The Effect of Perceived Value on Purchase Intention in the Life Insurance Industry: The Moderating Effect of Word Of. TWOM Traditional Word of Mouth EWOM Electronic Word of Mouth CFA Confirmatory Factor Analysis EFA Exploratory Factor Analysis FL Factor Loading.
INTRODUCTION
- Introduction
- Background of Study
- Problem Statement
- Research Questions
- Research Objectives
- Significance of the study
Based on the Life Insurance Association of Malaysia (LIAM) presidential statement from September 2020 #BUKAN EXTRA campaign, the insured population in Malaysia is only up to 41% of the entire population in the last 5 years (Krishnan, 2020). What is the relationship between customers' perceived value, life insurance purchase intention and traditional word of mouth.
LITERATURE REVIEW
Life insurance
Whole life insurance policies have a longer coverage period (effective up to 100 years of insured age) compared to term life insurance. Although there are different types of life insurance, not every risk is insured by insurance companies (Heo, 2020,43).
Dependent Variables
- Perceived Value
- Purchase Intention
Price is often used as advantage and sacrifice, which is important but insufficient in defining perceived value. In this study, I will use TRA to examine the effects of perceived value and the moderation of word of mouth in terms of consumers' attitudes towards their purchase intent.
Independent Variables
- Marketing Aspect
- Service Quality
- Perceived Price
- Word of Mouth
Therefore, there is an indication that the total perceived price will influence the perceived value of the service provided. Electronic word of mouth (EWOM) is defined as the involvement of the consumers by expressing their unbiased product information and advice about the product (Hennig-Thurau et al., 2004).
Formulation of hypothesis
WOM has also shown moderate effects in previous studies. 2020) showed that the moderating effect of WOM on the relationship between customer satisfaction and trust in offline shopping context. Study by Lin & Lu (2010) also shows that WOM has a moderating effect on the relationship between trust and purchase intention in tourism context. In medical tourism context, moderating effects of WOM have been shown on the effects of service quality, corporate credibility and corporate image to the perceived value (Lu et al., 2016).
Another study also shows that word of mouth has a positive effect on behavioral intention, which includes purchase intention (Chang & Lee, 2020). A study by Meskaran et al. 2013) showed a mediating role of word of mouth in the relationship between perceived value and purchase intention. The presence of TWOM may moderate the relationship between perceived value and life insurance purchase intention.
Based on the previous research (Amron et al., 2018; Husin et al., 2016), electronic word of mouth has indirect positive effect on the intention to purchase Sharia insurance and takaful insurance. Nevertheless, the positive reviews accumulated on the Internet will help consumers to indicate which life insurance company is reliable (Cheung et al., 2008).
Conceptual Framework
This is due to the increase in the chances that the customers will buy the life insurance even if they have a lower perceived value of the life insurance as they trust the recommendation of close associates. It is common for customers to search for online comments and reviews about the products or services before any purchase. H4: Traditional word-of-mouth moderates the relationship between perceived value and purchase intention, such that the relationship is stronger with higher scores in traditional word-of-mouth.
H5: Electronic word-of-mouth moderates the relationship between perceived value and purchase intent, so that the relationship is stronger with a higher score in electronic word-of-mouth.
METHODOLOGY
- Research Design
- Data collection method
- Subjects and participants
- Instruments
- Common Method Variance
- Data Processing
- Descriptive analysis
- Inferential statistics
- Confirmatory factor analysis
- Path Analysis/ Structural Equation Modelling
- Pilot Test
- Pilot Test result
- Data collection
The items for each of the variables are organized in a table as shown in the appendix. The factor loading (FL) of each of the 5 items is greater than or equal to 0.60. The second construct, perceived price, is measured using 4 questions, items 6–9, as shown in the appendix, to determine the customer's perception of sacrifice in purchasing life insurance products.
For easy interpretation, the presentation of the results can take place in the form of a table, graph or chart. Therefore, CFA is used in this study to test the validity of the construct and whether the measure is consistent across the population (Harrington, 2009). Before data collection for the study begins, a new sample of the population is required to determine the validity and reliability of the constructed questionnaire.
The purpose of the pilot test is to examine the performance of items adopted from past literature. Nieswiadomy (2002) recommended using 10 participants for the pilot test while Lackey and Wingate (1997) recommended using 10% of the sample size established in the research.
DATA ANALYSIS
- Descriptive analysis
- Gender
- Age Group
Gender
Education Level
Age Group
States (Location)
Education level
Both Kuala Lumpur and Johor give almost the same number of responses, which are 5% of the total respondents respectively.
State
Personal Income (Monthly)
Income Group
Number of Life Insurance Policies Purchased
Number of Life Insurance Policy Purchased
- Life Insurance Companies
- Descriptive statistics of the measurement items
- Confirmatory Factor Analysis
- Construct Validity
- Path Analysis
- Marker Variable
- Hypothesis testing
- Coefficient of Determination
- Effect size
The null hypothesis of the Webpower analysis is that there is multivariate skewness or multivariate kurtosis. The VIF value for all variables is lower than 5 as shown in Table 11, it means that there is no multicollinearity between the variables (Joseph F Hair et al., 2016), that is, there is no strong relationship between each of the variables. To examine the construct validity of a questionnaire, Campbell and Fiske (1959) introduced two aspects, namely convergent validity and discriminant validity.
R2 indicates the amount of variance of the exogenous variable that is explained by the model. The critical value of the t-statistic is 1.96, the t-statistic which is greater than 1.96 indicates the significance of the value. Based on table 19, it can be seen that the coefficient of determination (R2) of the exogenous variables is 0.439 for PV and 0.459 for PI.
The f2 value is calculated by determining the changes in R2 when each of the constructs is removed from the null model. As shown in Table 20, moderating effect shows 1-> PI 0 f2, indicating the insignificance of the construct.
DISCUSSION AND FINDINGS
Introduction
Determine the moderating effect of traditional word of mouth on the relationship between perceived value and purchase intent. Traditional word-of-mouth has a moderating effect on the relationship between perceived value and purchase intent, so that the relationship is stronger as traditional word-of-mouth ranks higher. Determine the moderating effect of electronic word of mouth on the relationship between perceived value and purchase intent.
Electronic word of mouth has a moderating effect on the relationship between perceived value and purchase.
Discussion
- Service Quality
- Perceived Price
- Perceived Value
- Traditional Word of Mouth (TWOM)
- Electronic Word of Mouth (EWOM)
This shows that Malaysian life insurance consumers may be satisfied with the agents of life insurance companies. The path analysis shows that perceived value has a significant and positive impact on customer purchase intention value in life insurance industry in Malaysia context (with which the β=0.306, p-value <0.05). This implies that customers will evaluate the life insurance products before deciding to buy them.
Different customers have different valuation considerations when determining the value of life insurance products. In this study, the item "I am generally aware of the value of the life insurance I have purchased". This shows that Malaysian consumers will understand and appreciate the value of life insurance before purchasing.
This result is consistent with Chang and Lee (2020) who studied the mediating effect of WOM in the life insurance industry. One of the reasons may be that customers in Malaysia are aware of the value of life insurance.
Theoretical Contribution
Managerial Implication
Therefore, the next managerial implication for the finding is that life insurance company should introduce new and less complicated type of price presentation for the life insurance policy. This can help save the time and energy of customers to understand what they are paying for the premiums, leading to higher perceived value of the life insurance. Another implication for this finding is to study and understand the customers' expectation of life insurance premium.
After that, life insurance company should focus on developing more flexible life insurance policy with different benefits to attract more customers. Nevertheless, the premium of life insurance policy is calculated to match the sum assured and is more difficult to discount. Customers will be more likely to choose offers from life insurance companies that offer more benefits.
Before promoting TWOM, customer experience with the life insurance company should be improved to ensure customer satisfaction leading to TWOM (Anderson, 1998). However, managers can encourage their customers to recommend life insurance to their colleagues and thus reap the benefits.
Limitation of the study
- Sampling Bias
- Lack of previous studies
- WOM motives
This indicates that TWO still influences the purchase behavior, therefore it should be considered in the manager's strategy to attract more customers. Satisfied customers who are loyal to the brand can help distribute and promote the products while dissatisfied customers will spread negative word of mouth that damages the company's brand and reputation. When there are new customers buy life insurance from recommendation, both customers can receive discount on first premium payment.
Therefore, the research typology developed in this study may be unfounded and should be further investigated as a possibility. However, the items used to measure both WOM in this study refer only to positive WOM. Negative affect, however, could not be measured in this study due to the limitations of the measurement items.
Recommendation for further studies
Conclusion
The impact of electronic word-of-mouth: The adoption of online reviews in online customer communities. Effects of word-of-mouth and product attribute information on persuasion: An accessibility and diagnostic perspective. The roles of mass media, word of mouth and subjective norms in family takaful purchase intention.
The effect of electronic word of mouth on brand image and purchase intention: An empirical study in the automotive industry in Iran. The influence of corporate image, relationship marketing and trust on purchase intention: the moderating effects of word-of-mouth. Influences on the perceived value of medical travel: the moderating roles of risk attitude, self-esteem and word-of-mouth.
The effect of word of mouth on consumer emotions and choice: findings from a service industry. The relationship between satisfaction, trust and repurchase intention: Examining the moderating role of word of mouth.
