I BỘ GIẢO DỤC VÀ ĐÀO TẠO ĐẠI HỌC KINH TÉ THÀNH PHỔ HÒ CHÍ MINH HOW DOES VICARIOUS LEARNING SHAPE THE IMPULSE BUYING BEHAVIOR IN LIVE-STREAMING SHOPPING? Thuộc nhóm chuyên ngành: Kinh tế. Hồ Chí Minh, tháng 02/2024 I ABSTRACT With the rise of live-streaming shopping, this research examines how vicarious learning experiences influence consumers' impulse buying behaviors. Adopting vicarious learning theory, the study distinguishes between coactive vicarious learning (CVL), involving active engagement with streamers, and independent vicarious learning (IVL) through passive observation. This research aims to explore the impact of vicarious learning on impulse buying behaviour, investigating how individuals' spontaneous purchasing decisions are influenced by observing others.
Utilizing a mixed-methods approach, including surveys and experimental designs, the study examines the vicarious learning experiences through live-streaming underlying impulse behaviors. Data from 300 students from many different customer groups in Vietnam were collected by the authors for analysis. The study contributes to a deeper understanding of the interplay between vicarious learning and impulsive buying behavior, offering practical implications for retailers and researchers in the field of consumer behavior. In view of the growth of live streaming, the findings provide useful insights for theorists and marketers to optimize platforms and streamer strategies for engaging consumers and prompting impulsive purchases.
The research offers a nuanced perspective on how diverse vicarious learning experiences shape emerging live-streaming shopping environments. KEYWORDS: Vicarious learning; Live Streaming; Impulse buying; Interactivity; Urge to buy impulsively. I II TABLE OF CONTENTS LIST OF TABLES. IV LIST OF FIGURES.
Research background and statement of the problem. 4 CHAPTER II: LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 5 2. Definitions and theoretical backgrounds. Vicarious learning theory.
Means-end chain framework. Prior relevant studies. Research framew ork and hypothesis development. Attributes of vicarious learning and perceived benefits by customer 42 2.
Perceived benefits and customers’ perceptionof value. V alue perception and customer intention to buyimpulsively. Customer buying intention and impulse buying behavior. The proposed research model.
48 CHAPTER III: RESEARCH METHOD. Sample and data collection. 59 CHAPTER IV: DATA ANALYSIS AND RESULTS. Assessment of measurement scale.
Assessment of structural model.4 Discussion of Result. 75 CHAPTER V: RESEARCH IMPLICATIONS AND CONCLUSION. Limitations and future research. I APPENDIX I: QUESTIONNAIRE DESIGN.I APPENDIX 2: TABLE DESIGN.I PART 1: GENERAL INFORMATION.
I PART 2: QUESTIONNAIRE TABLE. Ill IV LIST OF TABLES No.1 Overview of research papers Table 3.2 Measurement scales Table 4.1 Sample demographic characteristics Table 4.1 Scale accuracy analysis Table 4.2 Scale accuracy analysis: Discriminant validity assessment Table 4.3 Inner VIF value Table 4.4 Significance testing results of the structural model path coefficients V LIST OF FIGURES No.1 Proposed research model Figure 3.1 Research Process Figure 4.1 Research model in Stage I Figure 4.2 Research model in Stage II Figure 4.3 Analysis results LIST OF ABBREVIATION Words Acronyms Active control ACT Credibility CRE EULSIT EUL Impulse buying IB Perceived Usefulness PU Psychological proximity pp Social Presence SP Social proximity SOP Spatial proximity SPP Standardized root mean square residual SRMR Telepresence TP Temporal Proximity TEP Two-way communication TC Urge to buy impulsively UTBI VI VP Virtual Presence I CHAPTER I: INTRODUCTION 1. Research background and statement of the problem The general context of the modern economic industry is witnessing a strong transformation, with a significant increase in online platforms and the emergence of new business models (Bui et al., 2023, Swchee et al. In this context, TikTok has emerged as a global phenomenon, attracting billions of users and becoming one of the most popular applications in the world (about 1 billion users).
According to a report conducted by TikTok on user shopping behavior in Vietnam during the 2023 holiday season, 69% of users prioritize watching short-form videos to learn about products and services; 84% of users are convinced to buy a brand's products and services (Meltwater. Direct commerce revolutionizes the conventional e-commerce business model by providing unprecedented real-time interactions between sellers and consumers (Aug ct al. Livestream commerce has developed into an indispensable marketing channel of companies around the world thanks to the potential to exploit the impulsive psychology of consumers in the buying process ( ju and Pan, 202 ). Prior research on livestreaming predominantly concentrated on customer satisfaction and purchase intent.
Nevertheless, recent studies have elucidated the impact of consuming livestream content on social media platforms, particularly in influencing customers' uncertain and impromptu purchase decisions (Men Ct al. Livestreaming serves not only as a platform for product promotion but also as a rapidly interactive environment, generating intense stimulation and excitement for viewers. (Sun et al. Impulsive purchases take place when consumers have a sudden need to buy something.
Shopping through live streaming is easy, so it encourages consumers to have unplanned or impulsive shopping behaviors, and consumers even tend to not curb their desire to shop online (Mulyono el al. The advent of live streaming technologies has ushered in a new era of consumer engagement, transforming the way individuals learn about and interact with products or services. In the realm of commerce, direct vicarious learning and independent vicarious learning through live stream have emerged as compelling forces that wield considerable influence over consumer behavior, particularly in the context of impulse buying. (Men Ct al.
As consumers increasingly turn to live streams for real-time demonstrations, peer 1 2 recommendations, and interactive engagement, it becomes paramount to explore the intricate dynamics at play (Xdesegun Oyedele et al. Through these interactions, viewers not only satisfy their entertainment and entertainment purposes, but they can also learn indirectly. Several studies have shown that viewers can learn vicariously about health (Song Ct al. 2022), business (Park el al.
2022), and travel experiences ( u. 2019) through livestream on Tiktok. Vicarious learning is the process of gaining knowledge or skills by observing and imitating others rather than through direct personal experience (Gioia and Manz. Consumers can learn directly (coactive vicarious learning) or indirectly (independent vicarious learning) from the live streamers.
Consumers, through coaclivc vicarious learning, gain firsthand insights into product usage and features, directly from the live streamers. This direct interaction enhances their understanding of the showcased products and facilitates more informed purchasing decisions (Ying Hua et al., 2023, Myers et al. Moreover, independent vicarious learning allows consumers to observe the experiences and opinions of others in the livestream, contributing to a collective knowledge base that informs their own choices (Gioia and Manz, 1985). As this coalescence of vicarious learning avenues unfolds, the live streaming environment evolves into a nexus of shared knowledge, prompting consumers to make immediate and informed decisions (Men et al.
2023, Myers et al. The real-time engagement with live streamers not only nurtures the symbiotic relationship between vicarious learning and impulsive buying but also underscores the dynamic nature of this interactive marketplace (Sun Ct al. As consumers engage with live streamers in real-time, the potential for immediate and impromptu purchasing decisions becomes pronounced, creating a dynamic environment where the symbiosis of vicarious learning and impulsive buying manifests (Clemen Addo et al. 2021) This research endeavors to unravel the nuanced ways in which coactive and independent vicarious learning through live stream contribute to the shaping of impulse buying tendencies among consumers.
By delving into the psychological mechanisms, social influences, and real-time dynamics inherent in these learning processes, this study aims to provide valuable insights into the evolving landscape of consumer decision-making in the digital age. Research objectives To contextualize the study’s purpose, we propose two questions that this study aim to answer: 7. Are CVL and IVL from the vicarious learning experience critical components needed for consumers to understand the live streamer? 2. How CVL and IVL influence consumer perceived value and impulse buying behavior in Iivestream ing sh opping ? Firstly, we aim to investigate the extent to which coactive vicarious learning (CVL) contributes to consumers’ understanding of live streamers in live-streaming shopping environments.
This entails exploring how active engagement with content creators during live streams influences consumers' perceptions and comprehension of the personalities behind the streams. We seek to examine the impact of independent vicarious learning (IVL) on consumers' perceptions of live streamers in live-streaming shopping contexts. This involves analyzing how passive observation of live streams and the actions of content creators affects consumers' attitudes and opinions towards these individuals. Secondly, our research aims to analyze how coactive vicarious learning (CVL) and independent vicarious learning (IVL) influence consumer perceived value in the context of live-streaming shopping.
We will investigate the extent to which these learning experiences shape consumers' perceptions of the value derived from engaging with live streamers and participating in live-streaming shopping activities. We will explore the relationship between coactive vicarious learning (CVL), independent vicarious learning (IVL), and impulse buying behavior among consumers engaged in live-streaming shopping activities. This involves examining how these learning experiences influence consumers' propensity to make impulsive purchase decisions during live streams. Theoretical contributions: This research expands the application of vicarious learning theory within the context of live-streaming shopping, advancing our theoretical understanding of how different vicarious learning mechanisms operate in e-commerce settings.
By examining the relationship between coactive vicarious learning (CVL) and independent vicarious 4 learning (IVL) and their impact on customers' impulse buying behavior on live- streaming platforms, it sheds light on the nuanced dynamics of vicarious learning experiences in online shopping environments. Additionally, the study contributes to the theoretical discourse by exploring how CVL and IVL influence consumers' perceived learning from social cues and subsequent impulse buying behavior, elucidating the cognitive and behavioral outcomes associated with vicarious learning in the context of online shopping. Managerial contributions: This research is poised to yield significant managerial implications for both live streaming platforms and merchants, offering insights aimed at optimizing various facets of the live streaming experience to enhance customer engagement and stimulate impulse buying behaviors. Specifically, the findings pertaining to interactivity, EULS1T are intended to inform platform design, feature development, and streamer communication strategies through virtual presence and psychological proximity.
5 CHAPTER II: LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 2. Definitions and theoretical backgrounds 2. Vicarious learning theory Vicarious learning refers to learning that occurs through observation or instruction rather than direct experience. It involves acquiring knowledge by watching the behaviors and outcomes of others' actions (Bandura, 1977).
Prior studies have defined vicarious learning as a cognitive process in which people acquire new responses by observing others' behaviors and the consequences of those behaviors (Wedgewood, 2006; Zhou & Hu, 2019). Vicarious learning research has been applied across a wide range of industries due to its important implications for how humans acquire skills and knowledge observationally (Bandura, 1977; Weaver et al. Education studies have extensively examined vicarious learning processes in classroom and online learning contexts (Schunk & Hanson, 1985; Williams el al. In sports, research analyzes how athletes leverage observational practice and video modeling to enhance performance (Law & Stc-Maric, 2005; Morgan cl al.
The medical field utilizes vicarious learning principles through simulation training and observation of expert procedures (Van de Ridder et al. Within the military, vicarious learning informs tactical instruction by capitalizing on opportunities for coactive and independent learning models (Kemple et al., 2000; Litz et al. Organizational research examines how vicarious learning from colleagues impacts outcomes in the workplace like safety practices and skills development (Tullett et al., 2018; Turner et al. More recently, the emerging live streaming industry has provided a novel context for exploring interactive vicarious learning experiences (Weibel et al., 2008; He et al.
Additionally, applications of vicarious goal theory and comparative advertising highlight how vicarious learning influences consumers in marketing contexts (Lockwood & Kunda, 1997; Kãrkkăinen & Vincent- Lanchor, 2010). Overall, while originally situated in education, vicarious learning has emerged as a critical area of study for skills acquisition across domains involving complex, social and experiential forms of learning (Bandura & Walters, 1963; Greve & Seijts, 2006). In the context of live streaming, vicarious learning refers to learning that occurs 6 through observation of live streamers' behaviors and their outcomes, rather than through direct experience.