Determinants of Online Purchase Intention Toward Life Insurance in Malaysia: Moderating Role of Trust

Abstract

This article focuses on examining the impact of web skills, perceived usefulness, subjective norms, perceived web security, and perceived ease of use on online purchase intention. It was also designed to verify the moderating effect of trust among them. Required data was gathered from customers of insurance companies in Malaysia via an online questionnaire. SmartPLS was used to conduct statistical analyses and verify research hypotheses. The findings showed that subjective norms, perceived usefulness, perceived ease of use, and perceived web security are positively associated with online purchase intention. However, the effect of web skills on online purchase intention was not supported. In other words, customers tend to purchase an online life insurance if they believe the process will be easy, safe, and convenient for them. The results also showed that trust moderates the association among subjective norms and intent to buy life insurance online.

Keywords

Life insurance online purchase intention trust

Introduction

The advancement in information and communication technologies have provided organizations with multiple advantages. For instance, the Internet has allowed service providers to considerably save operating costs, make efficient transactions, improve brand interactivity, provide customer support, and foster better customer-brand interactions (Khare et al., 2012; Sharma et al., 2022). As more individuals and organizations are gradually migrating to online services, the previous part of intermediaries that involve physical or face-to-face interaction has been minimized due to the process called disintermediation (Eysenbach, 2008). Customers get disintermediated when they begin doing informed and self-directed online information searches. Customers are more inclined to buy life insurance online, for instance, they can rely on the product disclosure information displayed on insurers’ websites and have a high level of trust in life insurers, all without interacting with insurance agents at any point (Toukabri & Ettis, 2021). Since the advent of web technologies, the internet has become widely acknowledged as a useful medium through which businesses can promote, sell, advertise, and directly distribute a variety of products and services to consumers. It also serves as a useful channel for receiving and responding to customer feedback (Omisakin et al., 2020).

Previous studies have paid large attentions toward examining the factors that affect consumers’ purchase behaviors. While the factors of perceived ease of use, social influence process (subjective norm), and perceived usefulness are all known to influence customers’ behavioral intentions toward online purchase (Akther & Nur, 2022), the moderating role of trust was not widely incorporated into these models (Rehman et al., 2019). Buying insurance online has made it possible for consumers (policyholders) to do everything from research and comparison shopping to finalizing a purchase and receiving any necessary clarification from the provider, all from the comfort of their own homes, using the seller’s custom-built online insurance purchasing platform (insurer). The acceptance and availability of the system have a noteworthy influence on consumers’ tendency to involve in online purchasing, which in turn is likely to be affected by consumers’ intentions and attitudes toward using the new technology.

In Malaysia, insurance companies are currently facing high challenges with regards to attracting and maintaining customers due to the intense competition (Mihardjo et al., 2020). Besides that, the online purchase of insurance has experienced earlier a slow growth in the market as a result of minimal focus of service providers in the industry on understanding contemporary trends in purchasing. Few years ago, the Malaysian life insurance penetration rate has also remained stagnant at about 56%, and increased by merely 1.1% a year between 2014 and 2017 (BNM, 2018), which means that almost half of the Malaysian population are not covered under insurance protection. In view of this, the insurers have started to take further steps to improve the overall performance of insurance industry. This is because there is a positive tendency among the residents in the country to purchase insurance online in a relatively more matured market due to higher level of insurance awareness. Therefore, the service providers in Malaysian insurance sector have become concerned about creating better awareness toward their insurance products/services.

This article is deigned to make a noteworthy contribution to the literature and Technology Acceptance Model (TAM) by exploring if trust moderates the association amongst selected variables (web skills, perceived usefulness, subjective norms, perceived web security, and perceived ease of use) and online purchase intention toward life insurance in Malaysia. This research further contributes to the literature by verifying whether web skills affects online purchase intention as past studies have not paid adequate attention to the link between them. This is one of the earlier attempts to examine these variables collectively in one model and use trust as a moderator between them. Rehman et al. (2019) also indicated that previous studies found inconsistent results while examining the linkages among these factors. Furthermore, research evidence in the Malaysian context is inadequate, compared with that on western cultures. In past research, the previous studies have mainly examined the current constructs in different contexts, but, there is less focus on life insurance. The literature review for the mentioned factors is presented in the subsequent section.

Literature Review

Online Purchase Intention

With more and more people using the web, online stores are a common way for companies to promote their offerings. According to Wang et al. (2022), buying intention refers to a person’s desire to get the products/ services of a particular brand in an exchange of a fee. According to the existing literature, purchase intention occurs when a consumer is predisposed to buy a product under certain conditions. These conditions are typically associated with the internal and external motives, attitudes, behaviors, and perceptions. Dijesh et al. (2020) also indicated that an e-commerce transaction is the collection and transmission of data through the internet in order to acquire a service or good. Consumers’ faith in a brand and its reputation for quality influence their decisions to make a purchase (Rohit & Panda, 2018). For instance, online product search and time spent on a company’s website can be used as indicators of future purchase intent (Lim et al., 2016). Ettis and Haddad (2019) found that customers’ perceptions of hedonic and utilitarian gains from purchasing insurance online were positively correlated with their overall satisfaction with the transaction. Laohapensang (2009) also applied the theory of planned behavior to the Thai setting, demonstrating that subjective norms and the attitudes of others are most likely to impact the intention to shop online.

Subjective Norms

According to Ham et al. (2015, p. 740), subjective norms can be defined as “the belief that an important person or group of people will approve and support a particular behavior”. The authors added that subjective norms occur when an individual feels that he/she is under a social pressure from other people to conform for behaving in a certain way, and has the motive to respond to their expectations. In other words, when people think that the others they care about approve their behavior, they have higher tendency to engage in that behavior. Family member, peers, and friends can all have an impact on an individual’s behavior. In the previous researches, social norms and descriptive norms were identified as the two key components of subjective norms (Fishbein & Ajzen, 2011). Ham et al. (2015) expressed descriptive norms as the actual behaviors and activities that others are engaging in. On the other hand, social norms can be described as the generally accepted principles by which people are expected to act in social situations. When it comes to life insurance, customers have a tendency for more desire to buy insurance online if they receive excellent recommendations from their friends and family members. In addition, previous researches found that in the halal food industry, subjective norm is the foremost significant element that influences a person’s intent to buy. Similar results were reported by other scholars who verified the importance of subjective norms in determining purchase intention in the context of medical tourism (Chaudhary & Bisai, 2018) as well as in the market for green products (Seow et al., 2017). Subjective norms were further considered to be important determinants of online purchase intention of financial services goods, such as life insurance, credit cards, and other financing facilities (Husin et al., 2016; Sumarliah et al., 2021). Moreover, He et al. (2008) proved that the recommendations made by third parties (subjective norms) had a considerable influence on customers’ desires to purchase online items. Hasbullah et al. (2016) and Aji et al. (2021) conducted additional research and revealed that subjective norm has a positive impact on consumer intention to purchase online products/services. Consequently, the first hypothesis is projected:

H₁: Subjective norm has a positive effect on online purchase intentions.

Web Skills

According to Correa (2016), individuals’ web abilities are measured by how well they believe they can use search engines to find information. There are four main categories of internet proficiency: information competence, strategic competence, formal competence, and operational competence (Litt, 2013). In today’s technologically advanced world, the ability to use the internet effectively is the single most important factor influencing the frequency of online purchase (Livingstone & Helsper, 2007). According to Liu et al. (2016), users’ confidence in their own computing abilities is the source of their proficiency on the web. In other words, people who are seen as more tech-savvy have greater tendencies for adopting new devices and have a positive cognitive reaction toward them. Thus, buyers with more advanced web abilities are more likely to make purchases online (Wu et al., 2020). However, the research of Van Deursen et al. (2015) illustrated that individuals with lower education and economic levels tend to have less proficiency online. Yet, they utilize the internet for things other than shopping, like gaming, Facebooking, and interacting with others on other social networks. Consequently, the subsequent hypothesis is advocated:

H₂: Web skills has a positive effect on online purchase intention.

Perceived Ease of Use

Perceived ease of use was expressed earlier by Ozturk et al. (2016) as the extent to which a user has a confidence that he/she can complete a task with minimal efforts. Perceived ease of use was also described by Hasbullah et al. (2016) as the extent to which a client finds it easy to access, explore, navigate, and utilize the content on a service provider’s website. The TAM was initially presented to describe the central ideas regarding the perceived ease of use of technology systems. Consistent with the TAM, which was suggested by Davis (1989), one of the foremost significant factors in a product’s perceived value is how simple it is to use. It has been shown through the TAM that user perceptions of ease of using a website has both a direct as well as indirect effect on the intention to purchase online. Therefore, the perceived benefits of a technology have a substantial influence on the consumer’s desire to make a purchase since the more accessible the technology seems, the more likely it is to be adopted. Perceived ease of use, as it pertains to online buying can be understood through streamlined navigation that does not force users to put up additional effort in order to obtain the intended results (Lindh et al., 2020). Earlier research has shown that a customer’s perception of a website’s ease of use significantly influences his/her online purchase intentions (Morosan & DeFranco, 2016; Rehman et al., 2019; Wu et al., 2015). Eventually, customers have higher propensities to make online purchases after their positive experiences with the website or the company itself. Consequently, the next hypothesis is put forth:

H₃: Perceived ease of use has a positive impact on online purchase intention.

Perceived Usefulness

The term perceived usefulness was described by Davis et al. (1992, p. 320) as “the extent to which an individual anticipates that adopting a certain system or technology will improve his or her performance on the job”. Customers’ assessments of how helpful a company’s website while making purchases online represent a key measure of perceived usefulness (Lim et al., 2016). Effort reduction, productivity growth, cost savings, transaction speed, and total benefits are all variables that Nugroho (2016) suggested for measuring perceived usefulness. The TAM was utilized in earlier research (Joo & Sang, 2013; Park et al., 2013) to describe the associations between online features and their perceived utility. They found that people were more likely to shop online if they perceive an ease use of a seller’s website. An earlier study found that in the insurance industry, customers’ satisfaction with the usefulness of search engine results and the relevance of materials on insurers’ websites influenced their decisions to make purchases online (Moslehpour et al., 2018). Some prior researches (Joo et al., 2018; Özbek et al., 2014; Peña-García et al., 2020) have further shown that perceived usefulness correlates positively with intent to buy online. They also explained how a poor web browsing experience discourages visitors from returning, which in turn lowers sales. Therefore, the next hypothesis is projected:

H₄: Perceived usefulness has a positive impact on online purchase intention.

Perceived Web Security

Customers have legitimate security worries while making purchases online. They have higher tendencies to use a company’s app or visit its website if they feel safe about the protection of their financial information and the prevention of fraudulent monetary activities (Chandio et al., 2017). Perceived web security was long ago defined by Shin and Shin (2011) as an individual’s faith in the security of a given system in the online world to keep their private data safe. Another definition of web security encompasses the mechanisms put in place to safeguard users’ private information from hackers and other malicious parties. Security differs from trust because it is concerned with the protection and safety of consumer data, while trust refers to the confidence a consumer has toward the reliability, integrity, and benevolence of an online service provider. Trust also tends to be formed based on customers’ expectations and willingness to rely on a firm’s ability to fulfill it promises. In prior literature, perceived security has been regarded as an antecedent to trust (Damghanian et al., 2016; Kim et al., 2011; Ponte et al., 2015). Marketing information on a service provider’s various offerings can be found in a comprehensive online hub. Using the TAM, Arpaci et al. (2015a) found that the perception of safety while making an online purchase was a significant predictor of future behavior. According to Chawla and Kumar (2022), if shoppers have faith that their personal and financial information will be protected, they are more likely to buy things online. Arpaci et al. (2015b) found that when customers’ personal information is protected and their transactions are guaranteed to be secure, a larger percentage of their purchases will be made online. In addition, Tran and Nguyen (2022) argued that a poor web-based system is a key obstacle that prevents a client from performing financial transactions online. Insurance companies and other industries may be hesitant to embrace such technology due to concerns about the perceived lack of security on their websites. Accordingly, the subsequent hypothesis is projected:

H₅: Perceived web security has a positive impact on online purchase intention.

Trust

Having someone you can put your faith in is crucial in many different kinds of relationships, especially those where there is a lot of unknowns and uncertainties (Al-Debei et al., 2015). Trust was defined in the literature by Sirdeshmukh et al. (2002) as “the expectations held by the consumer that the service provider is dependable and can be relied on to deliver on its promises” (p. 17). In other words, trust encompasses the relationship formed between customers and service providers according to a set of learned expectations. Another popular definition of trust refers to a mechanism that simplifies people’s actions in uncertain contexts (Yu & Chen, 2018). Since consumers will be hesitant to make online purchases if they do not believe the seller’s website to be trustworthy, building trust online is crucial in the e-commerce industry (Chawla & Kumar, 2022). Hong (2020) also referred trust to the existence of faith in a firm’s dependability and integrity. Hershberger (2012) has further found that among other cognitive characteristics, trust moderates the association between internet use and brand choice. An individual’s knowledge, awareness, understanding, beliefs, and thoughts underpin their cognitive responses (Park et al., 2008). As a result, trust is very important to the success of the transaction between two parties. Fulfilling promises, confidence in online transactions, and being honest with customers are all ways in which service providers can influence users’ trust and intent to take action (Lien et al., 2015; Yu et al., 2015). Moreover, previous research has shown that trust increases the probability of making an online purchase (Choi et al., 2019) and aids in the long-term retention of clients (Choi et al., 2019). Metzger and Flanagin (2013) described internet trust in life insurance as the degree to which policyholders rely on the information promised by insurers. Individuals’ perceptions of a service provider’s reliability are often influenced by their familiarity with that provider’s information sources (Hilligoss & Rieh, 2008). That is, consumers have higher willingness to involve in online purchase if they have faith in the reliability of the business’ website.

Earlier researches utilized trust as a primary moderator between different variables. Some of these include how employees’ faith in their company can smooth over the tensions between HRM policies, firm output, and workers’ happiness (Alfes et al., 2012). In addition, trust was used as a moderator in the relationship among consumer purchasing habits and the length of food supply chains (Giampietri et al., 2018). For international business transactions, trust was seen as a way to bridge the gap between buyers and sellers from different countries and to facilitate the transfer of information across borders (Ho et al., 2018). The role of trust as an intervening variable between brand engagement on social media and brand equity in MNCs was also verified (Chahal & Rani, 2017). In addition, Jarvenpaa et al. (2017) employed trust as a moderator in an online virtual environment to determine buyer behavior and found that consumers have more intent to make a purchase when they perceive confidence in the reliability of a service provider’s website. Therefore, the subsequent hypotheses are proposed:

H₆: Trust moderates the relationship among subjective norms and online purchase intention.

H₇: Trust moderates the relationship among web skills and online purchase intention.

H₈: Trust moderates the relationship among perceived ease of use and online purchase intention.

H₉: Trust moderates the relationship among perceived usefulness and online purchase intention.

H₁₀: Trust moderates the relationship among perceived web security and online purchase intention.

In accordance with the above literature review and TAM, this article is primarily designed to explore the moderating effect of trust in the association among the selected variables (web skills, perceived usefulness, subjective norms, perceived web security, and perceived ease of use) and online purchase intention. Figure 1 displays the theoretical framework developed for this article.

Figure 1.

Research Framework.

Research Methodology

Data Collection and Procedure

Customers in Malaysia who were aged from 18 years or above made up the study’s population. Due to the geographically distributed nature of the respondents and the cheaper costs associated with convenience sampling, a survey tool was employed to gather the necessary data. To conduct the analysis, a sample size of 100 or above is required (10 predictors times 10). However, G*Power 3.1.9.2, software used for analyzing statistical power and determining the sample size for this particular investigation. However, 346 surveys were completed and returned by the respondents after administering online surveys to them using social media networks. The designed questionnaire was sent out to the targeted respondents through Facebook as it is regarded as the most popular social media network in Malaysia. It is also one of the most appropriate methods for reaching larger number of audiences at different times of the day (Rife et al., 2017). The analysis showed that 42.5% of the participants are males, whereas females accounted for 57.5%. Furthermore, 38.7% of the participants’ ages are between 26 and 35 years, 37.2% are aged from 36 to 45 years, 11.3% are aged from 46 years and above, while 12.8% are aged below 26 years. Also, 52.6% of the participants have bachelor degree qualification, 21.4% have postgraduate degree, 7.8% had diploma certificate, while 18.2% had high school certificate.

Measurement of Constructs

The constructs of this article were measured using various items (see Appendix A) taken from earlier studies. For instance, subjective norms was measured through four items taken from Han et al. (2010). Web skills was also measured through four items adapted from Koufaris (2002). To measure perceived ease of use, four items were extracted from Venkatesh and Davis (2000). Moreover, five items were taken from Cheng et al. (2012) and Chiu et al. (2005) to measure perceived usefulness. This study also relied on four items obtained from Ponte et al. (2015) for measuring perceived web security. Similarly, trust was measured using four items being adapted from Liu and Tang (2018) and Nguyen and Khoa (2019). Lastly, four measurement items were taken from Teng and Lu (2016) to measure online purchase intention. Responses to each question were measured on a five-point Likert scale, with one representing a strongly disagree and five a strong agreement.

Results

In order to execute data analysis and verify the connections between chosen variables, we used the Smart Partial Least Squares (Smart-PLS 3.0) program. The researchers in this article used a two-steps in Structural Equation Modeling analysis strategy. To begin with, the reflective measurement model was built to test the validity and reliability of selected measurement scales. Next, the structural model was generated in order to check the results for the proposed hypotheses when a good fit was found (Hair et al., 2011).

Validity assessment as well as reliability of the instrument were evaluated based on confirmatory factor analysis (CFA). Both discriminant validity as well as convergent validity are the main areas of focus that should be calculated to assess the validity of measurement model (Hair et al., 2011). Average variance extracted (AVE) was determined to check for convergent validity. As presented in Table 1, the CR values for all constructs were higher than 0.7. Both the AVE and the factor loadings were found to be more than 0.5. These analyses show that all values exceeded the lowest acceptable range (Abd Ghani et al., 2017; Hair et al., 2014; Sarstedt et al., 2021), indicating that all constructs have sufficient reliability.

Table 1.

CFA Results.

Constructs	Items	Factor Loadings	CR	AVE
Subjective norms	SNM1	0.940	0.941	0.799
	SNM2	0.945
	SNM3	0.910
	SNM4	0.769
Web skills	WBS1	0.892	0.942	0.803
	WBS2	0.854
	WBS3	0.917
	WBS4	0.919
Perceived ease of use	PEOU1	0.894	0.943	0.805
	PEOU2	0.897
	PEOU3	0.919
	PEOU4	0.877
Perceived usefulness	PUS1	0.895	0.922	0.703
	PUS2	0.893
	PUS3	0.830
	PUS4	0.831
	PUS5	0.733
Perceived web security	PWS1	0.416	0.894	0.641
	PWS2	0.895
	PWS3	0.880
	PWS4	0.873
	PWS5	0.834
Trust	TR1	0.832	0.937	0.748
	TR2	0.840
	TR3	0.873
	TR4	0.887
	TR5	0.889
Online purchase intention	OPI1	0.895	0.922	0.711
	OPI2	0.487
	OPI3	0.903
	OPI4	0.928
	OPI5	0.917

Moreover, the Heterotrait–Monotrait ratio (HTMT) approach was employed to assess discriminant validity in terms of identifying the connections between chosen constructs and the likelihood of overlap between them. To attain discriminant validity amongst chosen constructs, Kline (2005) and Henseler et al. (2015) suggested that a value of <0.85 is acceptable, while Rahi and Ghani (2016) and Segarra-Moliner and Moliner-Tena (2016) suggested that it should be lower than 0.9. Because all of the HTMT values in Table 2 are less than the cutoff value of 0.9, it shows that there is no indication of multi-collinearity among the measurement items in the model and that the selected constructs are statistically different from each other.

Table 2.

HTMT.

	SN	WS	PEU	PU	PWS	CPB	Trust	PI
SN
WS	0.446
PEU	0.556	0.890
PU	0.298	0.394	0.601
PWS	0.452	0.348	0.390	0.585
CPB	0.636	0.734	0.807	0.480	0.537
Trust	0.352	0.400	0.459	0.695	0.841	0.540
PI	0.625	0.626	0.708	0.388	0.627	0.869	0.649

Note: (HTMT < 0.9 / HTMT < 0.85).

Model Test

In addition, the study’s assumptions were checked against the structural model using the bootstrapping method. Table 3 demonstrates that only five of the hypotheses are accepted. H₁, H₃, H₄, and H₅ are all accepted because there is a support for the hypothesized causal pathways from subjective norms (β = 0.191, t value = 3.108, p < .05), perceived ease of use (β = 0.543, t value = 4.728, p < .05), perceived usefulness (β = 0.299, t value = 4.069, p < .05), and perceived web security (β = 0.191, t value = 2.014, p < .05). However, as there was no statistically significant correlation between web skills and intention to buy (β = −0.015, t value = 0.163, p > .05), it was decided to reject H₂. It also shows that just one of the moderating hypotheses (H₆) is supported by the data. The results suggest that trust significantly moderates the link between subjective norms and intent to buy. This means that when consumers’ subjective norms rise, their intentions to purchase insurance online rise alongside them. The hypotheses concerning the moderating role of trust among perceived ease of use, perceived benefits, perceived security, and web skills were not supported; thus, H₇, H₈, H₉, and H₁₀ are rejected.

Table 3.

Results of Hypothesis.

Hypothesis		Path Coefficients	t Value	P Value	Decision
Main Model
H ₁	Subjective norms → Online purchase intention	0.191	3.108	.001**	Accepted
H ₂	Web skills → Online purchase intention	−0.015	0.163	.435	Rejected
H ₃	Perceived ease of use → Online purchase intention	0.543	4.728	.000***	Accepted
H ₄	Perceived usefulness → Online purchase intention	0.299	4.069	.000***	Accepted
H ₅	Perceived web security → Online purchase intention	0.191	2.014	.022*	Accepted

Note: *p < .05.

Furthermore, the coefficient of Determination (R²) was employed to check the impact of selected variables on online purchase intention (Abd Ghani et al., 2017). In line with the findings, the R² value for purchase intent is 0.699, which indicates that these variables may account for around 70% of the variance in purchase intention. Also, R² of 0.20 would be deemed high in the field of customer behavior, whereas an R² of 0.75 would be considered large for endogenous latent variables in the structural model of marketing research studies. However, this judgment depends on the individual research discipline. The cross-validated Redundancy (Q2) metric employs a “blind” measuring technique to gauge the impact of endogenous variables with reflected measurements. With a Q2 value for purchase intent above 0, this model is relevant for its endogenous construct, and the model is thus fit.

Discussion and Conclusion

The TAM served as the grounded theory for investigating the impact of selected factors on consumers’ intentions to buy insurance online. Consistent with Wu et al. (2015) and Morosan and DeFranco (2016), the findings showed that perceived usefulness positively affected online purchase intention. Therefore, life insurers operating online have to put more priorities toward making their sites helpful and beneficial to their customers on hope to enhance their attitudes and likelihood to make online purchases. The findings also displayed that in agreement with previous researches (Hyun et al., 2022; Pillai et al., 2020), perceived ease of use has a positive impact on customers’ online purchase intentions. Thus, consumers who rate a business’s website as easy to use tend to make an online purchase from them. But if a website’s content is not “simple to comprehend,” customers tend to have less willingness to make a purchase, and there are higher chances for engaging in avoidance behavior. Additionally, the findings showed that subjective norms have positive effect on consumers’ intentions to purchase a life insurance plan. More support was reported by earlier studies which confirmed that subjective norms have positive impact on purchase intention (Ham et al., 2015; Husin et al., 2016; Zhuang et al., 2021). Sun and Wang (2020) also verified that subjective norm has a strong and positive effect on online purchase intention. This finding highlights the significance of subjective norms in determining consumers’ intent to buy a life insurance plan. In addition, a higher subjective norm makes a consumer more likely to invest in a life insurance plan. The result further reveals the importance of societal pressure for life insurance providers to consider when selling family insurance policies to their customers.

Furthermore, this article aimed to broaden the scope of the TAM model by incorporating the concepts of web security and trust in order to analyze their influences on consumers’ propensity to make an online purchase. The outcomes confirmed that higher levels of perceived web security tend to exert a positive influence on online purchase intention, which matches with the findings of prior studies (Arpaci et al., 2015b; Salisbury et al., 2001). That is, customer confidence in the safety of online transactions has a beneficial effect on the likelihood that he/she will actually complete an online purchase of life insurance. Thus, life insurers should take adequate precautions to reduce security risk by enhancing the security of their networks and websites to prevent the unauthorized use of customers’ personal and financial information during online transactions. Customers’ perceptions of online payment risk are usually reduced when they have safe access to websites (Bornschein et al., 2020). Insurers can benefit from this because it increases the likelihood that customers will make a transaction through an online channel.

Overall, this study demonstrates that perceived usefulness, subjective norms, perceived web security, and perceived ease of use are significant predictors of online purchase intention in the context of life insurance. This research also demonstrated that trust moderates the connection between subjective norms and online life insurance purchasing intention. Life insurers can better fulfill the needs of a wide range of potential clients by expanding the variety of distribution channels through which their products are offered to them (Richter & Wilson, 2020). It is also suggested that life insurers should improve their risk management strategies, constantly create and implement effective risk management programs, and take measures to detect, monitor, and deal with any dangers that may arise from using the internet. Integrity of data, authentication risk of users, privacy of data, confidentiality of information, and other transactions arising from internet technology are all examples of such dangers. In addition, it is important for life insurers to comprehend customers’ purchase intents in the context of Malaysia’s insurance business, as customers’ perceptions of the industry have a favorable or negative effect on their attitudes toward utilizing online insurers’ websites. Further, this study’s findings would serve as an important roadmap for future studies and add to our knowledge about what influences customers’ intentions to make purchases of life insurance online.

Theoretical and Practical Implications

There are some theoretical contributions that can be drawn from this research. As a first contribution to the TAM, this article focuses on examining if trust acts as a moderator in the association between selected variables and online buying intention toward life insurance in Malaysia. This study further contributes to the literature by testing the impact of web skills on online purchase intention as past studies have not paid adequate attention to the link between them. This is one of the earlier researches that are directed toward examining these variables collectively in one model and used trust as a moderator between them. Rehman et al. (2019) also indicated that previous studies found inconsistent results while examining the linkages among these factors. Furthermore, research evidence in the Malaysian context is inadequate, compared with that on western cultures. In the theoretical literature, earlier studies have mainly examined the current constructs in different contexts, but, there are limited emphasis on life insurance.

In this article, it was found that perceived security, perceived web usefulness, subjective norms perceived ease of use all have a significant positive effect on online purchase intention of life insurance. The findings also suggested that trust has only considerably influenced the association between subjective norms and purchase intention. However, in line with earlier literature, trust and perceived security are conceptualized and measured differently in this study. As trust can be captured through the ability to provide a reliable and dependable service, taking into account keeping customers’ best interests in mind and fulfilling the communicated promises, perceived security includes safety measures, protection of consumer data, and maintaining confidentiality. This article corresponds to the need for more research on the topic about the factors that affect consumers’ intentions to make purchases online from the perspective of the Malaysian customers. Most theories and constructs on online purchase intention, as stated by Rezaei et al. (2014) have only been tested in developed nations.

From the practical perspective, the findings of this research provide noteworthy suggestions for life insurance firms in Malaysia and indicate that they should prioritize perceived ease of use, perceived usefulness, web security, subjective norms, and trust in order to improve the willingness of their clients to buy life insurance through online platforms. Specifically, it is recommended for life insurers to emphasize on designing the user interface of their websites and ensure that it is simple enough to grasp customers’ attentions, ease their online transactions and increase their likelihood to make online purchases. As subjective norms were found to be positively associated with online purchase intention, life insurers should deploy a social influence strategy to get people talking about their offerings throughout their social circles. Marketers need to also emphasize usefulness on their online platforms by highlighting the uniqueness of their products and provide information that is both concise and clear. In order to maintain their clients’ trust and influence their purchase intentions, life insurers are urged to keep their promises to customers and put their best interests in mind. Insurers should also focus on improving the quality of their content, website usability, and functionality. Further, in order to consistently meet the security needs of their customers, insurers are urged to take strict security measures, such as establishing a solid risk management framework to address security risks like those related to data integrity, user authentication, data privacy and safety, confidentiality of information and transactions, and other potential threats that may arise from internet technology. Given this context, it is clear that the assistance and oversight provided by the Malaysian government are crucial in ensuring that life insurers always follow the rules. Using these strategies within an insurance company’s website improves the brand’s image and how customers view the company as a whole. So, if the level of trust between the website and the consumer is increased, the likelihood of the making an online purchase of life insurance increases.

Limitations and Future Research

Similar to other prior studies, this article has few limitations. Firstly, the participants are all from Malaysia; hence the results may not be applicable to other nations without further testing. Hence, to learn more about what influences customers to buy life insurance online, it is recommended to reexamine the research model in other developing nations in Asia, such China, Thailand, and India. Second, this survey was filled out exclusively by individuals who have internet access. Consequently, future studies can use both online and offline survey data collection techniques to examine the factors that shape purchase intention among Malaysian consumers. In addition, it is possible that the factors included in this study are insufficient to fully explain the determinants of online purchase intention; hence, future studies may take into account other factors, such as website quality. It is also suggested for future studies to investigate various aspects of perceived value, customer citizenship behavior, and information quality. Finally, additional research may be conducted to reexamine the mediating impact of perceived value among the selected variables and online purchase intention using a more representative sample.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Appendix

Appendix A.

Measurement Items of Constructs.

Construct	Item
Subjective norms	Most people who are important to me think that I should purchase insurance through an insurer’s website.
	People who are important to me want me to purchase insurance through an insurer’s website.
	The people in my life whose opinions I value purchase insurance through an insurer’s website.
	Most of my family members or friends purchase life insurance through an insurer’s website.
Web skills	I how to complete online forms available on an insurer’s website by myself.
	I know how to find what I want through search engines.
	I am very skilled at using an insurer’s website.
	I consider myself knowledgeable about good search techniques on an insurer’s website.
Perceived ease of use	Learning to use an insurer’s website is easy.
	I find it easy to locate information that I need on an insurer’s website.
	My interactions with an insurer’s website are clear and understandable.
	My interactions with an insurer’s website do not require a lot of mental effort.
Perceived usefulness	Insurer’s website saves my money.
	Insurer’s website is useful to purchase life insurance.
	The contents on an insurer’s website are useful to me.
	The online purchasing process of insurers’ website is fast.
	The advantages of purchasing life insurance through an insurer’s website will outweigh the disadvantages.
Perceived web security	Insurers’ websites implements security measures to protect users.
	I think insurers’ website have sufficient technical capacity to ensure no other organizations will supplant its identity on the internet.
	I feel secure about the electronic payment system of the insurer’s website.
	I am willing to use my credit card on this website to make a purchase.
	I feel safe in making transactions on insurers’ website.
Online purchase intention	I intend to purchase life insurance through insurers’ website.
	I plan to purchase life insurance through insurers’ website when I need to.
	I intend to purchase life insurance through insurers’ website in the future.
	I intend to keep purchasing life insurance through insurers’ website.
	Overall, I would purchase life insurance that I need through insurers’ website.
Trust	Insurer’s website is trustworthy.
	Insurer’s website is reliable.
	Insurer’s website is honest.
	Insurer’s website is one that keeps promises and obligations.
	I trust insurer’s website because it keeps my best interests in mind.

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