Competitive Strategy Alighnment in Enhancing Insurance Uptake: An Evaluation of Life Insurance Products in Uganda

Olobo Maurice^1*, Gerald Kagambirwe Karyeija², Protazio Sande², Ronald Regan Okello²

¹School of Business, Uganda Christian University, Mukono, Uganda.
²School of Management Science, Uganda Management Institute, Kampala, Uganda.

DOI: 10.4236/jfrm.2022.112012                

Abstract

The study examined the effect of competitive strategies on life insurance uptake in Uganda using Kampala Central Business District as a case study. Specifically, the study examined the extent to which differentiation strategy, cost leadership strategy and distribution channel affect life insurance uptake in Uganda. A cross-sectional research design was used with a mixed research approach employing both qualitative and quantitative methods of data collection and analysis. A sample size of 306 respondents was selected from a study population of 1500 using of Krejcie & Morgan’s table. Data was analyzed using mean and standard deviation for descriptive analysis. Pearson’s correlation and regression analysis were also used to analyze the relationship between competitive strategies and life insurance uptake, and to determine the most significant predicator variable among the independent variables respectively. At bivariate level, differentiation strategy, cost leadership strategy and distribution channels had a significant positive relationship with life insurance uptake. The multiple regressions established that differentiation strategy, cost leadership strategy and distribution channels had a significant influence on life insurance uptake. The researchers recommend that there should be more differentiation of life insurance products and services offering, as this will enable companies to experience growth in the areas of premium volumes, market share, and profitability. The researchers also recommend that life insurance companies should design low insurance premium and product to allow even low income earners afford life insurance policies; and that there should be diversified product distribution channels such that customers are able to access reliable products and services at very competitive prices.

Keywords

Completive Strategies, Differentiation, Cost Leadership, Distribution Channel and Life Insurance Uptake

1. Introduction

The need for greater insurance penetration in both life and non-life policies has been underscored by economic survey. Insurance penetration has remained low in Uganda and East Africa region generally. Congden, 2005, Tumbo, 2012 as cited by Otieno (2015), Insurance uptake in Uganda is quite lethargic hence it provides the industry with valuable prospects as a significant population does not have insurance cover. Utilization of insurance cover is vastly led by non-life insurance cover such as medical.

2. Background

Ogolla (2005a, 2005b), examines the extent to which lack of a comprehensive competitive strategy is a recipe for ultimate failure. The increased number of insurance companies in the business has necessitated the need for companies to come up with competitive strategies to increase insurance uptake and survive in the market. These strategies include product differentiation where new life products such as school fees schemes and health membership for organizations have been introduced to meet the needs of middle income class; improvement in distribution channels such as sales agents, office branches, and Banc assurance leveraging on technology. All these form part of the strategy for effective competition (Insurance Regulatory Authority, 2019). Despite these strategies, life insurance uptake in Uganda has remained low at 1% compared to its counterparts in East Africa (Financial Sector Deepening Uganda, 2018), as show in Table 1.

According to the 2019 Annual Market Report on the insurance industry in Uganda, insurance penetration dropped from .84 percent in 2018 to .772 percent in 2019 (Insurance Regulatory Authority, 2019). Life insurance uptake has remained relatively low in terms of market share (28.36 percent compared to 63.7 percent of non-life) with a decline in life premium growth rates (Insurance Regulatory Authority, 2019); as shown in Figure 1 below.

Figure 1. Life insurance uptake in Uganda. Source: IRA Uganda report 2019.

Table 1. Life insurance uptake in East Africa.

Source: Financial Sector Deepening Uganda, 2018.

With many companies offering several life insurance products, it is worth finding out why the majority of Ugandan population does not have any life policy. Therefore, this study sought to examine the effect of competitive strategies on life Insurance uptake in Uganda.

3. Porter’s Generic Competitive Model

This study was informed by Porter’s Generic Competitive Model (PGCM) as the primary theory, which emphasizes the need for creating a favorable position and outcompeting rivals in a business sector (Porter & Porter, 1998; Pearce et al., 2008). This theory is relevant to this study due to its two key strategies of differentiation and cost leadership which formed part of independent variables in the conceptual framework. The second theory that informed this study is the Resource Based View of the firm (RBV). Ansoff, 1965 as cited by Bindra, Parameswar, & Dhir (2019) and the theory focuses on a firm’s internal capacity as the main driver of competitive advantage. Chandler (1962) cites the link between strategy adoption and execution as business environment changes.

3.1. Competitive Strategies and Life Insurance Uptake

3.1.1. Differentiation Strategy and Life Insurance Uptake

According to Porter (1980) as cited in Kamau (2013), differentiation is a business strategy intended to increase the perceived value of the firm’s products or services compared to competitors so as to create a customer preference due to its distinct features. Kamau (2013) argues that differentiation can be done specifically for a product to make them attractive, or for a service through utilization of after sales services like consideration of quality, incentive programs, increased operating hours and so on (Kamau, 2013). Additionally Olegube (2014) as cited by Abwodha (2019) states that differentiation includes physical aspects covering location, space, design, display, layout and stores atmosphere. Moreover, Allen and Helms (2006) stress the importance of differentiation in a company image which increases the sensitivity of the buying process for customers. All this confirms to the statement made by Thompson et al. (2008) that there are numerous ways and dimensions by which firms can differentiate them.

Today’s cut throat competition is the driving force describing why most companies are putting a lot of effort to strategize on differentiation.

Aliqah (2012) examined the empirical evidence between differentiation strategy and organization firm performance among Jordanian manufacturing firms. The study adopted measures of product differentiation strategy using Chenhall and Langfield-Smith (1998) five product differentiation tools, “providing high-quality products, fast deliveries, making changes in design and introducing new products and providing unique product features” The results of the study revealed that there was a positive and significant relationship between differentiation strategy and organizational performance. In contrast, Dawes and Sharp (1996); Parker and Helm’s (1992) empirical study concluded that Porter’s competitive strategies (differentiation strategy and cost leadership strategy) had no effect on firms performance.

Dirisu, Iyiol, and Ibidunni (2013) as cited by Muia (2017), examined the effect of product differentiation strategy as a competitive advantage in Unilever performance. Results of the study revealed a positive and significant relationship between product design, unique product features, innovative product development and firm performance. Nolega et al. (2015) examined the effect of products differentiation strategy and seed company firm performance. Results of the study revealed that to enhance performance there is need to develop products which are resistant to diseases. The current study examines Differentiation Strategy and Life insurance uptake.

3.1.2. Cost Leadership Strategy and Life Insurance Uptake

Porter’s generic competitive strategies state that in cost leadership, a firm sets out to become a low cost producer in its industry (Ray et al., 2007). Cost leadership enables firms to establish a competitive advantage by increasing sales turnover to help in any expansion plans. Spulber (2009), emphasizes the importance of uitilising cost leadership strategy to enhance price leadership, effectiveness, high quality and profitability.

Barney (2002); Palepu and Healy (2008), both argue that application of the cost leadership strategy reduces economic cost amongst competitors while enhancing volume and competitiveness.

Mahdi et al. (2015) discovered that cost minimization tends to compromise standards with a goal of gaining advantage of the market share. This strategy widens the customer base. To the contrary, Duran and Yavuz (2015) argue that the low cost strategy has no positive and significant effect on firm performances as confirmed by the findings of the previous researchers. This kind of strategy tries to attract a wide group of customers. Huo, Qi, Wang and Zhao (2014) discovered that firms following a low-cost strategy stress operational efficiency which a firm can achieve by modernization, mechanization of the firm equipment, economies of scale, and applying experienced. On the other hand, Kim and Kim (2004) argue that firms pursuing a strategy of cost leadership could easily become locked in a malicious cycle of price-cutting because internet technologies tend to be based on cost structures that combine “low variable costs and high fixed costs”.

3.1.3. Distribution Channel and Life Insurance Uptake

The distribution channel is influential in insurance demand. To begin with, Regan and Tennyson (1996) show that the choice of distribution channel is associated with an insurer’s product lines. Similarly, Baranoff and Sager (2003) indicate that there is a relation between the distribution channel and the life insurance uptake. Previous literature also shows that intermediation can affect sales volume (Focht et al., 2013) and that certain distribution channels especially fit specific insurance customers (Karaca-Mandic et al., 2018).

In practice, consumers usually do not contact the insurer directly but go through an intermediary. Robson and Sekhon (2011) indicate that an intermediary’s recommendation significantly influences insurance sales. Shi et al. (2016) find that the perceived relationship investment strongly influences insurance customers and that employee can guide consumers’ perceptions. In general, sales intermediaries can reduce consumers’ search costs and information uncertainty, and thus the distribution channel plays an important role in insurance consumption (Karaca-Mandic et al. 2018). Consistently, Choi et al. (2015), show that the intermediary’s characteristics are important in developing and maintaining a buyer–seller relationship. Besides, the distribution channel is closely associated with operational efficiency due to the acquisition costs associated with commissions (Berger et al. 1997). Fields et al. (2007) find that banc assurance provides positive gains and enhances financial strength. It is expected that the insurer will choose a distribution channel according to its enterprise risks.

4. Methodology

This study used a cross-sectional survey design with a mixed research approach employing qualitative and quantitative approaches.

Questionnaire and Interview guides were used which were adopted from a number of studies and modified to fit in this study. A population of 340 respondents were targeted from which a sample of 181 respondents were selected to participate in this study most of whom were policy holders. Simple random and purposive approaches were used in determining fairness in the selection process. The questionnaire was anchored on a five point Likert scale ranging from 5 for strongly agree to 1 for strongly disagree, and was used to collect data from the customers with life assurance policies. Interview guide was used to collect data from key informants who comprised of general managers. The Questioned asked in the questionaries measured aspects of differentiation strategy, Cost leadership strategy and distribution channels. Such Questions included; how favorable is insurance cost to you? To what extent is life insurance appropriately priced, among others

To ensure that the research instruments were valid and reliable, Content Validity index (CVI) was computed and the value of .833 was obtained which was considered credible for the study (Oso & Onen, 2008). Cronbach’s alpha test was also done to ensure reliability of the instruments to be used and an alpha value of .731 was obtained which was considered reliable for the study as suggested by George and Mallery (2003).

The collected data was edited and analyzed through descriptive analysis of Mean and Standard Deviation were used. Pearson’s correlation and regression analysis were also used to test the relationship between competitive strategy and life insurance uptake. Qualitative data collected was analyzed using content analysis.

4.1. Analytical Model

Pearson’s-Product moment correlation coefficient was computed following the formula below;

$r_{xy}=\frac{n\left({{\displaystyle \sum }}^{\text{}}xy\right)-\left({{\displaystyle \sum }}^{\text{}}x\right)\left({{\displaystyle \sum }}^{\text{}}y\right)}{\sqrt{\left\{\left(n{{\displaystyle \sum }}^{\text{}}{X}^2\right)-{\left({{\displaystyle \sum }}^{\text{}}X\right)}^2\right\}\sqrt{\left\{n\left({{\displaystyle \sum }}^{\text{}}{y}^2\right)-{\left({{\displaystyle \sum }}^{\text{}}y\right)}^2\right\}}}}$ (1)

where;

n = The number of paired observations;

∑xy = The sum of the gross product of Competitive strategies and Life insurance uptake;

∑x² = The sum of all the squared values of Competitive strategies;

∑y² = The sum of all the squared values of Life insurance uptake;

(∑x)² = The sum of Competitive strategies Squared;

(∑y)² = The sum of Life insurance uptake squared.

4.2. Regression Model

The results were tested to see the extent of relationship using the following linear regression equation model:

$Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_3{X}_3+{\beta }_4{X}_4+\epsilon$ (2)

where; Y = Insurance Uptake in the insurance industry;

X₁ = Differentiation strategy of the insurance company;

X₂ = Cost leadership strategy of the insurance company;

X₃ = Distribution strategy of the insurance company.

ε = Error term Regression analysis which will be used. The β coefficient from the equation represented the strength and direction of the relationship between the variables.

5. Study Findings

5.1. Descriptive Analysis

From Table 2, the study showed that differentiation strategy has an effect on life insurance uptake as observed from the high global mean of (4.24) and low Standard Deviation of .288 which showed a fair variability meaning that despite the difference in opinions, the contrast between the opinions was not high. This concurs with Aliqah (2012) who avers that there is a positive and significant relationship between differentiation strategy and organizational performance.

Table 2. Aggregated descriptive statistics.

Consistently, Mashruwala and Tripathy (2014) opine that benefits that come as results of differentiation are more likely to be sustainable. However, this finding was in contrast with Acquaah and Yasai-Ardekani (2008) who argued that there is no significant difference that exists between performance of firms pursuing only the differentiation strategy.

In supplement to the finding, key informant R₁ opined that: “In Uganda,people have not yet embraced life insurance in large numbers,they see it as a waste.However,we try to come up with a variety of life policies such as school fees schemes to attract people to take life policies.Although many people think that the products/services offered by insurance sector are similar, we try much to differentiate our products.”

Further supplement comes fromkey informant R₃ who said that: “we have come up with different life policies segmented to meet different demands of customers such as mid—term life policies which are affordable to various sections of people.In fact I can say that we have as many products as our market segments. These products include but not limited to: medical product, travel policy, personal accident, machinery breakdown public liability and Medical Products, travel policy, personal accident, machinery breakdown public liability and medical product.”

The effect of cost leadership strategy on life insurance uptake was rated high with global mean of 4.25 and low standard deviation of .294. This implied that cost leadership strategy highly affects life insurance uptake. This is in line with Amoako-Gyampah and Acquaah (2008) who found a significant positive association between the cost competitive strategy and performance of firms, where the quality as a result of costs indirectly influences the customer perceived usefulness of the products and services of insurance companies’ hence increasing performance. This further supported the idea of Spulber (2009) who opined that insurance companies that implement cost leadership strategy have the capability of securing a large market share due to their low cost in the industry or market. Nonetheless, Palepu and Healy (2008) maintain that a firm that practices cost leadership strategy may suffer low profit margin.

Results from qualitative data also indicated an agreement that cost leadership has a positive effect on life insurance uptake. This was revealed by key respondent R₆ who said that: “we do whatever it takes to remain in the market irrespective of the high operational costs which at times increase the final price of our products.For instance we put a mobile money number to enable our customers pay conveniently;however,customers still travel to our branch offices to make payments.”

However, a key informant R₂ disagreed with other respondents and this is what he had to say: “The costs of operating an insurance business are high,for example,the taxes are so high,which translates into high prices of life policies.This,I think has deterred people from taking up life policies.”

The effect of distribution channels was also rated high with global mean score of 3.56 which implied that distribution channels have an effect on life insurance uptake. In agreement to this finding is Baranoff and Sager (2003) who indicates that there is a relation between the distribution channel and the life insurance uptake. Similarly, Berger et al. (1997) associated with commissions. This was similarly echoed by Fields et al. (2007) who found that banc assurance for example can provide positive gains and enhance financial strength. It is expected that the insurer will choose a distribution channel according to its enterprise risks, avers that the distribution channel is closely associated with operational efficiency due to the acquisition costs associated with commissions. This was similarly echoed by Fields et al. (2007) who found that banc assurance for example can provide positive gains and enhance financial strength. It is expected that the insurer will choose a distribution channel according to its enterprise risks.

Results from the key informants also demonstrated consistency with the study findings, one other key informant R₆ opined that: “Through the help of brokers, agents and direct channels, we have been able as a company to reach out to our customers.” Key informant R₄ also opined that: “We have made our products known to people through various channels such as the internet platform which has changed the way we used to do things.However,one of the common channels our customers access products and sign up for life policies is through agents and our branch offices scattered all over major towns.”

These demonstrate that the insurer will choose a distribution channel according to its enterprise risks.

5.2. Pearson’s Correlation Coefficient Analysis

Table 3 shows the matrix of Pearson’s correlation coefficient for the two variables of competitive strategies and life insurance uptake. The study revealed a significant positive relationship between differentiation strategy and life insurance uptake at Pearson’s correlation coefficient (r = .291, p = .000). This implied differentiation strategy significantly affects life insurance uptake. This conquered with Aliqah (2012) who examined differentiation strategy and organization firm performance among Jordanian manufacturing firms and revealed a positive and significant relationship between differentiation strategy and organizational performance. However, in contrary to this finding, Dawes and Sharp (1996) opined that differentiation strategy has no effect on firms’ performance.

The study also tested the relationship between cost leadership strategy and life insurance uptake and revealed a significant positive relationship between the two

Table 3. Pearson’s correlation coefficient.

**. Correlation is significant at the .05 level (2-tailed).

variables (r = .169, p = .023). This implied that cost leadership strategy significantly contributes to life insurance uptake. This agreed with Amoako-Gyampah and Acquaah (2008) who opined that there is a significant positive association between the cost competitive strategy and performance of firms, where the quality as a result of costs indirectly influences the customer perceived usefulness of the products and services of insurance companies hence increasing performance. However, on the contrary, Palepu and Healy (2008) who opined that a firm may suffer low profit margin by adopting cost leadership strategy.

Finally, the study established a significant positive relationship between distribution channel and life insurance uptake at Pearson’s correlation coefficient (r = .241,p = .001). This implied that distribution channel has a significant effect on life insurance uptake. This tallies with Baranoff and Sager (2003) who reported that there is a relation between the distribution channel and the life insurance uptake. Similarly, Focht et al. (2013) contends that the intermediation can affect sales volume.

5.3. Multiple Regression Analysis

From the regression findings, the substitution of the Equation (2) becomes;

$Y=\text{2}.\text{359}+.\text{275}{X}_{\text{1}}+.0\text{53}{X}_{\text{2}}+.\text{143}{X}_{\text{3}}+\epsilon$ (3)

where Y is the dependent variable (Life Insurance Uptake), X₁ is Differentiation strategy variable, X₂ is Cost Leadership strategy and X₃ is Distribution channel variable. (Table 4)

At 5% level of significance and 95% level of confidence, the regression coefficients results revealed a significant positive relationship between differentiation strategy and life insurance uptake (P = .001), thus the researcher rejected the null hypothesis that there is no significant relationship between differentiation strategy and life insurance uptake in Uganda and considered the alternative. Likewise, the regression analysis revealed a significant relationship between cost leadership strategy and life insurance uptake (P = .035) and rejected the null

Table 4. Multiple regression results.

a. Dependent Variable: Life Insurance Uptake.

hypothesis that there is no significant relationship between cost leadership strategy and life insurance uptake in Uganda and considered the alternative. Finally, the regression analysis revealed a significant positive relationship between distribution channel and life insurance uptake (P = .019), thus the researcher rejected the null hypothesis that there is no significant relationship between distribution channels and life insurance uptake in Uganda and considered the alternative.

According to the equation, taking all factors (Differentiation Strategy, cost leadership and distribution channel) constant at zero, Life Insurance Uptake will be 2.359. The data findings also show that a unit increase in differentiation strategy would lead to a .27582 increase in Life Insurance Uptake; a unit increase in Cost Leadership Strategy would lead to a .053 increase in Life Insurance Uptake; and a unit increase in Distribution Channel strategy would lead to a .143 increase in Life Insurance Uptake. This means that the most significant factor is differentiation strategy, followed by distribution channel and lastly cost leadership strategy.

6. Conclusion and Recommendations

The researchers conclude that differentiation strategy, cost leadership strategy and distribution channels have a significant positive influence on life insurance uptake. Customers are attracted by the unique life insurance products on the market which ultimately increase life insurance uptake. Availability of various distribution channels makes it easy for customers to access life insurance products thus, increasing uptake. The researchers recommend that there should be more differentiation of life insurance products and services offering, as this will enable companies experience growth in the areas of premium volumes, market share, and profitability levels. Within each life insurance product, there is need to look at Micro insurance for instance as a mechanism for products differentiations. This will enable companies target groups that were once over looked and forgotten hence bringing them in the insurance sphere of inclusion.

The researchers also recommend that the cost of life insurance premiums should be further reduced to allow even low income earners to afford life insurance policies; and that there should be varied product distribution channels such that customers are able to receive reliable and accessible products/services at very competitive prices. Companies have lagged behind in positioning themselves to take advantage of mobile payment platforms such as MTN Mobile money and Airtel Money which are flexible platforms where micro insurance payments can be made easily.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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