BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC KINH TÉ TP. HÒ CHÍ MINH BÁO CÁO TÔNG KẾT ĐỀ TÀI NGHIÊN CỨU KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024 THE IMPACT OF LIVE-STREAMING ON CUSTOMERS’ IMPULSIVE BUYING BEHAVIOR Thuộc nhóm chuyên ngành: Thương mại - Quán trị kinh doanh và Marketing TP. HỞ CHÍ MINH, tháng 02/2024 1 ABSTRACT As a new form of social commerce, live streaming is becoming increasingly popular among online consumers, which has aroused great interest among practitioners and researchers. This research was conducted to determine the relationships between symbolic value (SYM), hedonic value (HED), interactivity (INT), visualisation (VI), social presence (SP), trust in sellers (TI) and immersion (IM).
With the sample including 300 participants, the results are expected to provide new insight and call more attention to this phenomenon. During the research process, we employ mathematical concepts, compulations, and algorithms to combine, examine, and produce precise and particular data and outcomes that support the findings, arguments made. Based on previous empirical research, we will develop a conceptualised model to investigate the relationship between live streaming activity and customers’ impulsive buying behaviour. The research results show that symbolic value and hedonic value impact positively to social presence; interactivity and visualisation impact positively to trust in sellers; social presence affects to both trust in sellers and immersion; Trust in sellers both affects to immersion and impulsive buying behaviour; immersion impacts positively to impulsive buying behaviour.
Our research has just identified the relationship between live streaming activities and impulsive buying behaviour. Moreover, with the current situation based on the world's development trends as well as online shopping becoming so popular, our conduct of this research also provided some suggestions for sellers through live streaming, helping sellers easily better grasp customer psychology, and increasingly develop shopping methods through live streaming. KEYWORDS Social presence Immersion Live streaming e-commerce Impulsive buying behavior Trust in sellers 2 TABLE OF CONTENTS ABSTRACT. 1 TABLE OF CONTENTS.
2 LIST OF FIGURES AND TABLES.5 LIST OF ABBREVIATIONS. Research background and statement of theproblem:. Subject and scope of research:.2 Research scope and time:. Data collection method:.
11 CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT.2: Social commerce and live streaming:.9: Trust in Sellers:.10: Impulsive buying behaviour:. Paper 1: “How social presence influences impulse buying behavior in live streaming commerce? The role of S-O-R theory”. Paper 2: “The role of live streaming in building consumer trust and engagement with social commerce sellers”. Paper 3: “How to Use Live Streaming to Improve Consumer Purchase Intentions: Evidence from China”.
Paper 4: “The effects of live streaming attributes on consumer trust and shopping intentions for fashion clothing”. Paper 5: “Research on the Impact of Marketing Strategy^ on Consumers ’ Impulsive Purchase Behavior in Livestreaming E-commerce". Research framework and hypothesis:.1: Relationship between Interactivity and Social presence.2: Relationship between Visualization and Social presence.3: Relationship between Hedonic value and Trust in sellers.4: Relationship between Symbolic value and Trust in sellers. : Relationship between Social presence and Immersion.6: Relationship between Social presence and Trust in sellers.7: Relationship between Immersion and Impulsive buying behavior.8: Relationship between Trust in sellers and Immersion.9: Relationship between Trust in sellers and Impulsive purchasing behavior:.
28 CHAPTER 3: RESEARCH METHOD.2 Questionnaire and measures:. Sample and data collection:. 34 CHAPTER 4: DATA ANALYSIS AND RESULTS. Exploratory Factor Analysis (EFA):.
Structural Equation Model (SEM):. 45 4 CHAPTER 5: DISCUSSION AND CONCLUSION. Limitation and Development. QUESTIONNAIRE - VIETNAMESE VERSION.
CRONBACH’S ALPHA AND COMPOSITE RELIABILITY RESULT. EXPLORATORY FACTOR ANALYSIS (EFA).68 5 LIST OF FIGURES AND TABLES Figure 2.1: Research model of J Ming, z Jianqiu, M Bilal, u Akram, M Fan (2021).2: Research model of A Wongkit Rungrueng, N Assarut (2020).3: Research model of L Ma, s Gao, X Zhang (2022).4: Research model of E Chandrruangphen, N Assarut, s Sinthupinyo (2022) .5: Research model of B Chen. L Wang, H Rasool, J Wang (2022).6: Conceptual framework of livestreaming shopping affect customers* impulsive buying behavior.1 : Research outcome model.1 - Measurement scales items.2 - Demographics of respondents (n=300).2 - Cronbach’s Alpha and Composite Reliability.5 - KMO and Bartlett's Test.6 - Rotated Component Matrix.7 - Result of hypothesis testing. 46 7 LIST OF ABBREVIATIONS SYM: Symbolic value HED: Hedonic value INT: Interactivity VI: Visualization SP: Social presence TS: Trust in sellers IM: Immersion PLS: Partial Least Square SEM: Structural Equation Model S-O-R: Stimulus-Organism-Response HTMT: Heterotrait-Monotrait KMO: Kaiser-Meyer-Olkin Measure AR: Augmented reality VR: Virtual reality 8 CHAPTER 1: INTRODUCTION 1.
Research background and statement of the problem: The surge in popularity of live streaming has prompted numerous retailers to harness its potential as a tool for enhancing their sales outcomes.This has resulted in the development of a brand-new shopping method known as live streaming shopping, which has already led to an increase in sales for numerous online merchants. For example, renowned brands like L'Oreal, Chope, Innisfree have stated that their revenues have increased by 75% when they take part in a campaign of Shopee. Additionally, in Vietnam, the practice of selling products through livestreaming on social media platforms, particularly on TikTok, is booming. Sellers in this thriving market have the capability to promote and sell a wide range of products, often reaching thousands of items in their inventory.
The revenue generated through these livestreaming sales can be substantial, with some sellers reportedly earning up to one billion Vietnamese Dong (VND), showcasing the tremendous potential and profitability of this emerging trend. As live streaming shopping is a modern type of shopping, it has some advantages over the traditional online type of shopping according to a research of Wongkit Rungrueng and Assarut in 2018. Firstly, conventional online shoppers are confined to perusing product descriptions and static images. In contrast, live streaming shopping empowers streamers (online sellers) to exhibit products in real-time video streams, thereby providing customers with more comprehensive and detailed product insights.
Secondly, in the realm of conventional online shopping, customers seeking responses on product-related questions have to leave from the product page to contact the seller. On the other hand, live streaming shopping enables customers to pose questions via the bullet screen, letting streamers give real-time responses. Thirdly, traditional online shopping constrain merchants from giving immediate guidance to customers and addressing their queries concerning products. The lack of face-to-face interactions often causes customers to doubt suppliers' authenticity, which increases the perceived risk of online shopping.
Live streaming shopping, however, mitigates this issue by facilitating customer questions through the comment bar during live streams, enabling sellers to promptly provide highly personalized services and guidance. These real-time interactions have 9 the potential to significantly influence impulsive buying behavior. Live streaming, as a new phenomenon, has caught a lot of attention from researchers. Therefore, this study is conducted to somehow distribute more information about the relationship between live streaming and impulsive buying behavior.
Besides, this study also gives several mediators that also have an influence on customer’s impulsive buying behavior through live streaming. Research objectives: In order to achieve the main goal of exploring how live streaming affects impulsive buying behavior, the study developed a conceptualized model which visualizes relationships researched. The thesis attempts to realize these tasks: - Discover the relationship and explore the significance between live streaming and impulsive buying behavior - Give an insight to managers in applying this information to enhance their sales performance. - Results of the study will be able to be applied to understand customer behaviors and since then, live streaming can be adopted properly to improve sales performance.
Subject and scope of research: 1.1 Research subjects: Impact and influences of live streaming on online customers' impulsive buying behavior with live streaming shopping through studying with these following influences: Identify the effect of social presence of interaction with sellers on the immersion. Identify the relationship between social presence of interaction with sellers and impulsive buying behavior. Identify the relationship between social presence of interaction with sellers and trust in sellers. Identify the effect of trust in sellers on impulsive buying behavior.
10 Identify the effect of immersion on impulsive buying behavior.2 Research scope and time: Scope: 300 people using live streaming shopping who live in Ho Chi Minh City. Time: 1/10/2023 -31/10/2023 To test the relationship between variables as well as examine the hypotheses, data is going to be collected through surveying with users purchasing products online through live streaming. Conducted by distributing surveys online. Data was collected within 1 month.
Research method: A quantitative methodology was employed in the present thesis. In the initial phase, the scales for all examined constructs were adopted from existing studies and subsequently translated into the Vietnamese language. Subsequently, a questionnaire was formulated, pre-tested with a sample of 100 participants, and subsequently revised to enhance its clarity prior to distribution. Then, the dataset was analyzed using SPSS and SMART-PLS 3.0 and consisted of the following undertakings: Cronbach’s Alpha analysis, EFA analysis, outer loadings and hypothesis testing.
Data collection method: The study uses the quantitative method. Data was collected through an online survey questionnaire via a Google form Data were collected from HCM’s customers who have had experiences of live streaming shopping and aged 18-45 and above 45; with a purposive sampling based on gender (i. The survey was conducted online.2 Data analysis: Questionnaires have used questions that are measured by option scale 1 as strongly disagree, 2 degree, 3 neutral, 4 agree and 5 strongly agree. The data is analyzed by Partial Least Square (PLS) which is a variant-based Structural Equation Model (SEM) that can simultaneously perform model testing as well as structural model testing.
Research contribution: This study tries to offer several potential contributions in the context of live streaming: First, this study considers both the features of live streaming shopping and customers' perceptions thereof. Second, this study considers both the antecedents and results of customer engagement in the context of live streaming shopping. Finally, this study also provides some practical suggestions for sellers and e commerce platforms to better leverage live streaming for effectively marketing their products and increase their sales performance. Research structure: Our research is divided into the following chapters: Chapter 01 - Introduction: This chapter concentrates on the general aspects of our research: the research background and statement of problem, the research objectives, the subject and scope of research, the research methodology.
In general, in chapter 1, we will give a brief introduction of our study then indicate the scope and object of the research, as well as the subject of the study. Chapter 02 - Literature review In chapter 2, we focus on the research-related definitions of scales, variables, and objects. In addition, we will present the prior research that serves as the foundation for our research model. Chapter 03 - Research methodology This chapter is concerned with the method used for the current thesis, including the research process, measurement scale, questionnaire design, sample and data collection, as well as the sample characteristics.
Chapter 04 - Data analysis and results 12 Chapter 4 focuses on analyzing the dataset of the research. It consists of the following steps: performing data cleansing, assessment of measurement scales, test for common method bias, exclusion of incongruent variables or observations, assessment of structural model. Chapter 05 — Discussion and conclusion This concluding chapter summarizes the key findings from this thesis and offers practical suggestions for Shopee app and other e-commerce companies. Additionally, it discusses the limitations and recommendations for forthcoming research.
CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 2.1: S-O-R theory: The Stimulus-Organism-Response (S-O-R) theory (Mehrabian and Russell, 1974) serves as a foundational framework in deciphering the intricate dynamics of consumers' impulsive buying behaviours within the context of live-streaming. Utilizing the S-O-R theory as the conceptual framework for this study offers several benefits, primarily because it offers a solid theoretical foundation for comprehending consumer behavior. Moreover, it has been extensively employed to investigate consumer behaviors within the realm of e-commerce such as impulse buying behaviors as demonstrated by Chen and Yao in 2018.