Research on the influences of tik tok and tiktok shop on buying behavior of vietnamese consumers Nghiên cứu ảnh hưởng của tik tok và tiktok shop đến hành vi mua hàng của người tiêu dùng Việt
INTRODUCTION
Backgrounds
According to Digital 2021, mobile phones are the primary device for Internet access globally, with 90% of users connecting via smartphones Social networks enable limitless connections across distances and serve as valuable tools in various sectors, including economy, politics, and society This has expanded advertising and communication options for businesses of all sizes In Vietnam, the Iris Marketing Agency (2020) reports that 73.56 million people, or 75.6% of the population, are active on social media, with projections indicating growth to 93.68 million users by 2025.
In recent years, TikTok has rapidly emerged as a favored social networking platform among Gen Z, surpassing traditional platforms like Facebook, Instagram, and Twitter for marketing purposes As of September 2021, TikTok boasted 1 billion monthly active users globally, while in Vietnam alone, it achieved 16 million downloads and a remarkable 160% increase in iOS downloads in 2020 According to Statista's 2022 report, TikTok has quickly climbed to become the fourth most popular social network, following Facebook, Zalo, and YouTube.
Figure 1 1 Leading active social media apps among internet users in Vietnam as of
TikTok has effectively integrated entertainment and commercial models, launching its advertising platform, TikTok For Business, on June 25, 2020, to serve as a marketing hub for business accounts To further support small and medium enterprises, TikTok introduced TikTok Shop in Vietnam on April 29, 2022, transforming the platform into a seamless blend of social networking and e-commerce within a single application.
TikTok's dynamic algorithm effectively promotes engaging short videos that captivate and inspire creativity among young consumers globally (Weimann & Masri, 2020) Ultimately, TikTok is perceived as a light-hearted platform where businesses succeed by sharing fun, visually appealing content that aligns with current trends.
According to The New York Times (2019), as a result of TikTok, small businesses find new ways to communicate with their customers and generate revenue
Small business owners often juggle multiple roles, acting as CEO, marketing strategist, and product manager, especially in the face of challenges posed by the global pandemic TikTok is revolutionizing the marketing landscape by offering innovative ways for these entrepreneurs to engage with consumers and boost sales Unlike traditional platforms, TikTok emphasizes authenticity over high budgets or popular spokespersons, allowing businesses to connect their content with their brand identity Success on TikTok comes from sharing genuine stories and celebrating true colors, whether through self-made videos or collaborations with TikTok creators.
The rapid growth and well-established user base of TikTok are making advertising and business opportunities on the platform increasingly popular Consequently, this thesis aims to explore the factors that evaluate the impact of TikTok content on consumer purchasing decisions.
12 intention of Vietnamese consumers It will contribute practical knowledge related to how businesses operate on TikTok and influence people's purchasing decisions.
Research Objectives
The main purpose of the article is: Identify the factors affecting the purchasing behavior of consumers through social networking sites, especially TikTok social networks
To achieve the above main objective, this study was conducted to address the following specific objectives:
• Using the S-O-R framework by Chopdar & Balakrishnan (2020) related to consumer purchasing decisions
• Conclusion on the impact of factors affecting the intention to use
• From there, draw conclusions and professional solutions and recommendations for brands and businesses to attract potential customers by using TikTok to promote and sell effectively.
Research Questions
What factors on TikTok and TikTok Shop influence customer purchase intent?
Which factors have the strongest impact on purchase intention?
Research scope
A study in Vietnam explored the purchasing behavior of potential customers who buy products through TikTok referrals and brands on the platform The research aims to identify key categories influencing purchasing decisions on TikTok and TikTok Shop By analyzing these factors, the study seeks to determine which elements most significantly impact customer choices.
The study was carried out between February 2023 and June 2023.
Research structure
This research includes five chapters:
This chapter introduces the research background, i dentifies the research objectives, research scope, and research structure.
LITERATURE REVIEW AND HYPOTHESIS
Asses related research resources
The stimulus-organism-response (S-O-R) framework proposed by Mehrabian and Russell (1974) is a foundational concept in environmental psychology, illustrating how external environmental factors stimulate an individual's internal state, leading to approach or avoidance behaviors This framework is particularly relevant in understanding consumer behavior, as participation in brand communities on social media can significantly influence customers' emotional and psychological well-being According to Gao and Bai, this engagement in online communities motivates consumers to connect with brands on a deeper level.
In 2014, it was established that stimuli significantly influence individual behavior, particularly in online contexts where personal experiences shape cognitive assessments Flow experiences, characterized by emotional states that evolve based on situational interactions, play a crucial role in consumer satisfaction According to Floh & Madlberger (2013), an attractive website design enhances the shopping experience, leading to immediate consumer gratification Research indicates that factors such as comprehensive product details, effective information, appealing design, and reliable transactions serve as stimuli that impact consumer responses, ultimately shaping purchase intentions and overall satisfaction (Prashar, Vijay, & Parsad, 2017).
The "response" aspect of the S-O-R framework highlights the effects consumers experience when interacting with brand communities on social media, particularly regarding their purchase intentions Numerous studies have applied this framework to explore online impulsive buying behavior (Kawaf & Tagg, 2012).
In the context of this study, the factors that appear or exist on TikTok and Tiktok Shop are conceptualized as stimuli that, through the customer interaction (purchase) process,
15 are conceptualized as organisims, from which their response is purchase intention as well as behavioral expression
2.1.2 Purchase intention and Consumer buying behavior
Purchase intention refers to the likelihood that a consumer will buy a specific product, serving as a crucial stage in the purchasing process (Grewal et al., 1998) It reflects the reasons behind a customer's choice to purchase from a particular brand (Shah et al., 2012) and represents a conscious decision to acquire a brand's product (Spears et al., 2004) Understanding purchase intentions is vital for businesses as they can predict potential earnings (Morwitz et al., 2007) Additionally, factors such as product value and consumer recommendations, especially from social media, significantly influence purchasing decisions (Zeithaml, 1988) The synergy of company-generated advertising and word-of-mouth recommendations fosters automatic sharing and endorsement among users, highlighting the perceived value of the product (Hoy & Milne, 2010).
The visibility of brands in society has increased significantly, influenced by the active use of social media, which has transformed virtual markets and workplaces (Vițelar, 2019; PrakashYadav & Rai, 2017) As technology enhances customer interactions with businesses and each other, organizations are focusing on social media advertising to attract potential buyers (Alalwan, 2018) A customer's purchase intention, defined as their likelihood to buy a product or service soon, is largely shaped by their beliefs (Ha & Janda, 2012; Wu et al., 2011) Research indicates that a substantial 87.5% of consumers utilize the internet for purchases, and online video advertising positively influences their purchasing intentions (Bucko et al., 2018; Taylor et al., 2011) Additionally, informativeness in social media advertising is a key factor that drives consumer purchase intention (Alalwan, 2018).
16 posting the appropriate types of videos based on the user's desire to purchase the product (Alamaki et al, 2019)
Research by Rahman et al (2017) indicates that customer engagement significantly impacts purchase intention on social media platforms Additionally, Coursaris et al (2016) found that positive and engaging social media messages enhance consumers' brand attitudes, subsequently affecting their intention to purchase.
Purchase intent is crucial for testing new distribution channels, helping managers identify viable markets for further development Research by Morwitz et al (2007) highlights the importance of targeting specific consumers, as purchase intention is a key predictor of actual buying behavior (Montao and Kasprzyk, 2015) This study focuses on purchase intention, emphasizing the need to understand consumer attitudes and internal factors influencing their decisions (Fishbein and Ajzen, 1977) According to Pavlou (2003), online purchase intention refers to the willingness of consumers to buy products from online stores, making it a vital metric for online retailers.
Research on buying behavior extends beyond traditional in-store purchases to areas like green marketing, luxury brands, business-to-business transactions, and online shopping George (2004) defines online buying behavior as the frequency of consumer purchases on the Internet, while Ajzen (1991) suggests that consumer intention reflects the willingness to engage in specific behaviors, including online purchases A significant barrier to e-commerce development is the lack of online purchase intention, as highlighted by He et al (2008), prompting researchers like Lim et al (2016) to call for further exploration of the relationship between online purchase intention and buying behavior Consequently, this study aims to investigate how consumer online purchase intentions influence buying behavior.
Social Network foundation: Tik Tok
TikTok has emerged as a leading global music video platform and social network, distinct from traditional platforms like Facebook and Instagram, as it allows users to create and share short videos that can go viral through its trending algorithm This app has gained immense popularity, especially among teenagers, and has become the most downloaded app on the Apple App Store, surpassing competitors like Instagram and Snapchat However, TikTok's user base is not limited to the younger generation; many older users, including farmers and fishermen, have also embraced the platform to showcase their products and connect with audiences The Covid-19 pandemic further accelerated TikTok's growth, as it provided a vital means of communication and creativity during quarantine, enabling users to generate innovative content and promote their businesses amidst economic challenges.
TikTok, owned by the Chinese company ByteDance, reached 1 billion users by the end of 2021, according to its reports The platform is acclaimed for its seamless integration of photography, short video recording, and artificial intelligence (AI) By harnessing the creativity of its community and its innovative design, TikTok has rapidly attracted a growing user base.
2.2.2 How to buy on TikTok
2.2.2.1 Via the seller's biography link
"Link" is gradually becoming popular and interested by many users on social networking platforms such as TikTok or Instagram Due to the limitation from the fact
Instagram and TikTok users often face challenges due to the platform's restriction of allowing only one link in their bio This limitation can hinder individuals and businesses from sharing multiple resources effectively.
Link Bio was created to address the challenges faced by content creators and shoppers alike It enables users to seamlessly insert affiliate links in their bios, allowing shoppers to easily find and purchase desired products from e-commerce platforms like Shopee, Lazada, and Tiki Currently, many TikTokers, KOLs, and influencers utilize Link Bio to share product links and earn commissions based on user interactions with these links, enhancing their business opportunities while providing convenience to consumers.
On April 29, 2022, TikTok launched TikTok Shop in Vietnam, a new feature enabling individuals and businesses to sell directly through their accounts This innovative platform simplifies the shopping experience by allowing users to buy and pay within the TikTok app, eliminating the need for intermediary steps like visiting a bio link or other e-commerce sites TikTok Shop serves as an ideal marketplace for consumers, offering a wide range of products, while also providing sellers and businesses with an optimized platform to promote their offerings, engage potential customers, close sales during live advertisements, and ultimately boost revenue.
Previous Researches of Consumers Behavior
Table 2 1 Previous Researches of buying behavior
Research on online book buying behavior of students at Kristianstad
3 factors including price, convenience and trust -> price is the most important factor affecting online buying behavior via social
Online shopping behavior of Iranian consumers
Qualitative The relationships between risk perceptions, return policies, infrastructure and services affect innovation by product group, attitude, subjective norm and perceived behavioral control towards purchasing shop
The influence of Influencers Tik Tok on online shopping interests in communication studies students
Quantitative The Visibility variable of the
The popularity of TikTok influencers significantly impacts the purchase interest of Communication Science students in their fourth semester at the State Islamic University of North Sumatra This influence highlights the importance of social media personalities in shaping consumer behavior among young adults.
The Influence Of Tiktok Applications
Research on online shopping behavior of Vietnamese consumers
Education and monthly income significantly influence consumers' online shopping habits Additionally, the flow of information and goods positively affects the frequency of online shopping among consumers.
Consumer buying behavior towards online stores in Malaysia
Quantitative The study focused on 9 independent variables: website appearance, quick access, information security, sitemap, value relevance, promotion, attractiveness, trustworthiness and uniqueness
Development of a scale to measure the perceived benefits and risks of online shopping
Online shopping offers numerous benefits, including unparalleled convenience, a vast selection of products, and the comfort of shopping from home, all contributing to a pleasurable experience However, it is essential to consider potential risks associated with online shopping, such as financial risks, product quality concerns, time investment, and convenience challenges that may arise during the purchasing process Balancing these benefits and risks is crucial for a satisfying online shopping experience.
Factors Influencing Online Shopping Intention: An Empirical Study in Vietnam
Data collection and sample characteristics Questionnaire s Quantitative
The study reveals that online consumers' shopping intentions are positively influenced by their attitudes, subjective norms, perceived behavioral control, perceived usefulness, and trust Conversely, perceived risks associated with online shopping negatively impact these intentions, with risk perception emerging as the most significant factor affecting online shopping behavior.
Factors affecting purchase intention of Vietnamese young customers at Shopee
Trust has a strong significant relationship with online purchasing intention in Shopee context
Adoption of M- commerce in India:
Applying Theory of Planned Behaviour Model
Quantitative The results of this study show that attitude, subjective norm and perceived behavioral control have a positive impact on purchase intention
Factors affecting the online shopping intention of Genz generation in Thailand
The results show that only two factors of experience and perceived usefulness have a significant impact on this generation's online shopping intention; and perceived ease of use
22 does not seem to affect
Factors affecting the purchase intention of Thai consumers through online social networking platforms
The results show that perceived usefulness is found to have the most influence on purchase intention, followed by quality assurance, perceived ease of use, and social influence
The results indicate that impulse buying is believed to be the strongest predictor of consumers' online purchase intention in Malaysia; followed by belief, experience and quality orientation
Factors affecting the behavior of buying fresh food over the internet: An empirical study from the Hanoi market
Research indicates that the time risk factor adversely affects customer buying behavior, highlighting a widespread sentiment among consumers who generally dislike the drawbacks associated with trading.
METHODOLOGY
Research process
Figure 3.1 Research process proposed by the author
Sample Design
Academics Hair et al (2009) suggest that the required sample size for a survey should be five times the number of questions In this study, with 24 questions measuring 6 variables, the minimum sample size needed is 120 (24 questions multiplied by 5) A larger number of responses enhances the accuracy of the survey results.
This study collects samples in the form of non-probability sampling According to Leary
In 2004, research utilizing non-probability samples became accepted for hypothesis testing A questionnaire was created using Google Forms and subsequently shared across various social media platforms, including Facebook, Zalo, and Instagram, to gather responses.
The study focused on respondents who have either purchased or intended to purchase products on TikTok Shop To ensure the accuracy of the data, the author excluded responses from individuals who did not use TikTok or had never made a purchase.
The data collection process was conducted from April 15 to May 6 The author received
204 responses through an online survey After eliminating the inappropriate responses,
183 valid responses can be used for data analysis.
DATA PRESENTATION AND FINDINGS
Descriptive Statistics
The descriptive analysis classifies by the demographic information, comprising: Gender, Age, Occupation, Monthly income, Living Area, Using Frequency
This data will be presented by text and charts
This section presents an analysis and conclusions drawn from data collected during the author's online survey Utilizing a questionnaire on the Google Form platform, the author gathered 183 responses from users across various social networking platforms, including Facebook, Instagram, Zalo, and TikTok.
The following are the data results of those who took part in that survey:
In a survey of 183 respondents, 29.5% were male, totaling 54 participants, while female participants comprised 66.1%, amounting to 121 individuals Additionally, 4.4% of respondents, or 8 individuals, chose not to disclose their gender.
The survey participants predominantly fall within the age range of 21 to 25 years, comprising 56.8% of the total respondents, which amounts to 104 individuals The second-largest group consists of participants aged 26 to 30 years, accounting for 25.7%, while those aged 15 to 20 years represent 15.3% A small segment of the survey includes four participants aged 31 to 35, making up 2.2% of the total, with no respondents under 15 years or over 35 years of age.
The survey revealed that there were 245 responses in the occupation category, despite the actual number of participants being only 183.
35 proves that survey participants do many occupations at once At present, students in addition to studying at school also participate in internships in companies (Phan Thuy
Duong, 2022), or do part-time jobs to increase their income and, above all, improve their skills work experience for the future
Overall, survey respondents have a wide range of occupations, in which Students a nd
Freelancers represent the largest group of live participants in the survey, with 67 and 65 individuals, making up 36.6% and 35.5% of the total, respectively Office workers follow closely behind, totaling 59 participants and accounting for 32.2% Additionally, Business Owners and Self-Employed individuals collectively comprise about 18% of respondents, while only a small number of participants fall into other categories.
Teachers, Doctors, Nurses, Technicians, Designers and Flight Attendants
Source: By author Living Area: Of the total of 183 survey participants, people living and working in the
North make up the majority, including 125 people and accounting for 68.3% People living in the South and Central regions are significantly less, including 31 and 27 people, accounting for 16.9% and 14.8% respectively
Income: For income criteria, the scale is divided into 5 groups with different income levels The author estimates that 51 people, accounting for 27.9%, have an income of
11-15 million VND/month Income group from 5-10 million dong ranked second, with
43 respondents (accounting for 23.5%) Ranked third is the income group below % million dong, accounting for 21.3% The two income groups of 16 -20 million and over
20 million did not have much difference with the third gro up, about over 20 people in each group and accounting for 14.8% and 12.6% respectively
According to the author, TikTok usage time is categorized into six scales, with the majority of users, 37.2%, spending "Under 1 hour" on the app, totaling 68 individuals Following this, 23.0% of users, or 42 people, engage with TikTok for 1-2 hours daily The groups spending 2-3 hours and 3-4 hours show similar usage patterns, each comprising about 30 users Finally, only a small fraction, approximately 3%, or 13 individuals, report using TikTok for more than 4 hours a day.
A survey of 183 respondents revealed that 60.7% (111 individuals) have made purchases on TikTok Shop, while 39.3% (72 individuals) have not yet bought anything but express an intention to shop on the platform in the future.
4 Where do you live and work?
6 How much time do you spend in a day using Tik Tok?
7 Have you experienced buying at
Table 4.2 summarizes the descriptive statistics of the independent and dependent variables For each factor, the minimum value, maximum value, mean and standard deviation are specified.
Reliability Analysis
Cronbach's alpha is a widely recognized metric for assessing reliability (Hair et al., 2009) This study employs Cronbach's Alpha to evaluate the reliability of the scale's factors, with values ranging from 0 to 1 Generally, a higher alpha value indicates better reliability, although values between 0.95 and 1 may suggest redundancy among variables An alpha above 0.5 is deemed reliable, while values below 0.5 are considered unreliable, with the optimal range being between 0.9 and 0.95 (George & Mallery, 2010) Additionally, items with an item-total correlation below 0.3 will be removed, while those above 0.3 are accepted (Nunnally & Bernstein, 1994).
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
4.2.1 Reliability Analysis of PP scale
Table 4.3 Reliability of PP scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The Product Pricing scale consists of four items: PP1, PP2, PP3, and PP4 Reliability testing reveals a Cronbach’s Alpha value of 0.879, indicating strong internal consistency, as it falls between the acceptable range of 0.6 and 0.95.
The Corrected Item-Total Correlations for all four items of the PP scale exceed 0.3, with values of 0.795, 0.684, 0.731, and 0.751, respectively Consequently, all four items are accepted for further analysis, and none will be rejected.
In conclusion, after making reliability analysis, PP scale includes 4 items: PP1, PP2, PP3 and PP4
4.2.2 Reliability Analysis of PQ scale
Table 4.4 Reliability Analysis of PQ scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The Product Quality scale consists of four items: PQ1, PQ2, PQ3, and PQ4 Testing for reliability reveals a Cronbach’s Alpha value of 0.828, indicating good internal consistency, as it falls between the acceptable range of 0.6 and 0.95.
The Corrected Item-Total Correlations for all four items of the PQ scale are above 0.3, with values of 0.678, 0.705, 0.582, and 0.671 Consequently, all four items are accepted for further analysis, and none will be rejected.
In conclusion, after making reliability analysis, PQ scale includes 4 items: PQ1, PQ2, PQ3 and PQ4
4.2.3 Reliability Analysis of AC scale
Table 4.5 Reliability Analysis of AC scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The Advertising Content scale consists of four components: AC1, AC2, AC3, and AC4 Reliability testing, as indicated in Table 4.3, reveals a Cronbach’s Alpha value of 0.847, which falls within the acceptable range of greater than 0.6 and less than 0.95.
The Corrected Item-Total Correlations for all four items of the AC scale exceed 0.3, with values of 0.705, 0.698, 0.682, and 0.662 respectively Consequently, all four items are accepted for further analysis, and none will be rejected.
In conclusion, after making reliability analysis, AC scale includes 4 items: AC1, AC2, AC3 and AC4
4.2.4 Reliability Analysis of DI scale
Table 4.6 Reliability Analysis of DI scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The Digital Influence scale comprises four items: DI1, DI2, DI3, and DI4 Reliability testing indicates a Cronbach’s Alpha value of 0.807, which falls within the acceptable range of greater than 0.6 and less than 0.95.
The Corrected Item-Total Correlations for all four items of the DI scale exceed the threshold of 0.3, with values of 0.601, 0.628, 0.603, and 0.673, respectively Consequently, all items are accepted for further analysis, and none will be rejected.
In conclusion, after making reliability analysis, DI scale includes 4 items: DI1, DI2, DI3 and DI4
4.2.5 Reliability Analysis of WM scale
Table 4.7 Reliability Analysis of WM scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The eWOM scale comprises four items: WM1, WM2, WM3, and WM4 Reliability testing of these items reveals a Cronbach’s Alpha value of 0.821, indicating a strong level of internal consistency, as it falls between the acceptable range of 0.6 to 0.95.
The Corrected Item-Total Correlations for all four items of the WM scale exceed 0.3, with values of 0.636, 0.600, 0.639, and 0.705 Consequently, all items are accepted for further analysis, and none will be rejected.
In conclusion, after making reliability analysis, WM scale includes 4 items: WM1, WM2, WM3 and WM4
4.2.6 Reliability Analysis of PI scale
Table 4.8 Reliability Analysis of PI scale
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The Purchase Intention scale comprises four items: PI1, PI2, PI3, and PI4 Reliability testing of these items reveals a Cronbach’s Alpha value of 0.835, indicating good internal consistency, as it falls within the acceptable range of greater than 0.6 and less than 0.95.
The Corrected Item-Total Correlations for all four items of the PI scale exceed 0.3, with values of 0.673, 0.678, 0.682, and 0.637, indicating that all items are acceptable for analysis in the next phase, with no items being rejected.
In conclusion, after making reliability analysis, PI scale includes 4 items: PI1, PI2, PI3 and PI4
Exploratory Factor Analysis (EFA)
Exploratory Factor Analysis (EFA) is a quantitative method that simplifies a large set of variables, enhancing their utility while preserving the essential content of the original data (Hair et al., 2013).
Several criteria should be considered when performing exploratory factor analysis:
● Factor loading: Factor loading > 0.5 is considered to be of practical significance
The Kaiser-Meyer-Olkin (KMO) measure is essential for assessing the adequacy of sampling in factor analysis A KMO value between 0.5 and 1 indicates that exploratory factor analysis is appropriate for the dataset Conversely, if the KMO value falls below 0.5, it suggests that factor analysis is not suitable for the research data.
4.3.1 Exploratory Factor Analysis for independent variables
Table 4.9 KMO and Bartlett's Test for independent variable
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 6 iterations
Independent variables include 20 measuring items after examining the reliability test, and checking the validity in EFA As the table has shown, Kaiser -Meyer-Olkin (KMO)
The Measure of Sampling Adequacy is 0.784, indicating that the data used for factor analysis is suitable, as it exceeds the threshold of 0.5, with a significance value of 0.000, which is below the 0.05 level (Hair et al., 2009) The Total Variance Explained is 68.6%, demonstrating that five factors account for this percentage of data variation Additionally, the varimax rotation of the rotated component matrix confirms that the 20 selected observation items can be grouped into five distinct variables.
4.3.2 Exploratory Factor Analysis for dependent variables
Table 4.11 KMO and Bartlett's Test for dependent variable
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
The analysis of dependent variables involved four measuring items, which were assessed for reliability and validity through exploratory factor analysis (EFA) The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy was found to be 0.790, indicating that the data is suitable for factor analysis, as the significance value was 0.000, well below the 0.05 threshold (Hair et al., 2009) The Total Variance Explained accounted for 67.1%, with five factors explaining 65.9% of the data variation Additionally, the varimax rotation of the rotated component matrix confirmed that the four selected observation items clustered into one variable.
Correlation Test
According to Gayen (1951), in statistics, researchers use Pearson's correlation coefficient (symbol r) to quantify the closeness of the linear relationship between two quantitative variables
The Pearson correlation coefficient r ranges from -1 to 1:
● If r gets closer to 1, -1: the stronger the linear correlation, the closer it is Moving towards 1 is a positive correlation, moving to -1 is a negative correlation
● If r gets closer to 0, the linear correlation is weaker
● If r = 1: absolute linear correlation, when represented on the scatter plot as shown above, the points represented will merge into a straight line
● If r = 0: there is no linear correlation At this point, there will be 2 situations One, there is no relationship between the two variables Second, there is a nonlinear relationship between them
To determine the statistical relationship between correlation coefficients, it is essential to test the significance (sig) value According to Andy Field (2009), a sig value of less than 0.05 indicates a linear correlation between the variable pairs, while a sig value greater than 0.05 suggests no linear correlation, assuming a significance level of 5% (0.05).
PI PP PQ AC DI WM
** Correlation is significant at the 0.01 level (2 -tailed)
* Correlation is significant at the 0.05 level (2 -tailed)
The table 4.12 shows the index of Pearson Correlation between independent variables
PP - Product Pricing, PQ- Product Quality, AC- Advertising Content, DI- Digital Influencer, WM - Electronic WOM and dependent variable PI – Purchase Intention that illustrated the positive values
The Pearson correlation values (0.428, 0.417, 0.445, 0.393, 0.607) indicate a significant relationship between the independent variables PP, PQ, AC, DI, and WM, all falling within the range of 0 to 1 Additionally, the significance level for these variables is low, with p-values below 0.05 This analysis reveals a positive linear relationship between the dependent and independent variables, thereby supporting the hypotheses of this study.
Regression Analysis
Simple linear regression is a statistical method used to predict the value of a response variable based on a regressor It measures the relationship between independent and dependent variables, providing a clear function of the regression.
In that case, the abbreviations:
𝛽1: Coefficient between dependent variable and independent variable
In this model, the author must evaluate the P-value to determine the hypothesis's validity; a P-value greater than 0.05 indicates that the hypothesis is not supported, while a P-value less than 0.05 suggests support for the hypothesis Following this, the researcher should examine both the adjusted R-squared and R-squared values R-squared measures the extent to which independent variables account for the variance in the dependent variable, with higher values indicating a stronger explanatory power A model is considered suitable if R-squared exceeds 50% Adjusted R-squared also reflects model fit but adjusts for the number of independent variables; an increase in adjusted R-squared upon adding a new independent variable indicates its relevance in explaining the dependent variable.
In regression statistics, the Variance Inflation Factor (VIF) is essential for assessing multicollinearity A VIF value below 2 indicates no multicollinearity, meaning the variable can remain in the model, while a value of 2 or higher suggests the need for elimination of the variable.
Std Error of the Estimate
1 749 a 562 549 46719 2.391 a Predictors: (Constant), WM, PQ, PP, DI, AC b Dependent Variable: PI
Source: By author Table 4.14 ANOVA Test Result
Total 88.109 182 a Dependent Variable: PI b Predictors: (Constant), WM, PQ, PP, DI, AC
Standard ized Coefficie nts t Sig Collinearity
Check VIF: The value of the Variance inflation factor (VIF) can be used to check for multicollinearity
Table 4.15 presents the VIF index for independent variables, revealing that all VIF values are low (