Formulating a Novel Model for Information Commerce (I-Commerce) and Consumer Purchase Intention: An Empirical Investigation in the Malaysian Context

Formulating a Novel Model for Information Commerce (I-Commerce) and Consumer Purchase Intention: An Empirical Investigation in the Malaysian Context

Norzaidi Mohd Daud^1*, Intan Salwani Mohamed², Siti Nur Shuhada Nazuri³

^1,3Faculty of Business and Management, Universiti Teknologi MARA

²Accounting Research Institute/Faculty of Accountancy, Universiti Teknologi MARA

^*Corresponding author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.809024

Received: 21 August 2024; Accepted: 31 August 2024; Published: 27 September 2024

ABSTRACT

This study aims to develop a novel model for information commerce (I-commerce) and examine its relationship with purchase intention. As the landscape of electronic commerce (e-commerce) evolves towards this new paradigm of I-commerce, it is crucial to understand this transition. Despite its growing application and distinct role in the business sector, I-commerce remains relatively underexplored and underrecognized. The proposed model is designed to assist industry leaders who engage in online transactions by providing deeper insights into customer needs and preferences. Additionally, given that this may be one of the first studies to investigate I-commerce in detail, it holds the potential to offer significant contributions to the field of online marketing.

Keyword: I-commerce usage, intention to purchase, online marketing, customer needs

INTRODUCTION

Online marketing has fundamentally transformed e-commerce by bridging the gap between customers and sellers in the digital realm. In 2023, the global e-commerce market was valued at approximately $5.8 trillion, with regions such as India, Southeast Asia, and Latin America experiencing rapid growth rates, often exceeding 20% CAGR, driven by expanding internet access and rising consumer spending (Chevalier, 2024). This shift has revolutionized traditional brick-and-mortar businesses into global, direct-to-consumer models, offering a broader reach and more precise targeting capabilities. Nevertheless, as e-commerce continues to evolve and become more intricate, a new paradigm known as information commerce (I-commerce) has emerged (Norzaidi, 2024; Sultan & Uddin, 2011; Prasad et al., 2019)

Information commerce emphasizes the sale of digital information products or services through online platforms, in contrast to traditional e-commerce, which primarily deals with physical goods. I-commerce focuses on the creation, curation, and distribution of digital content, including reports, educational materials, and data. It underscores the necessity of delivering high-quality information to attract potential customers and actively engages with customer feedback to refine product offerings (Wibowo, 2021). As consumers increasingly depend on reviews and shared experiences to inform their purchase decisions, thorough research is essential for making informed choices.

Despite its advancements, I-commerce encounters several challenges that may hinder consumer purchases. Inaccurate or misleading product descriptions can lead to customer dissatisfaction when the delivered product fails to meet expectations, resulting in high return rates, negative reviews, and potential damage to the platform’s reputation. Additionally, the absence of critical information, such as product dimensions, materials, and usage instructions, can cause customers to hesitate or abandon their purchases due to insufficient transparency (Sultan & Uddin, 2011). Complaints regarding outdated or incomplete information can further erode consumer confidence, prompting customers to turn to competitors who offer more comprehensive and up-to-date details (Ali Taha et al., 2021; Wibowo, 2021).

Trust and security also pose significant challenges for I-commerce. Cyberattacks, including data breaches that compromise sensitive customer information such as credit card details and personal identification, can severely damage consumer trust and result in substantial financial and reputational harm (Kim et al., 2008). In 2022, over 42 million individuals globally were victims of identity theft (Statista, 2023). Such security concerns often deter customers from making online purchases, particularly on less-established platforms with perceived weak security measures (Flavián et al., 2006). A lack of trust in I-commerce platforms can diminish usage and negatively impact purchase intentions, threatening the growth of online marketing businesses (Pavlou, 2003).

Price and promotion are critical factors influencing consumer purchase intentions in I-commerce (Kim et al., 2008). Intense price competition can lead to price wars, eroding profit margins and threatening long-term sustainability. Consistently low prices may also diminish the perceived value of premium products, adversely affecting brand reputation and customer loyalty (Vigneron & Johnson, 1999). Furthermore, not all promotions are successful; ineffective targeting, poor timing, or irrelevant offers can fail to convert visitors into buyers, resulting in wasted marketing efforts and reduced returns on investment.

In addition to these challenges, there are several knowledge gaps in the study of I-commerce usage and purchase intentions. Research is limited on I-commerce, given its relatively recent emergence and its gradual replacement of traditional e-commerce functions (Liang & Turban, 2011). Understanding the impact of I-commerce on purchase intentions is therefore crucial. Moreover, there is insufficient research on the long-term effects of data breaches on consumer trust and purchasing behavior (Bansal et al., 2005). Investigating how persistent data breaches affect brand loyalty and consumer decision-making over time is important. Effective strategies for building and maintaining consumer trust in both established and emerging I-commerce platforms are not well understood (Kim et al., 2008). Additionally, the impact of dynamic pricing on consumer purchase intentions and overall satisfaction remains unclear, as does the phenomenon of promotion fatigue—how frequent promotions and discounts influence consumer perceptions of value and purchasing behaviour over time (Friesen, 2021).

Given these gaps, this study aims to:

1. To determine a relationship between product and quality information and I-commerce usage
2. To examine a relationship between perceived usefulness and I-commerce usage
3. To investigate a relationship between degree of trust and security and I-commerce usage
4. To determine a relationship between price and promotion and I-commerce usage
5. To investigate a relationship between I-commerce usage and intention to purchase

REVIEW OF LITERATURE

Related models and theories

Several models and theories are pertinent to this study, including the Technology Acceptance Model (TAM) (Davis, 1989), Theory of Planned Behavior (TPB) (Ajzen, 1991), and Customer Decision-Making Process Model (CDMPM) (Engel et al., 1968). This research will involve a comprehensive review and synthesis of these models to assess their relevance and applicability in achieving the research objectives and addressing existing knowledge gaps. Consequently, TAM will serve as the primary model due to its focus on technology acceptance, while TPB and CDMPM will provide supplementary insights.

Generally, TAM posits that the perceived ease of use and perceived usefulness are critical factors influencing users’ acceptance and use of technology (Davis, 1989). In the context of I-commerce, TAM facilitates understanding of how users’ perceptions regarding the usability and utility of an I-commerce platform impact their intention to use it and make purchases.

Besides, TPB asserts that an individual’s intention to perform a behavior is determined by their attitude towards the behavior, subjective norms, and perceived behavioral control (Ajzen, 1991). This theory will be employed to investigate how consumers’ attitudes towards I-commerce, the impact of external influences such as peer reviews and opinions, and their perceived control over the online shopping process affect their purchase intentions.

Lastly, the CDMPM delineates the phases consumers undergo in making a purchase decision, including problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase evaluation (Engel et al., 1968). This model is instrumental in examining how various elements of I-commerce platforms influence each stage of the decision-making process and subsequently affect purchase intentions.

Next, this section will provide a detailed examination of the potential factors contributing to the development of a research framework.

Product and quality information and I-commerce usage

Product information on an I-commerce platform encompasses all relevant details about a product, including descriptions, specifications, images, pricing, and availability. Accurate and comprehensive product information is essential for enabling consumers to make informed purchasing decisions (Chiu et al., 2014). Clear and detailed descriptions, complemented by high-quality images, help customers fully understand the product, thereby minimizing uncertainty and reducing the risk of returns (Moe, 2003). Transparent and reliable product information builds consumer trust, as customers who feel they have all necessary details are more likely to proceed with their purchase (Grabner-Kräuter & Kaluscha, 2003). Additionally, well-structured product information can enhance a product’s visibility in search engine results, driving increased traffic to the I-commerce site and improving the likelihood of sales (Yang et al., 2012). Moreover, the interplay between the quality of product information and the actual quality of the product itself significantly influences purchase intentions (Kim & Lennon, 2008). Detailed and accurate product information, when coupled with high product quality, not only enhances the likelihood of a sale but also elevates customer satisfaction (Park & Kim, 2003). The quality of both the product information and the product impacts customer reviews and ratings: positive experiences yield favorable reviews, while negative experiences lead to adverse reviews, potentially affecting future sales and overall brand reputation (Chevalier & Mayzlin, 2006). Consequently, we propose the following hypothesis:

H1: There is a relationship between product and quality information and I-commerce usage

Perceived usefulness and I-commerce usage

When consumers perceive an I-commerce platform as beneficial, their likelihood of adopting and using it regularly increases (Davis, 1989). Features that enhance the shopping experience—such as intuitive navigation, personalized recommendations, and streamlined payment options—play a significant role in shaping this perception (Liang & Turban, 2011). Users who find a platform advantageous are more inclined to engage with it frequently, investing more time in browsing, exploring products, and making multiple purchases, which consequently boosts overall platform usage (Kim et al., 2008). A platform deemed valuable typically offers comprehensive product details, user reviews, and an efficient checkout process, all of which contribute to a higher probability of completing a purchase (Chiu et al., 2014). Additionally, I-commerce platforms recognized for their utility can save consumers time and effort, rendering online shopping more convenient compared to traditional methods, thus fostering increased usage and preference for online shopping (Liang & Turban, 2011).

Therefore, the proposed hypothesis is:

H2: There is a relationship between perceived usefulness and I-commerce usage

Degree of trust and security and I-commerce usage

Higher levels of trust are associated with increased frequency of use of an I-commerce platform (Kim et al., 2008). When consumers perceive their data as secure and the platform as reliable, they are more likely to engage with it regularly for their shopping needs (Grabner-Kräuter & Kaluscha, 2003). Also, trust not only fosters consumer loyalty but also encourages users to return for future purchases and recommend the platform to others, thereby enhancing user retention and driving growth (Chiu et al., 2014). Furthermore, robust security measures mitigate consumer hesitation and anxiety related to online transactions (Flavián et al., 2006). Users who feel assured that their financial and personal information is safeguarded are more likely to complete purchases and maintain consistent use of the platform (Bansal et al., 2005). Effective security features, such as encryption, secure payment methods, and clear privacy policies, bolster consumer confidence, leading to increased platform usage and more frequent transactions (Liang & Turban, 2011). Thus, the hypothesis is:

H3: There is a relationship between degree of trust and security and I-commerce usage

Price and promotion and I-commerce usage

Consumers frequently compare prices across different I-commerce platforms, as competitive pricing can attract a greater number of users and drive increased traffic to a site (Kim et al., 2008). Lower prices have the potential to boost purchase volume and promote more frequent use of the platform (Monroe, 1973). Additionally, promotions play a critical role in driving traffic to I-commerce sites (Friesen, 2021). Time-limited discounts, flash sales, and special offers draw deal-seeking consumers, resulting in elevated site visits and heightened usage. Well-implemented promotions can improve conversion rates, as discounts and special offers may incentivize consumers to complete purchases they might otherwise have delayed or abandoned (Gupta & Cooper, 1992). Moreover, promotions enhance consumer engagement by creating a sense of urgency or excitement, motivating users to explore the site, capitalize on offers, and make multiple purchases when they perceive added value (Friesen, 2021). Consequently, the hypothesis is:

H4: There is a relationship between price and promotion and I-commerce usage

I-commerce usage and intention to purchase

Frequent engagement with I-commerce platforms substantially increases consumers’ exposure to a broad range of products and promotional offers. This heightened exposure is likely to enhance their intention to purchase, as familiarity with available products and options grows (Moe, 2003). Regular interaction with an I-commerce site fosters a greater sense of comfort and familiarity with the shopping process, thereby boosting consumers’ confidence in navigating the platform and completing transactions (Gefen et al., 2003). Consumers with a strong intention to purchase are more inclined to use I-commerce platforms frequently for product research, price comparisons, and finalizing transactions (Kim et al., 2008). This heightened level of engagement often results in increased platform usage. Additionally, pronounced purchase intentions frequently lead to repeat visits to the I-commerce site, as users committed to completing their purchases are likely to return to finalize transactions, track orders, or explore related products (Chiu et al., 2014). Therefore, the hypothesis is:

H5: There is a relationship between I-commerce usage and intention to purchase

Development of the research model

Figure 1 illustrates the proposed research model for I-commerce usage and purchase intention.

To outline the framework of the research, consider the following points:

Figure 1: Research model

• Product Information and Quality: This aspect plays a crucial role in driving customers to use I-commerce. Since I-commerce focuses on providing detailed product information and ensuring high product quality, these elements are essential for the platform’s success and user engagement (Kim & Lennon, 2008).
• Degree of Trust and Security: Trust and security are fundamental factors influencing I-commerce usage (Grabner-Kräuter & Kaluscha, 2003). Customers are more likely to use the platform if they trust its security measures; otherwise, they may refrain from using it (Bansal et al., 2005).
• Perceived Usefulness: In line with the Technology Acceptance Model (TAM), perceived usefulness is a key factor (Davis, 1989). Customers need to perceive I-commerce as beneficial for them to use it. If the platform is seen as ineffective, customers are less likely to engage with it.
• Price and Promotion: Price and promotional offers act as significant incentives for customers to use I-commerce (Monroe, 1973). Customers are attracted to the possibility of obtaining better prices, discounts, or deals online compared to traditional store purchases, where such offers might not be available.
• Intention to Purchase: The use of I-commerce influences the customer’s decision to purchase a product, beginning with the intention to buy and leading to the actual purchase decision. This study focuses on the intention to purchase due to the novelty of I-commerce, requiring further exploration and understanding (Kim et al., 2008).

RESEARCH METHODOLOGY

Research Design

This study will employ a quantitative research design using a survey questionnaire to collect data on I-commerce usage and intention to purchase among university students. This approach allows for the systematic collection of data that can be statistically analyzed to understand patterns and relationships (Creswell, 2014).

Population

University students currently enrolled in undergraduate programs at selected institutions.

Sampling Method

A stratified random sampling technique will be used to ensure a representative sample from different academic disciplines and year levels. This method helps in capturing a diverse range of perspectives (Taherdoost, 2016).

Instrument Development

Survey Questionnaire

The questionnaire will be developed based on the research objectives and theoretical models (TAM, TPB, CDMPM). It will consist of structured questions designed to capture data on the following aspects:

1. I-commerce Usage: Frequency of use, preferred platforms, and types of products purchased.
2. Intention to Purchase: Factors influencing purchase decisions, perceived usefulness, and likelihood of future purchases.
3. Product Information and Quality: Importance of product details, reliability of information, and impact on purchase decisions.
4. Trust and Security: Perceptions of platform security, trustworthiness, and its impact on usage.
5. Price and Promotion: Sensitivity to price changes, effectiveness of promotions, and their influence on purchasing behavior.

Questionnaire Structure

The questionnaire will include a mix of Likert-scale questions, multiple-choice questions, and demographic questions. Likert scales will be used to measure attitudes and perceptions, while multiple-choice questions will gather specific data on usage patterns and preferences (Brace, 2018).

Data Collection Procedure

Distribution

The survey will be distributed electronically using a university-approved survey platform (e.g., Google Forms). Invitations will be sent via email or through university student portals to reach a broad audience.

Data Analysis

Descriptive Statistics

Data will be analyzed using descriptive statistics to summarize key characteristics of the sample, such as mean, median, mode, and standard deviation.

Inferential Statistics

To examine relationships between variables and test hypotheses, inferential statistical methods such as correlation analysis, regression analysis, and hypothesis testing will be employed.

Software

Statistical analysis will be conducted using software tools such as SPSS and AMOS SEM.

Validity and Reliability

Pre-testing

The questionnaire will be pre-tested with a small group of university students to identify any issues with question clarity and to ensure the reliability of the instrument (Field, 2009).

Reliability Checks

Internal consistency will be assessed using Cronbach’s alpha to ensure that the scales used in the questionnaire are reliable (Tavakol & Dennick, 2011).

FINDINGS

Demographic Profile

Table 1 displays respondents’ demographics. Data was collected from 290 respondents from public and private universities in Malaysia. Most of the respondents (70%) fall within the 21-24 age range, indicating a predominantly young adult sample. The second largest group is 18-20 years old (16%). There is a very small representation of individuals aged 31 and above (3%). The sample population is predominantly female, with female making up 76% of the respondents, while male account for only 24%. Most respondents (83%) have attained a bachelor’s degree. Most of the respondents (83%) attended public universities, while only 17% went to private universities.

Table 1. Demographic Profile

Assessing validity and reliability

The Cronbach’s alpha is a crucial measure for evaluating the instrument’s reliability, with a commonly recognized cutoff of 0.5 or higher (Nunnally, 1978). According to Browne and Cudek (1989), the study’s Alpha values ranged from 0.66 to 0.89, demonstrating the questionnaire’s good reliability and confirming the data’s eligibility for analysis (see Table 2).

Table 2: Descriptive analysis and model fit test

Table 3: Confirmatory Factor Analysis (CFA) Results

In addition to content validity, this study also examines construct validity (Browne and Cudek, 1989). To assess construct validity, data underwent principal component analysis and rotation using the Varimax method. None of the attributes were excluded based on a loading cut-off of 0.40, and all eigenvalues exceeded 1.0, ensuring the retention of all variables in the analysis (refer to Table 3).

RESULTS

The findings presented in Table 4 encapsulate the outcomes of the five constructed hypotheses. The analysis indicates that product and quality information predict I-commerce usage (p-value = 0.046). Moreover, degree of trust and security predict I-commerce usage (p-value = 0.032), leading to the acceptance of hypothesis 2. Similarly, the study concludes that perceived usefulness is influence with I-commerce usage (p-value = 0.021), thus do not reject hypothesis 3. Next, price and promotion influence I-commerce usage (p-value = 0.002), hence do not reject hypothesis 4.

Table 4: Hypotheses testing

Finally, I-commerce usage is a predictor of intention to purchase (p-value = 0.000). The subsequent section will delve into further discussion and practical implications arising from these findings.

CONCLUSION AND DISCUSSION

This study proposes a novel model for examining information commerce (I-commerce) usage and purchase intention, addressing significant gaps in current research. By integrating elements from the Technology Acceptance Model (TAM) (Davis, 1989), Theory of Planned Behavior (TPB) (Ajzen, 1991), and Customer Decision-Making Process Model (CDMPM) (Engel et al., 1968), the proposed framework offers a comprehensive approach to analyzing the factors influencing engagement with I-commerce platforms and the intention to make purchases.

The study’s findings provide several critical insights:

1. Product Information and Quality: Detailed and accurate product information, coupled with high-quality presentations, is crucial in driving user engagement with I-commerce platforms. Comprehensive product details and high-resolution images enhance trust and reduce uncertainty, thereby increasing the likelihood of a purchase (Kim & Lennon, 2008).
2. Trust and Security: Confidence in the platform’s security measures is vital for promoting regular use. Consumers who perceive their personal and financial information as secure are more likely to engage frequently with the platform and complete transactions (Grabner-Kräuter & Kaluscha, 2003).
3. Perceived Usefulness: The perceived value and ease of use of I-commerce platforms significantly influence their usage. Platforms perceived as beneficial and user-friendly encourage more frequent interactions and increase the likelihood of purchases (Davis, 1989).
4. Price and Promotion: Competitive pricing and effective promotional strategies are key determinants of user behaviour. The study demonstrates that attractive pricing and timely promotions enhance user engagement and drive higher purchase volumes (Norzaidi, 2024; Monroe, 1973).
5. Intention to Purchase: The model highlights that frequent use of I-commerce platforms boosts exposure to various products and promotions, thereby amplifying purchase intentions. Users with strong purchase intentions are more likely to revisit the platform, engage in detailed research, and make informed purchasing decisions (Kim et al., 2008).

This study suggests that all antecedents of I-commerce usage serve as significant predictors of its adoption. Among these factors, price and promotion emerge as the most influential antecedents, driving I-commerce usage more effectively than other variables. In contrast, product and quality information were found to be the weakest predictors. These findings underscore the notion that buyers are predominantly attracted to I-commerce platforms due to competitive pricing and attractive promotions. This observation aligns with the marketing mix concept, which highlights the importance of price and promotion as critical elements in shaping purchase intention and behaviour (Norzaidi, 2024).

Given these findings, it becomes evident that sellers aiming to increase purchase intentions should focus on establishing themselves as leaders in market pricing and promotional strategies. Buyers are more inclined to make purchases when they perceive the prices as affordable and the promotions as appealing, alongside ensuring the quality of the products and services offered. Additionally, the perceived usefulness of I-commerce plays a crucial role in its adoption. The study reveals that perceived usefulness is another strong antecedent influencing I-commerce usage. Consequently, sellers should emphasize the value and importance of I-commerce to buyers, reinforcing the platform’s usefulness to encourage adoption.

This finding corroborates previous research, which has identified perceived usefulness as a key factor influencing both intentions to use and actual usage. Furthermore, antecedents such as the degree of trust, security, and the quality of product information also play pivotal roles in the success of I-commerce platforms. Buyers are unlikely to engage in transactions if they do not trust the platform’s security measures or if they perceive a risk of cybercrime. Moreover, buyers are more likely to remain engaged with I-commerce if the information provided on the platform is up-to-date, accurate, timely, easy to navigate, and supported by extensive feedback or reviews from existing users. Therefore, sellers should continuously improve their I-commerce platforms by providing high-quality and informative content, as well as enhancing security measures. These efforts will help boost buyers’ confidence in the platform, thereby increasing the likelihood of purchase and long-term engagement with I-commerce.

The study contributes valuable insights into the dynamics of I-commerce, presenting a robust framework for understanding how various factors interact to influence I-commerce behaviour. The practical implications indicate that improvements in product information, trust, perceived usefulness, and pricing and promotional strategies can significantly enhance platform engagement and drive purchase intentions. Future research should explore the long-term effects of these factors on consumer behaviour and investigate additional variables that may impact I-commerce usage. Expanding and validating the model across diverse contexts will further enrich the understanding of I-commerce dynamics and support the development of more effective online marketing strategies.

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