Keyword

1 Introduction

Business transaction worldwide depends upon customer retention. The service quality is crucial in businesses like tourism where services are intangible. Rahaman et al. (2020) propose that service quality increases customer retention tendencies in Bangladesh. This implies that service quality is associated with customer retention for repurchase as a result of satisfaction with the quality of service. Alketbi et al. (2020) linked the service quality with satisfaction, trust, and commitment in the United Arabs Emirates UAE hotels and found that service quality influences the retention and loyalty of customers. But this study focused on the hotel and hospitality industry in UAE instead of Tanzania. In supporting the findings of Alketbi et al. (2020), Fida et al. (2020) in Oman observed that empathy and responsiveness dimensions had an impact on customers’ satisfaction and retention in commercial banks. The study focused on the banking industry of Oman instead of KINAPA in Tanzania. It was further recommended that banks should not neglect the importance of other variables such as reliability, assurance, and tangibles. This implies that its findings cannot be generalized to the Tanzanian context. Ali et al. (2021) in Iraq had a similar conclusion to that of Alketbi et al. (2020) and Fida et al. (2020). However, the study did not focus on the tourism industry, instead, it was focused on the online meeting platforms.

Likewise, Gogoi (2020) in India agrees with Parasuraman et al. (1998) by proposing that customers’ retention is the function of service quality dimensions like service tangibility, service reliability, service assurance, empathy, service responsiveness, the competence of service providers, courtesy of services providers, the credibility of the institution, security of customers, service accessibility and communication. Although this study focused on the tourism industry, it was, however, conducted out of Tanzania with a dissimilar context to India. Similarly, Han et al. (2021) in China observed that the service quality of tourism in public health affects customers’ satisfaction, loyalty, trust and commitment. This implies that public health services are the potential in satisfying customers, and instill trust and loyalty which are important aspects of customer retention. Despite the comprehensive findings, the study ignored other aspects of tourism like accommodation, hotels, transportation, destination attractions and communication. Moreover, this study was conducted in China, hence, it cannot exhaustively address the situation in Tanzania. Also, satisfaction was found to have a positive effect on destination loyalty. Furthermore, the findings revealed that satisfaction had a partial mediation effect on the relationship between service quality, destination image and perceived value on the one hand and destination loyalty on the other. It was concluded that the provision of high-quality services increased tourists’ loyalty to the park. Abdul-Qadir et al. (2021) in Nigeria linked the service quality with customer retention of listed food and beverages companies in Kaduna State. This implies that customer retention of listed food and beverages companies in Nigeria was satisfied with service quality which derived the repurchase tendencies. Despite the clarity of findings, yet, this study had different research vicinity to the current study and had no link to tourism. Besides, did not focus on the listed food and beverages companies and other sectors.

Achieng (2021) studied a related topic in Kenya and the results revealed that there was a significant relationship between service integrity and customer retention in classified hotels in Mombasa county. The study focused on coastal tourism in Mombasa. Although, it was done in East Africa, yet, coastal tourism is different from Mountainous tourism like KINAPA in Tanzania. Kamna (2021) in Tanzania found that service quality has no impact on customer satisfaction in the retail banking sector. This study’s finding is contrary to other studies and the study focused on the retail banking sector contrary to tourism which is the focus of the current study. Matolo and Salia (2021) revealed that service quality affects the customer loyalty and satisfaction of the Serengeti National Park (SENAPA). While SENAPA is a lowland tourism field based on wild animals, KINAPA is mountainous tourism. Thus, a conclusion based on SENAPA cannot suffice to address the KINAPA concerns. Similarly, Ulaya (2017) linked the service quality and customer satisfaction and retention among commercial banks with a focus on Akiba Commercial Bank (ACB). The study ignored the tourism aspect, in this regard, the findings are not sufficient to address the current study. Burhan and Kalinga (2018) noted that quality hotel services offered to tourists in Tanzania are associated with satisfaction levels. It was further learnt that tangibility, reliability, responsiveness, assurance and empathy had a positive effect on the customers’ satisfaction. However, this study was confined to the hotel services in Tanzania and ignored the specificity of Mount Kilimanjaro tourists. The understanding and application of knowledge would curb state poverty.

Tanzania is one of the world’s poorest countries but endowed with valuable tourist attraction destinations, whose contribution to GDP is 13%, being second to the agricultural sector (Peat 2019; World Bank. 2019). Kilimanjaro National Park (KNP) alone earns about $50 million a year which is 45% of all income generated by Tanzania’s 15 national parks (TANAPA 2019). Moreover, Mount Kilimanjaro attracts over 35,000 climbers a year, plus 5000-day visitors, this is such a vital tourist attraction destination (TANAPA 2019). Previous studies link service quality and customers’ satisfaction, retention and loyalty (Achieng 2021; Ali et al. 2021; Han et al. 2021; Gogoi 2020). However, these studies were not conducted in Tanzania thus, such findings cannot be generalised tothe Tanzanian context. With this in view then, it was expected that the effects of service quality on customers’ retention would have been investigated and the findings emanating from such studies would be the effective implementation. However, this has not been the case, and the reasons for that have not been provided. The researcher was convinced that there was a need to study the effects of service quality on customers’ retention due to its vitality as an economic source for the country.

Globally, the success of tourist attraction destinations depends on the ability to retain tourists (Gogoi 2020). Thus, customers tend to have their expectations before the visitation of tourist attraction destinations. KINAPA earns about $50 million a year which is 45% of all income generated by 15 national parks (TANAPA 2019). This is a large amount of money collected from many visitors, however, there is a great fluctuation in the number of tourists indicating the poor retention of customers (TANAPA 2019). With this in view, retaining such a great number of customers is very crucial for economic development, but there are no conclusive studies regarding the effects of service quality on customer quality. Previous studies show that quality services are linked to customers’ satisfaction which in turn fosters the sales in tourism in Tanzania (Gogoi 2020; Rahaman et al. 2020; Mashenene 2019; Meesala and Paul 2018). Much of the previous research on the effect of service quality on customers retention in Tanzania has been done, however, not even one conclusive study has been conducted at KINAPA (Matolo and Salia 2021; Burhan and Kalinga 2018; Ulaya 2017) instead, they linked service quality and customer retention without association with the tourism industry. Although, satisfied customers are likely to be retained, however, decisive studies are missing. This elevated the urgency of investigating how the quality service links with customer retention. The question of whether tourists of Mount Kilimanjaro are being retained with quality services is not thoroughly addressed due to the insufficiency of literature. The failure to address the linkage between service quality and customers’ retention with regard to Mount Kilimanjaro is likely to affect the tourism business performance and deprive the country of the tourism subsector to unleash the economic potential opportunities from the tourists’ arrivals. Therefore, this study was designed to examine the effect of service quality on the customers’ retention of Mount Kilimanjaro in Tanzania.

2 Theory Underpinning the Study

This study was underpinned by SERVQUAL Model which was developed by Parasuraman et al. (1998). The model perceives the notion of service quality into five constructs as follows: -tangibles (physical facilities, equipment, staff appearance, etc.), reliability (ability to perform service dependably and accurately); responsiveness (willingness to help and respond to customer needs) and assurance (the ability of staff to inspire confidence and trust). SERVQUAL represents service quality as the inconsistency between a customer's expectations and service quality. It is unclear if all customers will perceive and react equally to service quality. Failure to respond to such a question by the model calls for a study to be performed. The way service quality dimensions relate to the customers’ retention attracted many scholars to employ in their studies (Matolo and Salia 2021; Burhan and Kalinga 2018; Ulaya 2017).

3 Research Methodology

This study used across-sectional research design in gathering information. The choice of this research design was preferred in this study due to its ability to avail vital and credible information, especially in settings with many respondents (Robson 2018; Yin 2017). Similarly, the design enables the researcher to collect data at a one-time point Kothari (2015).

The study was conducted at the Kilimanjaro National Park in Kilimanjaro region as this region has many tourists who were the major respondents of this study. Mount Kilimanjaro is markedly known for its height in Africa by being the highest mountain in Africa and the second-highest mountain in the world. This being the case now consideration of the Kilimanjaro region was worthwhile. However, a few customers were considered in this research.

The population of this study consisted of 172 potential KINAPA stakeholders. Specifically, 10 KINAPA officials, 12 TTB board members, 10 community members, 130 KINAPA tourists and 10 tourism service providers. Primarily, it is sometimes impractical to measure the entire population, thus, a sample was secured randomly to omit the possibility of getting respondents with bias.

The study employed Yamane formula (1967) to calculate the sample size of finite population.

$$ {\text{n}} = {\text{N}}/\left( {{1} + {\text{N}}\;{\text{e}}^{{2}} } \right) $$
(1)

  • N = finite (known) size of Population = 172

  • n = sample size

  • e = sampling error (5%)

  • n = 172 / (1+172 x (0.05)2) = 120

However, 104 out of 120 questionnaire sets were returned by respondents and used in the course of research. With this regard, the sample size of this study became 104 respondents.

The study used a proportional stratified sampling technique in selecting the sample as the study population was heterogeneous and therefore the population was stratified in form of strata of KINAPA tourists, KINAPA officials, community members, TTB members and service providers to tourists (Kothari 2015). However, due to the homogeneity of tourist lists provided by KINAPA, a simple random sampling was used to select tourists (Table 1).

Table 1. Composition of respondents by stratum
Full size table

In conducting this study, the researcher collected both primary and secondary data. Secondary data were collected from relevant documents like tourism quarterly reports and primary data were collected from tourists, community members, tour guides and government officials.

In this study, the researcher used the following data collection instruments/tools:

  1. (i)

    Questionnaires

    Primary data were collected using questionnaires and interviews (structured and non-structured). Each respondent was provided with a set of questionnaires immediately after getting service from the KINAPA. Questions were modified from the SERVQUAL model as formulated by Parasuraman et al. (1998).

    The questionnaire set was divided into four (4) parts. Part A was general information regarding the customers’ affairs. Part B included information regarding service quality with respect to customer expectation, part C comprised questions related to the effect of service quality on the customers’ perception and part D was information regarding customer retention. Questionnaires are a set of questions designed to collect data from respondents. Each person was administered the same set of questions in a predetermined order (Saunders 2009). In this study, questionnaires were both open and close-ended. To simplify the data analysis the researcher used the Likert Scale with with a 5-points. This was prepared and administered to respondents selected. The questionnaire were opted due to their effectiveness in data collecting especially in the situation with large number of the respondents within shortest possible period of time and low financial cost.

    A five-point Likert scale was used ranging from “1 = strongly disagree” to “5 = strongly agree” while 2, 3 and 4 are scaled as disagree, neutral and agree respectively. 4–5 indicate the positive influence of service quality dimensions on customer retention, while the range from 1–2 shows that, service quality dimension is not a factor which may influence customer retention. On the same questionnaire, respondents were required to indicate the length of stay with the KINAPA (in years).

    120 questionnaires were administered to the selected KINAPA tourists, Ministry of Natural Resources and Tourism, community members, members of TTB and tourist service providers. 104 questionnaires were properly filled out and returned. This represented an overall successful response rate of 86.7% as shown in Table 2. According to Kothari (2014), a response rate of above 50% is adequate for a descriptive study. Babbie (2004) also asserted that return rates of above 50% are acceptable to analyze and publish, 60% is good and 70% is very good.

    Based on these assertions from renowned scholars, an 86.7% response rate was very good for the study. Thus, the response rate of 86.7% in this study was very good for the study.

Table 2. Rate of return response of questionnaires
Full size table
  1. (ii)

    Interview

    The interview is a systematic way of talking and listening to people to collect data. It could be structured or non-structured interviews. This method provides room for clarification to both the researcher and respondents. It guarantees a good return rate and provides more information in detail. It also helps the researcher reduce time in his data collection process. The interview method of collecting data involves oral stimuli and replying verbally. Kothari (2015) perceives that interview exists in two forms which are structured interviews and/or unstructured interviews. Although, both forms of interviews involves questions in the earlier questions are preset and deterministic meanwhile, in the latter form, involves the verbal questions which are not formalised. An open-ended instrument consisting of nine (9) questions interview guide was prepared. The questions with prompts on the effect of service quality(SQ) on the retention of customer enlisted in the interview guide (see Appendix B). Interview guide was chosen in this study based on its flexibility and ability to gather an in-depth information which are of vital role to the study. Respondents were compelled furnish the researcher with information they have and understood as enabler of KINAPA to improve performance using the service quality. Questions included stating the reason for consuming services from KINAPA, the experiences of the respondents being customers, respondents’ expectations, and perceptions. Other aspects included identifying the KINAPA features that challenged them as customers.

  2. (iii)

    Documentary Review

    A checklist of documents was employed to collect secondary data vital to this research. A checklist of documents was important as not all documents related to the topic at stake were relevant and vital the current study, but this acted a tool for screening useful information for supplementing them to the primary data. Documentary review entails collection of information by rereading both internal documents on the topic of study and kept information regarding the subject matter about the performance of the organization. In this case records of the number of hotels, customers visited KINAPA and kind of tourists’ products) or may be external (specifications of tourists’ preferences, world annual tourism, world ecosystem and ecology). Documents take various forms of things such hardcopies or soft copies and may include reports of the year, the performance hints of the organisation, internal and external auditors reports of the year, tourists’ feedback, meeting minutes, newsletters, and marketing materials (Kumar 2014). On the other hand, Kothari (2015) views documentary analysis (document analysis) as a type of qualitative research in which documents are reviewed by the analyst to assess an appraisal theme. Dissecting documents involves coding content into subjects like how focus groups or interview transcripts are investigated. The study involved a review of various documents, published and unpublished materials (Kothari 2015). The researcher managed to find information on the contribution of service quality to customer retention at KINAPA in Tanzania by responding to research questions in this study. The study used questionnaires, documentary review and interview to collect primary and secondary data for the study to bring about research triangulation using accessible and available data. The choice of the documentary review was based on the fact that it is less expensive in the sense that various documents can be accessed with certainty in various forms as per the researcher's choice (Creswell 2014).

Data analysis means translation of ran data that involves interconnecting data so that the built relationship among variables is displayed to the researcher. It encampuses assembling, feigning, and reconvening data using a chosen method under precise investigative program (Dawson 2020; Yin 2014). Based on this study, data from various sources of choice were collected summarised, coded and were analyzed.

The respondents’ names in this study were concealed congruent to the ethical consideration so as to ensure that confidentiality and honour were preserved by adhering to the standards of ethics as per the university research policy. Johnson (2015) is of the opinion that SPSS software had a capacity to assign identity, analyze, store, identify the information regarding specific information for the study.

Data collected were analyzed objective wisely. To examine the level of customer retention, data from Likert Scale questions after being coded were subjected to transformation and later segregated into high or low retention rates. To determine the effect of service quality dimensions on customer retention, a binary logistic regression model was employed because the dependent variable was in binary responses (1=High, 0=low). A binary logistic regression model was applied to determine the chances of being a circumstance based on the levels of the independent variables (predictors). The chances (odds) imply the likelihood that a specific outcome is a case divided by the chance that does not occur. In this case, the responses were considered as either high or low retention levels.

$$ {\text{Pr}}\left( {{\text{Y}} = {\text{I}}} \right) =\upbeta _{0} +\upbeta _{{1}} {\text{X}}_{{1}} +\upbeta _{{2}} {\text{X}}_{{2}} +\upbeta _{{3}} {\text{X}}_{{3}} +\upbeta _{{4}} {\text{X}}_{{4}} +\upbeta _{{5}} {\text{X}}_{{5}} +\upvarepsilon $$
(2)

where, β0, β1, β2, β3, β4 and β5 are coefficients or constants, X1 = service tangibility, X2 = service reliability, X3 = service responsiveness, X4 = Service empathy, X5 = service assurance and Ɛ = error.

4 Findings and Discussion

4.1 Level of Customer Retention at Mount Kilimanjaro

The overall mean of the customer retention level is 4.436 as indicated in Table 3 implies that customer retention high.

Table 3. Level of customer retention at Mount Kilimanjaro (n = 104)
Full size table

Reliability of Hotel Services

Table 3 shows that the mean of respondents’ responses on whether or not to make repeated purchases due to reliable hotel services was 4.58 whereas the corresponding standard deviation was 1.112. This implies that the majority of respondents believed that the repeated purchase of KINAPA was attributed to reliable hotel services. This is evidenced by a mean of 4.58 which is very close to 5andindicatesstrongly agreed with this sentiment. This has also been evidenced by the magnitude of standard deviation showed a little dispersion (1.112) from the mean. This observation is in harmony with the research findings of Gong and Yi (2018) who affirm that customer satisfaction, retention, and happiness in five Asian countries are affected. It was revealed that overall service quality has a positive influence on customers’ satisfaction, which in turn leads to customer retention and customer happiness in Asian countries. The study linked the quality of service with customer retention in non-mountainous tourism in Asia. In supporting this observation, the participant stated that:

“.... Services that are provided by KINAPA has convinced me to keep on visiting KINAPA now and then……. this is because their service is tangible the manner that satisfies the customers compared to nearby countries of East African community …” (Interview held with tourist from European Union on 24thJune 2021).

Good Treatment of Customers

Table 3 shows the mean and standard deviation of respondents’ responses with respect to the customers’ retention level as a result of good treatment is 4.21 and 1.334 respectively. This implies that the majority of respondents were impressed with the good treatment at KINAPA. The research findings are congruent to the findings of Alketbi et al. (2020) who affirmed that service quality had an impact on customer retention. Additionally, the participant had this concern concerning the impact of the service reliability:

“…. I have been repurchasing the service at KINAPA because their services are well offered …………… there is customer service in offering their services a thing that has compelled me to keep on purchasing from KINAPA….” (Interview held with tourist from Australia on 24thJune 2021).

Likewise, John and Adebayo (2021) had a similar observation to the research findings by affirming that customers’ retention is linked with service quality in terms of customer care in Malaysian rural tourism. Therefore, it was revealed that customers are sensitive to the service they receive as a result of their money being exchanged. Furthermore, Rahaman et al. (2020) and (Gogoi 2020) support the research findings by asserting that dimensions of service quality have a positive influence on customer retention.

Attractiveness of Wildlife

Table 3 shows that the mean and standard deviation of respondents’ responses with regard to the impact of service attractiveness (wildlife) on customer retention are 4.60 and 1.084 respectively. This implies that the majority of respondents were strongly attracted to tourist destinations following the goodness of wildlife. This has also been evidenced by the size of the standard deviation showed a little dispersion (1.084) from the mean. This observation is in agreement with the findings of Rahaman et al. (2020) who contend that quality service correlates with customer retention in the tourism subsector. To cement the research findings, the FGD participant stated that:

“…. I don’t need to ask myself where I will visit next vacation, this is obvious assuredly provision of services with such quality dictates the place to go. ……. KINAPA services have highly impressed me and that is why I am here today…” (Interview held with Jewish tourist on 24thJune 2021).

Responsiveness of Employees to Customers Retention

Table 3 shows that the mean of respondents’ responses with regard to employees’ responsiveness with respect to customer retention is 4.21 and 1.334 respectively. This implies that the majority of respondents were pleased with the responsiveness of employees of KINAPA in service provision. This finding is in agreement with the research findings of Rahaman et al. (2020) who contend that KINAPA employees’ responsiveness impacts the customers’ retention in the tourism subsector. To affirm this sentiment, the participant from Key informants stated that:

“……Quality services provided to customers are the cause of the repurchases tendency at KINAPA whose services are responsively delivered to customers. ………. This is crucial, especially for the visitors who severally visit KINAPA…..” (Interview held with the service provider in Moshi on 24thJune 2021)

Dependability of Meals and Accommodation Services

Table 3 shows that the mean and standard deviation of respondents’ responses regarding the dependability of meals and accommodation services are 4.58 and 1.112 respectively. This implies that tourists were strongly attracted to the dependability of meal and accommodation services provided at KINAPA.

This finding is similar to the observation by Abdul-Qadir et al. (2021) in Nigeria who linked service quality including service dependability with customer retention in listed food and beverages companies in Kaduna State. These research findings were supported by an FGD participant who stated that:

“……Service superiority and dependability strongly attract customers to repurchase at KINAPA ……..This, has convinced tourists to come several times…..” (Interview held with Asian tourist on 24thJune 2021).

4.2 The Effect of Service Quality Dimensions on Customer Retention

Table 4 of binary logistic regression results shows that the Chi-square was 80.114 at a p-value = 0.000. This indicates that service quality dimensions predict the customers’ retention strongly. Cox & Snell R Square and Nagelkerke R Square were 0.537 and 0.847 respectively. This implies that 53.7% and 84.7% of the total variance in customer retention are accounted for by the service quality dimensions.

Specifically, services tangibles had a coefficient (β) of 2.231 coefficients which was significant. This finding implies that a unit change of intangibles will result in a 223.1% change in customer retention, furthermore, findings for tangibles show an odds ratio of 2.201 which implies the contribution of tangibles to the customer retention was 2.2 times. This conclusion resembled the findings of Gong and Yi (2018) who obtained similar findings where it was drawn that service quality affected customer satisfaction, retention, and happiness in five Asian countries.

Table 4. Binary logistic results
Full size table

Results from Table 4 further show that assurance had a coefficient (β) of 1.715 which was significant. This implies that a unit change in the assurance of services to customers will result in a 17.1.5%change in customer retention. The odd ratio of 1.004 for assurance in service provision implies that the contribution of assurance to the customers’ retention was 1.004 times. The research findings are congruent to the findings of Alketbi et al. (2020) who affirmed that service assurance had an impact on customer retention.

With regard to service responsiveness, it shows that the responsive had a coefficient (β) of2.796 which was significant. This finding implies that a unit change in responsiveness will result in a 279.6% change in customer retention. Furthermore, the odds ratio of 2.52 for responsiveness shows that the contribution of responsiveness to the customers’ retention was 2.520 times. The findings are congruent to the findings of Ali et al. (2021) who found that service responsiveness had an impact on customer retention.

Likewise, findings show that reliability had a coefficient (β) of 1.715 which was significant. This finding implies that a unit change in reliability will result in a 171.5 % change in customer retention.

Furthermore, findings for reliability show an odds ratio of 2.004which implies that the contribution of reliability to customer retention was 2,004 times. The research results are congruent with observations of Han et al. (2021) of China who noted that service reliability had an impact on customer retention.

Similarly, findings show that empathy had a coefficient (β) of 3.768 which was significant. This finding implies that a unit change in empathy will result in a 37.68 %change in customer retention. Furthermore, findings for a responsive show an odds ratio of 1.301 which implies that the contribution of empathy to customer retention was 1.3 times. The research findings are similar to that of Achieng (2021) in Kenya who noted that service empathy had an impact on the customer’s satisfaction, royalty and retention.

Furthermore, findings for a responsive show an odds ratio of 1.301 which implies that the contribution of reliability to the customer retention was 1.3 times. The research findings are similar to that of John who noted that service reliability had an impact on the customer’s satisfaction, royalty and retention.