culture associated with nationality has been extensively acknowledged to be one among the crucial factors differentiating individuals’ attitudes, beliefs and behaviors (Chen, 2000). National culture can be employed to reveal variations in the social behavior of different nationalities, especially in international settings such as tourism experiences (Kim et al., 2002). The findings of this study confirmed the results reported by Özdemir and Yolal (2016) that Americans and British people prefer to interact and socialize with other tourists when they travel. Additionally, Kozak (2002) pointed out that British tourists enjoy mixing themselves and having fun with other tourists when they travel. It seems that Tanzania is attracting tourists who have psychocentric personality. Individuals of this nature prefer visiting familiar places, having fun and relaxing when visiting new destinations (Plog, 1974).

Surprisingly, this study found that tourists, mainly from Kenya and South Africa, were motivated strongly to travel to the country for the intention of competing and being good at participating in leisure activities. This can be explained by the differences in the level of novelty seeking among tourists. Novelty seeking is one among the key reasons why tourists travel to new destinations (Dayour and Adongo, 2015). The findings of this study show that there is a possibility that tourists from Kenya and South Africa are sensation seekers. Individuals of this nature are risk takers, and this is why they prefer to travel to unfamiliar destinations (Pizam et al., 2004). Generally, tourists are attracted differently to different tourist attractions, and this is because they have different levels of tolerance for tourism experiences. Some people choose destinations where they can unwind their daily routine life while others look for destinations that can offer adventure life. The choice of a destination can sometimes be linked to tourists' personality traits. The findings of this study imply that Kenyans and South Africans may be allocentrics. Individuals of this caliber are usually seeking for arousal from unexpected and surprising stimuli (Ryan, 1997), they are outgoing, confident, relatively anxiety free, like to feel in control, prefer to visit new destinations, desire to explore the world around them and are moderately risk takers (Plog, 1973, 1974).

This study found that there was no significant differences in travel motivation among leisure tourists who are single and those who are married. However, a minor difference was revealed on intellectual travel motives to single leisure tourists. It was revealed that single leisure tourists were highly motivated to travel to Tanzania for intellectual purpose. This finding is consistent with a study by Fan et al. (2015) that single people place higher value when it comes to discovering and learning new things compared to married ones. The finding of this study is not surprising since Tanzania is blessed with multiple tourist attractions ranging from game reserves, controlled conservation areas and national parks (URT, 2014). Other attractions include Mount Kilimanjaro, museums, historical sites and buildings. Following these attractions, it is not surprising to see single leisure tourists travel to the country for intellectual reasons.

The findings further indicated that married leisure tourists were more motivated to travel to the country, mainly by their desire to unwind their daily life's hustle. This could be due to the fact that married couples spend less time enjoying leisure than singles. In addition, married couples have social and family obligations that limit their time to undertake holidays (Henderson, 1990) or participate in learning activities as singles. For them, escaping travel motive makes sense since they have been experiencing routine hectic daily life; therefore, it is understandable to see them ranking this motive important. This finding somehow corroborates the views of Leonard and Onyx (2009) that relaxation and escape motivations are two key psychological motives that drive people to take overseas trips. The desire to take a vacation is closely associated with the desire to escape (Jarvis and Peel, 2010). Therefore, tourists often choose to take a vacation to a new destination with the intention of breaking from the daily routine life of home and work (Kim and Ritchie, 2012). The break gives people an opportunity to refresh their minds by taking active role in nonroutine leisure activities (Ritchie et al., 2010) as well as offering a platform for them to liberate themselves from tension and anxiety.

Furthermore, the study revealed that married leisure tourists traveled to the country for social reasons. This finding is somehow consistent with the study by Passias et al. (2017) that married mothers prefer to spend quality time with their children by engaging themselves in both active and social leisure compared to single mothers. Generally, tourism offers opportunity to bring people of different cultural backgrounds together (Brown and Lehto, 2005), but also offers avenue for them to meet and communicate with others (Dayour, 2013). This study also found that married leisure tourists had higher mean scores for mastery competency travel motives compared to singles. This finding implies that may be Tanzania attracts married leisure tourists who are sensational seekers because tourists differ in the way they consume and obtain novel experience (Lee and Crompton, 1992). Tourists who are high sensational seekers prefer to engage in adventure activities such as scuba diving (Heyman and Rose, 1980) as well as mountain climbing (Robinson, 1985). This group also prefers to travel to new places or meeting new people (Zuckerman, 1979). This finding can be supported by the fact that Tanzania is endowed with more than eight known mountains that attract international tourists from all over the world. Moreover, the country is surrounded with both sandy and clean beaches that offer opportunity for tourists to take part in scuba diving and other water sports activities.

Therefore, the discussion of results for this study has theoretical, practical and policy implications, which are further highlighted in the implications section of this paper.

Conclusions

Based on the findings and discussions, this study can conclude that in examining demographic factors and travel motivation among leisure tourists, there are influential factors. The demographic factors that influence travel motivation (intellectual, social, mastery competency and stimulus avoidance) among local and international leisure tourists in the context of Tanzania are age, gender and family size.

Implications

Theoretical implication

The overall findings from this study imply that theoretically, the Beard and Ragheb leisure motivation theory and scale can be used to determine tourists’ travel motives in Tanzania. Age, gender and family size significantly influenced intellectual, social, mastery competency and stimulus avoidance motives among local and international leisure tourists.

Practical implication

From a practical implication, the differences in travel motivation among tourists are not homogeneous; therefore, they are not supposed to be treated equally. What is important to tourists from South Africa may not be important to tourists from other countries. Therefore, the government of Tanzania through the Ministry of Tourism and Natural Resources (MNRT) and Tanzania Tourists Board (TTB) should make sure that they promote Tanzania as a destination for people to discover new things, hence attract tourists from South Africa, Kenya, Australia, Germany as well as tourists from France. Furthermore, Tanzania can also be segmented as a friendly and social destination as this will attract tourists from the United States and the United Kingdom. Additionally, destination managers need to make use of the existing attractions such as mountains, beaches, national parks and game reserves to position the country as an adventurous destination. This can help to attract more tourists from Kenya and South Africa.

Policy implication

From a policy perspective, the government, destination marketers, policymakers and tourism stakeholders should make use of the tourists' marital status data because such data can develop better promotion campaigns that match their travel motives. For example, single tourists had higher mean value for intellectual travel motives. This implies that tourist attractions such as museums, historical sites, rock paintings, old town and old buildings can be used to segment this target group. Since singles travel more and spend more time enjoying leisure than married couples, then it would be better for destination managers as well as policymakers to use this opportunity to position the country as a destination that helps tourists to discover new things. On the other hand, married tourists were reported to have higher mean values for most of mastery competency and social and stimulus avoidance travel motives. This implies that the destination managers should advertise tourist activities such as boat cruising, shopping, swimming, as well as beach sports activities for this group. These activities will help them to meet other people, to relax near the sandy beaches as well as to take part in various adventurous games.

Limitations and suggestions for further studies

This study examined travel motivation differences among leisure tourists who were married and those who were single. It did not cover widowers and those who were divorced. Focus was on international tourists who traveled to Northern tourist circuit and islands of Zanzibar and Pemba for leisure. Therefore, the results from the study may not be generalized beyond the selected population. This geographically limited survey may produce different results and conclusions in terms of the magnitude and the strength of relationships among variables. Tourists who visited other circuits (Southern tourist circuit) may have different opinion preferences regarding the importance of travel motives. Replication of similar studies in other tourist circuits should be done to see whether similar findings could be generated.

Additionally, this study employed nonprobability sampling. Therefore, this may affect the external validity. Other studies should try to adopt probability sampling design so as to avoid this problem. Furthermore, the data collection was done between January and May, which is the low season. Thus, the findings of this study are limited to this particular period. Therefore, the tourists who travel in different seasons, for instance, high peak season, might have different opinions regarding the importance of their travel motives. In tourism, seasonality limits the generalization of the study findings and should always be taken into consideration in the interpretation stage. Future research should conduct similar studies in different seasons to overcome this limitation. The obtained results can then be compared to identify similarities and differences between them. Also, the generated findings can be used to validate the findings of this study.

Table 1

Tourists’ demographic characteristics (age, gender, education, occupation, marital status and family size)

Variable	International frequency	Percent (%)	Domestic frequency	Percent (%)
Age
18–30	114	45.6	123	49.2
31–43	79	31.0	81	32.4
44–56	46	18.4	31	12.4
57+	11	04.4	15	06.0
Total	250	100	250	100
Gender
Male	153	61.2	152	61.8
Female	97	39.0	98	39.2
Total	250	100	250	100
Level of education
Primary	02	0.8	26	10.4
High school	26	10.4	33	13.2
Certificate	09	03.6	20	08.0
Diploma	35	14.0	32	12.8
University education and above	178	71.2	139	55.6
Total	250	100	250	100
Occupation
Employed	149	59.6	137	54.8
Unemployed	101	40.4	113	45.2
Total	250	100	250	100
Marital status
Single	117	46.8	128	51.2
Married	133	53.2	122	48.8
Total	250	100	250	100
Family size (number of children)
Large (3 children and above)	131	52.4	150	60.0
Small (0–2 children)	119	47.6	100	40.0
Total	250	100	250	100

Source(s): Fieldwork (2018)

Table 2

Tourists’ demographic characteristics (country of origin)

Variable	International frequency	Percent (%)	Domestic frequency	Percent (%)
Country of origin
Argentine	01	0.4	00	00
Australia	22	7.5	00	00
Austria	02	0.8	00	00
Bangladesh	01	0.4	00	00
Belgium	04	1.6	00	00
Benin	01	0.4	00	00
Brazil	01	0.4	00	00
Cambodia	01	0.4	00	00
Canada	01	0.4	00	00
Chile	03	1.2	00	00
China	09	3.6	00	00
Comoro	09	3.6	00	00
Denmark	02	0.8	00	00
DRC	01	0.9	00	00
Finland	02	0.5	00	00
France	01	2.9	00	00
Germany	11	4.9	00	00
India	18	6.5	00	00
Italy	01	0.9	00	00
Japan	03	1.2	00	00
Kenya	10	4.0	00	00
Korea	02	0.8	00	00
Malawi	03	1.2	00	00
Muscat	01	0.4	00	00
Mexico	01	0.4	00	00
Mozambique	01	0.4	00	00
Namibia	03	1.2	00	00
Nepal	01	0.5	00	00
Netherlands	01	0.4	00	00
New Zealand	01	0.4	00	00
Nigeria	07	2.8	00	00
Norway	02	0.8	00	00
Oman	06	2.4	00	00
Pakistan	02	0.9	00	00
Palestine	04	1.6	00	00
Philippines	01	0.4	00	00
Poland	03	1.2	00	00
Rwanda	01	0.4	00	00
South Africa	01	0.4	00	00
Spain	25	10	00	00
Sri Lanka	01	0.4	00	00
Sweden	02	0.8	00	00
Switzerland	13	5.2	00	100
Taiwan	04	1.6	00	00
Tanzania	01	0.4	230	100
UAE	00	0.0	00	00
Uganda	01	0.4	00	00
UK	05	0.2	00	00
USA	16	6.4	00	00
Zambia	16	6.4	00	00
Zimbabwe	02	0.8	00	00
Zurich	01	0.4	00	00
	01	0.4	00	00
Total	250	100	250	100

Source(s): Fieldwork (2018)

Table 3

Reliability results for IL, SO, MC and SA

Variable	Scale items	Scale if mean item deleted	Corrected item–total correlation	Cronbach's alpha if item deleted	Overall Cronbach’s alpha(α)
Intellectual motivation (IL)	To learn things around me (IL 1)	38.68	0.592	0.871	0.880
	To learn about myself (IL 2)	39.11	0.618	0.869
	To explore new ideas (IL 3)	38.71	0.774	0.852
	To expand my knowledge (IL 4)	38.36	0.701	0.861
	To discover new things (IL 5)	38.34	0.672	0.864
	To be creative (IL 6)	38.90	0.613	0.869
	To use my imagination (IL 7)	39.25	0.528	0.879
	To satisfy my curiosity (IL 8)	38.68	0.735	0.856
Social motivation (SO)	To build friendship with others (SO 1)	34.93	0.748	0.874	0.894
	To interact with others (SO 2)	34.82	0.711	0.878
	To develop close friendships (SO 3)	35.33	0.708	0.877
	To meet new and different people (SO 4)	34.65	0.549	0.891
	To reveal my thoughts, feelings or physical skills to others (SO 5)	35.69	0.651	0.883
	To be socially competent and skillful (SO 6)	35.06	0.752	0.874
	To gain a feeling of belonging (SO 7)	35.45	0.747	0.873
	To gain other's respect (SO 8)	35.62	0.564	0.894
Mastery competency motivation (MC)	To challenge my abilities (MC 1)	35.21	0.565	0.907	0.907
	To be good in doing them (MC 2)	35.24	0.721	0.893
	To improve my skill and ability in doing them (MC 3)	35.04	0.712	0.894
	To be active (MC 4)	34.61	0.648	0.900
	To develop physical skills and abilities (MC 5)	35.05	0.746	0.891
	To keep in shape physically (MC 6)	35.50	0.749	0.891
	To use my physical abilities (MC 7)	35.42	0.758	0.890
	To develop physical fitness (MC 8)	35.56	0.733	0.892
Stimulus avoidance motivation (SA)	To calm down (SA 1)	32.91	0.579	0.869	0.878
	To be alone (SA 2)	34.31	0.324	0.896
	To relax physically (SA 3)	32.47	0.712	0.856
	To relax mentally (SA 4)	32.15	0.725	0.855
	To avoid the hustle and bustle of daily activities (SA 5)	32.71	0.596	0.868
	To rest (SA 6)	32.30	0.743	0.853
	To relieve stress and tension (SA 7)	32.32	0.779	0.848
	To unstructure my time (SA 8)	32.66	0.719	0.854

Table 4

Validity results

	CR	AVE	MSV	ASV	SO	IL	SA	MC
SO	0.899	0.531	0.375	0.259	0.729
IL	0.889	0.504	0.320	0.231	0.546	0.710
SA	0.886	0.507	0.122	0.100	0.321	0.273	0.712
MC	0.905	0.548	0.375	0.272	0.612	0.566	0.349	0.740

Table 5

Independent t-test results for intellectual motivation (IL) among tourists

Travel motivation		t-test for equality of means
		t	df	Sig. (two-tailed)	Mean	SD	Partial Eta squared (%)
To learn things around me	I	−0.711	498	0.477	5.56	1.613
	L				5.66	1.529
To learn about myself	I	−6.766	437.305	0.000	4.69	1.905	0.20
	L				5.67	1.288
To explore new ideas	I	−2.383	498	0.018	5.43	1.512	1.1
	L				5.73	1.294
To expand my knowledge	I	−2.011	479.438	0.045	5.82	1.387	0.8
	L				6.05	1.136
To discover new things	I	0.852	498	0.394	6.00	1.234
	L				5.90	1.284
To be creative	I	−4.196	492.834	0.000	5.09	1.656	3.4
	L				5.68	1.494
To use my imagination	I	−2.332	498	0.020	4.86	1.654	1.1
	L				5.22	1.757
To satisfy my curiosity	I	−3.246	483.300	0.001	5.41	1.508	2.1
	L				5.81	1.265

Note(s): I = International Tourists, L = Local Tourists, SD = Standard Deviations

Table 6

Independent t-test results for social motivations (SO) among tourists

Travel motivation		t-test for equality of means
		t	df	Sig. (two-tailed)	Mean	SD	Partial Eta squared (%)
To build friendship with others	I	−5.968	472.733	0.000	4.88	1.713	6.7
	L				5.70	1.353
To interact with others	I	−3.828	498	0.000	5.14	1.582	2.9
	L				5.66	1.428
To develop close friendships	I	−7.257	478.233	0.000	4.32	1.933	9.6
	L				5.47	1.573
To meet new and different people	I	−1.686	498	0.093	5.46	1.454
	L				5.68	1.465
To reveal my thoughts, feelings or physical skills to others	I	−7.294	490.426	0.000	3.94	1.898	9.7
	L				5.11	1.675
To be socially competent and skillful	I	−7.002	477.033	0.000	4.66	1.763	8.9
	L				5.66	1.425
To gain a feeling of belonging	I	−11.389	457.908	0.000	3.93	1.882	20.7
	L				5.62	1.387
To gain other's respect	I	−7.469	494.423	0.000	3.96	1.990	10.1
	L				5.24	1.827

Note(s): I = International Tourists, L = Local Tourists, SD = Standard Deviations

Table 7

Independent t-test results for mastery competency motivation (MC) among tourists

Travel motivation		t-test for equality of means
		t	df	Sig. (two-tailed)	Mean	SD	Partial Eta squared (%)
To challenge my abilities	I	1.617	498	0.106	5.14	1.649
	L				4.90	1.778
To be good in doing them	I	−0.457	498	0.648	4.96	1.720
	L				5.03	1.603
To improve my skill and ability in doing them	I	−1.905	498	0.057	5.05	1.716
	L				5.33	1.615
To be active	I	−2.314	487.835	0.021	5.48	1.468	1.1
	L				5.76	1.269
To develop physical skills and abilities	I	−5.561	464.280	0.000	4.79	1.812	5.8
	L				5.59	1.375
To keep in shape physically	I	−4.739	490.172	0.000	4.34	1.933	4.3
	L				5.12	1.702
To use my physical abilities	I	−5.821	486.136	0.000	4.34	1.941	6.4
	L				5.28	1.658
To develop physical fitness	I	−6.426	481.751	0.000	4.14	2.029	7.7
	L				5.21	1.685

Note(s): I = International Tourists, L = Local Tourists, SD = Standard Deviations

Table 8

Independent t-test results for stimulus avoidance motivation (SA) among Tourists

Travel motivation		t-test for equality of means
		t	df	Sig. (two-tailed)	Mean	SD	Partial Eta squared (%)
To calm down	I	−4.829	485.930	0.000	4.10	1.963	4.5
	L				4.89	1.674
To be alone	I	−2.561	489.322	0.011	2.88	1.805	1.3
	L				3.32	2.064
To relax physically	I	−5.848	466.290	0.000	4.48	1.958	6.4
	L				5.39	1.499
To relax mentally	I	−5.041	462.577	0.000	4.87	1.895	4.8
	L				5.63	1.426
To avoid the hustle and bustle of daily activities	I	−0.868	495.114	0.386	4.62	1.977
	L				4.76	1.831
To rest	I	−5.579	473.575	0.000	4.67	1.900	5.9
	L				5.53	1.508
To relieve stress and tension	I	−5.062	466.663	0.000	4.69	1.963	4.9
	L				5.48	1.506
To un-structure my time	I	−7.437	464.574	0.000	4.16	1.991	10
	L				5.33	1.512

Note(s): I = International Tourists, L = Local Tourists, SD = Standard Deviations

Table 9

Multivariate tests for age, gender and family size on travel motivation

Effect		F	Hypothesis df	Sig
Age	Pillai's Trace	1.396	96.000	0.008
Gender	Pillai's Trace	2.005	32.000	0.001
Family size	Pillai's Trace	2.610	32.000	0.000
Age * Gender	Pillai's Trace	1.154	96.000	0.153
Age * Family size	Pillai's Trace	1.322	96.000	0.023
Gender * Family size	Pillai's Trace	1.299	32.000	0.131
Age * Gender * Family size*	Pillai's Trace	1.514	96.000	0.001

Table 10

Tests between subjects effects for age, gender and family size on travel motivation

Effect	Dependent variable	df	Mean square	F	Sig
Age	To develop physical skills and abilities	3	12.594	4.972	0.002
Gender	To explore new ideas	1	8.906	4.451	0.035
	To discover new things	1	6.081	3.899	0.049
Family size	To develop physical skills and abilities	1	56.811	22.428	0.000
	To develop physical fitness	1	67.625	18.772	0.000
	To unstructure my time	1	50.424	14.955	0.000
Age * Family size	To relieve stress and tension	3	19.051	6.112	0.000
	To develop physical fitness	3	20.517	5.695	0.001
	To unstructure my time	3	18.159	5.386	0.001
	To use my physical abilities	3	11.260	3.322	0.020
Age*Gender*Family size	To satisfy my curiosity	3	5.223	2.693	0.046
	To develop close friendships with others	3	8.729	2.634	0.049