MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN LE KIM QUOC THE IMPACT OF FACTORS OF LIVESTREAM ON CONSUMER’S PURCHASE INTENTION: THE MEDIATING ROLE OF PERCEIVED RISK GRADUATE THESIS MAJOR: BUSINESS ADMINISTRATION CODE: 7340101 HO CHI MINH CITY, 2023 MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN LE KIM QUOC THE IMPACT OF FACTORS OF LIVESTREAM ON CONSUMER’S PURCHASE INTENTION: THE MEDIATING ROLE OF PERCEIVED RISK GRADUATE THESIS MAJOR: BUSINESS ADMINISTRATION CODE: 7340101 SUPERVISOR DR. PHAM THI HOA HO CHI MINH CITY, 2023 i ABSTRACT Due to its greater potential for traffic conversion, the live streaming e-commerce model has since 2016 become a breakthrough in the transition of traditional e- commerce. Live streaming e-commerce, as opposed to conventional e- commerce, can give customers a more direct and authentic shopping experience and encourage them to make decisions more rapidly. Due to the covid-19 epidemic's effects, several offline retailers experienced significant losses in 2020.
But, in these conditions, the number of livestreaming users has rapidly increased, which has brought about a significant increase in traffic support for livestreaming commerce. As a result, the live streaming e-commerce model has not only provided offline retailers with a new means of survival, but has also ushered them into a new phase of online business growth. For businesses and e- commerce platforms, it is crucial to investigate and comprehend the factors that affect customers' purchase intentions under the live streaming e-commerce model in order to enhance their own attractiveness, develop more effective marketing plans, and encourage customers to make purchases. The appearance of perceived risk was examined in this study along with one dependent variable, buy intention, and four independent variables, including streamer's credibility, interactivity, trustworthiness, and product risk.
In order to better understand how these potential variables can affect consumers' intentions to make purchases in the livestreaming e-commerce industry. The dataset is examined using 350 samples using structural equation modeling (SEM) to assess the hypothesis put forth in this study. Keywords: Livestreaming, purchase intention, perceived risk, impacted factors ii AUTHOR’S DECLARATION I hereby declare that the thesis ―The impact of factors of livestream on consumer’s purchase intention: The mediating role of perceived risk‖ is the result of my research conducted over 10 weeks. Except for references from previous research works as stated in the thesis, the survey data and the results of the thesis are completely honest and have not yet been published in any research work before.
Ho Chi Minh, April 2023 Quoc Nguyen Le Kim Quoc iii ACKNOWLEDGEMENT First and foremost, I would like to express my whole-hearted gratitude to my supervisor, Dr. Pham Thi Hoa. Thanks to her teaching in transmitting a myriad of important knowledge, and good recommendations in line with her patience and devotion, I could able to complete a well-rounded my bachelor's thesis. During conducting my thesis process, I received a bunch of meaningful teaching and inspiration from my respected lecturer.
Furthermore, I am grateful to all the professors and lecturers from the Banking University of Ho Chi Minh City who educate me with vital comprehensive knowledge and essential skills throughout my syllabus at university. Last but not least, I also want to thank the examiners for your pivotal time and consideration to review my graduation thesis. iv TABLE OF CONTENTS ABSTRACT. iii TABLE OF CONTENTS.
iv LIST OF ABBREVIATIONS. vii TABLE LIST. viii FIGURE LIST. OVERVIEW OF THE RESEARCH.
The urgency of the research. Subjects of the research and scopes of study. The basics of concept. The concept of purchase intention.
The concept of perceived risk. Overview of the livestream shopping in Vietnam. Previous empirical studies. The evaluation of previous related studies.
The Hypothesis and conceptual model. Process of research. Methodology of theoretical research. Practical research method.
Building the scale. Data processing method. Cronbach’s Alpha analyzing. Structural Equation Model.
THE RESEARCH RESULTS. Scale Reliability Testing. Exploratory Factor Analysis. Practical implication and suggestion.
Limitations and future research .80 APPENDIX 1: QUESTIONAIRE DESIGN .80 APPENDIX 2: DATA ANALYSIS RESULT .84 vii LIST OF ABBREVIATIONS Acronym Definition PI Purchase intention PE Perceived risk SC Streamer’s credibiltiy IN Interactivity TR Trustworthiness PR Product risk EFA Exploratory factor analysis KMO Kaiser–Meyer–Olkin test Sig. Significance level SPSS Statistical Package for the Social Sciences CFA Confirmatory factor analysis SEM Structural equation modeling viii TABLE LIST Table 2.1: Previous study summary .1: Measurement scale of observed variable .2: Coding the variables of the scale.2: Scale Reliability Testing .3: KMO and Bartlett's Test for the independent variable .4: Eigenvalues and covariance deviations for the independent variable .5: Factor loading for the independent variable .6: Results of confirmatory Factor Analysis- Factor loadings and composite reliability.9: The mediating testing .10: Summary of hypothesis testing results. 67 ix FIGURE LIST Figure 2.1: The proposed research model .1: Standardized Regression Weights .2: Analysis result of SEM. OVERVIEW OF THE RESEARCH 1.
Introduction Technology advancements have continuously altered consumer behavior by enabling new ways for consumers and businesses to interact (Cambra-Fierro et al. As expected, in the disruptive technology era, many marketers and practitioners have developed approaches to engage with consumers and increase brand awareness through the use of communication messages by leveraging digital technologies and collaboration among such actors (Krishen et al. Recently, e-commerce and social networks are creating attraction and great business opportunities for businesses because in Vietnam, the number of internet users is over 65 million. According to the Ministry of Industry and Trade, the growth rate of e-commerce in Vietnam at the time before the Covid-19 epidemic was 43%-45%.
In fact, this number may be higher, because according to Google, Vietnam's e- commerce growth rate in the past 2 years is approximately 80%. Just 43%-45% speed, after 2-3 years, the level of e-commerce development in our country is huge. Because this is a channel for businesses to reach customers faster. In 2020, when the Covid-19 epidemic occurs, online sales, transactions, and purchases through e-commerce platforms will flourish, confirming this is the future trend.
In 2020, the scale of e-commerce in Vietnam is forecast to reach 13 billion USD. According to the assessment of the Ministry of Industry and Trade, in 2022, the size of the e-commerce market in Vietnam's retail industry is estimated at 16.4 billion USD, accounting for 7.5% of the revenue of consumer goods and services of Vietnam. With a growth rate of 20%/year, Vietnam is ranked by eMarketer in the top 5 countries with the world's top e-commerce growth rates. Entering the post-Covid-19 recovery period, e-commerce is one of the pioneering fields of the digital economy, creating a driving force for economic development and leading digital transformation in businesses.
Live video streaming is available on some s-commerce and e-commerce websites, like Facebook and Taobao. While companies like Burberry and Starbucks have utilized Facebook Live to stream their marketing events (like fashion shows), a number of lone vendors in various nations go beyond promotion to actually sell 2 their goods in real time. Live streaming is used to answer customer inquiries in real time, display different perspectives of products, explain how things are made and used, and host live events that entice customers to make in-person purchases (Lu, Xia, Heo, & Wigdor, 2018; Lu, Xia, Heo, & Wigdor, 2018). Importantly, live streaming enhances the value of social networking platforms by allowing broadcasters and streamers to exist (Smith, Obrist, & Wright, 2013).
It allows sellers to display their identities, places of business or residence, and personalities (i., social presence), and it puts the offline buyer-seller interpersonal contact and associated selling strategies online. Such livestreaming-enabled social interaction and presence can improve the shopping experience, soothe buyers' concerns, and boost their trustworthiness in the s-commerce merchant (Hajli, 2015). Live video streaming has become a powerful marketing tool that is enabled by modern technology and accessible through desktop computers and mobile phones (Chen & Lin 2018). Particularly, the benefits of the Internet include convenience, accessibility, and two-way communication.
Additionally, social media (SM) platforms give businesses the opportunity to interact with and build relationships with their target audiences (Sun et al. Thus, live-streaming is described as an electronic medium platform in the context of marketing that broadcasts online in real-time to reach target audiences for certain goals. The urgency of the research The way that online business is done has changed as a result of live streaming. It demonstrates the significant part live-streamed shopping plays in e-commerce.
Live streaming has been widely discussed as a new media form that triggers people’s continuous watching behavior (Kaytoue et al., 2012; Sjöblom & Hamari, 2017). The live-streaming shopping platform, in contrast to other live-streaming platforms, is built on an e-commerce foundation and has a heavy focus on results; specifically, live viewers are expected to lead to increased transactions. It is clear that live streaming shopping, a new e-commerce media channel, has a significant impact on advertising the sale. Alibaba and JD.com are just two of the numerous well-known tech and e-commerce giants that have entered the live-streaming purchasing space.
3 Similar to this, large shops like Amazon in the US have since 2019 expanded their e-commerce to include live-streaming purchasing after realizing the immense potential impact of live streaming on e-commerce (Wowza Media Systems, 2019). Live broadcasting appears to be gaining popularity in e-commerce. But many who are reluctant to use live-streamed shopping have voiced their worries. The two primary reasons why individuals choose not to use live-streamed purchasing are product quality (60.5%) and after-sales service (44.8%), according to a research by the Chinese Consumer Association (CCA) in 2020.
This demonstrates that the perception of danger by the consumer is still present when shopping on live streaming. Online purchasing uncertainty is related to perceived risk, which has been generally acknowledged in e-commerce studies as a significant barrier to sales (Forsythe & Shi, 2003; Michaelidou & Christodoulides, 2011). By reading reviews of the products and learning about the reputations of the merchants, online shoppers typically lower the perceived risk in transactions. The allure and effect of streaming media have a significant impact on how engaged consumers who are dependent on the streaming retail environment are in the live streaming situation (Cai et al.
When users become dependent on the live streaming environment, they might disregard the risk as a result. The lack of face-to-face interaction that characterizes online purchasing creates a perception of risk, which may be diminished in a live streaming shopping setting. Customers can ask inquiries during live-streamed shopping and receive an immediate response from streamers. This will therefore change the way that customers make purchases (Chen et al., 2017; Zhou et al.
Consumers can acquire rich information from the streamer's presentation, the product information page, and other consumers' remarks at the same time through live streaming, as opposed to typical internet buying, which simply relies on the text, photo, or video. The customer's trustworthiness and level of buy intent are also increased by the streamer's engaging introduction of the merchandise (Hajli, 2015). Live streaming shopping is still being investigated as a new business strategy (Sun et al. The IT affordance viewpoint (Sun et al., 2019), the marketing strategy perspective (Min et al., 2019), and the streamer's endorsement and product 4 matching views were some of the previously studied aspects that may influence the customer's buy intention in live-streaming purchasing (Park & Lin, 2020).
Although perceived risk is a key cognitive component influencing consumer behavior, it is still unclear what factors can make customers less risk averse when purchasing live. Additionally, there is minimal study that looks at the "holistic customer environment interaction" when examining the variables impacting consumer behavior (Xu et al. This study uses the stimulus-organism-response (S-O-R) model as a framework to overcome the aforementioned shortcomings and provide an explanation of how live-streaming shopping impacts on consumers' perceptions of risk and purchase intentions.