Acta Universitatis Danubius. Œconomica, Vol 13, No 1 (2017)

The Influence of Relationship Proneness on Relationship Satisfaction and Relationship Commitment: Empirical Evidence from Domestic Tourists in Cape Town, South Africa

Eugine Tafadzwa Maziriri1, Thobekani Lose2, Welcome Madinga3

Abstract: In South Africa, small tourism enterprises lie at the heart of the industry and form a major part of the tourism sector. There are the cornerstones of tourism development in local economies. This study assessed the influence of relationship proneness on relationship satisfaction and relationship commitment among domestic tourism clients within the Cape Town Metropolitan Area of South Africa. In spite of the increasing research on small tourism enterprises, they seem to be a paucity of studies that have investigated the influence of relationship proneness on relationship satisfaction and relationship commitment. The study utilised a quantitative research design using a structured questionnaire. The design was suitable to solicit the required information relating to relationship proneness, relationship satisfaction and relationship commitment. The findings indicate that relationship proneness has a positive influence on relationship satisfaction, relationship proneness has a positive influence on relationship commitment and relationship satisfaction exerts a positive influence on relationship commitment. All the posited three hypotheses were supported. The empirical study provided fruitful implications to academicians by making a significant contribution to the relationship marketing literature by systematically exploring the influence of relationship proneness on relationship satisfaction and relationship commitment. This study therefore, stand to immensely contribute new knowledge to the existing body of relationship marketing literature in Africa – a context that is often most neglected by some researchers in developing countries.

Keywords: Relationship Proneness; relationship commitment; relationship satisfaction; small tourism enterprises

JEL Classification: O55; R11

1. Introduction

In today’s post-modern era the ability to build a competitive network through relationships can be seen as one of the company’s core competencies. According to Johann (2014, p. 98) a company which develops a better marketing network and builds mutually profitable relationships gains competitive advantage in the market. Marketing scholars have suggested that firms should leverage firm–customer relationships to gain privileged information about customers’ needs and thereby serve them better than competitors (Ndubisi, Malhotra & Wah, 2009). Verhoef (2003) reported that a relationship is important for firms since establishing and maintaining relationships with customers will foster customer retention, customer share development and increased profit. According to Mostert and De Meyer (2010, p. 28) relationships hold benefits for the organisation and its customers and organisations should increasingly focus on building relationships with customers in an effort to better their results by identifying, satisfying, and retaining their most profitable customers. Lombard (2009, p. 410) stipulate that in any form of relationship between customer and service provider the attitude of the customer towards such a relationship is likely to be of importance, thus the stronger the customer perceives the importance of relationships in general, the more likely the customer is to develop a stronger relationship with the service provider. Therefore, the purpose of the current study is to investigate the influence of relationship proneness on relationship satisfaction and relationship commitment.

2. Cape Town

Kayster (2014) points out that Cape Town is a popular global and local tourist destination because of its natural beauty, cultural and historical characteristics. The British newspaper, The Guardian, and the United States of America publication, The New York Times, rated the city the top holiday destination for 2014 (Sapa, 2014). In addition, Cape Town is South Africa’s second most visted city after Johannesburg with an estimated 389 012 visitor arrivals at the Cape Town International Airport in July 2015 (Airports Company of South Africa, 2015). The major motivators for travel to Cape Town have been identified as nature culture and heritage purposes (City of Cape Town 2013). Moreover, Ezeuduji, November and Hautpt (2016) points out that Cape Town is emerging as a leading business and events destination in South Africa.

3. Research Problem

According to Rogerson, (2015) net declines in numbers of domestic tourism trips are evidenced in other parts of the country. The declining municipalities for domestic tourism are all situated in the Western Cape, Northern Cape or Free State provinces. Most striking are the declines recorded in the two metropolitan destinations of Cape Town and Mangaung (Bloem-fontein) (Rogerson, 2015). The largest decline is shown in Cape Town and explanations for Cape Town’s demise as a domestic tourism destination are related in part to its weak performance for VFR travel, which is the core component of domestic tourism (Rogerson, 2015). In addition Singh and Krakover (2015) suggest another cause for neglect of domestic travel results from “the popular assumption that tourists invariably originate from distant lands and other cultures” with the consequence that domestic travellers sometimes are discounted as tourists. Scheyvens (2002) as well as Canavan, (2013) also concurs that within tourism scholarship domestic tourists are given far less attention than their inter-national counterparts. The context for this research is mainly focusing on how domestic tourists build up rapports with small tourism enterprises. Therefore, this research paper presents some good news for Cape Town domestic tourism.

4. Literature Review

The review of literature plays a crucial role in the current research. Therefore, in this section efforts are directed to explore or assess the findings of the studies conducted by various scholars in the same field.

4.1. Relationship Proneness

The relationship proneness of a buyer is viewed as the behavioral tendency of a buyer to actively maintain and enhance a relationship with one particular seller (Wulf & Odekerken-Schröder). Researchers use the term relationship proneness to reflect the consumer’s relatively stable and conscious tendency to engage in relationships with sellers of a particular product category (Feng, Zhang & Ye, 2015) Relationship proneness has been associated with an interest for stable exchanges, and has been measured in terms of “willingness to be a regular customer” and “a steady customer”, and for “going the extra mile” to buy at the same shop (De Wulf et al., 2001).

4.2. Relationship Satisfaction

Homburg & Rudolph (2001) define satisfaction as a relationship constructs describing how a supplier fills the expectations of a customer in the following areas: characteristics of the product, information related to product, services, taking orders, complaints management, interactions with commercial and with internal staff. Thus, satisfaction appears as a concept highly integrated in the relationship. Relationship satisfaction refers to the extent to which an individual customer is satisfied with the relationship with a firm (Verhoef, 2003). De Wulf et al. (2001) consider the relationship satisfaction placed in affective theory. It is defined as a consumer’s affective state resulting from an overall appraisal of his or her relationship with a retailer (Anderson & Narus, 1990).

4.3 Relationship Commitment

Anderson and Weitz (1992) states that commitment to a relationship entails a desire to develop a stable relationship, a willingness to make short term sacrifices to maintain the relationship, and a confidence in the stability of the relationship. In addition, Rauyruen and Miller (2007) further elucidates that commitment as “a psychological sentiment of the mind through which an attitude concerning continuation of a relationship with a business partner is formed”. Relationships are built on the foundation of mutual commitment, and the commitment level has been found to be the strongest predictor of the voluntary decision to pursue a relationship (Ibrahim & Najjar 2008). Relationship commitment is a deeply held commitment to rebuy or repatronize from a preferred retailer consistently, despite situational influences that might encourage switching behavior (Oliver, 1997).

4.4. Small Tourism Enterprises

The vast majority of tourism enterprises around the globe are deemed to be small, belong to the indigenous population, and are family run (Morrison & Teixera, 2004, p. 167).The role of Small tourism enterprises in tourism is pervasive, since most travellers would come into contact with small tourism enterprises operating in a destination (Thomas & Thomas, 2006). Small tourism enterprises are important for retaining the economic benefits of tourism within a region and can act as the entry point for spending in the local area (Hawkins, 2004); they are a key component in regional economic development. Rogerson (2004, p. 7) agrees and adds that small tourism enterprises are numerically the largest component of the South African tourism economy and, thus, warrant close research attention.

5. Conceptual Model

Drawing from the literature review and the postulated hypotheses, a conceptual model was developed (Figure 1). The model consists of three research variables: one predictor –relationship proneness; one mediator relationship satisfaction and one outcome variable – relationship commitment.

Figure 1. Conceptual Model

5.1. Research Hypothesis Development

Based on the literature review, the following research hypotheses have been formulated to examine the relationships.

H1: relationship proneness positively influences relationship satisfaction;

H2: relationship proneness positively influences relationship commitment;

H3: relationship satisfaction positively influences relationship commitment.

6. Research Methodology

The study utilized a quantitative research design using a structured questionnaire. The design was suitable to solicit the required information relating to relationship proneness, relationship commitment and relationship satisfaction. The approach enables to examine the causal relationships with the constructs used in the study.

6.1. Sample and Procedure

The sample of the study comprised domestic tourists from the Cape Town metropolitan area of South Africa. A non-probability convenience sampling method was chosen for the purposes of this study since the characteristics of this method have particular appeal to financial and time constraints. Every attempt was made to ensure geographical representation of the sample.

7. Target Population and Data Collection

The target population for the study was domestic tourism clients or customers in the Cape Town Metropolitan area who have ever had any form of business with small tourism enterprises. Participation by the clients of these small tourism enterprises was purely voluntary. Students from the AAA School of Advertising, Cape Town campus were recruited and trained to serve as data collectors. A total of 200 questionnaires were collected from respondents. A covering letter accompanied the questionnaire stipulating the purpose of the study. In addition, the covering letter ensured respondents anonymity and confidentiality. A total of 151 questionnaires were eventually used for the analysis as 49 were discarded due to incomplete responses on the questionnaire.

8. The Questionnaire Layout and Questions Format

A four-section questionnaire was designed to collect data from the participants. Section A comprised of multiple choice questions pertaining to the respondents’ demographic factors such as gender, population group, age and type of small tourism enterprise that a domestic tourist is frequently in a relationship or in business with. Section B assessed relationship proneness and consisted of questions adapted from Feng, Zhang and Ye (2015). Section C measured relationship commitment and consisted of questions adapted from Wei, McIntyre & Soparno (2015). Section D of the questionnaire comprised questions on relationship satisfaction that where adapted from the study of Wei, McIntyre & Soparno (2015). In this research study, all the responses for Sections B, C and D were measured by a five-point Likert scale whereby, strongly agree=5 ,strongly disagree=1 and 3= neither agree or disagree.

9. Data Analysis and Results

A Microsoft Excel spread sheet was used to enter all the data and in order to make inferences of the data obtained, the Statistical Packages for Social Sciences (SPSS) and the Smart PLS software for Structural Equation Modeling (SEM) technique was used to code data and to run the statistical analysis. Additionally, these statistical packages were used for testing and confirming relationships among hypothesised variables.

10. Sample Composition

Of the 151 participants in this study, 60 percent (n=90) were male while 40 percent (n=61) were female. This gender composition tends to suggest that in Cape Town men are substantially more likely to be engaged in business with small tourism enterprises than women. The age structure of the sample, indicated that only 34% (n=51) of the respondents were under the age of 30 years, 32% (n=48) were aged between 30 and 39 years, 25.0% (n=38) represented the 40–49 year age group, 8% (n=12) represented the 50–59 year age group and a meagre 1% (n=2) of the sample were 60 years of age and above. The majority 34% (n=51) of the respondents were aged 30–39 years. Therefore it seems that the domestic tourists in the Cape Town metropolitan are greatly concentrated within the age bracket of 30–39 years. Lastly the respondents had to indicate the type of small tourism enterprise they are frequently in a relationship or in business with. Findings indicate that the majority of the respondents 55% (n=83) are in business with tourism accommodation enterprises, of the 151 respondents 23% (n=34) indicated that there are in business with those enterprises that mainly focus on food and beverage services, 11% (n=17) indicated that they are in business with small tourism enterprises that specialize in recreation and entertainment, 8% (n=12) admitted that they are in a relationship with or they frequently make use of transport services provided by small tourism enterprises that specialize in transport. Lastly a small number of the respondents 3% (n=5) specified that they engage with other type of small tourism enterprises such as those which are involved in the manufacturing of metal products as well as those with are involved in sculpturing of statues for tourism purposes.

Table 2. Scale reliabilities and accuracy statistics

Research constructs

Descriptive Statistics*

Cronbach’s test



Item Loadings




α Value

Relationship Proneness (RP)















Relationship Commitment(RC)















Relationship Satisfaction(RS)















RP1 to RP3 = relationship proneness scale items; RC1 to RC3 = Relationship commitment scale items; RS1 to RS3 = relationship satisfaction items. AVE = Average variance extracted. CR = Composite reliability. SD = Standard deviation

Reliability was assessed through Cronbach alpha values and Composite reliabilities All reliability values (Cronbach and composite rialiabilities) ranged from 0.763 to 0.890 (Table 2) these were above the recommended 0.7 (Nunnally 1978) suggesting excellent acceptable levels of research scale reliability. The study checked for both convergent and discriminant validity of the measurement instruments. To ascertain convergent validity, the factor loadings were considered in order to assess if they were above the recommended minimum value of 0.5. Table 2 shows that the factor loading for the research construct ranged from 0.729 to 0.926 and therefore above the recommended 0.5 (Anderson & Gerbing 1988) indicating acceptable individual item convergent validity as 69 % or more of each item’s variance was shared with its respective construct. The factor loadings for scaleitems (Table2) were above the recommended 0.5, which indicated that the instruments were valid and converging well on the constructs that they were expected to measure. Moreover discriminant validity was established by checking if the AVE values. The AVE estimates in Table 2 reflected that the overall amount of variance in the indicators were accounted for by the latent construct (Neuman, 2006:59). All AVE values were above 0.4, thus acceptable according to the literature (Fraering & Minor 2006:249). AVE values indicated indexes between 0.676 and 0.731. Therefore, these results provided evidence for acceptable levels of research scale reliability.

11. Correlation Analysis

One of the methods used to ascertain the discriminant validity of the research constructs was the evaluation of whether the correlations among latent constructs were less than 0.60. These results are reported in Table 3.

Table 3. Latent variables correlations

Research constructs

Construct correlation




Relationship Proneness (RP)


Relationship Satisfaction (RS)



Relationship Commitment (RC)




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

A correlation value between constructs of less than 0.60 is recommended in the empirical literature to confirm the existence of discriminant validity. As can be observed from Table 3, all the correlations were below the acceptable level of 0.60. A significant and medium correlation was revealed with the RP and RS association (r=0.562; p<0.01). A strong positive linear relationship between RC and RP was also shown at (r=0.456, p<0.01) level of significance, indicating that relationship proneness influences relationship commitment, and lastly, there was a positive strong relationship between RS and RC at (r=0.534, p<0.01), thus confirming that relationship commitment influences relationship satisfaction.

12. Structural Equation Modeling (SEM) Approach

In order to statistically analyze the measurement and structural models, this study used Smart PLS software. PLS is an SEM technique based on an iterative approach that maximizes the explained variance of endogenous constructs (Hair, Sarstedt, Hopkins & Kuppelwieser 2014) In SEM, the measurement model refers to the linkages between the latent variables and their manifest variables and the structural model captures the hypothesized causal relationships among the research constructs (Chin & Newsted, 1999). In addition to that, Smart PLS combines a factor analysis with near regressions, makes only minimal assumptions, with the goal of variance explanation (high R- square) (Anderson, Schwager & Kerns, 2006). Furthermore, Smart PLS supports both exploratory and confirmatory research, is robust to deviations for multivariate normal distributions, and is good for small sample size (Hair, Ringle, & Sarstedt, 2013). Since the current study sample size is relatively small (151) Smart PLS was found more appropriate and befitting the purpose of the current study.

13. Path Model Results and Factor Loadings

Below is Figure 2, indicating the path modeling results and as well
as the item loadings for the research constructs.

Figure 2. Path Model

14. Path Modeling & Hypotheses Testing

Table 4 presents the results of the structural equation modeling followed by a discussion.

Table 4. Results of structural equation model analysis



Path coefficients (β)

T- Statistics

Decision on Hypotheses

Relationship Proneness (RP) Relationship Satisfaction (RS)




Accept/ Significant

Relationship Proneness (RP)Relationship Commitment (RC)




Accept/ Significant

Relationship Satisfaction (RS) Relationship Commitment (RS)




Accept/ Significant

aSignificance Level p<.10; bSignificance Level p<.05; cSignificance Level p<.01.

Table 4 presents the three hypothesised relationships, path coefficients, the t-statistics and the decision criteria. The value of the t-statistic indicates whether the relationship is significant or not. A significant relationship is expected to have a t-statistics that is above 2. Drawing from the results provided in Table 4, three of the hypothesised relationships (H1, H2 and H3) were statistically significant.

16. Discussion

The first hypothesis stated that relationship proneness has a positive influence on relationship satisfaction. In this study, this hypothesis was supported. It can be observed in Figure 2 and Table 4 that relationship proneness exerted a positive influence (r =0.204) and was statistically significant (t=3.336) in predicting relationship satisfaction. This result suggests that higher the level of relationship proneness the higher the level of relationship satisfaction. The second hypothesis suggested that relationship proneness has a positive influence on relationship commitment. This hypothesis was supported in this study. Figure 1 and Table 4, indicate that this relationship H2 was supported. Relationship proneness exerted a positive influence (r= 0.563) on relationship commitment and was statistically significant (t= 7.049). This result denotes that relationship commitment is positively and significantly related to relationship satisfaction. Thus higher levels of relationship proneness will lead to higher levels of relationship commitment. The third hypothesis, which advanced that relationship satisfaction exerts a positive influence on relationship commitment was supported and accepted in this study. It is reported in Figure 1 and Table 4 that H3 relationship satisfaction employs a positive (r=0.086) influence on relationship commitment and that this influence is statistically significant (t=1.360). Thus higher levels of relationship satisfaction will lead to higher levels of relationship commitment.

17. Limitations and Future Research Direction

Although this study makes significant contributions to both academia and practice, it was limited in some ways, and therefore some future research avenues are suggested. First, the data were gathered from Cape Town Metropolitan area of South Africa and the sample size of 151 is relatively small. Perhaps, the results would be more informative if the sample size is large and data gathered from the other Metropolitan areas in South Africa. In addition since this study used a quantitative approach, future studies could also use a mixed method approach so that in depth views from domestic tourists can also be captured. Future studies can also extend the current study conceptual framework by studying the effects of a larger set of variables. For instance, the influence of relationship quality, relationship value, relationship cultivation, perceived relationship benefits, and relationship longetivity could be investigated.

18. Recommendations to Marketing Managers or Owners of Small Tourisms Enterprises

In formulating relationship strategies, small tourism enterprises therefore should consider customers as the ‘ultimate object of loyalty’, which they must earn, in the form of consumer to firm relationships. The researchers recommend marketing managers or owners of small tourisms enterprises to resort to relationship marketing so as to improve the business performance of their enterprises. Van Tonder (2016) reviews relationship marketing as such can be viewed as a business strategy aimed at establishing and sustaining long -term relationships with customers that are mutually rewarding and which are achieved through having conversations with customers, treating customers as individual persons and fulfilling promises. In a study that was conducted by Maziriri & Chinomona (2016) in order to examine how relationship marketing, green marketing and innovative marketing influence the business performance of Small, Medium and Micro Enterprises (SMMEs) in Southern Gauteng, South Africa. Their study’s results reviewed that relationship marketing exerted a positive influence and was statistically significant in predicting business performance and this result suggested that higher the level of relationship marketing the higher the level of business performance in the SMMEs. Taking into account, Maziriri & Chinomona’s (2016) findings it can be noted that small tourism enterprises who wish to build up strong lasting rapports with domestic tourists as well as increasing their business performance should engage in a high level of relationship marketing.

19. Conclusions and Managerial Implications

The study validates that factors such as relationship proneness and relationship satisfaction are instrumental in stimulating the relationship commitment of domestic tourism clients with their tourism enterprises within the Cape Town metropolitan area. The study further validates those small tourism enterprises that are engaged in rapport building with their domestic tourism clients enhance customer satisfaction, customer loyalty and ultimately enhancing high business performance. The study has both theoretical and managerial implications. Theoretically, this study makes a noteworthy progression in marketing theory by methodically examining the interplay between relationship proneness on relationship satisfaction and relationship commitment. In this manner, the study is an important contributor to the existing literature on this subject. The study also underwrites a new direction in the research on relationship marketing by opening up a discussion on the importance of rapport building (between domestic tourists and small tourism enterprises) in the development and improvement in developing countries such as South Africa.

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1 PhD Candidate, Marketing Division, School of Economic & Business Sciences, Faculty of Commerce Law and Management, University of the Witwatersrand, South Africa, Address: Richard Ward, 1 Jan Smuts Ave, Braamfontein, Johannesburg, 2000, South Africa, E-mail:

2 PhD Candidate, Department of Logistics, Faculty of Management Sciences, Vaal University of Technology, South Africa, Address: Gauteng Province, Vanderbijlpark, South Africa, Corresponding author:

3 PhD Candidate, Department of Marketing Management, School of Management Sciences, Faculty of Business and Economic Sciences, Nelson Mandela Metropolitan University, Address: Port Elizabeth, South Africa, E-mail:

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