The effect of service quality on revisit intention: The mediating role of destination image

Abstract

The study investigates the effect of service quality on revisit intention and the mediating role of destination image. Data were gathered from tourists who visited ZimParks tourist destinations (n = 400) using structured questionnaires. The study adopted a cross-sectional survey. Findings show that service quality positively influences revisit intention. Service quality is found to have a positive impact on destination image. Findings also reveal that destination image significantly impacts revisit intention. Destination image was found to mediate the effect of service quality on revisit intention. The findings contribute to the existing body of tourism and marketing literature. Destination Management Companies (DMCs) are advised to consider service quality and destination image when developing strategies to improve tourist revisit intention.

Keywords:

• destination image
• revisit intention
• service quality
• Zimbabwe Parks and Wildlife Management Authority

PUBLIC INTEREST STATEMENT

Service quality and destination image contribute to a crucial role in the success of a destination management company. The study examines the effect of service quality on revisit intention and the mediating role of destination image using Zimbabwe a developing nation as a point of reference. The study specifically tests the effect of service quality on revisit intention; the effect of service quality on destination image; the effect of destination image on revisit intention; and the mediating role of destination image on service quality and revisit intention. Service quality is found to have a positive impact on destination image. Findings also reveal that destination image significantly impacts revisit intention. Destination image was found to mediate the effect of service quality on revisit intention. Subsequently, tourism destination management companies are advised to consider service quality and destination when developing strategies to improve tourist revisit intention.

1. Introduction

Tourism is recognized as a substantial growth sector amongst various nations and a major foundation for better livelihoods, wealth establishment and income generation (Abbasi et al., 2021; Merli et al., 2019). The industry is also rated as the leading and fast-developing sector that significantly contributes to the development of countries (Abel & Le Roux, 2017; Khuong & Phuong, 2017). The industry has managed to successfully experience exponential growth, and diversification and globally, the industry developed into the best emerging economic area (Alam & Paramati, 2016). In Africa, tourism contributes a total of 24.3 million African jobs (Matolo et al., 2021). In developing nations, tourism has become a critical commercial sector (Viet et al., 2020). Ranjbarian and Pool (2015) concluded that tourism is a clean industry since it is associated with less pollution and other adverse consequences.

Tourism is a service-orientated sector that is significantly influenced by tourists’ experience with service quality and assessments done on facilities and services provided (Gani et al., 2019). Service quality is significant for the functioning of corporates in environments that are highly competitive (Al-Ababneh, 2017). Service quality in the tourism industry is also of paramount importance from the viewpoints of both customers and managers (Kleisari & Markaki, 2019). As such, higher service quality influences customer satisfaction, motivating consumers to repurchase the service (Namin, 2017).

Service quality is a positive predictor of intention to revisit a destination, leading to a significant effect on behavior of tourists (Abbasi et al., 2021). Tourists that perceive superior quality service in a destination are motivated to revisit the same destination (Quintal & Polczynski, 2010). Tourist intention to revisit a destination is regarded as a substantial variable that leads to organizational expansion and survival in the industry (Abbasi et al., 2021). For organizations to develop and succeed, tourist intention to revisit is rated very high (Ngoc & Trinh, 2015). The primary motive is that repeat visits by tourists decrease costs incurred in promoting the destination (Abbasi et al., 2021; Loi et al., 2017). Tourism service quality is related with destination image Yang et al. (2014) and superior service quality advances tourist destination image. Akroush et al. (2016) posit that tourists that are satisfied with the image of the destination develop a positive attitude towards the destination (Akroush et al., 2016). Destination image is a major element that explains the reason why tourists choose to visit the destination again and the will to endorse it to prospective tourists (Yilmaz & Yilmaz, 2020).

Existing tourism literature established that service quality and destination image are considered key influencers of tourists’ revisiting a particular tourism destination and this translates to a significant impact on tourists’ behavior (Allameh et al., 2015; Ranjbarian & Pool, 2015; Seetanah et al., 2020; Zhang et al., 2018). However, it is essential to note that majority of studies were conducted in developed nations Abbasi et al. (2021) in Malaysia; Alzaydi (2020) in Saudi Arabia; Kumar et al. (2020) in Malaysia; Tosun et al. (2015) in Turkey; Timur (2018) in Turkey; Quintal et al. (2010) in Western Australia; Yang et al. (2022) in China. There are scarce studies in developing nations that have examined the mediating role of destination image on the effect of service quality on revisit intention. Moreover, research is unconvincing in developing nations on the impact of service quality and destination image on revisit intention. As a result, this study seeks to close this knowledge gap by examining the mediating role of destination image on the effect of service quality on revisit intention using Zimbabwe a developing nation as point of reference. From a marketing and tourism perspective, the study will add knowledge on how destination image mediates the relationship between service quality and tourist revisit intention in a developing nation. The specific objectives are to determine the effect of service quality on revisit intention; to ascertain the effect of service quality on destination image; to establish the effect of destination image on revisit intention; and to test the mediating role of destination image on service quality and revisit intention.

2. Literature review

2.1. Service quality

The service quality concept has captured several researchers’ attention (Izogo & Ogba, 2015). Service quality is defined differently by many scholars (Abbasi et al., 2021), and it is a total amount of a customer’s evaluation with regards to overall performance of a particular product or service (Allameh et al., 2015). Service quality is not limited to the ability of the firm to satisfy consumer wants, but it is further extended to consumers’ feedback and ability of the company to resolve customer problems (Palazzo et al., 2021). Reliability, tangibility, assurance, responsiveness and empathy are the five dimensions of service quality (Al-Ababneh, 2017). Gobena (2019) posits that reliability is the firms’ capacity to deliver promises made to clients in marketing campaigns. Assurance is the knowledge and courteousness of the organization’s workforce that motivate customers to feel assured and confident (Gobena, 2019). Jansri et al. (2020) identify tangibility as the visual attractions that include equipment, employees, written materials and physical facilities. Responsiveness focuses on the firm’s capacity to offer assistance to its clients and further deliver prompt services (Brett, 2019). Empathy is generally concerned with how organizations provide care and individualized attention to customers (Jansri et al., 2020).

2.2. Revisit intention

Nguyen (2020) posit that prior research in the field of tourism destination regards revisit intention as a key topic and has been further revealed as a significant behavioral intention. Tourists’ ability to return and visit a particular tourism destination is regarded as tourist post-consumption behavior and is associated with visitors repeating a specific action or revisiting a destination (Nguyen, 2020). Revisit intention further relates to the judgment made by a visitor with regards to the possibility to return and visit the destination in future (Khasawneh & Alfandi, 2019; Stylos et al., 2017) and will of endorsing the destination to others. The tourism industry regards revisit intention as a key aspect that leads to business growth and survival (Abbasi et al., 2021).

2.3. Destination image

Destination image is considered a critical element in predicting behavior of tourists, mainly their intention to return and visit the destination; for instance in tourism literature, destination image has been used to give details on individuals’ feelings, attitudes, beliefs, and holistic impressions of leisure destinations (Yang et al., 2022). Existing tourism marketing literature indicates that destination image has drawn extensive attention and various scholars defines it differently (Akgün et al., 2019). Yang et al. (2022) recognized destination image as tourists’ general impressions of a destination. Destination image is viewed as the tourists’ general view or the total set of impressions towards a particular place (Abbasi et al., 2021). Iordanova (2017) identified destination image as set of thoughts, anticipations, impressions and emotional feelings developed towards a particular place. Tourism literature considers destination image as a crucial and noteworthy aspect in several conceptual frameworks that explains the tourists’ overall decision-making process (Nguyen, 2020). Iordanova (2017) posits that, buying decisions made by tourists are grounded on the mental images they hold towards a particular place. Destination image influences prospective tourists’ general perceptions and decision-making related to their travelling and it is further essential in development of country or place image (Yang et al., 2022).

2.4. Development of hypotheses and conceptual framework

Abbasi et al. (2021) in Malaysia found that service quality directly impacts tourist intention to revisit. Service quality was found to positively influence revisit intention within the sport tourism sector in Iran (Allameh et al., 2015). In Australia, Worsfold et al. (2016) confirmed that service quality and intention to revisit are significantly related. Shen et al. (2016) found that service quality impacts revisit intention positively. A study by Wantara and Irwti (2021) in Indonesia found that service quality positively contributes to tourist revisit intention. Hence, it is hypothesized that

H1:

Service quality has a positive effect on revisit intention.

In Turkey’s tourism and hospitality industry, Timur (2018) confirmed that service quality and destination image are significantly related. Kumar et al. (2020) in Malaysia’s avitourism industry found that service quality is positively and directly associated with destination image. In Jordan, Akroush et al. (2016) established that service quality dimensions positively influence destination image. Various studies confirmed that tourism service quality dimensions and destination image are positively related (Forster & Sidharta, 2019; Namukasa, 2013; Phi et al., 2022; Timur, 2018). It is therefore, hypothesized that

H2:

Service quality has a positive effect on destination image.

A study in New Zealand established that destination image positively affect intention of Chinese tourists to revisit New Zealand (Yang et al., 2021). It has been established that destination image positively impacts the intention to revisit Indonesia (Barkah & Febriasari, 2021). Yang et al. (2022) in China found that destination image leads to travel intention of tourists. A study in Vietnam established that destination image positively influence revisit intention (Phi et al., 2022). Abbasi et al. (2021) in Malaysia found that destination image and intention to revisit are significantly related. Moreover, in Indonesia, destination image was found to positively impact tourist intention to revisit (Agustina, 2018; Forster & Sidharta, 2019). Song et al. (2017) in China found that destination image significantly impacts tourists’ intention to revisit a destination. Hence, it is hypothesized that

H3:

Destination image has a positive effect on revisit intention.

A research study in Turkey by Timur (2018) found that revisit intention, service quality and destination image are significantly related. In Aceh Indonesia, Siregar et al. (2021) established that indirectly, destination image significantly contributes to revisit intention through service quality. In addition, Siregar et al. (2021) revealed that destination image directly and significantly influences service quality and revisit intention. Another study in Indonesia by Rismawati and Sitepu (2021) reveals that destination image and service quality significantly influence tourist revisit intention. It is therefore, hypothesized that

H4:

Destination image mediates the effect of service quality on revisit intention.

Based on the discussion, the research model is proposed in Figure 1.

Figure 1. Research model.

3. Research methodology

3.1. Questionnaire design and measures

Appendix A indicates the measurement scales together with items adopted in the study to measure elements of service quality that includes tangibility (TAN), responsiveness (RES), reliability (REL), assurance (AS) and empathy (EMP). In addition, Appendix A also presents measurement scales with items used to measure destination image (DI) and revisit intention (RI). A five-point Likert scale was applied. The study adopted and modified items used in prior related studies (Akroush et al., 2016; Gobena, 2019; Kleisari & Markaki, 2019; Phi et al., 2022; Soleimani et al., 2018; Song et al., 2017; Tosun et al., 2015) All items focused on tourist perceptions.

3.2. Sampling and data collection

A total of 20 000 tourists visit ZimParks destinations each month (ZimParks, 2021). Considering that primary data were gathered from 15 November 2022 to 15 May 2023, a period of 6 months and 20,000 tourists visit per month, the target population comprises 180,000 tourists. The Yamane formula of sample size determination was adopted. The Yamane formula is highlighted as follows:

1 $\mathrm{n}=\frac{\mathrm{N}}{1+\mathrm{N}{\mathrm{e}}^2}$1

where n = sample size

N = population size

e = level of precision always set the value of 0.05

Calculation of sample size for the study using Yamane formula of size determination:

N = 180,000 tourists

e = 0.05

2 $\mathrm{n}=\frac{\mathbf{180000}}{\mathbf{1}+\mathbf{180000}{\left(\mathbf{0}.\mathbf{05}\right)}^{\mathbf{2}}}$2

n = 399

Sample size is 399 based on the Yamane formula. However, 399 was rounded to the nearest whole number and 400 was considered as the sample size. As such a cross-sectional survey of 400 tourists was adopted. Data were collected from tourists who visited ZimParks tourist destinations that includes, national parks, recreational parks and hunting safari areas. A structured questionnaire was used to collect data from tourists, and a random selection of tourists was done by intercepting them as they left ZimParks tourist office after completing the check-in process. Respondents were kindly requested to complete the questionnaire during the period of their stay at the park and they were further requested to submit completed questionnaires at the tourist office as they conduct their checkout process as they prepare to leave the park. Data were analyzed using SPSS version 21 and AMOS version 21. Respondents were not coerced to take part in the study, but they participated willingly. Researchers observed privacy and confidentiality as data were used for purpose of academics. Consent was sought from respondents and all respondents were notified that they were free to withdraw from participating in the study at any given time. The demographic characteristics of tourists are presented in Table 1.

Table 1. Demographic characteristics

Characteristic		Frequency	%
Gender	Male	215	53.8
	Female	185	46.2
Age (years)	18–19	40	10.0
	20–29	96	24.0
	30–39	97	24.2
	40–49	101	25.3
	50 and above	66	16.5
Education	Primary	15	3.8
	Secondary	129	32.2
	Tertiary	256	64.0
Level of income per annum (USD)	Less than 1000	103	25.7
	1000–4999	155	38.8
	5000–9999	72	18.0
	10,000 and above	70	17.5
Tourist nationality	Zimbabwean	363	90.7
	Non-Zimbabwean	37	9.3
Number of visits	Less than 5	72	18.0
	5–10	170	42.5
	More than 10	158	39.5

Sources: Research data (2023).

Results in Table 1 show that there were more male tourists (53.8%) than female tourists (46.2%). Findings in Table 1 indicate that 40 tourists were between 18 and 19 years; 96 tourists were between 20 and 29 years; a total of 97 tourists were between 30 and 39 years, meanwhile, 101 tourists were between 40 and 49 years; 66 tourists were above 50  years. The respondents in the study attained the following educational levels: primary education (4%), secondary education (34%) and tertiary (62%). This is plausible because Zimbabwe comprises educated people (Manyanga et al., 2022). As shown in Table 1, a total of 103 participants earn salary less than USD 1,000. A total of 155 participants earn income between USD 1,000 and USD 4.999 per annum. A total of 72 participants earn income between USD 5,000 and USD 9.999 per annum. Meanwhile, 70 participants earn USD 10,000 and above per annum. The majority of tourists who visited ZimParks tourists’ destination were Zimbabweans (91.8%), while the remaining were non-Zimbabweans (8.2%). As shown in Table 1, 18% of the respondents visited ZimParks destinations less than 5 times, 42.5% of the participants visited 5–10 times and 39.5% of the respondents visited more than 10 times.

4. Analysis and results

4.1. Descriptive statistics

Descriptive statistics were presented on the three constructs (service quality, destination image and revisit intention) that underpin the study. Mean (M) and standard deviation (SD) are presented in Table 2.

Table 2. Mean (M) and standard deviation (SD)

Construct	M	SD
Reliability (RE)	4.05	.798
Assurance (AS)	4.40	.637
Tangibility (TA)	3.89	.828
Empathy (EM)	4.31	.672
Responsiveness (RES)	4.31	.727
Destination Image (DI)	3.86	.828
Revisit Intention (RI)	3.58	.467

Source: Research data (2023).

As shown in Table 2 overall = mean 4.05 and SD = 0.798. This implies that tourists agreed that ZimParks tourism services are reliable. Research findings in Table 2 indicate that overall mean = 4.40 and SD = 0.637. The results suggest that ZimParks employees have knowledge on tourism services offered to tourists and they make tourist feel much safer. Results in Table 2 show that tangibility produced an overall mean = 3.89 and SD = 0.828. Suggesting that tourist are satisfied with ZimParks tourist facilities. As shown in Table 2 empathy recorded an overall mean = 4.31 and SD = 0.672. This implies that ZimParks staff demonstrates empathy towards tourists. Table 2 indicates that responsiveness produced an overall mean score = 4.31 and SD = 0.727. This suggests that ZimParks staff are responsive to tourists’ request. Findings in Table 2 also indicate that destination image attained a mean = 3.86 and SD = 0.828 highlighting that ZimParks provides tourism destination with beautiful scenery and attractive natural attractions. Lastly, results in Table 2 indicate that revisit intention recorded mean = 3.58 and 0.467 suggesting that tourist are willing to return and visit ZimParks destinations.

4.2. Data validation

Discriminant validity and convergent validity were used to validate data.

4.2.1. Discriminant validity

As shown in Table 3, the study successfully achieved discriminant validity. In addition, Table 3 indicates that all the AVEs (diagonal elements in bold) surpassed the squared inter-construct correlations (SICC) (Fornell & Larcker, 1981).

Table 3. AVE and SICC

Construct	RE	AS	TA	EM	RES	DI	RI
Reliability (RE)	.601
Assurance (AS)	.369	.624
Tangibility (TA)	.405	.414	.561
Empathy (EM)	.503	.254	.336	.598
Responsiveness(RES)	.298	.323	.411	.346	.603
Destination Image (DI)	.501	.419	.378	.298	.285	.579
Revisit Intention (RI)	.393	.197	.147	.337	.276	.400	.586

Note: Diagonal elements in bold represent AVEs.

Source: Research data (2023).

4.2.2. Convergent validity

The study considered measurement model fit indices namely χ²/degrees of freedom (DF), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), normed fit index (NFI), Tucker-Lewis index (TLI), comparative fit index (CFI) and root mean square error of approximation (RMSEA). As shown in Table 4, the model successfully achieved good fit (χ²/df 2.06; GFI 0.947; AGFI 0.951; NFI 0.920; TLI 0.912; CFI 0.938; RMSEA 0.059). To accept the model, the value of χ²/df should not be above 3, the values of GFI, AGFI, NFI, TLI and CFI must be near 1 and RMSEA must range from 0.05 to 0.10 (Hair et al., 2016; Hooper et al., 2008). As presented in Table 3 the AVEs ranged from 0.561 to 0.624 therefore, results exceeded the suggested minimum rate of 0.50 (Fornell & Larcker, 1981) indicating that convergent validity was attained.

Table 4. Measurement model

Fit Indices	Actual Measurement	Recommended	Sources
χ^2/DF	2.06	≤3.000	Hair et al. (2016), Hooper et al. (2008), Song et al. (2017)
GFI	.947	>0.900
AGFI	.951	>0.900
NFI	.920	>0.900
TLI	.912	>0.900
CFI	.938	>0.900
RMSEA	.059	<0.080

Source: Research data 2023.

Table 4 presents the results of the measurement model fit indices.

Table 5 presents the results for standardized factor loadings, critical rations, Cronbach’s alpha and composite reliability.

Table 5. Constructs, items, standardized factor loadings (λ) critical ratios (CR), and Cronbach’s alpha

Constructs	Items	λ	CR	Cronbach’s alpha	Composite reliability
Reliability	RE1	.789	-	0.863	0.912
	RE2	.701	7.325***
	RE3	.722	11.201***
	RE4	.746	22.125***
	RE5	.778	15.362***
Assurance	AS1	.814	-	0.875	0.901
	AS2	.775	12.364***
	AS3	.731	15.221***
	AS4	.725	30.124***
	AS5	.881	10.021***
Tangibility	TA1	.779	-	0.899	0.890
	TA2	.771	9.654***
	TA3	.725	12.037***
	TA4	.746	16.078***
	TA5	.732	8.574***
Empathy	EM1	.776	-	0.879	0.904
	EM2	.782	9.678***
	EM3	.774	18.214***
	EM4	.726	19.375***
	EM5	.888	14.857***
Responsiveness	RES1	.794	-	0.856	0.845
	RES2	.745	14.065***
	RES3	.756	19.085***
	RES4	.776	25.471***
	RES5	.737	13.571***
Destination Image	DI1	.763	-	0.866	0.934
	DI2	.769	16.347***
	DI3	.778	19.364***
	DI4	.716	21.258***
Revisit Intention	RI1	.711	-	0.915	0.875
	RI2	.731	17.216***
	RI3	.795	21.362***
	RI4	.727	11.298***

Notes: - CR is fixed; *** p < 0.001.

Source: Research data (2023).

Results presented in Table 5 show that the study achieved convergent validity since all standardized factor loadings were within recommended values of 0.50 and 0.95 (Hair et al., 2016). The CR was large enough at significant at p < 0.001. Cronbach’s alpha, composite reliabilities and individual item reliabilities values were all satisfactory as they achieved acceptable threshold value of 0.7 (Heale & Twycross, 2015). AVE’s of all constructs were generally greater than 0.5 as shown in Table 3.

4.3. Testing research hypotheses

4.3.1. Structural equation modelling

Structural modelling equation (SEM) was used to test hypotheses H1 to H3. Table 6 indicates results for the model (χ2/DF = 2.01; GFI = 0.921; AGFI = 0.935; NFI = 0.914; TLI = 0.944; CFI = 0.974; RMSEA = 0.057) and results were satisfactory. Table 6 presents the hypotheses test results for H1, H2 and H3. Service quality and revisit intention are significantly related (SRW = 0.402, CR = 13.247, p ˂ 0.001). Hence, H1 was supported. As shown in Table 6, service quality positively contributes to destination image (SRW = 0.386, CR = 11.201, p ˂ 0.001). Thus, H2 was supported. Furthermore, results in Table 6 show that destination image is positively related to revisit intention (SRW = 0.214, CR = 15.212, p ˂ 0.001). Consequently, H3 was supported.

Table 6. Measurement model

Fit indices	Actual measurement	Recommended	Sources
χ^2/DF	2.01	≤3.000	Hair et al. (2016), Hooper et al. (2008), Song et al. (2017)
GFI	.921	>0.900
AGFI	.935	>0.900
NFI	.914	>0.900
TLI	.944	>0.900
CFI	.974	>0.900
RMSEA	.057	<0.080

Source: Research data (2023).

Table 6 shows results for measurement model fit indices.

Table 7 presents hypotheses test results.

Table 7. Hypotheses test results for H₁, H₂ and H₃

Hypotheses	Hypothesized relationship	SRW	CR	Remark
H1	Service quality → revisit intention	.402	13.247***	Supported
H2	Service quality → destination image	.368	11.201***	Supported
H3	Destination image → revisit intention	.214	15.212***	Supported

Notes: SRW standardized regression weight, CR critical ratio, **significant at p < 0.05, ***significant at p < 0.001.

Source: Research data (2023).

4.3.2. Mediating effect of destination image

Table 8 presents results for measurement model fit indices.

Table 8. Measurement model

Fit indices	Actual Measurement	Recommended	Sources
χ2/DF	2.48	≤3.000	Hair et al. (2016) Hooper et al. (2008) Song et al. (2017)
GFI	.992	>0.900
AGFI	.996	>0.900
NFI	.927	>0.900
TLI	.919	>0.900
CFI	.935	>0.900
RMSEA	.056	<0.080

Source: Research data (2023).

Results in Table 8 present that the structural model fitted data well: (CMIN/DF = 2.48; GFI = 0.992; AGFI = 0.996; NFI = 0.927; TLI = 0.919; CFI = 0.935; RMSEA = 0.056 (Hair et al., 2016; Hooper et al., 2008; Song et al., 2017).

Table 9 presents results for the hypothesis test on the mediating role of destination image on the effect of service quality on revisit intention.

Table 9. Hypothesis test results for mediation effect

Hypothesis	Path	Description	Path coefficient	Results/Comments
H4	SQ→DI→RI	DI mediates the effect of SQ on RI	.359***	Partial mediation

Note: ***Significant at p < 0.001.

Source: Research data (2023).

Results in Table 9 show path SQ → DI → RI, path coefficient 0.359 (significant at p < 0.001). The results suggest that destination image partially mediates the relationship that exists between service quality and revisit intention. Hence, H4 is supported.

5. Discussion

5.1. Discussion

Majority of research studies that have examined the relationship between tourist revisit intention, service quality and destination image were conducted in developed nations. However, limited studies were conducted in developing nations. Based on this phenomenon the study was conducted to close the existing gap. The research sought to ascertain the effect of service quality on revisit intention, to determine the effect of service quality on destination image; to establish the effect of destination image on revisit intention; and to test the mediating role of destination image on the effect of service quality on revisit intention.

The study found that service quality positively and significantly influences intention to revisit. This suggests that the superior the service quality, the more tourist revisit the destination in future. Similarly, tourists who perceive service quality to be superior and excellent are expected to revisit the destination in future. The research finding validates the existing understanding that service quality and revisit intention are positively related (Allameh et al., 2015; Naibho & Hariyanto, 2022; Wantara & Irwti, 2021). The study further established that service quality and destination image are positively related. The result suggests that superior service quality positively influences the image of a tourism destination. The result is in tandem with existing literature (Akroush et al., 2016; Kumar et al., 2020; Phi et al., 2022; Timur, 2018). As expected, the study established that destination image positively contributes to revisit intention. This indicates that tourists are enticed to return to visit when they perceive a positive image in a particular destination. The finding is in line with prior studies that empirically proved that destination image is essential and play a critical role in influencing tourist revisit intention (Abbasi et al., 2021; Rismawati & Sitepu, 2021; Siregar et al., 2021; Yang et al., 2022). The mediating role of destination image on the effect of service quality on revisit intention has not been conferred with enough attention in developing nations. Therefore, this research study expands tourism literature by effectively acknowledging that destination image partially mediates the effect of service quality on revisit intention. Timur (2018) postulated that destination image partially mediates the effect service quality of on revisit intention. Results show that all hypotheses were supported. This implies that relationships that exist between service quality, destination image and revisit intention are not likely to change in developing countries.

6. Implications

Theoretical and practical contributions to marketing and tourism literature are generally provided by this study. The study provides theoretical contributions from different perspectives.

6.1. Theoretical implications

The present study is the first of its nature to examine the mediating role of destination image on the effect of service quality on revisit intention of tourists in Zimbabwe a developing nation. Previous study on tourism in Zimbabwe concentrated mainly on sustainable destination image recovery towards improving the performance of the tourism industry in Zimbabwe (Kanokanga et al., 2019). However, Zimbabwe’s tourism industry lacks studies that have managed to examine the mediating role of destination image on the effect of service quality on the revisit intention of tourists. The study focused on Zimbabwe’s tourism industry. Consequently, the study provides and broadens the existing literature that relates to the tourism sector from a contextual perspective. The majority of the previous research studies on tourism draw their sample from developed nations. Additionally, this study used three variables that include service quality, destination image and revisit intention. The proposed model of this study included the three variables thus, adding more value to available literature.

6.2. Practical implications

From a practical perspective, this study is significant for tourist destinations managers who seek to reach and influence tourist revisit intention.

Managers of tourist destinations are recommended to solve issues that are generally associated with service quality when developing business strategies projected to intensify tourist revisit intention. Improvement of services quality offered is vital to the realization of tourist intention to revisit. Managers of tourist destinations and the service providers, thus, should safeguard that frontline staff that advocate for higher levels of service quality to incoming tourists. As such, tourism service providers and Zimbabwe Tourism Authority (ZTA) the policy maker in the tourism industry should put extra effort on providing training and development that encourages employees to provide superior quality service to consumers and promote a positive image of the destination. Management of tourist destination organizations should heavily advance tourism activities intended at improving service quality and increasing revisit intention. One of the key tactic is to concentrate on service quality dimensions that include assurance, reliability, empathy, responsiveness and tangibility (Gobena, 2019; Wu et al., 2015). Favorable destination image may be attained through maintaining beautiful scenery and natural attractions and by providing superior tourism facilities that include lodges and chalets. In addition, it is advised that managers of tourist destination should improve destination image by providing safe and secure destinations Consequently, a favorable image motivates tourists to return and visit the destination, but tourists that are not happy and not satisfied with destination may not return to visit the destination. ZTA and the Ministry of Tourism in Zimbabwe are advised to monitor destination management companies (DMCs’) so that they provide superior tourism facilities that will improve the image of the destination. The study will effectively guide ZTA and the Ministry of Tourism to develop strategic policies and standard operating procedures (SOPs’) that will guide tourism service providers to provide superior service quality and a positive destination of the image that subsequently leads to tourist intention to return and visit. As tourists are increasingly visiting Zimbabwe, a developing nation, this study provides the much needed insights for destination marketers to effectively target tourists to return and visit again.

7. Future Research Recommendations

The study encountered limitations that motivated the need for more research. For instance, the study only focused on the tourism and hospitality sector. In addition, the study focused on a single country. Hence, it is not practical and feasible to generalize the results. As such, it is anticipated that more research work be conducted in other industries. Moreover, in different nations so as to improve the generalizability of results. Additionally, a cross-sectional approach was adopted. However, future scholars are recommended to adopt the longitudinal survey to gather data on the attitude and subsequent behavior of tourists.

8. Conclusion

The major objective of study was to examine the mediating role of destination image on the effect of service quality on revisit intention in a developing country. The study findings reveal that service quality and revisit intention are positively related. Results also indicate that service quality positively and significantly influences revisit intention. Furthermore, destination image significantly contributes to revisit intention. The study results conclude that the relationship between service quality and revisit intention is mediated by destination image.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Masimba Elvis Manyangara

Masimba Elvis Manyangara is a final-year PhD student at Chinhoyi University of Technology. He is currently a Marketing Officer in the Marketing and Quality Assurance Department at Zimbabwe Parks and Wildlife Management Authority (ZIMPARKS). His research area of interest is service quality and consumer behavior.

Charles Makanyeza

Charles Makanyeza is a senior academic, researcher and consultant who commands respect among his peers. Among many educational qualifications, he holds a PhD in Marketing from the University of KwaZulu-Natal, South Africa. He is an Associate Professor of Marketing and Strategy at the Namibia Business School, University of Namibia. His research areas of interest include marketing and strategy.

Zororo Muranda

Zororo Muranda is a Professor of Marketing. He is a former lecturer and Pro Vice Chancellor Business Development and Resource Mobilization at Chinhoyi University of Technology. His research area of interest is marketing. He is the present Chief Executive Officer of the Consumer Protection Commission.

Appendix A

Table

Measurement Scale
Reliability REL: 1 ZIMPARKS provides its services timeously as promised REL2: ZIMPARKS shows sincere interest in solving problems I encounter REL3: ZIMPARKS provides services correctly the first time REL4: ZIMPARKS provides error-free and up-to-date records REL5: When ZIMPARKS promises to deliver within a given time, it does so Assurance AS1: Behavior of ZIMPARKS staff instils confidence in me AS2: ZIMPARKS staff are consistently courteous with me A3: ZIMPARKS staff have the knowledge to answer my questions AS4: ZIMPARKS staff members are highly experienced AS5: ZIMPARKS staff makes customers feel safe in their service delivery Tangibility TA1: ZIMPARKS tourism administrative offices are attractive and appealing TA2: ZIMPARKS staff dress neatly and are always smart TA3: ZIMPARKS marketing material and documents on tourism services are visually appealing TA4: ZIMPARKS has modern tourist game drive vehicles TA5: ZIMPARKS has modern computers & software for tourist accommodation bookings Empathy EM1: ZIMPARKS gives me individual and personal attention EM2: ZIMPARKS operating hours are convenient to all customers EM3: ZIMPARKS staff understand my specific needs EM4: ZIMPARKS staff listen to customer problems EM5: ZIMPARKS staff are committed to ethics and promote ethical behavior at workplace Responsiveness RES1: ZIMPARKS provides prompt services RES2:ZIMPARKS staff are always willing to help RES3: ZIMPARKS staff are never too busy to respond to my requests RES4: ZIMPARKS staff informs customers exactly when services will be provided RES5: ZIMPARKS staff attends to complaints even after working hours	An et al. (2019); Coetzee and Coetzee (2019); Soleimani et al. (2018)
Destination Image DI1: ZIMPARKS destinations have beautiful scenery and natural attractions DI2: ZIMPARKS offers good value for money to tourists DI3: ZIMPARKS destinations possess superior tourism facilities (lodges, chalets) DI4: ZIMPARKS offers exciting and interesting places to visit DI5: ZIMPARKS destinations are safe and secure	Abbasi et al., (2021); Song et al. (2017); Tosun et al. (2015).
Revisit Intention RI1: I would like to revisit ZIMPARKS destinations often RI2: I intend to revisit ZIMPARKS destinations in future RI3: I will make an effort to revisit ZIMPARKS destinations in the near future RI4: I am willing to spend time and money to revisit ZIMPARKS destinations	Puspitasari et al. (2019), Soleimani et al. (2018), Song et al. (2017), Tosun et al. (2015