INTRODUCTION
Research Background
E-commerce has been becoming an effective trading channel for many companies, beside traditional stores, to sell their products and services, and to interact with customers That are stores open 24 hours a day, seven days a week, and 365 days a year, a sales person who doesn’t need breaks or holidays With low running cost, online stores create opportunity to reach the new markets because of unlimitedness for any customer who wants to find the products over the world
The rapid increase in internet users worldwide is driving significant growth in e-commerce, particularly in Vietnam, which is identified as a promising market in Southeast Asia According to Tran (2014), head of the Vietnam E-commerce and Information Technology Agency (VECITA), Vietnam boasts the highest number of internet users in the region, with 16.1 million users recorded in July 2013, representing 36 percent of the population This surge in internet usage is closely linked to the robust expansion of e-commerce in the country.
In 2013, 57% of Internet users in Vietnam's major cities, Hanoi and Ho Chi Minh City, engaged in online shopping, contributing to an estimated e-commerce sales figure of USD 2.2 million With a projected increase of 40-45% in Internet users by 2015, online purchasing is expected to soar to approximately USD 4 million, presenting a lucrative opportunity for companies aiming to boost revenue and expand their market presence.
To enhance profitability and business growth, companies are increasingly recognizing the critical role of e-commerce in their strategies Ignoring e-commerce is not an option for businesses that aim to thrive in the future The essential challenge lies in how entrepreneurs can effectively implement e-commerce in alignment with their business models and strategies.
Problematic of Research
E-commerce in Vietnam, however, is still earlier market, not reach its full potential yet Some companies have been successful in building an online shopping channel or thriving in business by attracting more and more customers While the other just pause at install and experiment a website, revenue from selling online is still low In accordance to VECITA report, survey result in Vietnam in 2013, 41 percent of businesses only announce their increased through the e-commerce channel, 13 percent is decrease and 46 percent almost is unchanged
In the realm of B2C e-commerce, online shopping remains unfamiliar to many internet users, particularly when excluding software transactions, hardware, and travel services While customers benefit from access to a global market and diverse options from various e-retailers, trust issues often arise regarding the vendors supplying these products and services.
Gefen and Straub (2003) argue that the absence of human interaction, or the perception of social presence in online systems, is a key factor distinguishing physical stores from their online counterparts (Suki, 2007) In physical retail, customers can engage directly with products and sellers, fostering a sense of warmth and connection In contrast, online shopping is characterized by its impersonal and automated nature, where interactions are mediated by computers, leading to a lack of face-to-face contact and sociability (Gefen and Straub, 2003) Furthermore, many e-commerce websites primarily focus on product display, often lacking emotional or social engagement (Hassenein and Head).
In 2005, a key challenge for business professionals was to create online transactions that closely resemble the experience of traditional stores while offering a socially engaging environment Addressing this challenge necessitates a comprehensive understanding of customer attitudes, intentions, and behaviors.
This study explores the influence of social presence on consumer attitudes and purchase intentions in e-commerce Previous research has demonstrated that social presence enhances trust, perceived usefulness, and enjoyment, thereby positively affecting online shopping behavior However, while various studies have analyzed the effects of these factors across different products and cultures, the specific impact of social presence on purchase intention remains underexplored This gap suggests a significant opportunity for further investigation into how social presence can encourage repeat purchases in online retail environments.
In 2013, research on social cue design highlighted a gap in understanding the effects of social media elements, such as customer ratings and recommendations This thesis aims to address this gap by incorporating these social factors into website interfaces to examine their influence on consumer attitudes and ultimately their online purchase intentions.
Research Objectives
This study critically evaluates online buyers' purchase intentions, focusing on the influence of perceived social presence in website interfaces Despite numerous empirical studies on this topic, the varied implications and diversity of information systems continue to drive the need for further exploration Specifically, this thesis aims to investigate these dynamics within the Vietnamese market.
- To identify the effect of social presence on purchase intention through perceived usefulness, enjoyment, trust and customer’s attitude
- To evaluate how the elements of social presence contribute to enhance purchase intention of online customers.
Significance of Research
This research reviews the theory of social presence in e-commerce websites, examining how perceived social presence influences consumer attitudes and purchase intentions The findings will help business professionals identify the key elements of social presence that affect customer purchasing decisions, enabling them to implement effective investment strategies in website design to enhance user engagement.
Scope of Research
Jewelry is an ideal online product due to its easily identifiable materials, such as diamonds, gold, and silver, allowing customers to visualize the items without needing to touch them The familiar components of jewelry resonate with users, making it a significant gift or a luxurious fashion accessory that enhances personal presentation With the right website development, selling jewelry online has strong growth potential, as highlighted by Hassanein et al.
In 2009, the importance of social descriptions related to products emerged as a key factor in fostering positive attitudes toward online stores To explore this concept, a fictitious website featuring social cues was created specifically for selling jewelry A survey was conducted among experienced online customers in Ho Chi Minh City to gather insights on their perceptions and behaviors.
Structure of thesis
This research is organized into five key sections: an introductory overview of the study, a literature review that outlines the hypotheses, a detailed explanation of the research methodology, an analysis of the results along with the limitations of the findings, and finally, a concluding section that summarizes the overall research.
This chapter examines the current state of e-commerce in Vietnam, focusing on the role of social presence in website interfaces It outlines the research problem, objectives, and the significance of the study, providing a comprehensive overview of the topic.
LITERATURE REVIEW
Introduction
This study explores the connection between social presence and the factors influencing customer attitudes, as well as their effect on purchase intentions The research model is based on prior studies conducted by Gefen and Straub (2003) and Hassanein and Head, providing a foundation for understanding these relationships.
In 2007, the author conducted a purposeful discovery, synthesizing knowledge from various fields of electronic technology systems This comprehensive analysis defines each construct and explores the hypothesized relationships among them.
Theoretical background
Argyle and Dean (1965) define social presence through the concept of "immediacy behavior," which fosters "intimacy" and serves as a foundational element for subsequent research aimed at clarifying the definition of social presence Researchers, including Short et al (1976), describe social presence as the ability of a medium to convey information such as facial expressions, posture, attire, and non-verbal cues Fulk et al (1987) further refine this definition, stating that social presence is the extent to which a medium enables users to perceive others as psychologically present.
Mediated communication refers to how the properties of a medium influence the perceptions, behaviors, and attitudes of participants engaged in mediated interactions (Gunawardena, 1995) Social presence is defined as the extent to which users perceive the presence of others during these interpersonal interactions, highlighting their awareness of another human being or intelligence in the communication process (Biocca and Nowak, 2011).
Researchers highlight the strong link between social presence and information richness, focusing on media interactivity (Rice et al., 1989; Straub, 1994) Gefen and Straub (2003) introduce the idea that social presence also involves a psychological aspect, emphasizing the importance of "human warmth." Consequently, the effectiveness of social presence is determined by how well a medium can convey sociability, warmth, sensitivity, and intimacy (Shen and Khalifa, 2009).
Karimov et al (2011) summarize extensive research on website design, highlighting the importance of "social cue design," which includes human-like interfaces, assistive features, and social media elements Human-like cues enhance social presence through facial representations, emotional product displays, and positive text Assistive interfaces, such as avatars and recommendation agents, also contribute to social presence but are often overlooked in studies Social media cues, including user-generated content, ratings, and interactions from platforms like Facebook and Twitter, further enhance this sense of connection Research indicates that fostering social presence can be achieved by encouraging user imagination of interactions with others Technologies like personalization, recommendations, and consumer reviews create environments that promote social interaction, thereby increasing the social presence of websites, as noted by Kim and Benbasat (2003) and Hassanein and Head (2007).
Social presence is crucial for connecting users to online stores, as it serves as a key design principle that influences online behavior and community interactions According to Shen and Khalifa (2009), social presence encompasses multidimensional psychological aspects, including awareness, affective responses, and cognitive engagement, which collectively contribute to the overall sense of social presence Additionally, Rajasekhar and Vijayasree (2012) highlight that emotions and sociability are significant psychological factors that impact decision-making processes, enhancing both the effectiveness of making and correcting choices in the online shopping experience.
The Technology Acceptance Model (TAM) is a significant framework for understanding user behavior in online shopping environments, focusing on two key factors: perceived usefulness (PU) and perceived ease of use (PEOU) Perceived usefulness refers to the belief that new technology enhances user performance, ultimately improving the online shopping experience (Davis, 1989) TAM effectively predicts individual adoption and willingness to engage with technology (Rauniar et al., 2014) In the context of online platforms, high levels of PU and PEOU encourage users to interact with websites For instance, social media platforms like Facebook and Twitter attract millions of users due to their perceived usefulness in facilitating communication and their user-friendly interfaces that allow for simple navigation.
Building on the Technology Acceptance Model (TAM) developed by Chen et al (2002) and Davis (1989), Zhou et al (2007) introduced the Online Shopping Acceptance Model (OSAM), which enhances understanding of consumer acceptance in online shopping This model extends the belief-attitude-intention-behavior framework of TAM by focusing on online shopping-specific factors It emphasizes perceived usefulness beyond generic information systems, highlighting the ultimate benefits of online shopping, such as convenience, searchability, and access to rich product information These aspects contribute to the concept of "perceived gain" (Bhatnagar and Ghose, 2004a, p.765) and underscore the necessity of minimizing uncertainty and risks associated with online shopping.
The rapid growth of online shopping is largely due to the numerous advantages it offers over traditional retail methods The Internet enables consumers to shop anytime and anywhere, enhancing convenience and accessibility Each e-commerce website plays a crucial role in improving user experience by saving both time and money Additionally, online shopping allows users to find the best deals and obtain relevant product information efficiently, further increasing the appeal and usefulness of internet shopping.
2.2.3 Trust in an online environment
Trust is a multifaceted and dynamic concept that is challenging to define (Hassanein and Head, 2007; Ambrose and Johnson, 1998; Lewicki and Bunker, 1996) The most widely accepted definition describes trust as the "willingness of a party to be vulnerable to the actions of another based on the expectation that the other will perform a particular action important to the trustor" (Rousseau et al., 1998; Mayer et al., 1995) Furthermore, a higher level of trust often leads to a greater willingness to engage in risk-taking interactions (Hassanein and Head, 2007) For example, consumers are more inclined to buy from a vendor they trust, believing that the vendor will honor their commitments and not exploit their vulnerabilities (Geyskens et al., 1996).
In the context of online shopping, consumer trust is defined as the willingness to rely on an Internet merchant, anticipating that they will act in a trustworthy manner despite the consumer's inability to monitor their actions (Lee & Turban, 2001) This trust encompasses the perceived reliability and trustworthiness of e-vendors providing products or services (Hassanein & Head, 2007) It is built upon specific beliefs, including the vendor's ability, benevolence, and competence (Gefen, 2000).
Trust plays a crucial role in the acceptance of new technologies, particularly in the realms of the web and e-commerce It is essential in commerce due to the inherent uncertainties that arise from relying on others during various interactions.
In 1985, Williamson highlighted the risks associated with opportunistic behavior, where vendors may not fully disclose relevant risks or act unpredictably, a concern that extends to e-commerce Consumers often rely on unfamiliar e-vendors, who may engage in similar opportunistic practices, as noted by Frederick (2000) and Gefen (2000).
In the realm of online shopping, consumers face vulnerabilities due to potential opportunistic behaviors from e-vendors, such as selling personal information and unauthorized use of credit card details This can lead to unsatisfactory product performance and unfair pricing, ultimately diminishing the perceived benefits of online purchases Research indicates that as product risk increases, the likelihood of making a purchase online decreases, causing unease among e-consumers and contributing to the failure of online shopping experiences Consequently, establishing trust in the online environment is crucial for positively influencing consumer attitudes and enhancing purchasing intentions.
The concept of "flow state," defined by Csíkszentmihályi in 1990, refers to a mental state where individuals are fully focused and engaged in an activity Researchers Clarke and Haworth (1994) expanded this definition to include enjoyment as a crucial component of flow They describe flow as a deeply satisfying experience that transcends mere fun, characterized by a heightened sense of playfulness In the context of online shopping, this enjoyment stems from the fun and playful aspects of the experience, reflecting consumers' perceptions of the entertainment value associated with Internet shopping.
Online shopping has become a favored activity among e-consumers, who seek satisfaction through advanced technology As noted by Shen (2012), this voluntary and hedonic behavior is driven by intrinsic motivation Beyond economic benefits, consumers engage in online shopping as a leisure activity, finding it enjoyable and fun (Mathwich, 2002) This aligns with the positive psychology theory of flow, which suggests that enjoyable experiences can lead to lasting happiness and positive outcomes (Csíkszentmihályi, 1990).
Research Model and Hypotheses Development
Building on the foundational model research by Hassenien and Head (2007), this author enhances the framework by focusing on the psychological aspects of internet users' purchase intentions, a crucial factor in the buying decision process The proposed research framework and hypotheses are illustrated in Figure 2.3.
2.3.1 Social presence and Perceived of usefulness
Research indicates a psychological link between the perception of warmth in a medium and its effectiveness in various communication tasks (Rice and Case, 1983; Steinfield, 1986) Numerous studies have explored the relationship between perceived social presence and perceived usefulness While Gefen and Straub (2003) found no correlation in e-Services, earlier studies by Straub (1994) and Karahanna and Straub (1999) confirmed that social presence positively influences perceived usefulness in online shopping Additionally, Hassanein and Head (2007) and Shen (2012) assert that social presence communicated through a website enhances perceived usefulness and user experience Therefore, substantial evidence supports the following hypothesis.
H1: Social presences have positive impact to perceived usefulness in online stores
2.3.2 Social presence and trust in an online shopping
Trust is established within a social environment, as noted by Fukuyama (1995) Simon (2001) emphasizes the connection between information richness and social presence, stating that consumer-oriented websites rich in information can reduce ambiguity, enhance trust, and lower perceived risk, ultimately encouraging purchases with less consumer dissonance Gefen and Straub (2003) further assert that social presence significantly impacts online consumer trust and is essential for its development Designing websites with a strong social presence can foster greater trust, as highlighted by various studies (Gefen and Straub, 2003; Wang and Emurian, 2005; Hassanein and Head, 2007) This is particularly important in e-commerce, where customers are more influenced by direct relationships with online merchants than by indirect ones (Lah et al., 2013) Therefore, it is hypothesized that enhancing social presence on websites will lead to increased trust among consumers.
H2: Social presences have positive impact to trust in online stores
The psychological impact of social presence is significantly linked to enjoyment, as noted by Lombard and Ditton (1997) Heeter (1995) found that users of a virtual reality entertainment system reported higher enjoyment levels when they experienced a stronger sense of social presence Research has consistently demonstrated a positive correlation between social presence and perceived enjoyment on various platforms, including apparel websites (Hassanein and Head, 2007) and virtual world environments (Yeh et al., 2011; Shen, 2012) Based on these findings, the author hypothesizes that
H3: Social presences have positive impact to enjoyment in online shopping websites
2.3.4 Perceived of usefulness and attitude’s customer
The Technology Acceptance Model (TAM) defines perceived usefulness as the extent to which individuals believe that using a specific system will improve their job performance Research has demonstrated the significant influence of perceived usefulness on customer attitudes across various sectors, including online airline ticket transactions (Renny et al., 2013) and e-banking (Jarhangir and Begum, 2007) According to Davis, Bagozzi, and Warshaw (1992), perceived usefulness reflects consumers' perceptions of the benefits derived from their experiences Consequently, a system with high perceived usefulness fosters a positive relationship between usage and performance.
H4: Perceived usefulness have positive to attitude in online shopping websites
2.3.5 Trust in an online shopping and attitude’s customer
Trust is a crucial factor in online shopping, significantly influencing consumers' intentions to adopt e-commerce (Gefen and Straub, 2000) It serves as a key element that alleviates risk perception, encouraging customers to feel more secure when sharing personal information (McKnight and Choudhury, 2006) Higher levels of trust in a company's website lead to more positive attitudes towards the vendor and an increased willingness to make purchases (Li and Yang, 2002; Gefen and Straub, 2003; McKnight and Choudhury, 2006) Research indicates a direct relationship between trust and customer attitudes, alongside perceived risk in online shopping environments.
Jarvenpaa et al (1999) find that increasing trust reduce the perceived risk, and positive impact the attitude toward internet shopping Thus, author hypothesizes that:
H5: Trust will result in a more positive attitude towards online shopping website
Childerset et al (2001) identify "enjoyment" as a key predictor of attitudes toward online shopping, suggesting that a positive shopping experience leads to a greater likelihood of adopting the Internet for purchases Subsequent studies (Gefen and Straub, 2003; Hassanein and Head, 2007; Shen, 2012) further support this by demonstrating that perceived enjoyment significantly enhances consumer attitudes toward online vendors and their websites Additionally, Kim (2007) finds that the perceived entertainment and enjoyment value strongly influences attitudes toward product virtualization technologies Based on these findings, the author posits that enjoyment plays a crucial role in shaping consumer attitudes in the online shopping environment.
H6: Enjoyment will result in a more positive attitude towards online shopping website
2.3.7 Perceived usefulness and Purchase intention
Numerous studies have explored the factors influencing online purchasing intentions, with perceived usefulness identified as a key determinant (Atchariyachanvanich et al., 2006) Individuals tend to seek out information technology that maximizes their perceived usefulness, which significantly impacts their motivation to engage in subsequent tasks Research has shown that perceived usefulness positively affects individuals' behavioral intentions regarding computer usage (Davis et al., 1989) Therefore, we propose the following hypothesis:
H7: Perceived usefulness will result in a more positive attitude towards online shopping website
Research indicates that enjoyment is a key component in creating a flow experience, significantly influencing e-satisfaction and user intentions to revisit websites Childers et al (2001) highlight that factors such as enjoyment, entertainment, and humor enhance consumers' likelihood of returning to online platforms They advocate for the development of more enjoyable online shopping environments through the use of engaging elements like images, colors, humor, animation, and interactive features Furthermore, perceived playfulness (Koufaris and Hampton-Sosa, 2002) and a consumer's hedonic orientation (Delafrooz et al., 2011) have been shown to significantly affect purchase intentions Therefore, the author hypothesizes that these elements play a crucial role in online shopping experiences.
H8: Enjoyment will result in a more positive attitude towards online shopping website
Research by Yu and Wu (2007) indicates that a positive attitude significantly enhances the intention to engage in online shopping, while a negative attitude diminishes this intention Additionally, Donthu and Garcia (1999) found that consumer innovativeness positively affects online shopping behaviors and intentions, with attitude acting as a mediating factor Various studies, including those by Vijayasarathy (2003) and Chang and Chen (2008), have utilized the theory of planned behavior and the technology acceptance model to analyze consumer attitudes and intentions regarding online shopping Collectively, these findings underscore the critical role of attitude in shaping online shopping intentions and behaviors, leading to the hypothesis that attitude is a key predictor of online shopping engagement.
H9: Positive attitude will enhance purchase intention towards online shopping website
Conclusion
This chapter defines the key constructs in B2C e-commerce, highlighting the pivotal role of social presence as a factor influencing perceived usefulness, trust, and enjoyment, which in turn affect consumer attitudes and purchase intentions Despite varying discussions, research indicates a positive correlation among these constructs The empirical studies conducted provide insights into internet user decision-making trends and enhance the understanding of existing theories.
RESEARCH METHOD
Introduction
This section outlines the methodological approach for the research, detailing each step of the research process It explains the development of measurement scales and describes the strategy for gathering qualitative data, as well as the primary data needed for quantitative analysis Finally, it selects appropriate data analysis methods that align with the research model's objectives.
Research process
In this study, we utilized a combination of qualitative and quantitative methods to refine measurement scales and evaluate the research model The data collection process was structured in two distinct phases: initially, a pilot test employing qualitative research, followed by a main survey that incorporated quantitative research techniques (see Figure 3.2).
Qualitative research
A qualitative research study was conducted to validate the proposed model and delve into the impact of social presence on the antecedents of attitudes towards online shopping The study employed open-ended interview questions to gather in-depth insights from customers with online shopping experience The interview questions were carefully designed to be neutral and non-leading, allowing participants to share their genuine thoughts and opinions via email or direct inquiry.
The survey showed clearly the objective of studies and interpreted clearly about the social elements appearing in website interface There were14 participants experienced in online shopping reply this survey
Cronbatch’s Anpha EFA- Exploratory factor analysis
Mediator effect SEM – Structural Equation Model
Previous studies have highlighted the importance of social presence in addressing the absence of human warmth in online interactions (Chen et al., 2002) Enhancing social presence through the use of avatars or rich social descriptions and images of products can significantly improve customer engagement and increase the likelihood of purchase decisions (Song et al., 2008).
A recent study explored the factors influencing customer attitudes and purchase intentions in online shopping, revealing that 85% of interview participants found websites more useful when socially rich elements, such as customer ratings and recommendations, were incorporated These features provided users with a more engaging and informative experience, with 50% of respondents describing the product presentation as enjoyable and realistic Furthermore, 21% felt a sense of trust and persuasion due to the perceived fit of the products for their needs When discussing factors affecting their attitudes towards online stores, participants highlighted website design, privacy security, trustworthiness, customer service, price comparison, and warranty policies Specifically, 35% emphasized the importance of trust, 14% noted the website's usefulness, and 28% appreciated the enjoyment derived from a visually appealing and user-friendly interface Overall, the survey results align with customer psychology in online shopping and support the research model, confirming the significance of these factors.
Measurement Scales
To ensure the reliability of our research and effectively understand the concepts involved, we utilized items adapted from previous studies According to Hassanein and Head (2007), all items should derive from existing literature and demonstrate strong content validity across various research efforts Consequently, we employed well-established scales commonly used in studies addressing attitudes, intentions, and behaviors in electronic commerce.
As literature review section, there were six factors in the research model
Scales item of social presence were adapted from Gefen and Straub (2003), Shen (2012) They were included:
SP1 There is sense of human contact on this website
SP2 There is sense of sociability on this website
SP3 There is a sense of human warmth on this website
SP4 There is a sense of human sensitivity in the website
Scales item of perceived of usefulness were gathered from the research of Moon and Kim
(2001) and Chen et al (2002) They were included:
PU1 This website provides good quality information
PU2 This website improves my performance in assessing jewelry online
PU3 This website increases my effectiveness for jewelry assessment online
PU4 This website is useful for assessing jewelry online
Measuring this factor, author synthesized the scales of enjoyment from three studies: Ghani and Deshpande (1994), van der Heijden (2003), Hwang and Yi (2002) They were included:
E1 I found my visit to this website interesting
E2 I found my visit to this website entertaining
E3 I found my visit to this website enjoyable
E4 I found my visit to this website pleasant
As Gefen and Straub (2003) had thoroughly research related to conceptual of trust, scales item of trust were adapted from their studies They were included:
T1 I feel that this online vendor is honest
T2 I feel that this online vendor is trustworthy
T3 I feel that this online vendor cares about customers
T4 I feel that this online vendor would provide me with good service
Scales item of attitude were collected from van der Heijden et al (2001) They were included:
A1 I would have positive feelings towards buying a product from this site
A2 The thought of buying a product from this website is appealing to me
A3 It would be a good idea to buy a product from this website
Adopted the scales item from Jarvenpaa et al (1999), scales item of purchase intention were included:
PI1 How likely is it that you would consider purchasing from this website?
PI2 How likely is it that you would consider purchasing from this website?
PI3 In case you intend to buy jewelry in online store, how likely is it that you would buy from this website?
The study utilized a seven-point Likert scale, ranging from one (strongly disagree) to seven (strongly agree), to measure various items While some constructs were derived from two or three validated sources, it is assumed that these items assess the same underlying construct The reliability of these measurements will be evaluated in the following section using Cronbach's alpha.
Quantitative research
A quantitative survey was conducted following qualitative research that indicated social presence cues significantly influence customer perceptions The objective of this study was to analyze how social presence affects attitudes and purchase intentions by examining data collected from a representative sample of online shopping customers.
An empirical study was conducted to validate the proposed research model and test the hypotheses, utilizing a sample of approximately 300 participants The study featured 22 items measuring six conceptual variables, with participants tasked to purchase a gift for a friend from online jewelry stores.
Survey questions were distributed via email and social networks like Facebook, Skype, and Yahoo to individuals familiar with online shopping in Ho Chi Minh City Three distinct websites were created, each showcasing varying levels of social presence: the first featured a simple interface with essential product details (price, code, material), the second included enriched text and images, and the third combined the elements of the second site with customer ratings and recommendations Participants were organized into three groups of 100 members each to complete the survey, which assessed their responses to the different website interfaces as outlined in Appendix C.
There were 292 people take part in answering this survey However, author only chose
A study involving 210 correspondents, primarily aged 23 to 35, revealed that this demographic represents approximately 71 percent of the online store's customer base This age group is particularly adept at using internet applications and demonstrates a strong demand for online shopping Data from this investigation were analyzed using SPSS 20 and AMOSS 22 for statistical processing.
Data analysis method
According to Connely (2011), Cronbach’s alpha was used as only one criterion for judging instruments or scales It was commonly used as an estimate of the construct reliability
In their book "SPSS for Intermediate Statistics," Nancy, Karen, and George (2005) highlighted the widespread application of a method that offers a reliable measure of consistency, valid across different testing sessions or questionnaire administrations.
3.6.2 Contruct validity - Exploratory factor analysis (EFA)
Norris and Lecavalier (2010) posited that Exploratory Factor Analysis (EFA) is grounded in a testable model that can be assessed for its alignment with the proposed population model, utilizing fit indices for enhanced interpretation (p.9) This analytical approach aids in uncovering the latent constructs that underlie a collection of manifest variables In this process, we focused on evaluating the convergent and discriminant validity of each item, which are essential components of construct validity as outlined by Campbell (1959).
The research aimed to assess the impact of social presence across three levels of website interface, revealing significant differences in means among the groups at each level To achieve this, an ANOVA (analysis of variance) was performed to simultaneously compare the three levels of social presence.
3.6.4 The structural equation model (SEM)
Structural Equation Modeling (SEM) served as the primary analytical method for examining the research model, allowing for the testing of assumed causal relationships among various dependent and independent variables This approach facilitated the exploration of the interrelationships between concepts within the model Notably, the author highlighted key model fit indices, including Chi-Square, RMSEA, TLI, CFI, and SRMR, to assess the adequacy of the model.
This chapter outlines the research methods employed in this thesis, beginning with the development of the survey questions based on prior studies, which were validated through qualitative research Subsequently, quantitative research was carried out by distributing the survey to participants online The data collected met the necessary requirements for analysis using SPSS and AMOS software The analysis methods included Cronbach’s alpha, Exploratory Factor Analysis (EFA), ANOVA, and Structural Equation Modeling (SEM), which serve as foundational tests to elucidate the research outcomes in the following chapter.
ANALYSIS AND RESULTS
Introduction
This chapter presents a comprehensive analysis and interpretation of the collected data Initially, the demographic characteristics of respondents were analyzed using SPSS statistical software Subsequently, the reliability of the scale was assessed through Cronbach's alpha, while validity was primarily evaluated using Exploratory Factor Analysis (EFA) Additionally, an ANOVA test was performed to establish a prerequisite for examining the manipulation of social presence across three levels The model's fitness was further assessed through mediation testing, Structural Equation Modeling (SEM), and bootstrap methods Lastly, hypotheses testing was conducted to investigate the relationships among the model's variables.
Respondents demographic
From the collected data of 210 answers, author used SPSS – Statistical Software package to release the frequencies of each demographic factor as table 4.2
Demographic Profile Category Frequency Percentage
Buying Online Experience Not yet 16 8
This research targeted a specific customer segment, focusing on participants aged 23 to 35 years Descriptive statistics revealed that the gender distribution among participants was relatively balanced, with an equal percentage of females and males.
A significant majority of respondents, 81 percent, achieved a college or bachelor’s degree, while 13 percent held postgraduate qualifications and only 6 percent completed high school Income levels were predominantly between VND 5 million and VND 10 million, accounting for 55 percent of participants, with 15 percent earning less than VND 5 million, and another 15 percent earning between VND 10 million and VND 15 million or over VND 15 million Most respondents had extensive experience with internet services, with 61 percent using the internet for over six years, 26 percent for four to six years, and only 13 percent for one to three years Additionally, over 90 percent had engaged in online shopping, although 7 percent were familiar with the concept but had not made any purchases.
Scale validation
According to Nancy et al (2005), Cronbach's alpha is the most widely utilized measure of internal consistency reliability for multi-item scales This statistic is calculated to evaluate whether the individual items can be combined to form the observed variables, as highlighted in Gefend's research.
According to Rivard and Huff (1988), the reliability measure should exceed 0.5, with an ideal threshold of 0.7, while Nancy, Karen, and George (2005) emphasized that Cronbach’s alpha must be above 0.7 for items to be considered as a cohesive construct As detailed in Table 4.3.1, the alpha values ranged from 0.853 for social presence to 0.891 for perceived usefulness, demonstrating that the items achieved reasonable internal consistency reliability Consequently, the research constructs met the criteria for construct reliability.
Observed Variable Scale Mean if
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Construct validity is assessed by analyzing how items are grouped and how well they represent the intended construct To identify which items correlate closely, it is essential for items within the same construct to show high correlations (convergent validity) while demonstrating low correlations with items from different constructs (discriminant validity) (Campbell, 1959; Straub and Karahanna, 1998).
Exploratory factor analysis (EFA) was performed to evaluate all items within the measurement scales, with the results detailed in Appendix D of the research model.
In the factor analysis, the author first evaluated the Kaiser-Meyer-Olkin (KMO) measure, which yielded a value of 0.929, exceeding the acceptable threshold of 0.7, indicating that the items were adequate for factor analysis Additionally, Bartlett’s test showed a significant value close to zero, below 0.05, confirming a strong correlation among the variables The Total Variance Explained indicated that variance was distributed across 22 potential factors, with five factors having an Eigenvalue greater than 1, justifying their significance The first factor explained 50.8% of the variance, followed by the second factor at 8.3%, the third at 6%, the fourth at 5.2%, and the fifth at 4.9%.
To assess convergent and discriminant validity, the author analyzed item loading, retaining items with high loadings on their respective factors and low loadings on unrelated factors Following Hair et al (as cited in Nguyen, 2009), it is essential for observed variables to have factor loadings exceeding 0.5; those below this threshold should be discarded to ensure convergent validity Additionally, for discriminant validity, cross-loadings must differ by more than 0.3, necessitating the removal of items that do not meet this criterion The findings, illustrated in the Rotated Component Matrix (Appendix D), reflect these reductions in the research model.
The Principal Component Analysis with varimax rotation revealed that items TR2, TR3, TR4, AT3, PU1, and EN1 exhibited loadings greater than 0.5, but also showed significant loadings on other factors, with gaps of less than 0.3 Consequently, these items were excluded from the research model to enhance clarity The majority of items demonstrated strong loadings within the initial constructs of social presence, enjoyment, perceived usefulness, and purchase intention, while items related to trust and attitude were excluded Notably, AT1, AT2, and TR1 clustered together with strong loadings, indicating they pertain to the same factor Therefore, these items were combined into a new factor termed "trust attitude" for subsequent analyses.
After removed the unsatisfied items, EFA was run again as table 4.3.2
The analysis revealed that all loadings exceeded the thresholds of very good (over 0.63) and excellent (over 0.7) as per Comrey and Lee (1992) guidelines Consequently, the five constructs—social presence, perceived usefulness, enjoyment, trust attitude, and purchase intention—demonstrated both discriminant and convergent validity This further validates that the accepted items in this phase are crucial and preserve all significant information from the original data.
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 6 iterations
This research involved three groups of participants who completed a survey on three websites specifically designed to exhibit varying levels of social presence: low, medium, and high The study aimed to explore how enhancing social presence could influence user interaction, serving as a marketing tool for online business owners To validate the effectiveness of the experimental treatment, a social presence scale was utilized The primary research question focused on whether there were significant differences in social presence perceptions among the three groups A one-way ANOVA test was performed, with the results detailed in Appendix E.
The analysis revealed distinct mean scores for social presence: 2.5 for low, 4.17 for medium, and 4.68 for high social presence, indicating a clear differentiation among the groups The Homogeneity of Variances test yielded a Levene statistic significance value of 0.61, confirming that the assumption of equal variances was not violated This validation allowed for further exploration of mean differences The ANOVA test indicated a significance value close to 0, below the 0.05 threshold, while the post hoc Tukey test also showed significant mean differences between the pairs These findings suggest that the variations among the three experimental websites are unlikely due to chance and are likely attributable to the manipulation of social presence.
Std Error Sig 95percent Confidence
Interval Lower Bound Upper Bound
* The mean difference is significant at the 0.05 level
Modified research model
Following the analysis of the measurement scale through Exploratory Factor Analysis (EFA), three observed variables from the trust scale were eliminated Only the variable TR1 remained, which was grouped with the two items AT1 and AT2 from the attitude scale Consequently, the trust variable was excluded from the research model.
The modified measurement scale, now encompassing TR1, AT1, and AT2, effectively measures the new construct of trust attitude, which is influenced by perceived usefulness and enjoyment The research model was refined to include the following hypotheses: H1 posits that social presence positively impacts perceived usefulness on online shopping websites, while H2 asserts that social presence enhances enjoyment in the online shopping experience.
H3: Perceived usefulness will result in a more positive trust attitude toward online shopping website
H4: Enjoyment will result in a more positive trust attitude toward online shopping website H5: Trust attitude has positive impact to purchase intention in online shopping website
H6: Perceived usefulness has positive impact to purchase intention in online shopping website H7: Enjoyment has positive impact to purchase intention in online shopping website
Model fitness
This section discusses the results of the structural equation model (SEM) using AMOS 22 software While exploratory factor analysis (EFA) primarily concentrates on measurement scales, SEM provides a comprehensive measurement model that can be represented diagrammatically or mathematically through equations (Barbara, 2009, p.7) This statistical model offers a more efficient and convenient alternative to traditional methods like multiple regression In addition to fit model indices in SEM, the validity of the model is also emphasized.
Intention assessed by evaluating the structure path and R 2 value and bootstrap at well (Oredein et al.,
Before mediator variable (perceived usefulness and enjoyment) enter in the model
After mediator variable (perceived usefulness and enjoyment) enter in the model
The proposed model highlights that perceived usefulness and enjoyment serve as mediators in the relationship between social presence, attitude, and purchase intention Utilizing the methodology of Afthanorhan et al (2014), the analysis conducted with AMOS revealed a direct path from social presence to trust attitude and purchase intention The introduction of mediating variables, perceived usefulness and enjoyment, resulted in a decrease in the effect of social presence on trust attitude (from 0.557 to 0.136) and purchase intention (from 0.604 to 0.111), rendering these effects insignificant (p-values of 0.118 and 0.244, respectively) Additionally, the predictors for attitude and purchase intention increased from 0.289 and 0.331.
0.537; 0.487 This result revealed that the mediator effect was supported to be occurred and perceived usefulness and enjoyment was indeed full mediators in model research
Structural Equation Modeling (SEM) is an advanced multivariate technique that effectively tests the psychometric properties of scales measuring unobservable constructs and estimates the parameters of structural models, including the relationships among variables (Gefen et al., 2000) For SEM analysis to be valid, five key criteria must be met: (1) the normalized Chi-square value (χ2/df) should be less than 3; (2) Goodness-of-fit (GFI) values should ideally exceed 0.9, although values above 0.8 may be acceptable in some cases; (3) the Tucker & Lewis index (TLI) must be greater than 0.9; (4) the Comparative fit index (CFI) should also be above 0.9; and (5) the Root Mean Square Error of Approximation (RMSEA) should range between 0.03 and 0.08 Additionally, a Standardized Root Mean Square Residual (SRMR) value of 0.1 or less indicates an acceptable model, as noted by Hu and Bentler (1999).
The results of the structural model, as illustrated in Figure 4.5.2, reveal standardized regression estimates and a normalized Chi squared value of 1.849 (chi squares = 717.570, df = 388, p-value = 0.000), which is below the recommended threshold of 3 Additional fit indices indicate a strong fit for the measurement model, with a goodness-of-fit index of 0.836, surpassing the cut-off level of 0.8 The Tucker & Lewis index stands at 0.901 and the comparative fit index at 0.920, both exceeding the 0.9 benchmark Furthermore, the root mean square error is 0.045, well below the recommended maximum of 0.1 Collectively, these findings suggest that the measurement model adequately fits the data.
Figure 4.5.2: SEM result of research model (Standardized)
Table 4.5.2: Relationship between constructs in research model (standardized)
In table 4.5.2, standardize regression weights displayed how influence between dependent constructs and independent constructs Each pair of relationships had significantly different from 0 at the 0.001 level (two tailed)
Structural equation modeling typically requires a large sample size, which can be time-consuming and costly (Anderson & Gerbing, as cited in Nguyen & Nguyen, 2008) To address this, bootstrap estimation is a viable alternative (Schumacker & Lomax, as cited in Nguyen & Nguyen, 2008) In this study, bootstrap estimation was applied with a sample size of N00, and the results, shown in Table 4.5.3, indicated minimal bias, confirming the reliability and validity of the model estimates.
Estimate S.E SE SE-SE Mean Bias SE-Bias
Hypotheses testing
The primary focus of the model testing procedure was to evaluate the fit of the hypothesized model to the sample data (Barbara, 2009) Initially, the research proposed nine hypotheses; however, subsequent analysis revealed that certain measurement scales did not align with the data As a result, the modified research examined only seven hypotheses The testing results indicated that all seven hypotheses were supported, as shown in Table 4.6.
Hypothesis Path Result SE P Result
Table 4.6: Result of hypotheses testing
Hypothesis 1 and 2 assumed that social presence had both a direct effect on perceived usefulness and enjoyment, as well as indirect effects on trust attitude The hypothesized paths between these variables were all positive and significant The path between social presence and perceived usefulness is statistically significant with standardized regression coefficient of 0.58 with se=0.088 and p-value near to zero Also, the result showed the regression estimate between social presence and enjoyment was 0.566 with se 0.085 and p-value near to zero The implication of this result is that social presence had affected to perceived usefulness and enjoyment of customer with online store, however the influence weighted a little stronger with perceived usefulness than enjoyment
Hypothesis 3 and 4 proposed that perceived usefulness and enjoyment was positively associated with trust attitude Regression estimate of the relationship between perceived usefulness and trust attitude was 0.38 with se = 0.059, p-value = 0.000, while regression estimate of relationship between enjoyment and trust attitude was 0.49 with se = 0.069, p-value
= 0.000 These results suggested that trust attitude was impacted by both factors of perceived usefulness and enjoyment, in this case enjoyment effect to trust attitude more than perceived usefulness did
The analysis revealed that both perceived usefulness and enjoyment positively influenced purchase intention, with regression weights of 0.27 and 0.255, respectively, and p-values close to 0 However, their impact was found to be weaker compared to the effect of trust attitude on purchase intention.
The statistical analysis revealed a significant positive relationship between trust attitude and purchase intention, with a strong effect size of β = 0.353 Consequently, all hypotheses within the research model were validated, supporting the proposed framework.
Conclusion
This chapter discusses the results of data analysis concerning measurement scales, the research model, and hypotheses The findings revealed that many measurement scales required adjustments to align with market data, and the research model needed simplification by reducing the number of constructs Following this analysis, a revised research model was evaluated using structural equation modeling, with all model fit indices meeting the necessary standards Consequently, all hypotheses of the new research model were supported.
CONCLUSIONS AND LIMITATIONS
Discussion and conclusions
Research by Hassanein and Head (2007) highlights that social presence significantly influences perceived usefulness, enjoyment, and trust, which are crucial for shaping attitudes By enhancing websites with richer social presence through images and contextual elements, additional social cues such as links to mass media platforms (like Facebook, Google, and Twitter) and customer reviews can be integrated Notably, the findings indicate that when trust and attitude are combined, they alter the proposed model, yet the interplay among the model's concepts continues to exhibit complex dynamics.
Trust and attitude are interconnected concepts explored in various studies According to Jones (1996), trust is considered an emotional attitude, where individuals are positively influenced by optimistic perceptions of an object This trust is demonstrated through goodwill towards people or things of significance From a psychological standpoint, trust embodies both emotional excitement and a reflective attitude Aghdaie et al (2011) define trust attitude as an independent concept, focusing on confidence, belief, and reliance In their research, trust attitude comprises components AT1, AT2, and TR1, where AT1 and AT2 reflect positive feelings about an attractive website, and TR1 assesses the customer's belief in the supplier's truthful information Consequently, trust attitude is recognized as a favorable behavior among online users.
In this research, trust concept is eliminated from research model Hence the related connection between this factor and other is deducted, and not exist as analysis issue anymore
A trust attitude is influenced by two key components: belief and confidence The author examines how social presence affects perceived usefulness and enjoyment, and how these factors subsequently impact trust attitudes and purchase intentions.
The SEM model results indicate that the social presence level of commercial websites significantly enhances perceived usefulness (b=0.58) and enjoyment (b=0.57) While Gefen and Straub's (2003) findings on perceived usefulness are not widely accepted, they align with earlier studies by Hassanein and Head (2007) and Shen (2012) within the e-service context The discrepancies among these studies can be attributed to the differing nature of the products examined, such as air tickets compared to clothing and jewelry Notably, social presence contributes similarly to both perceived usefulness and enjoyment, as reflected in the comparable path coefficients However, the impacts of perceived usefulness and social presence on attitude and purchase intention are distinctly different.
The analysis reveals a significant positive impact on consumer attitudes when perceived usefulness and enjoyment serve as antecedents to trust, with social presence also contributing positively (b=0.38, b=0.49) This finding aligns with earlier studies, such as Jarhangir et al (2007) on E-banking and Renny et al (2013) on online ticket purchases, both of which demonstrated that perceived usefulness enhances customer attitudes Furthermore, it supports long-standing research on the enjoyment-attitude relationship in online environments, as established by Childers et al (2001), Gefen and Straub (2003), and Hassanein and Head.
Research indicates that perceived usefulness and enjoyment significantly influence online shopping purchase intentions, with attitude serving as a partial mediator This aligns with earlier studies by Delafrooz et al (2011) and Davis (1989), reinforcing the importance of perceived usefulness Additionally, findings from Koufaris (2002), Moon and Kim (2001), and Childers et al (2001) suggest that enjoyment, linked to consumers' hedonic orientation, enhances purchase intentions Attitude has the strongest effect on intention (b= 0.35), highlighting the close relationship between psychological processes in decision-making While Donthu and Garcia (1999) noted that attitude impacts online purchase intention primarily as a mediator, this thesis supports the direct relationship found in the works of Davis (1989), Chang et al (2005), and Vijayasarathy and Jones (2000).
This thesis aims to explore how social presence influences perceived usefulness and enjoyment, ultimately affecting online customer attitudes and purchase intentions By utilizing open-ended questions, the author can effectively gauge customer perspectives.
A website with low social presence may effectively showcase products for knowledgeable and professional buyers, particularly if it is optimized for mobile viewing However, users accessing the site from notebooks or desktops may find it too simplistic and lacking essential information, leading to a less satisfying experience The unengaging design of the surface web can make it appear boring and unattractive, ultimately reducing the likelihood of visitors staying longer to evaluate the product's value.
The website's medium social presence effectively showcases products worn by real people, enhancing user connection and visualization Participants appreciated seeing individuals wearing the jewelry, which made the products more appealing and relatable, despite some challenges in viewing the design details Many noted that the social-rich content helped them stay updated on the latest fashion trends, particularly benefiting those less experienced in online jewelry shopping One participant highlighted the value of seeing how jewelry looks on different people, as it sparked ideas on outfit coordination and style harmony.
To enhance social presence, websites are increasingly incorporating social media elements, such as customer ratings and reviews However, this abundance of content can lead to confusion, as users typically prefer to scan for key information rather than read everything in detail As a result, they often overlook customer reviews or doubt their authenticity, suspecting they may be manipulated by the website owner Consequently, users tend to avoid lengthy and complicated content, seeking instead clear and concise points that guide them through the page.
The phrase "Keep it simple, stupid" has become a fundamental principle in web design However, many users advocate for the inclusion of more ratings and reviews Inexperienced online shoppers often rely on feedback from previous users, viewing it as valuable guidance that helps them make informed purchasing decisions and avoid potential mistakes.
Implications
In this section, the author begins by outlining the theoretical contributions of this work and explaining the practical implications of our findings
Research indicates that incorporating socially rich descriptions and images into websites enhances social presence, which positively influences users' perceived usefulness and enjoyment of commercial sites This enhancement fosters more favorable attitudes and increases purchase intentions towards the online store The study contributes to the theoretical understanding of social presence in the e-commerce sector, building on previous research that examined its effects on online digital products such as airline and concert tickets.
Research indicates that social presence significantly influences positive consumer attitudes and purchase intentions on jewelry websites Enjoyment, alongside perceived usefulness, emerges as a crucial outcome of social presence, reinforcing previous studies linking trust and enjoyment to online consumer behavior The findings highlight the necessity of measuring online purchase intentions, revealing that consumers with favorable attitudes towards online shopping are more likely to intend to make purchases Stronger positive attitudes correlate with higher behavioral intentions, while negative attitudes diminish them As online shopping continues to evolve, addressing attitude-related issues becomes vital for adoption Online retailers should focus on attributes such as fun, entertainment, and usefulness to enhance customer attitudes and increase shopping intentions Therefore, incorporating social elements, like showcasing products on people and evoking positive emotions, is essential for boosting perceived social presence, ultimately driving purchase decisions.
This study focuses on specific interface features that influence the perception of social presence, which is crucial in online environments Research indicates that social design cues significantly affect user engagement, with findings showing that socially rich text and images enhance user attitudes and behavioral intentions Additionally, platforms like Facebook and Twitter improve social presence through their web interfaces However, there is limited evidence regarding the effectiveness of customer ratings and reviews The results suggest no significant difference in social presence levels concerning user enjoyment and perceived usefulness, prompting online marketers to consider minimizing unnecessary social elements in their web interfaces.
This study highlights the importance of social presence in online shopping, suggesting that designers can enhance user experience by incorporating emotionally evocative descriptions and images featuring people in dynamic settings These elements, which are easily integrated into web pages without requiring advanced technology, can help e-vendors create a more engaging shopping environment Despite the differences between offline and online shopping, both settings fulfill consumers' need for social interaction Traditional shopping experiences emphasize entertainment and community, with research indicating that the pursuit of pleasurable experiences often surpasses the mere acquisition of products Online shoppers also seek socially rich experiences, yet many e-vendors currently offer functional sites with minimal social appeal To maximize the benefits of adding social elements, e-vendors should consider the specific product types and consumer segments, conducting controlled experiments to evaluate the impact of these enhancements on their target audience.
Limitations and future research 47 REFERENCES
Similar to the other entire studies, there are a few limitations to this research that should be noted:
This study highlights the limitations in understanding the complexities of purchasing goods from online stores, emphasizing the necessity for longitudinal research to better analyze the relationship between purchase intention and buying behavior It acknowledges that the current research does not address the impact of these factors on actual purchasing behavior, leaving room for future studies to explore this issue further.
Research has yet to explore the differences in purchase intentions between experienced and inexperienced online buyers The study's representative samples are subjective, making it challenging to identify specific distinctions among groups based on gender, education, or income.
The research examines the psychology of internet users by showcasing images, content, and icons that represent social presence in website interfaces, but it does not create an actual website for user interaction As a result, the study overlooks the various devices that users can engage with proactively.
In general, the research can not reflect all respects of e-commerce, so that future research should be included:
Future studies should investigate how social presence impacts consumer behavior differently for products with symbolic value, such as clothing and jewelry, compared to functional goods that demand more detailed technical specifications.
The research focused solely on enhancing social presence through the integration of rich text, images, and social media However, it is essential for empirical studies to explore additional social cues, including direct human interactions facilitated by website features like email support, virtual communities, chats, message boards, and human web assistants Furthermore, the impact of simulated interactions—such as personalized greetings, human audio, human video, and intelligent agents—should also be considered, along with the influence of mass media elements like secondhand reputation advertising, objective source ratings, and vendor reputation.
The limitations of research in B2C e-commerce highlight the need for further exploration into the effectiveness of social presence on websites, particularly within the business-to-business (B2B) and consumer-to-consumer (C2C) markets.
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Research by Suki (2007) highlights the influence of perceived value, perceived risk, and perceived enjoyment on online buying innovativeness Additionally, Van der Heijden et al (2001) conducted studies at the Hawaii International Conference on System Sciences, focusing on predicting online purchase behavior through various competing models These findings underscore the complex interplay of factors that drive consumer decisions in the digital marketplace.
A longitudinal study by Venkatesh and Brown (2001) examines the factors influencing personal computer adoption in homes, highlighting both determinants and emerging challenges Additionally, Tran (2014) provides insights into the state of e-commerce in Vietnam, as detailed in the Vietnam E-commerce Report 2013, which outlines the growth and trends within the digital marketplace.
Vijayasarathy, L.R., & Jones, J.M (2000) Print and catalog shopping: Assessing attitudes and intentions Internet Research, 10, 191-202
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In "The Economic Institution of Capitalism," Williamson (1985) explores the intricate frameworks that govern economic interactions within capitalist systems, emphasizing the importance of institutional structures Complementing this, Yeh, Lin, and Hsi-Peng (2011) investigate how social roles influence user behavior in virtual worlds, revealing that these roles can significantly moderate interactions and engagement in online environments Together, these studies highlight the critical interplay between economic institutions and social dynamics in shaping human behavior in both real and virtual contexts.
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Appendix D: EFA results of main survey before removing items 8
Appendix F: Survey in Vienamese 10 on the impact of social presence in the web interface on customer’s purchase intention toward online stores
I would appreciate for your support if you spend a few minutes to filling in this questionnaire
4 Have you ever known or bought product from an online stors? □Yes □No
A fictitious jewelry website was created as part of a research project, showcasing product images alongside essential details such as price, material, size, color, and originality The website interface will also incorporate additional features to enhance user experience.
- Socially- rich text: descriptions aimed at evoking positive emotions
- Socially- rich picture: products are shown worn by people in emotional, dynamic settings
- Socially rich media: customer rating, customer recommendations, sharing with other social website such as facebook, twister, google etc
5 If adding the socially rich – text and picture you feel:
6 If adding socially rich media, you feel
7 In your opinion, your purchase intention toward online store depends on:
As a student at the International School of Business (ISB) at UEH, I am researching the influence of social presence in web interfaces on customer attitudes towards online stores I would greatly appreciate your support by taking a few minutes to complete this questionnaire Please remember that there are no right or wrong answers.
Thank you for your time and cooperation
Have you ever known or bought product from an online store?
If Yes, continue to the next questions
If No, stop your interview and thanks for your supports
Number of times bough product on the internet
In assumption, you have demand to buy jewelry (for example necklet) as a gift for your girlfriends and you are visiting the below websites (appendix C)
1 There is sense of human contact on this website 1 2 3 4 5 6 7
2 There is sense of sociability on this website 1 2 3 4 5 6 7
3 There is a sense of human warmth on this website 1 2 3 4 5 6 7
4 There is a sense of human sensitivity in the website 1 2 3 4 5 6 7
1 This website provides good quality information 1 2 3 4 5 6 7
2 This website improves my performance in assessing jewelry online 1 2 3 4 5 6 7
3 This website increases my effectiveness for jewelry assessment online 1 2 3 4 5 6 7
4 This website is useful for assessing jewelry online 1 2 3 4 5 6 7
1 I found my visit to this website interesting 1 2 3 4 5 6 7
2 I found my visit to this website entertaining 1 2 3 4 5 6 7
3 I found my visit to this website enjoyable 1 2 3 4 5 6 7
4 I found my visit to this website pleasant 1 2 3 4 5 6 7
1 I feel that this online vendor is honest 1 2 3 4 5 6 7
2 I feel that this online vendor is trustworthy 1 2 3 4 5 6 7
3 I feel that this online vendor cares about customers 1 2 3 4 5 6 7
4 I feel that this online vendor would provide me with good service 1 2 3 4 5 6 7
2 The thought of buying a product from this website is appealing to me 1 2 3 4 5 6 7
3 It would be a good idea to buy a product from this website 1 2 3 4 5 6 7
With the following statements, please check cross (X) the number that most fits your opinion (Anchored by: 1 Strongly improbable; 2 Improbable; 3 Somewhat improbable; 4 Neutral; 5
Somewhat probable; 6 Probable; 7 Strongly probable)
1 How likely is it that you would return to this store's website 1 2 3 4 5 6 7
2 How likely is it that you would consider purchasing from this website? 1 2 3 4 5 6 7
In case you intend to buy jewelry in online store, how likely is it that you would buy from this website?
Following the survey items, three open-ended questions were presented to users in a blank text area The
1 After viewing this website, what do you like about it, and why?
2 After viewing this website, what don't you like about it, and why?
3 How do you feel when exploring this site?
Monthly income (unit millions VND)
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 7 iterations
N Mean Std Deviation Std Error 95% Confidence Interval for Mean Minimum Maximum
Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig
Sum of Squares Df Mean Square F Sig
Tôi đang tiến hành nghiên cứu về tác động của các yếu tố xã hội trên giao diện website đến thái độ của khách hàng đối với các cửa hàng trực tuyến Nghiên cứu này nhằm hiểu rõ hơn cách mà các yếu tố này ảnh hưởng đến trải nghiệm mua sắm trực tuyến và quyết định của khách hàng.
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PHẦN A: THÔNG TIN TỔNG QUÁT
1/ Số lần bạn đã mua sắm qua mạng internet * o Chưa có o 1 lần o 2 lần o 3 lần o Nhiều hơn 3 lần
2/ Thời gian sử dụng internet * o Dưới 1 năm o 1-3 năm o 4-6 năm o Trên 6 năm