RESEARCH ARTICLES

 

Relational benefits and customer satisfaction - a South African short-term insurance industry perspective

 

 

N Mackay; DJ Petzer; PG Mostert

North-West University

 

 

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ABSTRACT

South African short-term insurers struggle to maintain and grow market share due to industry competitiveness and decreasing customer retention rates. One way of retaining customers is to establish and maintain long-term relationships with them. For relationships to last, customers should derive benefits from these relationships. It is furthermore professed that the relational benefits that customers gain from customer-business relationships positively impact customer satisfaction, which in turn enhances the quality of these relationships.
This paper aims to determine whether relational benefits (confidence, social and special treatment benefits) predict customer satisfaction in the South African short-term insurance industry. Research focussing on customer relational benefits is limited, and such research has not been conducted within this industry or context. A quantitative, descriptive research design was undertaken and convenience sampling was used to select respondents. Data was collected by means of self-administered surveys from short-term insurance policy holders residing in Gauteng, South Africa.
The results indicate that confidence benefits best predict customer satisfaction, followed by social and special treatment benefits. It is therefore recommended that, in order to improve customer satisfaction and maintain long-term relationships with customers, short-term insurers adapt their product and service offerings to include confidence, social and special benefits to customers.

Key phrases: confidence benefits; customer satisfaction; relational benefits; short-term insurance; social benefits; special treatment benefits

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1. INTRODUCTION

"Growth in the South African short-term insurance industry is under pressure" (KPMG 2013:75) which is ascribed to economic changes (or the lack thereof), strict regulatory requirements, demanding customers and increased rivalry (KPMG 2013:81; PwC 2012:4). Kurtz (2014:354) professes that customers are more informed and sophisticated in their requirements than ever before, which results in them growing more demanding and less loyal. The Accenture 2013 Global Consumer Pulse Survey (Accenture 2013:10) also revealed that 66% of customers end their relationship with a business due to dissatisfaction with customer service.

In view of the fact that it is generally more expensive to attract new customers than to keep current ones, businesses aim to create lasting relationships with customers in order to enhance their satisfaction and overall loyalty (Bolton & Christopher 2014:23). Kaura, Datta and Vyas (2012:74) established that satisfied customers are more likely to increase their spending, return for repurchases, spread positive word-of-mouth, and invest in a long-term and loyal relationship with the business.

The work of Egan (2011:128) established four factors that could determine customer satisfaction, namely the core product or service offering, supporting services, technical performance, and customer interactions. The initial research of Gwinner, Gremler and Bitner (1998), however, suggested that apart from the core offering, the business should also provide customers with additional relational benefits, in order to motivate them to remain within the relationship. The importance and relationship of relational benefits on customers' satisfaction and behavioural intentions was further supported by the research of Chen and Hu (2013) and Yen, Liu, Chen and Lee (2014). These researchers propose that, instead of simply providing quality services in an attempt to satisfy customers, the business should also provide relational benefits, which will in turn contribute significantly to customers' satisfaction levels.

From the above overview, it is clear that positive relational benefits generally result in positive behavioural outcomes, such as satisfied customers. Evidently, timely and reliable information regarding the relational benefits that short-term insurance customers receive can be particularly valuable in enhancing these customers' experiences, their satisfaction levels, and ultimately their future behavioural intentions. The aim of this study is, therefore, to uncover whether relational benefits predict South African short-term insurance customers' levels of satisfaction.

 

2. PROBLEM STATEMENT, PURPOSE AND OBJECTIVES

South African short-term insurers are finding it increasingly difficult to maintain market value amidst current erratic economic conditions - with inflation, interest rates and exchange rates reaching new and unpredictable highs and lows (SAIA 2012:5; Snyders 2014:25).

In addition, the short-term insurance industry is faced with two critical challenges: the increasing number of short-term insurers entering the industry and the significant decrease in customer retention rates (PwC 2012:14).

These challenges present short-term insurers with a strategic imperative - they need to adopt a customer-focused approach, incorporating an integrated customer focus aimed at satisfying customers (Egan 2011:8). Bolton and Christopher (2014:11) note that, if businesses are to succeed, they need to develop insights into their customers' perceptions of the service offering and the existing relationship with their service provider (i.e. short-term insurer). Such insights regarding the South African short-term insurance industry are, however, limited. It is, furthermore, important to keep in mind that customers' perceptions, expectations and behaviours can differ significantly between various cultures and demographics (Kurtz 2014:173). Cross-country research results might thus not necessarily be applicable to the South African context.

The purpose of this study is, therefore, to gain insights into the relational benefits customers receive from being in a relationship with their short-term insurers, and to determine if these benefits predict customers' satisfaction levels. Subsequently, the following objectives are formulated:

■ Measure the relational benefits customers receive from their short-term insurers.

■ Measure the level of satisfaction customers receive from their short-term insurers.

■ Determine whether the relational benefits customers receive from their short-term insurers predict their customer satisfaction levels.

 

3. LITERATURE BACKGROUND

This section provides an overview of the South African short-term insurance industry, followed by a discussion of the key constructs under investigation (i.e. relational benefits and customer satisfaction).

3.1 The South African short-term insurance industry

The South African insurance industry contributes approximately 2.5% to the South African GDP and consists of 87 long-term and 108 short-term registered insurers (FSB 2012:41). Long-term insurers include those insurers that offer financial protection, pension funding, or death coverage, whereas short-term insurers provide customers with immediate coverage against low probability losses, damages or liabilities - insuring household contents, vehicles, properties and personal accidents (Breckenridge, Farquharson & Hendon 2014:50, 51). Certain types of coverage, such as motor and property insurance, are often considered compulsory by financing companies (MarketLine 2013:12).

The value of the short-term insurance industry, calculated in terms of gross written premiums, increased by 9.3% from 2010 to 2011, and dropped to a 7.9% increase from 2011 to 2012 (KPMG 2013:75). Despite this decline, the South African short-term insurance industry is still considered an enabling mechanism for economic growth, as it was able to increase its earnings in 2012 to exceed the R70 billion mark (SAIA 2012:23).

In terms of market share, Santam and Mutual & Federal have been dominating the short-term insurance industry since 2001 (KPMG 2013:76). Whilst these two insurers are still prominent representatives in the short-term insurance industry, they have been exposed to significant changes and challenges in the marketplace. Aspects such as the changing nature of consumerism, new entrants to the market, and degree of competitiveness all contributed to declining market shares (PwC 2012:23). By 2013, Santam and Mutual & Federal were still leading the South African short-term insurance industry, with a 23.1% and 10.5% market share respectively. OUTsurance followed shortly, with a 9.8% market share (KPMG 2013:77).

A report by MarketLine (2013:13) notes that customer loyalty in the short-term insurance industry is relatively low, since customers tend to shop around for the best cover and lowest premium offerings. In addition, technological advances and Internet access are enabling customers, providing them with the opportunity to compare insurers' prices, services and experiences. Customers, , tend to easily switch between insurers, posing another challenge for insurers (Accenture therefore 2013:16; PwC 2012:22).

On a final note, Accenture (2013:16) recorded that customer satisfaction levels in the casualty and property insurance industry have been declining, which consequently affected customers' loyalty towards insurers. Together with the economic uncertainty, South African short-term insurers are finding it increasingly difficult to maintain their market value (Snyders 2014:25), and are therefore advised to focus on satisfying or delighting customers' expectations by means of beneficial relationships (Li, Ford, Zhai & Xu 2012:5446).

3.2 Relational benefits

It is common practice for service businesses to measure service quality as the only service factor influencing customers' behaviours and intentions (Gwinner et al. 1998). Hennig-Thurau, Gwinner and Gremler (2002) have, however, introduced relational benefits as an essential factor that also relate to customers' perceptions about the service and the service provider. These authors reason that the benefits that customers experience from their relationship with the service provider affect their satisfaction with the service and service provider (Hennig-Thurau et ai. 2002; Lee, Choi, Kim & Hyun 2014:244).

In other words, despite the benefits that customers receive with respect to the quality of the services on offer, they are also likely to gain benefits from simply being in a relationship with the service provider (Chen & Hu 2013:1091). These additional benefits that customers receive above and beyond the core service are referred to as relational benefits (Hennig-Thurau et al. 2002:234), and include confidence benefits, social benefits and special treatment benefits.

3.2.1 Confidence benefits

According to Dagger and Danaher (2014:56), confidence benefits describe a combination of psychological benefits that customers experience. These benefits, therefore, relate to customers' feelings of security and comfort with the service business in knowing what to expect in the service encounter. In a trusting customer-business relationship, customers are confident in the business' performance. As a result, they are less anxious regarding their purchasing processes, since they know they will receive the business' highest level of service and, therefore, feel confident that operation risks are limited (Lovelock & Wirtz 2011:375).

Confidence benefits are commonly regarded as having the most important effect on customer satisfaction and hold most advantages for customers. This means that customers favour feelings of safety and trust in a service business, instead of some form of price discount (Yu & Yang 2012:216). If these feelings and assurances are promoted within customer-business relationships, the possibility of achieving customer satisfaction and loyalty will be much greater (Yen et al. 2014:17).

3.2.2 Social benefits

According to Lovelock and Wirtz (2011:374), customers can develop a sense of familiarity and even form a social bond with a service business over time. The benefits that customers derive from this close relationship are known as social benefits, and relate to the emotional part of the customer-business relationship (Yen et al. 2014:5). These benefits include, among others, personal recognition of customers, a sense of belonging, being known by name, and feelings of familiarity and friendship towards the service business (Hennig-Thurau et al. 2002:234).

Kim, Jeon and Hyun (2011:778) note that social benefits can develop through any type of interpersonal contact between the customer and service business. Customers who are in a positive social relationship with a service business will experience the benefits related to this relationship. The relationship of these benefits might cause customers to manifest their satisfaction through loyalty and commitment to the service business.

3.2.3 Special treatment benefits

Hennig-Thurau et al. (2002:234) describe special treatment benefits as the result of employees' unusual behaviours towards those customers who have developed a relationship with the service business. In these relationships, customers receive benefits in the form of economic and customisation benefits (Yen et al. 2014:6). Economic benefits include discounts, as well as non-pecuniary benefits such as receiving faster service than other customers, or it could simply be the time saved by the customer in searching for another service business to provide the required service. Customisation benefits include customers' perception of preferential treatment, extra attention and individualised additional services not available to other customers (Lovelock & Wirtz 2011:374).

Service businesses' offer of special treatment benefits is often perceived as part of the service performance itself. Offering special treatment benefits such as discounts or individualised services can encourage customers to remain in the relationship with the service business (Li et al. 2012:5457).

3.3 Customer satisfaction

Bolton and Christopher (2014:17) defines customer satisfaction as the customer's 'post-consumption assessment or fulfilment response'. Thus, if the customer experiences fulfilment, he or she will be satisfied, while underfulfilment results in dissatisfaction, and overfulfilment results in delight.

Several scholars are, therefore, in agreement that customer satisfaction is a fundamental construct in marketing research (Kaura et al. 2012; Sun & Kim 2013; Yeung, Ramasamy, Chen & Paliwoda 2013). Without customers, businesses have no reason to exist. However, without satisfied customers, businesses will exist with great difficulty - this means that satisfied customers are imperative for most businesses (Dagger & Danaher 2014:60).

The research of Yeung et al. (2013:413) adds that service businesses should focus on developing and maintaining long-term and profitable relationships with customers. It is, thus, essential that service businesses firstly understand customers' expectations, and secondly also meet (i.e. satisfy) and/or exceed (i.e. delight) their expectations (Kurtz 2014:192). As a result, service businesses should aim to retain profitable customers for as long as possible, by constantly measuring and improving customer satisfaction levels. Sun and Kim (2013) and Yeung et al. (2013), confirmed the favourable attributes of increased customer satisfaction levels to include customer loyalty and repeat business, decreasing price sensitivity amongst customers, protecting the business against price competition, reduced marketing expenses, enhanced reputation, and positive word-of-mouth communications.

Apart from the numerous benefits of ascertaining satisfied customers, it is also necessary to understand what determines whether customers are satisfied or not, since these determinants provide valuable insight into the strategies the business needs to implement in order to achieve customer satisfaction (Egan 2011:128). Kaura et al. (2012:44) and Ledden, Kalafatis and Mathioudakis (2011:1247) identified various customer-perceived service factors as determinants of satisfaction, including service and/or product quality, relational benefits, and even demographic variables.

In other words, if a service business's offering is inadequate, the business could risk losing potentially valuable customers. As a result, the business will also lose revenues and its competitive advantage (Bolton & Christopher 2014:18).

3.4 The relationship between relational benefits on customer satisfaction

The research of Hennig-Thurau et al. (2002:243) and Yen et al. (2014:13) have found that confidence benefits and social benefits (as relational benefits) affect customers' levels of satisfaction significantly and positively. Thus, the customer's satisfaction with, and loyalty towards the service business will increase as the social relationship between the customer and employee improves (Kim et al. 2011:778). It is evident that social benefits concern the buyer-seller relationship itself, rather than the performance or the level of service quality.

Yen et al. (2014:6) emphasise that, as a service business increases the number and level of special treatment benefits, emotional barriers to switching to another service business will increase. As a result, satisfaction, loyalty and commitment on the part of the customer will indeed intensify (Kim et al. 2011:778). Dimitriadis (2011:308) furthermore suggest that, instead of focusing on the economic aspects of special treatment benefits (which can easily be imitated by other service businesses), service businesses should rather focus on non-financial benefits as a sustainable source of competitive advantage.

Lee et al. (2014:245) also found that confidence benefits have a positive influence on customer satisfaction. This is based on the notion that high levels of trust and confidence in a service business will result in lower anxiety during customers' purchasing actions. As a result, Kim et al. (2011:778) suggests that businesses can maintain committed and loyal customer relationships by making customers feel more secure in their choices and purchases.

From the foregoing discussion, it is evident that relational benefits generally do have a positive effect on customer satisfaction. Thus, if a customer experiences positive benefits from being in a relationship with the insurer, he/she will most likely be satisfied, and consequently have positive behavioural intentions towards this insurer.

From the literature provided, the following alternative hypotheses have been formulated:

H1: Confidence benefits predict customer satisfaction in the South African short-term insurance industry.

H2: Social benefits predict customer satisfaction in the South African short-term insurance industry.

H3: Special treatment benefits predict customer satisfaction in the South African shortterm insurance industry.

 

4. RESEARCH METHODOLOGY

4.1 Research design

The researchers followed a quantitative descriptive research design. The design was also cross-sectional in nature and respondents were surveyed once at a particular point in time.

4.2 Target population

The target population included all those individuals who have short-term insurance at the time the survey was conducted and reside in the Gauteng Province of South Africa. This population was chosen based on its accessibility, and also because the province represents the largest share (23.7%) of all provinces of the South African population (Statistics South Africa 2011:Internet).

4.3 Sampling plan

A non-probability convenience sampling technique was used since a sampling frame that truly represents the target population was not available. Prospective respondents were approached to participate in the research on the basis of convenience. The initial sample size consisted of 907 responses. However, due to a number of response errors, a final sample size of 891 was realised and 769 responses were finally included in the multiple regression analysis since missing values were treated on a case-wise basis (case-wise deletion) and two outliers were removed.

4.4 Questionnaire

Data was collected by means of a self-administered questionnaire. The first section of the questionnaire measures respondents' short-term insurance patronage habits. The second section measures the relational benefits respondents receive from their short-term insurers, as well as their levels of customer satisfaction with the short-term insurer. Each of the items included in the scales measuring relational benefits and customer satisfaction was measured on a ten-point unlabelled Likert-type scale, with 1 representing 'strongly disagree' and 10 'strongly agree'. The final section of the questionnaire measures the demographic profile of respondents.

4.5 Data collection

Trained fieldworkers were assigned to distribute the questionnaires to respondents. Fieldworkers approached respondents on the basis of convenience, subsequently ensured they meet the criteria for participating in the study, and asked them to complete the questionnaire. Upon completion of the fieldwork, the fieldworkers returned the completed questionnaires to the researchers, who checked for errors that might have occurred during the data collection process.

4.6 Data analysis strategy

The data was entered from the paper-based questionnaires into an electronic data file using the SPSS statistical package. Subsequently the data was edited, cleaned and analysed. Frequencies and percentages were calculated to present the demographic profile and insurance patronage habits of respondents.

Standard deviations and means for each of the items measuring the three dimensions of relational benefits (confidence, social and special treatment benefits) and the customer satisfaction construct were also calculated.

Confirmatory factor analyses (CFAs) were conducted to confirm the validity of each of the dimensions of relational benefits and the customer satisfaction construct. The reliability of the scales measuring each of the relational benefits dimensions and the customer satisfaction construct was determined by assessing Cronbach's alpha values.

Subsequently, overall mean scores were calculated for the valid and reliable dimensions and construct. A simple multiple regression technique was then employed to test the alternative hypotheses formulated for the study.

 

5. FINDINGS OF THE RESEARCH

5.1 Demographic profile of respondents

Table 1 provides insights into the demographic profile of the respondents who participated in this study. The table reports the frequencies and percentages of each of the demographic variables concerned.

It can be seen from Table 1 that the respondents are fairly equally represented with respect to gender, with females representing 53% and males 47% of the sample. With regard to age, 41.1% of the respondents are 20 to 30 years old and 44.1% speak English as home language. Almost half of the respondents (46.7%) spend more than R1 000 per month on insurance premiums.

5.2 Insurance patronage habits of respondents

Table 2 indicates the insurance patronage habits of respondents.

With regard to the insurance patronage habits of respondents, Table 2 indicates the largest group of respondents are insured with OUTsurance (17.8%), followed by ABSA (10.2%), and Mutual & Federal (9.3%). Most respondents (70.7%) have their vehicles insured, while 38.8% and 32.1% of the respondents hold household contents insurance and house owner's insurance respectively. In addition, most respondents (62.8%) have been insured for a period of 1 to 5 years.

5.3 Descriptive results for individual scale items

Table 3 presents the standard deviations (SD) and means for each of the items measuring the three dimensions of relational benefits (confidence, social and special treatment benefits) and the customer satisfaction construct. It is evident from Table 3 that with respect to the confidence benefits dimension of relational benefits, the means for the items are fairly uniform ranging between 6.39 and 7.05 on a ten-point scale.

The items 'I have confidence that my insurer will deliver the required services correctly' and 'My insurer has clear and reasonable service offerings' both realised the highest means of 7.05, and the item 'I receive my insurer's highest level of service' realised the lowest mean (mean = 6.39).

With respect to the social benefits dimension of relational benefits, the means for the items are fairly uniform ranging between 5.04 and 5.28 on a ten-point scale.

The item 'I am familiar with the employees who perform the service' (mean = 5.28) realised the highest mean, and the item 'I have developed a friendship with the related employee' realised the lowest mean (mean = 5.04). With respect to the special treatments dimension of relational benefits, the means for the items are fairly uniform ranging between 4.94 and 5.35 on a ten-point scale. The item 'My insurer offers me special services' (mean = 5.35) realised the highest mean, and the item 'My insurer offers me better prices than for other customers' realised the lowest mean (mean = 4.94).

5.4 Validity

All items were either adopted or adapted from existing scales measuring relational benefits (Gwinner et al. 1998) and customer satisfaction (De Wulf, Odekerken-Schröder & lacobucci 2001 ; Evans, Kleine, Landry & Crosby 2000; Mano & Oliver 1993). These authors found the scales valid to measure these constructs.

Furthermore, confirmatory factor analyses (CFAs) were conducted to confirm the validity of each of the dimensions of relational benefits and the customer satisfaction construct. The results of the CFAs conclude that each confidence benefit dimension can be reduced to one factor explaining 67.92% of the variance or more. The results of the CFA therefore confirm the validity of each of the dimensions of relational benefits, as well as the customer satisfaction construct.

5.5 Reliability

The reliability of the scales measuring the relational benefits dimensions and the customer satisfaction construct was determined by assessing Cronbach's alpha values, which determine the inter-item correlation between items in a scale which is, in turn, used to establish the internal reliability of the scale. Table 4 indicates the Cronbach's alpha values for the above-mentioned dimensions of relational benefits and the customer satisfaction construct.

As can be seen in Table 4, the Cronbach's alpha coefficients for all dimensions and the constructs are greater than 0.70, which indicates a high level of reliability between items that measure relational benefits and customer satisfaction (Pallant 2010:6). Once validity and reliability of the scales were established, standard deviations and overall mean scores could be calculated for the relational benefits dimensions and the customer satisfaction construct of the study.

5.6 Descriptive results for relational benefits dimensions and the customer satisfaction construct

Table 5 presents the standard deviations (SD) and overall mean scores for the relational benefits dimensions and the customer satisfaction construct of the study.

The overall mean scores for the three dimensions of relational benefits range between 5.153 and 6.889 on a ten-point scale with confidence benefits realising the highest mean score (6.889), followed by social benefits (5.162) and special treatment benefits (5.153) respectively. It is evident that only confidence benefits realised a fairly positive overall mean score with social benefits and special treatment benefits only realising overall means scores close to the middle of the scale.

5.7 Hypothesis testing

Before a simple multiple regression technique can be used to test the alternative hypotheses of the study, it was important to ensure that the assumptions regarding the data that underlie the use of this technique were met (Allen & Bennett 2010:180).

In the end, the data of 769 respondents was included for analysis well above the 74 respondents suggested when three independent variables are included in a regression model (Tabachnik & Fidell 2007, cited in Allen & Bennett 2010:180). The P-P and Scatterplots both indicate that the distribution of the data can be considered normal, the assumption of homoscedasticity of variance has been satisfied and by considering a Mahalanobis distance of 16.27 as cut-off point, two cases were deleted from the data set as they were identified as outliers (Allen & Bennett 2010:180-187; Pallant 2010:159).

With respect to possible multicollinearity between the three independent variables, the regression coefficients indicating the strength of the relationships between the variables concerned were all < 0.85, the Tolerance > 0.10 and the Variance Inflation factor < 10.00 (Allen & Bennett 2010:180, 186; Pallant 2010:158). Based upon these measures, multicollinearity is ruled out. With respect to residual statistics, a maximum Cook's distance of less than 1.00 was realised in each case, indicating no issues with respect to homoscedasticity of the residuals (Allen & Bennett 2010:180; Pallant 2010:160). Tables 6 to 8 provide insight into the results of the multiple regression analysis performed. It is evident from Table 6 that the model, with customer satisfaction as the dependent variable and confidence, social and special treatment as the independent variables or predictors, indicate that the three independent variables explain 72.70% (R² = 0.727) of the variance in the dependent variable (customer satisfaction).

It is furthermore evident from Table 7 that the model is significant with p < 0.0005.

Table 8 indicates that the constant is significant (p < 0.0005) and according to the standardised (P) regression coefficients and corresponding p-values confidence benefits, social benefits and special treatment benefits are all predictors of customer satisfaction with p-values ranging between p < 0.0005 and p = 0.003 and p-values ranging between P = 0.081 and p = 0.750.

With respect to the alternative hypotheses formulated for the study the following can be concluded:

■ H1 that confidence benefits predict customer satisfaction in the South African short-term insurance industry can be accepted (P = 0.75, p < 0.0005).

■ H2 that social benefits predict customer satisfaction in the South African short-term insurance industry can be accepted (P = 0.098, p = 0.001).

■ H3 that special treatment benefits predict customer satisfaction in the South African short-term insurance industry can be accepted (P = 0.081, p = 0.003).

 

6. DISCUSSION AND IMPLICATIONS

Gwinner et al. (1998) introduced the idea that customers' behaviours and intentions (in a service environment) are affected by more than just the quality of the service, and highlighted that additional relational benefits (social, confidence and special treatment benefits) are just as influential. Additional research (Dimitriadis 2011; Hennig-Thurau et al. 2002; Yen et al. 2014) set out to establish the significance of the effect of relational benefits on customers' satisfaction, noting that, within various service settings, the three relational benefit dimensions generally positively affect customers' satisfaction with the related service provider.

In this study, the results of the hypothesis testing supported existing literature, in that all three relational benefit dimensions (confidence benefits, social benefits, and special treatment benefits) were found to predict customer satisfaction with short-term insurers, although to varying extents. Confidence benefits were found to be the best predictor of customer satisfaction. This is in accordance with the findings of Yen et al. (2014:13) and reinforces the premise that confidence in the short-term insurer is the key to a positive, longterm relationship between the customer and the insurer.

South African short-term insurers ought therefore to emphasise confidence benefits in positioning their services to customers, instead of just focusing on aspects such as performance, efficiency or convenience. This would entail that marketing strategies facilitate and accelerate the delivery of confidence benefits in particular, by establishing and enhancing feelings of security and comfort within the customer. In addition, policy holders expressed their lack of confidence in their short-term insurer in terms of the level of service they receive. Thus, in order to ascertain satisfied customers, South African short-term insurers should employ competent personnel to ensure the delivery of continuously high levels of service, with the lowest associated risks.

Even though social benefits and special treatment benefits were found to predict customer satisfaction to a lesser extent, their ability to predict customer satisfaction is still significant and positive. In addition, these two relational benefits were also identified as being less positively perceived by respondents. Due to people's general need for social affiliation, it is recommended that short-term insurers focus on the emotional part of the customer-business relationship and cultivate a sense of belonging among customers.

Short-term insurers should also employ workers who enjoy interacting with customers on a regular basis, and encourage these employees to develop some sort of friendship with customers. This can be achieved by employees using information contained in short-term insurers' records (i.e. within CRM-software) to engage in conversations with customers on areas of interest to them, for example sports and hobbies, thereby creating a feeling of familiarity with customers (Hennig-Thurau et al. 2002:234).

Short-term insurers could therefore gain higher levels of customer satisfaction since social benefits could develop through interpersonal interaction with customers (Kim et al. 2011:778). Special treatment benefits were perceived as least positive by respondents, which coincide with the research of Dimitriadis (2011:307) as well as Kim et al. (2011:777). However, since special treatment benefits do predict short-term insurance customers' satisfaction, South African short-term insurers should therefore benefit from efforts to increase customers' perceptions of the special treatment benefits they receive from the relationship. These insurers can capitalise on customers' desire for preferential treatment, by means of customised offerings and financial benefits. Short-term insurers can build on the concept of customising insurance policies, and accordingly adapt the individual's policy premium based on the insured content. It can furthermore be recommended that short-term insurers consider other forms of special treatment benefits, not necessarily related to insurance-related products and services, to make customers feel special. For example, short-term insurers could offer customers free magazine subscriptions or give free tickets to, for example, movies, sport or other events relating to customer interests.

From the empirical results, respondents indicated that they are the least satisfied with their short-term insurer's efforts, as well as the social contact. This alludes, again, to the additional benefits offered by the insurer, namely confidence and social benefits. In other words, if South African short-term insurers wish to improve policy holders' overall levels of satisfaction, they need to pay attention to the three relational benefit dimensions. By offering relational benefits, short-term insurers can establish high levels of customer satisfaction, thus enabling them to maintain long-term relationships with their customers, which should in the end, reward the short-term insurer with several positive behavioural outcomes.

 

7. CONCLUSION

Quality secondary sources of a scholarly nature on the short-term insurance industry are limited, as well as literature on South African insurance studies (specifically pertaining to problems associated with customers' behavioural intentions), which meant that the literature discussion had to be based on international studies focusing on various service industries.

In addition, the researchers were unable to gain access to customer databases in the industry (to serve as a framework), which means that the study had to rely on convenience sampling. The results of this study are therefore not representative of the entire population, and only represent those respondents who participated in the study. Future research should attempt to involve short-term insurers in order to use their customer databases as a sampling frame to conduct probability sampling. This study can be repeated nationally in all nine South African provinces, and comparisons can be drawn to determine whether significant differences exist between respondents from different geographic locations. A similar study can also be conducted amongst long-term insurers and comparisons can be drawn between the different sectors.

 

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