Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11, 160-172 2025 Publisher: Learning Gate DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 8 August 2025; Revised: 6 October 2025; Accepted: 9 October 2025; Published: 31 October 2025 * Correspondence: nadiajosel@yahoo.fr Factors influencing online insurance purchasing decision-making among car owners in Mafikeng Joseline Nadia Ndeudjeu1*, M Potgieter2 1,2Department of Economies and Management Science, North-West University, South Africa; nadiajosel@yahoo.fr (J.N.N.). Abstract: This study explores the factors influencing online car insurance purchasing decisions among car owners in Mafikeng, in the context of rising digital adoption in the insurance sector. The extended Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) were applied to investigate determinants such as trust, service quality, consumer attitudes, and social media influence. The research used a quantitative approach with a cross-sectional design conducted among 200 car owners. Data were collected using a structured questionnaire and analyzed with Chi-square tests, with reliability and validity confirmed. The results show that trust, service quality, consumer attitudes, and social media promotion significantly influence online purchasing decisions, while social media usage and perceived tangibility have relatively weaker effects. The findings highlight the importance of enhancing trust, transparency, and service quality in online insurance platforms. Insurance providers should also leverage targeted and credible social media strategies to foster consumer engagement and adoption in Mafikeng’s digital insurance market. By integrating TAM and TPB, this study contributes to the limited literature on digital insurance adoption in emerging markets and provides actionable insights for insurers seeking to strengthen customer trust and participation in online platforms. Keywords: Consumer behavior, Digital marketing, Online insurance, Social media influence, Technology acceptance, Trust, Service quality. 1. Introduction Marketing in the digital age is increasingly focused on building technology-enabled, trust-based relationships with consumers. The insurance industry, traditionally known for limited customer interaction, is now being transformed by digital tools and platforms that enable real-time communication, service customization, and broader outreach [1]. Unlike retailers, insurance providers have historically engaged customers only at policy inception, renewal, or during a claim [2]. However, with the growth of social media and digital platforms, insurers now have the opportunity to create more interactive and personalized customer experiences. As digital transformation accelerates, insurance companies face increasing pressure to adapt their distribution and engagement strategies. This includes using digital channels not just for advertising but also for enhancing trust, transparency, and service quality [3, 4]. Social media, in particular, plays a critical role in shaping consumer perceptions and purchasing behavior by offering platforms for peer reviews, company updates, and service feedback [5]. Yet, despite the growing adoption of online tools, many consumers, especially in developing regions, still struggle with the complexity of purchasing insurance online due to limited guidance, information overload, or lack of trust [6]. This study focuses on Mahikeng, a mid-sized South African city where digital financial literacy and adoption are rising but remain uneven. Consumers in such markets often depend on social influence or offline recommendations when choosing car insurance. As the industry shifts online, understanding the drivers of digital https://orcid.org/0000-0003-0854-2165 161 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate insurance purchasing decisions becomes essential for both insurers and policymakers aiming to increase participation and inclusion in the digital economy. To examine these drivers, this study draws on two established frameworks: the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). TAM is used to assess how perceived usefulness and ease of use affect consumers’ acceptance of online platforms [7] while TPB helps explore how attitudes, perceived trust, and social norms influence behavioral intentions [8]. While previous studies have explored technology acceptance or digital trust independently, few have applied an integrated TPB and TAM framework to understand how attitudes, trust, and digital touchpoints shape online insurance purchasing behavior in localized, under-researched markets like Mahikeng. Hence, this research seeks to fill that gap by providing a comprehensive understanding of the behavioral and technological factors driving online insurance decisions among car owners in the region. 2. Background of the Study South Africa’s insurance industry, established in the Cape Colony in 1835, has undergone significant digital transformation since Santam revolutionized the sector in the mid-20th century with its integrated Multiplex policy [9, 10]. Today, the industry remains Africa’s largest by premiums and assets under management, yet it faces unprecedented disruption from technology and shifting consumer expectations [11, 12]. While the sector achieved a record-high global insurance penetration rate of 17.2% in 2023 [13] short-term insurers have struggled to keep pace with digital adoption, particularly in social media integration. This gap persists despite evidence that digitally mature insurers achieve customer acquisition rates 2 to 3 times higher [14]. Current industry dynamics reveal that while established players like Sanlam (19.2% market share), Outsurance (16.1%), and Old Mutual (12.7%) dominate South Africa's short-term insurance sector, they face rising competition from digital insurtechs like Naked Insurance [15]. This competition is intensified by a significant shift in consumer behavior, as 83 percent of policyholders now compare insurance online and 71 percent expect real-time social media engagement for service needs. In response, 67 percent of insurers now prioritize AI and social media in their strategies; however, only 28 percent leverage these beyond basic brand awareness, revealing a critical implementation gap. This gap is especially relevant, given the dramatic surge in social media's influence, where it once influenced only 19.4 percent of car owners, now 52 percent of South Africans aged between 18 to 35 use platforms like Instagram and TikTok for insurance research [11]. A behavioral shift amplified in high-potential growth hubs like Mahikeng, which is home to over 48,200 registered vehicles. Nevertheless, insurers struggle to convert engagement into sales. While embedded insurance grows globally, South African providers remain isolated in traditional promotional combinations. Only 31 percent leverage influencer partnerships or user-generated content (UGC) tactics proven to boost trust in high-distrust markets [16]. Thus, this study investigates how an integrated social media promotion mix can bridge the gap between insurers’ digital ambitions and consumer decision-making in underserved markets such as Mahikeng. 3. Problem Statement Despite global norms mandating car insurance, South Africa’s voluntary system faces a deepening crisis of underinsurance. Intensified competition allows consumers to switch insurers instantly, heightening pressure on providers to leverage digital channels for customer acquisition and retention. While insurers globally harness social media for consumer engagement, South African firms still struggle to systematically integrate these tools into their promotion mix to influence purchase decisions effectively. Despite the increasing digitalization of financial services in South Africa, the adoption of online car insurance platforms remains inconsistent, especially in semi-urban and regional areas such as Mafikeng. While digital access has grown, many car owners still depend on traditional, in-person insurance 162 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate methods or remain uninsured altogether. According to Khumalo [17], over 25% of South Africans admitted to driving without insurance, citing affordability and lack of trust in online systems as key barriers. This gap is more evident in areas like Mafikeng, where income differences, limited digital literacy, and concerns about online fraud can prevent full participation in digital insurance markets. Recent data underscores the severity of underinsurance: The Automobile Association of South Africa [18] estimates indicate that between 60 and 70 percent of vehicles are uninsured, translating to 12 to 15 million uninsured cars on the roads. The South African Insurance Crime Bureau (SAICB) [19] links this directly to rising premium evasion and "ghost broking" fraud. Economic pressures, including inflation (5.3%), high unemployment (32.9%), and fuel price volatility, exacerbate affordability challenges [20]. Consumers increasingly perceive insurance as discretionary, citing cost, distrust in claims processes, and a belief that accidents are unlikely [21]. Additionally, recent studies also reveal that while urban consumers increasingly use comparison websites, mobile apps, and AI-powered quoting tools, regional car owners are less engaged with these innovations. According to Mupangavanhu and Kerchhoff [22] noted that 95% of consumers in South Africa check online reviews before making an insurance purchase, indicating a shift toward digitally influenced decision-making. However, the extent to which this behavior applies in Mafikeng is unclear, particularly given variations in internet access, technology adoption, and trust in online platforms. Furthermore, affordability remains a persistent issue, with many car owners opting out of insurance entirely due to high premiums [23]. Simultaneously, digital engagement has surged: 43.5 million South Africans actively use social media [24] with platforms like TikTok and Instagram Reels driving youth consumption habits. Insurtech adoption is accelerating, yet insurers’ social media strategies often remain siloed in brand awareness rather than integrated into the promotion mix for conversion. In Mahikeng, a growing administrative and academic hub, digital literacy is rising, but localized data on insurance uptake remains sparse. Electronic National Administration Traffic Information System (ENATIS) [25] reports approximately 48,000 licensed vehicles in the municipality, yet industry estimates suggest more than 60 percent lack adequate coverage. Despite the potential of social media to educate consumers, build trust, and personalize offerings, insurers lack empirical evidence on which social media promotion elements (content virality, influencer credibility, real-time engagement, targeted ads) most effectively drive car insurance decisions in cost- sensitive markets like Mahikeng. Thus, this research seeks to examine how an integrated social media promotion mix affects consumer decision-making for short-term insurers in Mahikeng, and the findings will aid in developing more inclusive, regionally aware digital insurance strategies. 3.1. The Main Objective Of this Study The main objective of this study is to identify the key factors that influence online car insurance purchasing decisions among car owners in Mahikeng. The research is guided by the following null hypotheses: • H01: There is no significant relationship between trust and online insurance purchasing decisions among car owners. • H02: Service quality does not significantly affect online insurance purchasing decisions. • H03: The social media promotion mix has no significant impact on the likelihood of purchasing insurance online. 3.2. Research Gap Despite rising awareness of South Africa’s underinsurance crisis, especially in car insurance, most research has focused on national trends or urban centers, leaving regional hubs like Mafikeng underexplored. The digital divide, characterized by differences in affordability, internet access, and insurance literacy, has been documented, yet there is a lack of localized studies on how these structural 163 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate barriers influence online insurance adoption in semi-urban areas. Additionally, most studies rely on broad consumer behavior models without considering how psychological and promotional factors interact in smaller, cost-sensitive markets. This gap underscores the need for a targeted investigation into the decision-making processes of Mafikeng’s car owners to better inform theory and marketing strategies in the digital insurance sector. 3.3. Significance of the Study This study offers valuable insights into the behavioral, technological, and promotional factors that influence online car insurance purchasing decisions in Mahikeng, a setting that has been largely overlooked in existing research. By focusing on key variables such as attitude, service quality, perceived trust, and the social media promotion mix, the study provides a localized understanding of what drives or hinders digital insurance adoption in a semi-urban, cost-sensitive environment. This is especially relevant given South Africa’s high rate of uninsured vehicles, where national statistics indicate that up to 70% of cars may be uninsured, many of which are in smaller municipalities like Mahikeng. Practically, the findings can help insurance companies craft more targeted digital marketing strategies that go beyond brand awareness and emphasize conversion and consumer trust. It also adds to academic literature by applying and validating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) within a specific South African context, filling a notable gap in regional consumer behavior research. Policymakers can also use the findings to guide digital financial inclusion efforts, while local stakeholders, including municipalities and NGOs, may leverage the insights to raise awareness about the value of insurance and improve digital readiness among residents. 4. Literature Review This literature review identifies independent variables within the conceptual framework that influence the intention to purchase car insurance online. These variables, drawn from prior studies, include factors such as trust, promotional mix, perceived security, perceived tangibility, service quality, and social media platforms. The Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) are grounded for this study. Below is the explanation of the independent variables within the conceptual framework that influence the intention to purchase car insurance online: 4.1. Trust Trust is a central factor in online purchasing behavior, especially for intangible services like car insurance. In digital settings, where face-to-face interaction is absent, trust serves as a substitute for certainty and reduces perceived risk [26]. In the Theory of Planned Behavior (TPB), trust enhances both attitudes toward behavior and perceived behavioral control, which in turn influence intention [27]. Likewise, extended versions of TAM recognize trust as a key external variable that shapes perceived usefulness and ease of use [28]. Recent studies in the South African insurance sector highlight the importance of digital transparency, peer reviews, and real-time support in building consumer trust [15, 29]. However, concerns about fraud, data privacy, or hidden costs continue to limit adoption [30]. In this study, trust is examined as a predictor of online purchasing intention; it reflects the confidence consumers must feel before engaging with insurance providers online. 4.2. Promotion Mix The promotion mix refers to the set of tools used to stimulate interest and accelerate consumer decisions, including advertising, personal selling, and digital promotions. In online contexts, social media advertising and sales promotions have become critical in shaping consumer engagement and driving conversions [31]. According to TAM extensions, promotional content can enhance perceived usefulness by highlighting product value and simplifying decision-making [32]. Likewise, in TPB, strategic promotions can influence attitudes and subjective norms, particularly when recommendations or endorsements are shared within peer networks [33]. Recent studies show that targeted digital 164 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate promotions, such as time-limited offers, referral codes, and influencer content, can boost purchase intention, especially in markets where price sensitivity is high and brand familiarity is low [34]. In the insurance sector, well-designed promotions help reduce consumer hesitation by clarifying product benefits and offering incentives for online engagement. This study examines the promotion mix as a factor influencing car owners’ willingness to purchase insurance online in Mahikeng, focusing on how social media-based promotions impact decision-making behavior. 4.3. Perceived Attitude Attitude is a central construct in the Theory of Planned Behavior (TPB) and reflects a consumer's overall evaluation, positive or negative, toward performing a specific behavior, such as purchasing insurance online [35]. A favorable attitude increases the likelihood of behavioral intention and eventual action. In digital contexts, attitudes are often shaped by exposure to online content, such as reviews, social media engagement, and brand messaging. Consumers who perceive online insurance platforms as trustworthy, user-friendly, and beneficial are more likely to form positive attitudes toward using those platforms [36]. These attitudes, in turn, predict intention and purchasing behavior. Studies show that attitudes toward online reviews, ads, and peer recommendations significantly influence purchase decisions, especially among younger, digitally active consumers [37, 38]. As consumers increasingly rely on digital channels for financial decisions, fostering positive attitudes through engaging, relevant, and credible content becomes critical. This study investigates attitude as a predictor of online car insurance purchase intention, positioned at the core of the Theory of Planned Behavior (TPB) and directly aligned with the study’s behavioral focus. 4.4. Perceived Tangibility Perceived tangibility refers to how real a product or service appears in a digital context. Although services like car insurance are inherently intangible, consumers seek tangible cues such as detailed visuals, testimonials, or clear policy descriptions to reduce uncertainty and perceived risk [39]. In the context of TAM, these cues enhance perceived usefulness, helping consumers better understand what they are purchasing [40]. From a TPB perspective, they also shape attitudes by influencing how consumers evaluate the benefits and trustworthiness of a digital insurance service [41]. Research from Wang et al. [42] shows that visual clarity, transparency, and website quality contribute to consumers' sense of product tangibility in online environments. For car insurance, presenting tangible information such as benefit comparisons, digital contracts, and real-user feedback can improve consumer confidence and influence purchasing intention. This study explores perceived tangibility as a potential factor influencing online car insurance purchases, particularly in markets where consumers remain cautious about non-physical transactions. 4.5. Service Quality Service quality is a crucial determinant of consumer behavior in online environments, such as car insurance. In the absence of face-to-face interaction, consumers evaluate quality based on factors such as responsiveness, reliability, website usability, and after-sales support [43]. Aligned with TAM, high perceived service quality enhances perceived ease of use and usefulness, increasing consumers’ willingness to transact online [40]. In TPB, service quality also influences attitudes and perceived behavioral control, shaping a consumer’s confidence in using digital insurance platforms [44]. Studies from Madhuri et al. [45] confirm that consistency, timely, and personalized service build trust and improve digital purchase intention. In the case of car insurance, digital service quality can directly impact not only consumer satisfaction but also the likelihood of follow-through on a purchase. This study evaluates perceived service quality as a factor influencing online car insurance decisions in Mahikeng’s evolving digital landscape. 165 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate 4.6. Social Media Usage Social media usage is a major driver of digital engagement and has reshaped how consumers interact with brands, particularly in emerging markets like South Africa. Platforms such as Facebook, TikTok, and Instagram facilitate information sharing, peer influence, and real-time interaction, which can affect consumer trust, awareness, and behavior [46]. From a TPB perspective, social media use influences subjective norms through peer recommendations and user-generated content, which shape perceptions of what is socially acceptable or desirable [47]. For TAM, frequent engagement with social media may indirectly improve a platform's perceived usefulness by making information more accessible and relatable [48]. Although insurance remains a low-engagement category, recent studies show that social media promotions, educational content, and customer reviews can influence purchase decisions by enhancing perceived credibility and relevance [49]. However, passive usage may not be sufficient to influence intention unless supported by targeted, meaningful content. In this study, social media usage is examined as a contextual factor that may impact online insurance purchasing decisions in Mahikeng. 4.7. Perceived Usefulness Perceived usefulness (PU) is a core construct in the TAM, defined as the degree to which a person believes that using a system will enhance their task performance [40]. In online insurance contexts, PU refers to how effectively digital platforms help consumers compare options, understand policies, and complete transactions with ease. Empirical research confirms that when consumers perceive an online system as useful, their intention to adopt and engage increases significantly [28]. PU is also a known driver of attitude formation, which aligns with the TPB framework, further reinforcing its relevance to behavioral intention. In digital insurance, consumers are more likely to complete a purchase when platforms provide clear, actionable content, including pricing, coverage comparisons, and real-time support tools [50, 51]. Thus, perceived usefulness directly influences not only user satisfaction but also the intention to buy. In this study, PU is examined as a determinant of online car insurance purchase behavior in Mahikeng’s growing e-insurance environment. 4.8. Purchase Decision The purchase decision reflects the final step in the consumer decision-making process, where intention is translated into action. In both the TPB and TAM, behavioral intention is the most direct predictor of actual usage or purchasing behavior [40, 52]. However, intention alone does not guarantee purchase. Factors such as trust, perceived risk, service quality, and convenience often act as facilitators or barriers to action [36]. For online car insurance, where the product is intangible and often misunderstood, reducing uncertainty through transparent communication, user-friendly platforms, and targeted incentives can significantly influence conversion rates [53]. In South Africa, digital-savvy younger consumers are increasingly engaging with online services but may still hesitate without proper support and clarity [54]. Therefore, bridging the gap between intention and action requires more than awareness; it demands value alignment, usability, and trust reinforcement. This study considers the purchase decision as the ultimate behavioral outcome, shaped by the variables modeled across TAM and TPB. 4.9. The Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) The Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) underpin this study, and the next section explains both theories. TAM focuses on two main constructs: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). In the context of online insurance in Mafikeng, PU reflects how consumers see digital insurance platforms as saving time, offering better prices, and providing access to multiple quotes or customizable options. PEOU refers to how easily users, particularly those with limited technical experience, can navigate insurance websites or mobile 166 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate applications. If consumers in Mafikeng find online insurance tools simple and helpful, they are more likely to adopt them. For example, the increase in telematics-based or AI-enhanced insurance services [3] shows how users value convenience and control, reinforcing TAM's role in explaining digital adoption behavior in this market. Meanwhile, TPB offers a broader psychological and social framework to understand user intentions. TPB states that behavior is influenced by attitude toward behavior, subjective norms, and perceived behavioral control. In Mafikeng, a car owner’s attitude toward buying insurance online might depend on personal beliefs about digital security, convenience, or affordability. Subjective norms, such as influence from friends, family, or local community groups, are particularly relevant in Mafikeng, where word-of- mouth and social proof strongly influence actions [55]. Lastly, perceived behavioral control involves how capable consumers feel about completing an online transaction, which may depend on digital literacy, internet access, and trust in online systems. By combining both TAM and TPB, this study can explore how individual perceptions of TAM and social-psychological factors from TPB influence online insurance purchase decisions in Mafikeng. For example, a consumer might see online platforms as useful and easy to use (TAM) but still avoid them due to a lack of social support or perceived difficulty with online payments (TPB). This combined approach allows for a more detailed analysis of both internal motivations and external pressures. Applying these theories can also guide targeted actions, such as simplifying user interfaces, providing digital literacy programs, or utilizing local influencers to encourage the adoption of TPB. 5. Methodology Ghanad [56] defines quantitative research as “a research strategy that emphasizes quantification in the collection and analysis of data.” It means quantitative research aims to answer questions starting with how many, how much, and to what extent, Alford and Teater [57]. Fischer et al. [58] view quantitative research as the systematic process of applying quantitative principles. Barroga et al. [59] state that quantitative research allows researchers to test theories by examining relationships among variables, measured using detailed instruments and analyzed with statistical procedures. This study adopted a quantitative, cross-sectional research design and used a structured questionnaire to explore the factors influencing online car insurance purchasing decisions. The target population included South African car owners aged 18 to 65, aligning with the legal driving age and representing a demographically diverse group of consumers. The study focused on residents of Mahikeng and Mmabatho, where car ownership is common, and digital service adoption is increasing. The sample size was calculated using Rao-Soft software based on a total population of 46,463 licensed vehicles in the Mahikeng municipality. With a 90 percent confidence level, 5 percent margin of error, and 50 percent response distribution, the recommended sample size was 263 respondents. Ultimately, 200 valid responses were collected through purposive sampling, targeting individuals who had purchased or considered purchasing car insurance online. While this non-probability sampling method enhances contextual relevance, it may limit broader generalizability. The self-administered questionnaire included items aligned with constructs from the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), measured on a 5-point Likert scale. Reliability was assessed using Cronbach's Alpha, with all constructs exceeding the minimum threshold of 0.6 [60], indicating internal consistency. Construct validity was supported through expert review and internal item correlation. Data were analyzed using SPSS, with Pearson's Chi-square test applied to examine statistically significant associations between independent variables and the online car insurance purchase decision at a significance level of p < 0.05. This approach helped identify key decision-making factors among consumers in an emerging digital insurance landscape. 167 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate 6. Results and Discussion In order to determine the relationship between different factors and online car insurance purchasing decisions, this paper first discusses reliability and validity to check the agreement among constructs. This is followed by testing their association with online purchasing decisions using the Chi-square. 6.1. Presentation of Results 6.1.1. Reliability Analysis To assess the internal consistency of the measurement constructs, Cronbach’s Alpha was calculated for each factor. The results are presented in Table 1. Table 1. Internal consistency of measurement constructs (Cronbach’s Alpha). Constructs Cronbach’s Alpha (α) Social Media Usage 0.632 Perceived Usefulness 0.600 Attitude 0.610 Service Quality 0.600 Perceived Trust 0.641 Perceived Tangibility 0.675 Social Media Promotion Mix 0.661 Note: All constructs exceeded the reliability threshold of 0.6. As indicated in Table 1, all constructs exceeded the acceptable reliability threshold of 0.6, confirming satisfactory internal consistency. Social Media Usage (α = 0.632), Perceived Usefulness (α = 0.600), Attitude (α = 0.610), Service Quality (α = 0.600), Perceived Trust (α = 0.641), Perceived Tangibility (α = 0.675), and Social Media Promotion Mix (α = 0.661) all demonstrated reliable measurement of their underlying constructs. 6.1.2. Chi-Square Test Analysis The Chi-square test was employed to examine the associations between each independent variable and the dependent variable of online car insurance purchase decision. The outcomes are summarized in Table 2. Table 2. Chi-square test results – association with online car insurance purchase decision Construct p-value Significant (p < 0.05) Social Media Usage 0.067 No Perceived Usefulness – – Attitude 0.033 Yes Service Quality 0.005 Yes Perceived Trust 0.031 Yes Perceived Tangibility 0.406 No Social Media Promotion Mix 0.001 Yes Note: Significant associations were observed for Attitude, Service Quality, Perceived Trust, and Social Media Promotion Mix. As shown in Table 2, Attitude (p = 0.033), Service Quality (p = 0.005), Perceived Trust (p = 0.031), and Social Media Promotion Mix (p = 0.001) were found to have statistically significant associations with online car insurance purchase decisions. These findings highlight the importance of these constructs in shaping consumer behavior. In contrast, Social Media Usage (p = 0.067) and Perceived Tangibility (p = 0.406) did not demonstrate significant associations, suggesting a limited role in influencing purchasing decisions in this context. 6.2. Discussion of Results 168 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate The result of this study reveals insights into online car insurance purchases in Mahikeng. Among the seven factors examined, Attitude, Service Quality, Perceived Trust, and Social Media Promotion Mix showed statistically significant associations with consumers’ likelihood to purchase insurance online. H01: There is no significant relationship between trust and online insurance purchasing decisions among car owners. The finding that attitude significantly impacts online purchase behavior aligns with the Theory of Planned Behavior (TPB), which identifies attitude as a primary driver of behavioral intention. Consumers who hold positive beliefs about the convenience, credibility, or value of online insurance platforms are more inclined to proceed with a digital purchase. This supports prior research suggesting that strengthening consumer attitudes through awareness and user experience can improve adoption rates [36, 52]. H02: Service quality does not significantly affect online insurance purchasing decisions. Service quality also emerged as a critical determinant. In the context of intangible services like insurance, the perceived reliability, responsiveness, and professionalism of service delivery strongly influence trust and satisfaction, both of which are essential for digital engagement. This reinforces findings in TAM literature, where system quality and ease of use directly affect perceived usefulness and behavioral intention [40]. H03: Social media promotion mix has no significant impact on the likelihood of purchasing insurance online. Perceived trust was another strong predictor, reflecting consumers’ need for assurance in online environments. As supported by both TAM and TPB extensions, trust enhances both attitude and perceived control, reducing perceived risk and strengthening intention [61]. In the South African digital landscape, transparency and customer support are essential to building trust. The significant impact of the Social Media Promotion Mix further highlights the evolving role of digital marketing in shaping insurance behavior. Well-targeted campaigns, influencer endorsements, and customer testimonials can serve as informational and normative cues, influencing both attitudes and subjective norms as outlined in TPB [62]. Conversely, social media usage and perceived tangibility did not show significant effects. This suggests that simply being active on social platforms is insufficient to influence insurance-related decisions unless paired with credible content and perceived value. Similarly, the intangible nature of insurance may limit the relevance of tangibility cues in this context. Overall, the findings affirm that behavioral intention in online insurance purchasing is shaped by a combination of attitudinal, relational, and promotional factors, consistent with TAM and TPB. These insights offer a foundational understanding for refining digital marketing strategies and consumer engagement models in emerging insurance markets. 7. Conclusion and Recommendations This study examined the key factors influencing online car insurance purchasing decisions among car owners in Mahikeng, using constructs derived from the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). Seven variables were tested: attitude, service quality, perceived trust, perceived usefulness, social media usage, perceived tangibility, and social media promotion mix. Among these, attitude, service quality, perceived trust, and social media promotion mix were found to have statistically significant associations with online purchase behavior. The findings confirm that positive attitudes, trust in digital interactions, high-quality service experiences, and targeted promotional strategies significantly enhance consumers’ likelihood to purchase car insurance online. These results support and extend TAM and TPB by validating their constructs within the context of a digitally evolving insurance market in a developing region. Based on these insights, several recommendations are proposed for online insurance providers. First, digital marketing strategies should focus on building trust through transparent communication, user-friendly interfaces, and real-time customer support. Second, enhancing service quality through responsive claims processing, personalized services, and multilingual access could strengthen consumer 169 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 160-172, 2025 DOI: 10.55214/2576-8484.v9i11.10813 © 2025 by the authors; licensee Learning Gate perceptions and satisfaction. Third, the use of targeted social media campaigns, featuring clear benefit comparisons and customer testimonials, may improve attitudes and reduce hesitation, particularly among first-time buyers. While the study provides relevant and context-specific findings, it is not without limitations. The use of non-probability purposive sampling limits the generalizability of the results beyond Mahikeng and similar municipalities. Additionally, reliance on self-reported data may introduce social desirability bias, and the cross-sectional nature of the study does not allow for tracking changes over time. Future research should consider adopting a longitudinal design to observe how digital insurance behavior evolves. Further studies could also explore mediating or moderating effects of factors such as digital literacy, mobile accessibility, or generational differences. Expanding the model across other regions or including additional constructs such as perceived risk, e-trust mechanisms, or price sensitivity would offer deeper insights into the dynamics of online insurance adoption in emerging markets. Funding: This research was funded by the Department of Economics and Management Sciences, Faculty of Management Sciences, North-West University. The invoice for the article processing charge was submitted by Prof. Marius Potgieter. This study adhered to the ethical standards of academic research and was granted clearance by the Faculty of Management Sciences, North-West University, in line with the university’s research policy. Participants’ privacy was respected throughout the process, and all information gathered was treated with confidentiality. Informed consent was obtained from all respondents prior to participation. All general research ethics and conventions were observed during the study, and all consulted sources were duly acknowledged. 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