1 © 2025 by the author; licensee Asian Online Journal Publishing Group Asian Journal of Economics and Empirical Research Vol. 12, No. 1, 1-8, 2025 ISSN(E) 2409-2622 / ISSN(P) 2518-010X DOI: 10.20448/ajeer.v12i1.6323 © 2025 by the author; licensee Asian Online Journal Publishing Group Influential factors of online purchase intention in the financial industry: A perspective from an emerging economy Shimei Wen Sichuan Sanhe College of Professionals 500 Licheng Road, Hejiang LuZhou City, Sichuan Province, China. Email: 1028373389@qq.com Abstract This study addresses the gap in understanding the impact of product types on online purchasing decisions in the financial industry. It examines how key factors—product features, financial needs, institutional reputation, and government regulations—affect online purchase intention while also investigating the mediating roles of consumer perceptions. Data from 218 respondents in China was collected via a structured questionnaire distributed across various social media platforms. Quantitative analysis was employed to explore the direct effects of influential factors on online purchase intention, along with the mediating effects of perceived value and purchase risk. The study reveals that product features, financial needs, institutional reputation, and government regulations positively influence online purchase intention in the financial sector. Perceived value amplifies these effects, while purchase risk attenuates them, underscoring the significant mediating role of consumer perceptions. Managers in the financial sector should prioritize brand building and real- time customer engagement to bolster online purchase intentions. Strengthening institutional reputation and highlighting product value can positively sway consumer decisions. Policymakers are advised to enact regulations ensuring e-commerce transaction safety, fostering consumer trust and a secure online purchasing environment. Keywords: Financial needs, Government regulations, Institutional reputation, Online purchase intention, Perceived risk, Perceived value, Product features. JEL Classification: D12; G21; L81; M31. Citation | Wen, S. (2025). Influential factors of online purchase intention in the financial industry: A perspective from an emerging economy. Asian Journal of Economics and Empirical Research, 12(1), 1- 8. 10.20448/ajeer.v12i1.6323 History: Received: 9 May 2024 Revised: 12 December 2024 Accepted: 30 December 2024 Published: 20 January 2025 Licensed: This work is licensed under a Creative Commons Attribution 4.0 License Publisher: Asian Online Journal Publishing Group Funding: This study received no specific financial support. Institutional Review Board Statement: The Ethical Committee of the SiChuan Sanhe College of Professionals, China has granted approval for this study on 24 March 2023. Transparency: The author confirms that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Data Availability Statement: Shimei Wen may provide study data upon reasonable request. Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper. Contents 1. Introduction ......................................................................................................................................................................................... 2 2. Theoretical Background and Hypotheses .............................................................................................................................. 2 3. Research Method ............................................................................................................................................................................. 4 4. Result and Analysis ......................................................................................................................................................................... 5 5. Conclusion .......................................................................................................................................................................................... 6 References ............................................................................................................................................................................ 7 mailto:1028373389@qq.com https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ https://www.doi.org/10.20448/ajeer.v12i1.6323 https://orcid.org/0009-0003-0022-7686 Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 2 © 2025 by the author; licensee Asian Online Journal Publishing Group Contribution of this paper to the literature This study offers a new exploration of how product features, financial needs, institutional reputation, and government regulations directly influence online purchase intentions in the financial industry. Additionally, it investigates the mediating roles of perceived value and purchase risk, areas that have not been thoroughly examined before. 1. Introduction The adoption of information technology (IT) empowers businesses to establish online platforms facilitating e- commerce operations (Blake, Neuendorf, & Valdiserri, 2003). Utilizing the advantages offered by online platforms, such as improved accessibility, convenience, and cost-effectiveness, creates value for both businesses and consumers. Despite substantial research on consumer online purchasing behavior, the influence of product category on purchase decisions remains relatively unexplored. In the domain of financial services, the Internet's pervasive influence has impacted how financial institutions plan and market their products. The COVID-19 pandemic and the imperative of social distancing have further accelerated the adoption of online financial services. However, financial products, characterized by their intangible nature and complexity, entail higher levels of risk and uncertainty, prompting customers to exhibit greater caution and risk aversion toward online transactions. The classification of financial products has the potential to shape customers' perceptions regarding the characteristics, features, and benefits of these products, subsequently impacting their inclination to engage in a purchase. This phenomenon is explained through the lens of product differentiation, representing the strategic process of establishing distinctions among comparable products in the consumer's perception. Moreover, the perceived value associated with online purchases of financial products may exhibit variations across distinct product categories, resulting in disparities in purchase intention. Consequently, it becomes imperative for managers within the financial sector to attentively factor in the influence of product categories on consumer behavior and the decision- making process. The likelihood of increased purchase intention correlates with a streamlined purchasing process. In the context of financial products, customers, desiring comprehensive information, tend to prefer personal interaction for financial management. However, online purchasing behavior exhibits caution due to concerns about technical and institutional hurdles in information security. Notably, the recent banking turmoil, exemplified by the 2023 collapse of Silicon Valley Bank and Signature Bank, has instilled widespread fear of a financial crisis. This has led to significant distrust in governmental stability and the accountability of financial managers. Without a demonstrated commitment to ensuring robust customer protection, the current landscape suggests that online channels for financial product purchases may not be deemed a necessity. The synergy of IT development and implementation yields a symbiotic relationship, offering customers instant access to products/services and enabling businesses to expand markets and profitability. However, this study contends that financial products, with unique attributes setting them apart from tangible goods, warrant a thorough exploration of factors influencing online purchase behavior in the financial sector. The findings make a noteworthy contribution to existing literature, shedding light on the impact of purchase perception on consumer behavior in the e-commerce realm of the financial industry. Additionally, the study provides practical insights for business managers and policymakers. 2. Theoretical Background and Hypotheses Different from the extant literature that has investigated the determinants of online shopping behavior in a broad context, this study suggests that an alternative approach should be employed in examining the intrinsic value of financial products/services. Accordingly, the conceptual framework is constructed to integrate firm reputation and government regulations as key determinants that influence online purchasing behavior in the financial sectors while additionally considering the mediating effect of product category on the hypothesized relationships. The proposed research model is represented in Figure 1. Figure 1. Research model. 2.1. Dependent Variable: Purchase Behavior Purchase behavior can be predicted through intentions (Ajzen, 1991). The purchasing process, as explored by Bhatnagar, Misra, and Rao (2000) encompasses various considerations such as consumption preferences, time, and financial resources. Decision-making becomes the guiding force behind purchasing behavior, with the research proposing that intentions act as a reliable indicator for predicting consumer decisions. Notably, studies by Li, Xu, and Xu (2018) and Lee and Allaway (2002) highlight a positive correlation between purchase intention and perceived control, indicating that consumers who feel a sense of control are more likely to make final purchasing decisions Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 3 © 2025 by the author; licensee Asian Online Journal Publishing Group based on their intentions. This holistic view underscores the interplay between intentions, decision-making, and the various factors influencing consumer behavior in the purchasing process. 2.2. Independent Variable: Influential Factors 2.2.1. Product Features Beneke, Flynn, Greig, and Mukaiwa (2013) examined the perceived value from the perspective of product itself, claiming that value perception regarding product characteristics is critical in the buying process. The perceived product value has significant impacts on relative price and willingness-to-buy. Some researchers examined the relationships among the product type, price, and quality, indicating that product characteristics (i.e., quality and price) indeed play a significant role in purchase intention (Haryanto, 2014; Haryanto, Purwanto, Dewi, & Cahyono, 2019; Setiawan & Haryanto, 2014). Product features are the first concern when consumers reach a product. The product itself and the quality are the most important criteria for consumers to perceive value. However, unlike tangible goods, online financial services are intangible. The quality of online financial services is not the quality of the product itself but the benefits the customers can obtain, perceiving the real value of the financial products as additional income, risk-averse tools, and risk avoidance. Therefore, this paper proposed that: H1: Product Features affect online purchase intention in financial industry. 2.2.2. Financial Needs Technological advancements have significantly enhanced opportunities for the financial industry, transforming the way consumers access financial services. Effective financial services play a crucial role in helping customers manage their finances and safeguard against unforeseen circumstances. For instance, the COVID-19 pandemic and the need for social distancing have boosted the usage of online financial services. A survey released in 2020 by ESET1 showed that in the US, 65% of people use at least one Fintech app or platform, and 85% use either banking apps or online banking platforms. Another survey released in mid-2020 by KPMG2 highlighted the surge in online access to financial planning services during the lockdown. Additionally, a global survey conducted in 2020 by McKinsey3 indicated a global decrease in the use of cash and a simultaneous increase in digital transactions. As consumers expect to increase their reliance on online financial services to improve their financial health that would support their better selves, they seek proactive financial institutions that keep them informed about security investments. The tendency is dramatically increasing the number of online users and the variety of services available provided by the financial institutions. Therefore, this paper proposed that: H2: Financial Needs affect online purchase intention in financial industry. 2.2.3. Institutional Reputation Financial products often possess intricate features that can be challenging for consumers to comprehend fully. In many cases, consumers lack the necessary information to make optimal choices among various options. Given the ongoing struggle of consumers to access objective and trustworthy information about available financial products, a crucial avenue for ensuring consumer protection is to furnish them with comprehensive materials that facilitate well- informed decision-making. The growing call for increased accountability and legitimacy in the financial sector emphasizes the significance of disclosures as a primary means to enhance transparency and, consequently, cultivate trust among consumers. Trust is crucial in linking perceived online interactivity to purchase intention (Hansen, Saridakis, & Benson, 2018; Jeon, Jang, & Barrett, 2017). Studies have shown that trust in e-commerce enhances online retailers' reputations and positively affects their performance (López-Miguens & Vázquez, 2017; Pratono, 2018). Reputation significantly influences trust (Yahia, Al-Neama, & Kerbache, 2018) with a strong reputation boosting online shopping trust (Bleier, Harmeling, & Palmatier, 2019; Chen, Huang, & Davison, 2017; Izogo & Jayawardhena, 2018). Reputation is reflected in brand and website image, which are easily perceived by consumers. Brand affects consumer engagement and subsequently brand trust, while website image impacts perceived security and trust. Additionally, concerns about financial security shape consumers' attitudes and trust towards a website. A positive reputation can mitigate perceived risks and foster trust in an online retailer (Walsh, Schaarschmidt, & Ivens, 2017; Zhang, Ren, Wang, & He, 2018). Therefore, this study proposed that: H3: Institutional Reputation affects online purchase intention in financial industry. 2.2.4. Government Regulations Concerning consumer perceptions of the Internet as a marketplace, Bhatnagar et al. (2000) discovered that online financial services are still perceived as risky instruments, with the perceived risks outweighing the convenience they provide. The risks associated with security and integrity, such as fraud and privacy concerns, may exacerbate without adequate safeguards and regulations. In this context, the role of government regulations becomes pivotal in mediating between consumers and financial institutions. Enforcement of laws and regulations serves to hold companies accountable, offering enhanced protection to individuals engaging in financial transactions. This regulatory framework not only instills confidence in consumers but also contributes to the overall integrity and security of online financial services. Engaging with online financial services presents a distinct paradigm compared to traditional economic transactions, emphasizing the essential need for consumers to place trust and confidence in both the products and companies involved. The absence of this trust can be viewed as a market failure, prompting the imperative role of regulations in rectifying such shortcomings. Regulatory frameworks act as crucial mechanisms, creating an environment that allows consumers to interact with online financial services with increased assurance. By addressing inherent challenges related to trust and confidence, regulations play a pivotal role in fostering a more secure and reliable landscape for consumers in this unique market context (Llewellyn, 2005). Therefore, this paper proposed that: H4: Government Regulations affects online purchase intention in financial industry. 1 ESET is a global digital security company. Refer to https://mma.prnewswire.com/media/1453186/ESET_1.pdf?p=pdf. 2 KPMG is a global network of professional firms providing Audit, Tax and Advisory services. Refer to https://home.kpmg/au/en/home/media/press-releases/2020/07/four- fifths-consumers-prefer-digital-financial-services-covid-19-study-8-july-2020.html. 3 Refer to https://www.mckinsey.com/industries/financial-services/our-insights/a-global-view-of-financial-life-during-covid-19Description (optional). Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 4 © 2025 by the author; licensee Asian Online Journal Publishing Group 2.3. The Mediating Variable: Consumer Perception Online shopping is often perceived as a venture fraught with uncertainty, primarily hinging on consumers' doubts about whether the purchased product will align with their expectations (Bhatnagar et al., 2000). According to the Stimulus-Organism-Response (SOR) model, the progression of purchase behavior commences with the product category, leading to psychological adjustments through experiences. Positive signals during this psychological shift ultimately influence subjective perceptions, shaping the actual purchase behavior (Kawaf & Tagg, 2012). Applying the SOR model to online purchase intention within the financial services sector reveals three pivotal phases: motivation, perception, and decision-making. As customers navigate the complexities of motivation, perception, and decision-making phases, the centrality of consumer perception becomes evident. In the Motivation phase, the transparent presentation of product advantages significantly influences how customers perceive online financial products, serving as a potent stimulus for engagement (Solomon, Bamossy, Askegaard, & Hogg, 2010). This psychological impact is particularly pronounced during the subsequent Perception phase, where critical determinants like institutional features, trust, and perceived institutional assurance play pivotal roles in driving trade on e- commerce platforms (Malhotra, Sahadev, & Purani, 2017; Sisson, 2017; Sullivan & Kim, 2018). The intricate interplay between consumer perceptions shaped by various stimuli has a profound impact on trust-building mechanisms and reputational factors. This influence is particularly pronounced in guiding the final Decision phase, offering a nuanced understanding of the cognitive processes steering online purchase behavior within the dynamic realm of the financial sector (Bleier, Harmeling, & Palmatier, 2019; Izogo & Jayawardhena, 2018). Alternatively, the Theory of Planned Behavior (TPB) suggests that purchase intentions are primarily driven by attitudes toward the behavior, subjective norms, and perceived behavioral control (Ajzen, 1991). This theory highlights that consumers aim to maximize positive outcomes and minimize negative ones in their decision-making process (Kumar & Reinartz, 2016). For online purchasing in financial services, consumer perceptions are shaped by external stimuli and internal cognitive processes. These perceptions are influenced by factors such as perceived value, product or service characteristics, financial needs and planning, institutional features, and the overall state of the financial industry. 2.3.1. Perceived Value Perceived value stands out as a pivotal determinant shaping consumer perception towards purchase intentions. In contrast to the traditional mode of shopping, online purchases offer consumers distinct perceived values, encompassing convenience, cost savings, and time efficiency (Margherio, 1998). The factors of price fairness and quality assume crucial roles, especially concerning tangible products, influencing perceived value and subsequently impacting repurchase intentions (De Toni, Eberle, Larentis, & Milan, 2018). These perceived benefits contribute to heightened customer satisfaction, fostering loyalty over time (Curtis, Abratt, Rhoades, & Dion, 2011; Howat & Assaker, 2013; Yu et al., 2014). Likewise, positive experiences in financial services enhance consumers' perceived value, establishing a positive correlation between favorable encounters and heightened perceived value. Therefore, this study proposed that: H5a–H5d: Perceived Value has mediating effects of four influential factors (i.e. Product Feature, Financial Needs, Institutional Reputation, and Government Regulations) on online purchase intention in financial industry. 2.3.2. Perceived Risk The anticipated fulfillment of a purchase decision is typically met with positive expectations. However, during the selection process, consumers engaging in online transactions for financial products and services often exhibit heightened awareness of potential risks. Despite a strong inclination to make a purchase, consumers encounter perceived risks as their purchase intention transitions from potential negative consequences to a realm of uncertainty (Stone & Grønhaug, 1993). Perceived risk, as a comprehensive assessment, involves the subjective evaluation of risks and value judgments (Skjong & Benedikte, 2001). The determination of purchase intention, prior to product utilization, relies on subjective evaluations that integrate past experiences and judgments of potential losses. When this subjective evaluation is compromised, consumers inevitably experience a sense of disappointment or loss, leading to the incurrence of perceived risk. Numerous studies examining online purchases have consistently highlighted the significant negative relationships between perceived risk and purchase intention, examining diverse perspectives such as product evaluation (Han & Kim, 2017) brand effects (Bleier et al., 2019) website reputation (Sullivan & Kim, 2018) familiarity (Gibreel, AlOtaibi, & Altmann, 2018) and social norms (Xie, Song, Peng, & Shabbir, 2017). The online financial services offered by the financial industry present a novel way for consumers. Consumer decisions to engage in online purchases are influenced by perceived benefits such as convenience, cost savings, and a diverse product range (Khatibi, Haque, & Karim, 2006). Nevertheless, in contrast to traditional modes that involve substantial paperwork, conservative customers may associate online purchases with increased risks. Research indicates that to encourage more customers to embrace online transactions, financial institutions should mitigate potential risks by emphasizing optimal service quality and providing reassurances to customers (Beneke et al., 2013). Therefore, this paper proposed that: H6a-H6d: Perceived Risk has mediating effects of four influential factors (i.e. Product Feature, Financial Needs, Institutional Reputation, and Government Regulations) on online purchase intention in financial industry. 3. Research Method 3.1. Construct Operationalization and Questionnaire Development The construction of the questionnaire involved a comprehensive literature review and variable discussion to operationalize the constructs. The instrument comprised seven constructs, each measured by three items, resulting in a total of 21 items. A five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), was employed for participant responses. To ensure the reliability and validity of the measurement model, several criteria were applied, following the guidelines of Hair, Ringle, and Sarstedt (2011). Initially, validation required each construct's Cronbach’s alpha coefficient to exceed 0.6, ensuring internal consistency. Additionally, factor loadings were scrutinized, necessitating standardized values above 0.5. Furthermore, the examination encompassed Bartlett’s test and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO-MSA). Noteworthy Bartlett’s Test outcomes Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 5 © 2025 by the author; licensee Asian Online Journal Publishing Group and KMO-MSA values surpassing 0.50 were considered indicative of the suitability for factor analysis (Kaiser & Rice, 1974). Convergent validity was assessed using the average variance extracted (AVE), with values greater than 0.5 indicating that latent variables could explain more than the average. The final criterion was composite reliability (CR), set at a threshold above 0.7 to confirm the robustness of the shared variance among indicators, aligning with the recommendations of Hair et al. (2011). In the structural model, a two-step path analysis was conducted to evaluate the roles of perceived value and perceived risk as mediating variables between the four influential factors and online purchase intention. The first step involved examining the direct effects of each influential factor on online purchase intention using SPSS AMOS. The second step assessed the paths between each influential factor and online purchase intention after incorporating perceived value and perceived risk constructs, respectively. Indirect effects were examined using the PROCESS Template, Model 4 (Hayes, 2017). 3.2. Data Collection and Analysis Technique A structured questionnaire was designed and administered by inviting participants to complete an online survey via different social media platforms. In China, 300 questionnaires were disseminated, and 218 responses were deemed sufficient, meeting the minimum sample size requirement of 200 observations. Among the 218 valid respondents, 114 were male (52.3%) and 104 were female (45.9%). Most respondents were aged 31-40, with a total of 66 (30.03%), and 109 (50.0%) obtained Bachelor's degree in college. Annual incomes over 200,000 RMB were 54 (24.8%). 4. Result and Analysis In this study, factor analysis was employed alongside dimension and Cronbach’s alpha tests to evaluate the reliability of the survey. Table 1 illustrates that all questionnaire items exhibited factor loadings above 0.7 (ranging from 0.713 to 0.841). The majority of Cronbach’s alpha coefficients for research items surpassed 0.8 (ranging from 0.808 to 0.893), with only one exception (Perceived Risk = 0.791), still aligning closely with the generally accepted guideline by Hair et al. (2011). Moreover, the KMO value (0.894) and Bartlett’s Test (p < 0.000) both support the utility of factor analysis. Consequently, the study aptly concludes that all questionnaire items demonstrated a high level of internal consistency, and their respective factors are suitable for further analysis. Table 1. Reliability and validity. Research items Factor loading AVE CR Cronbach’s α Product features 0.792 ~ 0.841 0.665 0.856 0.858 Finance needs 0.795 ~ 0.821 0.657 0.852 0.867 Institutional reputation 0.777 ~ 0.850 0.661 0.854 0.862 Government regulations 0.808 ~ 0.829 0.665 0.856 0.893 Perceived value 0.746 ~ 0.836 0.615 0.827 0.808 Perceived risk 0.731 ~ 0.801 0.603 0.820 0.791 Purchase intention 0.713 ~ 0.826 0.585 0.808 0.845 Table 1 reveals that all Composite Reliability (CR) values fall within the range of 0.808 to 0.856, significantly surpassing the suggested benchmark of 0.5. Additionally, the Average Variance Extracted (AVE) values for the constructs span from 0.585 to 0.665, surpassing the recommended threshold of 0.5. These findings indicate the acceptability of the measurement model. Furthermore, the correlations among the constructs remained below 0.85, signifying the absence of any discriminant validity issues within the model. Figure 2. Summary of results in hypothesized structural model (Standardized). The model fit indices (Chi-square/df = 1.042, p-value = 0.335; RMSEA = 0.014; GFI = 0.931; AGFI = 0.905; CFI = 0.997) are satisfactory. The empirical results in Figure 2 show that Product Feature (β=0.098; p<0.05) have a significant impact on the Purchase Intention. In addition, Financial Needs (β=0.113; p<0.05) have a significant impact on the Purchase Intention. Furthermore, both Institutional Reputation (β=0.086; p<0.05) and Government Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 6 © 2025 by the author; licensee Asian Online Journal Publishing Group Regulations (β=0.376; p<0.05) have significant influences on the Purchase Intention. The outcomes support H1, H2, H3, and H4. Table 2. Evaluation of the research model. Hypothesis/ Path Estimate t P-value H1: Product features à purchase intention 0.098 2.902 0.011 H2: Finance needs à purchase intention 0.113 3.506 0.023 H3: Institutional reputation à purchase intention 0.086 3.229 0.018 H4: Government regulations à purchase intention 0.376 6.424 0.037 Mediating effect of perceived value → Purchase intention Coeff Coeff of PV Indirect effect H5a: Product features 0.2548 0.2594 0.0896 H5b: Financial needs 0.1922 0.2813 0.0995 H5c: Institutional reputation 0.1936 0.2901 0.0945 H5d: Government regulations 0.3157 0.2511 0.0723 Mediating effect of perceived risk → Purchase intention Coeff Coeff of PR Indirect effect H6a: Product features 0.2548 -0.2292 0.0661 H6b: Financial needs 0.1922 -0.2278 0.0776 H6c: Institutional reputation 0.1936 -0.2253 0.0769 H6d: Government regulations 0.3157 -0.1600 0.0554 Note: PV: Perceived value. PR: Perceived risk. In Table 2, the indirect effects of the four influential factors on Purchase Intention, mediated by Perceived Value and Perceived Risk, exhibit statistical significance. The confidence intervals for the indirect effects of the two mediators on Purchase Intention fall within the specified bounds, with 0 lying outside the 95% confidence interval. According to Table 2, the mediating effect of Perceived Value positively influences the relationship between the four influential factors and Purchase Intention, while Perceived Risk exerts a negative significant influence on this relationship. As a result, hypotheses H5a – H6d find support in the data. 5. Conclusion Recent advancements in information technology have led to a substantial rise in online transactions. External factors have significantly contributed to this trend. For Instance, the COVID-19 pandemic has accelerated the transition toward heightened online purchases, with anticipated enduring effects. This shift has been particularly prominent within financial institutions, where online shopping has now become the predominant norm. Nevertheless, despite global managerial efforts to leverage engaging online channels, financial institutions in emerging economies contend with more pronounced issues and challenges compared to their counterparts in advanced markets. 5.1. Theoretical Implications From an academic viewpoint, this study centers on discerning the intricate relationships between online purchase intention and the mediating factors, such as perceived value and perceived risk, along with the key influencers like product features, financial needs, and institutional reputation. This theoretical lens allows for a deeper comprehension of the mechanisms at play in shaping consumer decisions in the digital financial landscape. More importantly, the incorporation of product category considerations, which most existing research tends to overlook, adds a layer of complexity to theoretical frameworks. This recognition aligns with the evolving nature of consumer behaviors and their multifaceted evaluation processes, contributing to the enrichment of theoretical models within the academic domain. In addition, theoretical exploration also highlights the cognitive aspect of consumer perception by clustering and attributing influential factors as components of consumers' cognitive processes. This theoretical framing aligns with the broader theoretical perspectives on decision-making processes and cognitive frameworks, enriching the understanding of how consumers navigate choices in the online financial realm. 5.2. Managerial Implications From a pragmatic standpoint, the positive and substantial coefficients revealed in the path analysis connecting online purchase intention through mediating factors with the four influential factors yield four managerial implications. Firstly, heightened positive product features correlate with an elevated value perceived by customers. Financial institutions should strategize to comprehend the evolution of online products in financial services, facilitating the identification of conditions where specific financial services are in demand and others offer a diverse range of features. Targeting product value becomes paramount, maximizing user needs through customer-centric product design. Secondly, when product features align with consumer needs, purchasing decisions predominantly hinge on institutional reputation. To instill trust, financial institutions can enhance disclosures to render them more meaningful for consumers, emphasizing product values such as safety, convenience, and swift service. For consumers with limited information or online purchasing experiences in financial services, reputation emerges as a crucial factor influencing purchase intention. Consequently, prioritizing brand establishment becomes the foremost task within the financial industry. Thirdly, supervision improvement and real-time customer engagement are efficient ways for financial institutions to build up their reputation in the financial industry. For the former, financial institutions either launch initiatives by themselves to improve governance or reluctantly abide by the government regulations, which would help earn reputation (Romero, 2003). For the latter, numerous studies showed that establishing consumer’s engagement is beneficial for the company, for it raises corporate reputation (Van Doorn et al., 2010) and results in a remarkable relationship in the form of commitment, trust, and brand loyalty (Brodie, Hollebeek, Jurić, & Ilić, 2011). Asian Journal of Economics and Empirical Research, 2025, 12(1): 1-8 7 © 2025 by the author; licensee Asian Online Journal Publishing Group The real-time customer engagement may provide impartial advice that will lead a customer through their journey while building trust in the company’s brand. Finally, government regulations can significantly affect the financial industry. The main regulatory body protecting investors from mismanagement and fraud encourages investor confidence and investment. In emerging markets such as China, the financial industry develops lag behind more developed economies largely due to outdated regulations. The situation can be observed from the samples collected in China, where most consumers are not satisfied with the current status of online financial services. Governments in emerging markets need to introduce regulatory reforms to promote growth and mitigate risk, including levels of financial inclusion and regulations surrounding financial services. This study encounters three main limitations. Firstly, the selected country, China, falls under the category of emerging economies with a substantial population. While the sample size used in the study is appropriate, expanding it could potentially yield different results. Additionally, despite China having some of the most advanced online payment systems globally, its financial systems have not been operating optimally, mainly due to recent awareness of the benefits of financial services. Consequently, there might be additional influential factors not considered in this study. 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