Abstract
Short video advertisements are a novel and influential medium for promoting furniture products, but their effects on consumers’ purchase intentions remain underexplored. This study applies the extended stimulus-organism-response (SOR) framework, a psychological theory that elucidates how stimuli (short video ads), organisms (consumers), and responses (purchase intentions) are interrelated. This study quantitatively examines these relationships using structural equation modeling (SEM). The results reveal that the Flow experience and Telepresence experience significantly affect purchase intentions, indicating that consumers who experience high levels of engagement and immersion while viewing short furniture-related video ads are more likely to exhibit buying behavior. This study also identifies three critical antecedents of the Telepresence experience: social influence, perceived entertainment value, and perceived interactivity. These factors may enhance the effectiveness of short-form video advertising by increasing consumer interaction and engagement. Moreover, convenience conditions, perceived entertainment value, and media richness significantly influence consumers’ flow experience. This suggests that these factors should be considered when designing short video advertisements to optimize consumers’ flow experience and thus increase purchase intentions. This study provides empirical evidence for the SOR framework, investigates the impact of short video advertisements on furniture consumers’ purchase intention, and offers practical implications and recommendations for marketing practitioners.
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Consumer Behavior Based on the SOR Model: How Do Short Video Advertisements Affect Furniture Consumers’ Purchase Intentions?
Shulan Yu,* Hongli Zhang, Qun Zheng, Dongdong Chu, Tianyue Chen, and Xinran Chen
Short video advertisements are a novel and influential medium for promoting furniture products, but their effects on consumers’ purchase intentions remain underexplored. This study applies the extended stimulus-organism-response (SOR) framework, a psychological theory that elucidates how stimuli (short video ads), organisms (consumers), and responses (purchase intentions) are interrelated. This study quantitatively examines these relationships using structural equation modeling (SEM). The results reveal that the Flow experience and Telepresence experience significantly affect purchase intentions, indicating that consumers who experience high levels of engagement and immersion while viewing short furniture-related video ads are more likely to exhibit buying behavior. This study also identifies three critical antecedents of the Telepresence experience: social influence, perceived entertainment value, and perceived interactivity. These factors may enhance the effectiveness of short-form video advertising by increasing consumer interaction and engagement. Moreover, convenience conditions, perceived entertainment value, and media richness significantly influence consumers’ flow experience. This suggests that these factors should be considered when designing short video advertisements to optimize consumers’ flow experience and thus increase purchase intentions. This study provides empirical evidence for the SOR framework, investigates the impact of short video advertisements on furniture consumers’ purchase intention, and offers practical implications and recommendations for marketing practitioners.
DOI: 10.15376/biores.19.2.2639-2659
Keywords: Furniture; Short video; Advertising; Consumer behavior; SOR model; UTAUT model; Flow experience; Structural equation modeling; Consumption behavior
Contact information: College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China; *Corresponding author: yusl@njfu.edu.cn
GRAPHICAL ABSTRACT
INTRODUCTION
Short-form video platforms, a relatively new phenomenon, have seen a rapid increase in global users over the past 15 years. This trend has ushered in innovative ways for marketers to engage with consumers. These platforms are ripe with growth potential, representing a novel advertising approach in the mobile internet era. Their development emphasizes personalization, differentiation, and verticalization, enhancing the precision of information delivery to consumers (Yang et al. 2019). These platforms equip vendors to accurately convey messages to a targeted consumer group, facilitating a more transparent comprehension of consumer tastes, choices, and preferences. The extensive reach of short video advertisements also allows marketers to connect with a larger pool of potential customers. Consumers’ information acquisition has transitioned from passive reception to active search in the digital age. External information stimuli largely influence consumers’ shopping decisions in the online milieu. Consequently, short videos have emerged as a potent marketing tool in an era of fragmented time (Cheng et al. 2007).
With its vast market size and prospects, the furniture industry plays a pivotal role in international trade (Miller et al. 1998). The entire industry is progressing towards industrialization. For instance, China’s furniture production value escalated from RMB 140 billion in 2001 to RMB 11.3 trillion in 2012, contributing to 2% of the national GDP (RMB 519,322 billion in 2012). This accounted for a quarter of the world’s furniture output (Xiong et al. 2017). During the COVID-19 pandemic, there was a noticeable increase in online furniture purchases, propelled by short-form video advertisements. This trend underscores the growing influence of digital marketing strategies in shaping consumer behavior across various industries (Koo and Youn 2021).
Numerous studies have delved into the impact of short video ads on consumption intentions. For instance, some researchers have explored the mechanism of how fast video ads influence young people’s consumption behavior. They employed the stimulus-organism-response (SOR) theory and established a theoretical framework encompassing fashion, social aspects, entertainment, personalization, branding, psychological needs, satisfaction, and consumption behavior (Tian et al. 2022). Moreover, other studies have concentrated on specific characteristics of short video ads (such as visibility, interactivity, and authenticity) and how these traits influence purchase intentions through consumers’ perceived value and trust (Song et al. 2022). Despite the significance of the furniture industry in the consumer goods market, there is a relative dearth of studies investigating the factors influencing furniture purchase intention via short video advertisements. This study aims to fill this gap by focusing on furniture consumer groups.
The theoretical basis of this study is the SOR theory, which is the Stimulus-Organism-Response (SOR) theory proposed by Mehrabian and Russell (1974). The SOR theory emphasizes the critical role of internal psychological factors in behavior. The thesis argues that stimuli affect individuals’ responses and internal psychological states, which further affect their responses. Therefore, the SOR theory indicates that individuals’ behavior results from complex interactions between stimuli, internal psychological states, and responses. Compared with its predecessor, the “Stimulus-Response” theory (SR), the SOR theory provides a more comprehensive explanation of behavior because it considers the internal psychological processes that support behavior (Thorndike 1898). In addition, the SOR theory focuses more on the analysis and explanation of the internal psychological activity process of the organism, systematically clarifies which psychological factors play a role in the generation of individual behavior, and effectively clarifies the influence mechanism between stimuli and individual behavioral intentions (Mehrabian and Russell 1974). The SOR model is widely used in consumer behavior research. It helps in the understanding of how external stimuli affect individuals’ internal responses, including emotions and cognition, and further affect their purchase intentions (Kim and Lennon 2013).
In this study, the authors amalgamated influential factors on short video advertisements’ impact on purchase intention through a literature review and examined the direct or indirect relationships between these factors. To study furniture consumption intention, the authors integrated and expanded the abovementioned factors to construct a more comprehensive and predictive framework. It was hypothesized that while watching short video ads, consumers’ purchase intentions are influenced by the Unified Theory of Acceptance and Use of Technology (performance expectations, effort expectations, social influences, facilitating conditions), short video factors (perceived interactivity, perceived entertainment, and content resource factors). Simultaneously, consumers’ low experience and telepresence experience while watching short video advertisements mediate the effect on furniture purchase intention.
Data were gathered on basic information about furniture consumers, their viewing experience, and the impact of technology and the content of short videos on their willingness to purchase home furnishings. These data were subsequently analyzed and tabulated. Structural Equation Modeling (SEM) was used to construct, estimate, and test causal models. It considers both manifest and latent variables and is used to analyze path relationships between complex variables. Many empirical studies have employed SEM as a data analysis technique (Li 1975; Smith and Naylor 1987; Landis et al. 2000; Cui et al. 2022; Liu and Zheng 2022). In this study, SEM was used to test and validate the proposed model.
The subsequent sections of this paper will elaborate on the literature review, research model and hypotheses, research methodology, analyzed results, and findings.
LITERATURE REVIEW
Short Video Advertising Perception
Advertising is an activity that disseminates information to elicit stimuli through various advertising attributes such as credibility, entertainment, information, information relevance, and excitement (Ge et al. 2021). This process shapes positive consumer perceptions of a product or brand. Effectively managing the triggering of these stimuli can foster positive product perceptions and consequently influence positive purchase intentions.
Perceived entertainment refers to the degree of pleasure, enjoyment, and significance users experience when utilizing a specific system or platform. It plays a crucial role in influencing consumer acceptance of short-form video advertising. In short video research, perceived entertainment can denote users’ subjective pleasure from watching or creating short videos. This impacts user satisfaction, engagement, loyalty, and purchase intention (Balog and Pribeanu 2010; McMillan and Hwang 2002). Perceived interactivity, conversely, is a psychological state that users experience when interacting with media content, such as short videos. It reflects whether users feel engaged in a simulated human-computer interaction (Chu and Kim 2017; Sally and Jang-Sun 2002). Perceived entertainment and perceived interactivity are fundamental characteristics of short video advertisements (Zhao and Wang 2020).
The Media Richness Theory, initially proposed by Daft and Lengel (1986), refers to how users comprehend short video advertisement messages within a specific timeframe following their dissemination and processing via media. Short video advertisements with high media richness can effectively present product information through diverse content and expressions, facilitating understanding among individuals of varying educational backgrounds, ages, social classes, and genders. The media richness of short video advertisements significantly influences users’ browsing behavior and willingness to view short videos. In this study, the unique characteristics of short videos was considered, and the Media Richness Theory was broken down into three dimensions: information content richness, information expression richness, and information quality richness (Burnsed and Hodges 2014). Information content richness pertains to the comprehensiveness and exhaustiveness of the information on home furnishings in short videos. Information expression richness involves the variety of ways the short video presents home furnishings and allows users to express themselves through text, images, emoticons, audio, and video. Information quality richness evaluates whether the quality of the information provided by the short video meets consumers’ expectations and whether it allows consumers to perceive the quality of the product and trust the content of the short video ads.
UTAUT
The Unified Theory of Acceptance and Use of Technology (UTAUT) model, proposed by Venkatesh et al. (2003), is a theoretical framework used to explain individual adoption behavior towards technology (Venkatesh and Davis 2000). Past research has demonstrated that the UTAUT model can be applied to study consumer purchase intentions (Chen et al. 2021). The UTAUT model explains the adoption of new technologies by examining social influence and cognitive processes. Social influence pertains to whether an individual’s surrounding people believe they should use the new product, technology, or feature (Venkatesh et al. 2003).
Performance Expectation (PE) is the consumer’s anticipation of the effects and benefits of purchasing furniture as perceived through advertising (Sair and Danish 2018). It can be characterized by factors, such as features, content, and services, on short-form video platforms (Khatimah and Halim 2014). For instance, consumers may be influenced by the quality of products, prices, and after-sale guarantees displayed in short videos, which may enhance their willingness to purchase household products (Onaolapo and Oyewole 2018).
Effort Expectancy (EE) refers to consumers’ expectations about the ease and convenience of purchasing furniture using short video platforms (Onaolapo and Oyewole 2018; Sair and Danish 2018). It can be characterized by interface, operation, and interaction on short video platforms (Hidayatullah et al. 2020). For example, consumers may be influenced by popular trends, brands, celebrity endorsements, or user reviews shown in short videos, which may increase their willingness to purchase furniture.
Social Influence (SI) refers to consumers’ concern about the perceptions and behaviors of others and how they adjust their purchasing decisions based on those perceptions and behaviors (Lin et al. 2022). It can be demonstrated through fashion, sociability, and trust on short-form video platforms (Tian et al. 2022). For example, consumers may be influenced by trends, brands, celebrity endorsements, or user reviews displayed in short videos, which may increase their willingness to purchase household products (Sriram et al. 2021).
Facilitating Conditions (FC) are consumers’ expectations of external support and assistance when purchasing furniture products (Ferreira et al. 2023; Lin et al. 2022). The FC can be characterized by technological, policy, and social factors on short-form video platforms. For instance, consumers may be influenced by product reviews, returns, and customer service shown in short videos, which may increase their willingness to purchase home furnishings (Tian et al. 2022).
Telepresence and Flow Experience
Telepresence, a state of mind that gives users the feeling of being in another place, plays a significant role in e-commerce and short video advertisements (Draper et al. 1998). It can influence users’ attitudes towards websites and products and their purchase intentions. Telepresence has been shown to have a positive predictive effect on consumers’ purchase intention, with the flow experience mediating the effect of telepresence on purchase intention (Zhu et al. 2022). In short-form video advertising, telepresence refers to the authenticity and immersion experienced in an online shopping environment (Zhu et al. 2022). It positively correlates with consumer autonomy and stickiness, thereby increasing consumers’ purchase motivation and loyalty in the online shopping marketplace (Gao et al. 2018).
The study also explores how individuals achieve an optimal mental state, known as a flow state, while participating in various activities (Csikszentmihalyi 1988). This state is characterized by high concentration, enjoyment, and creativity. Previous research has demonstrated a significant, influential relationship between the flow experience and online purchase intentions (Huang 2012). The stronger the flow experience, the higher the likelihood of sustained intention, purchase intention, and impulse purchase.
In conclusion, flow experience and telepresence are crucial in marketing as they can positively influence consumer attitudes and behavioral intentions in online marketing.
Furniture Consumption Intention
According to Fishbein and Ajzen’s (1977) Theory of Reasoned Action (TRA), consumer behavior is largely determined by their intentions. The furniture industry, a significant consumer goods market, has seen the increasing importance of online home sales platforms with the rapid advancement of smart manufacturing technology and e-commerce (Xiong et al. 2018; Rangaswamy et al. 2022). To maintain a competitive edge in the marketplace and cater to consumer demand for various types of furniture, understanding consumer needs and consumption influences has become particularly crucial (Burnsed and Hodges 2014). Various studies have confirmed that consumers’ attitudes towards short video advertisements impact their purchase intentions (Yang et al. 2017; Sheng et al. 2022; Dou and Zhang 2023). Researchers have examined the diverse factors that consumers consider when purchasing furniture, including product type, price, brand, quality, and features (Burnsed and Hodges 2014). Xu et al. (2020) found that consumers were more likely to have positive attitudes towards purchasing furniture if they had a positive experience in the past when purchasing furniture products through short-form video advertisements. Therefore, this study will consider consumers’ willingness to purchase furniture.
Hypothesis Formation and Research Modeling
This paper expands the SOR framework based on the UTAUT model, short video feature variables, flow theory, and immersion theory to construct a research model of furniture purchase intention.
Structural equation modeling is used to verify the effects of Consumption Intention, Effort Expectancy, Facilitating Conditions, Flow Experience, Media Richness Theory, Performance Expectancy, Perceived Enjoyment, Perceived Interactivity, Social Influence and Telepresence on consumers’ willingness to purchase furniture. The research model is depicted in Fig. 1. The SOR framework considers the various influences of short video advertisements as stimuli (S), which affect the internal states of individual organisms (O) and thus drive their behavioral responses (R) (Song et al. 2022). Previous research indicates that immersion experience and flow experience significantly affect human behavior, with flow experience mediating between immersion experience and user behavior (Wang et al. 2022). When individuals are in telepresence and flow experiences, they typically concentrate all their attention on short video advertisements. In a shopping context, this implies that consumers may be more focused on browsing and evaluating furniture products, making them less susceptible to other distractions. This aids them in understanding and considering purchase options more thoroughly, thereby increasing the likelihood of a purchase. Simultaneously, it also enhances the interaction and connection between consumers and furniture products.
Fig. 1. Research framework
Therefore, this paper proposes the following hypotheses to explore the relationship between telepresence and flow experiences on furniture purchase intentions:
H1a: Telepresence experience positively influences the willingness to purchase furniture.
H1b: Telepresence experience mediates the causal relationship between flow experience and purchase intention.
H2: Flow experience positively influences the willingness to purchase furniture.
This study posits that the unique characteristics of short video advertisements must be considered. Short video advertising, an emerging form of advertising, differs from traditional methods. These ads are delivered to users through images, text, videos, and interactive elements on short video platforms. Three dimensions of perceived factors in short video advertisements have been summarized from past research to investigate their impact on purchase intention. Perceived entertainment, a key psychological factor, assesses the degree of enjoyment an individual derives from ad content (Khatimah and Halim 2014; Antoniadis et al. 2019; Chen et al. 2021). If short video ads can elicit pleasure in consumers, then they are more likely to develop a positive attitude toward the ads. This positive attitude could translate into purchase intentions as consumers tend to interact with brands or products, they find enjoyable and interesting (Zhou et al. 2023). The Media Richness Theory emphasizes the information-carrying capacity of different media forms. For short video ads, the combination of visual and auditory elements often makes the ad more engaging and compelling. Perceived interactivity refers to the degree of interaction between consumers and ad content. Short video ads often provide opportunities for viewers to interact with the content, such as clicking links, participating in polls, or sharing ads. This interactivity could increase purchase intention by enhancing consumers’ sense of engagement and motivation.
Therefore, this paper proposes the following hypotheses:
H3a: Perceived entertainment has a positive effect on the flow experience.
H3b: Perceived entertainment has a positive effect on the telepresence experience.
H4a: Media richness theory has a positive effect on the flow experience.
H4b: The theory of media richness has a positive effect on the telepresence experience.
H5a: Perceived interactivity has a positive effect on the flow experience.
H5b: Perceived interactivity has a positive effect on telepresence experience.
This paper argues that for the furniture industry, short video ads are a relatively new form of advertising that needs to be considered in terms of user acceptance of short video ads. The UTAUT model is a widely used model for understanding the acceptance and adoption of information technology, and it can also be used to study other types of advertising and consumer behavior. Many past studies on advertising, willingness, and consumer behavior have used UTAUT-related models such as TAM (the predecessor of the UTAUT model) to conduct research (Chen et al. 2021, Khatimah and Halim 2014). Therefore, this paper cites the measurement indicators in the UTAUT model used as research and proposes the following hypotheses for further research:
H6a: Facilitation positively affects the flow experience.
H6b: Facilitation positively affects the immersion experience.
H7a: Social influence positively affects the flow experience.
H7b: Social influence positively affects immersion experience.
H8a: Effort expectancy positively affects the flow experience.
H8b: Effort expectancy has a positive effect on immersion experience.
H9a: Performance expectation has a positive effect on the flow experience.
H9b: Performance expectation has a positive effect on immersion experience.
Methods
Data Collection Process
This study collected primary data from China (predominantly developed coastal areas) using a convenience sampling technique. The sample size was determined based on the principle that the sample size should be 5 to 10 times the number of questionnaire items, with a minimum sample size of 200 (Boomsma 1987). A total of 669 questionnaires were collected, with 504 valid for SEM analysis.
Data was collected online using “Question Star” software and through online questionnaire surveys distributed by furniture companies. Additionally, data were obtained offline by distributing keychains and masks at subway stations. To ensure data authenticity, each respondent’s IP address and location information were recorded, with only one questionnaire allowed per IP address. No personal information was collected, with the goal of maintaining confidentiality and anonymity.
Before respondents filled out the questionnaire, they were informed about the study’s purpose, and the data collection period spanned from March 1 to April 1, 2022. Respondents were informed about their option to decline participation.
Out of the 717 questionnaires submitted, 504 were considered valid. The respondents comprised 205 males (40.7%) and 299 females (59.3%). Indeed, the largest age group among the respondents, accounting for 76.6% of the total, was between 18 and 45 years old. This aligns with the fact that individuals within this age range constitute the primary audience for short videos (Guo and Deng 2022).
The education level and monthly income of the respondents were relatively evenly distributed. It is worth noting that 75.3% of respondents have watched furniture video clip advertisements and made a purchase after watching the advertisement. Further, this item was used as an exclusion. Specific sample information can be found in Table 1.
Table 1. Demographics of Respondents (n = 504)
Measurement Process
To study the influencing factors of short video advertisements on the consumption intention of furniture consumers, this paper conducted a questionnaire survey for the population of furniture consumers and designed a questionnaire based on previous studies. In addition, small-scale interviews were conducted with short video ad creators and furniture industry professionals to better design the questionnaire.
To ensure the quality of the questionnaire, a small-scale pre-survey was conducted among 40 college students who frequently browse short videos, and the reliability and validity of the questionnaire were analyzed. The opinions of five industry professionals were also incorporated to modify some measurement items involved in the questionnaire to finalize the formal questionnaire.
The questionnaire was divided into two parts. The first part aimed to collect basic information about the users, including gender, age, monthly income, short video viewing habits, and household goods consumption. The second part was designed to measure influencing factors with indicators taken from previous studies. The questionnaire used a 5-point Likert scale, with values ranging from “strongly disagree” to “strongly agree.”
Table 2. Reliability and Validity Analysis Results of the Questionnaire
Reliability tests for questionnaire scales typically include internal consistency coefficients (Cronbach’s α), average variance extraction coefficients (AVE), and composite reliability (CR). As per the data in Table 2, Cronbach’s α values for all of the factors were greater than 0.8. Additionally, the AVE values for each of the measurement item factors were all greater than 0.5, and the composite reliability had CR values greater than 0.7. The Cronbach’s α of the total measurement items was 0.952, which was also greater than 0.8. This data indicates that the measurement items of the questionnaire have high reliability, and the results are reliable and trustworthy.
Table 3. Reliability Analysis Data Table
Validity tests in this study include content validity and structural validity. The research scale was designed through three processes: literature research, expert interviews, and pre-survey. The items were carefully refined and revised, resulting in high content validity. From the data in Table 3, the Kaiser-Meyer-Olkin (KMO) value of 0.928 was greater than 0.8, while Bartlett’s sphericity value was statistically significant (p < 0.001). These results indicate that there was a high degree of correlation between the research data, making it suitable for a factor analysis to verify structural validity. In the validated factor analysis (CFA), the factor loadings for each item were greater than 0.7, indicating good validity of the measurement model. Factor loadings represent the degree of association between each item and the latent factor it represents, and factor loadings greater than 0.7 are generally considered high, further confirming the structural validity of the scale.
The normal distribution, or Gaussian distribution, is a continuous probability distribution that describes real-valued random variables. The maximum likelihood method usually requires that the sample data obey a normal distribution. According to the data shown in Table 4, the sample data in this study meets the assumption of a normal distribution as the absolute values of the skewness coefficient and kurtosis coefficient are less than 1.96. Therefore, it is suitable for the structural equation modeling approach.
Discriminant validity is crucial in assessing whether a measurement instrument or construct can distinguish between different dimensions or concepts. In this study, discriminant validity was examined by comparing the square root of the AVE value of the latent variable with the correlation coefficients of other variables (Hair, Jr. et al. 2014). The criterion proposed by Fornell and Larcker (1981) can also be used to test discriminant validity. This criterion requires that each construct’s average variance extracted (AVE) should be greater than the highest squared correlation with any other construct. In other words, the square root of the AVE value should be greater than the maximum value of the correlation coefficient with any other construct. Based on the data shown in Table 5, each latent variable has sufficient discriminant validity as the square root of the AVE value for each construct is greater than the highest correlation coefficient with any other variable.
Table 4. Normal Distribution Test Questionnaire
Table 5. Results of the Discriminant Validity Test
Table 6. Analysis of Model Results
Structural Model
This study utilized Amos 26.0 (IBM, Armonk, NY, USA) for the overall model fit assessment and hypothesis testing. As per the data presented in Table 5, the model’s fit met the established criteria. This suggests that the data collected aligned well with the authors’ constructed model, and the proposed path hypothesis aligns with the actual situation, ensuring the accuracy and validity of the model coefficient results.
The authors evaluated the overall model’s explanatory power and the significance of the relevant hypotheses through path coefficients, C. R. values, and p-values (refer to Table 5 for details). Among these, 11 paths had a critical ratio (C. R.) with an absolute value greater than 1.96 and a significance probability value (p) less than 0.05, leading to the acceptance of these hypotheses. Conversely, six paths had a C. R. absolute value less than 1.96 and a p-value greater than 0.05, indicating that these can be regarded as invalid hypotheses.
Based on these validation results (Table 6), it can be concluded that some of the hypotheses proposed in this study had been successfully validated.
Discussion
The results from this study indicate that immersion and flow experiences significantly impact furniture purchase intentions. Furthermore, factors such as social influence, perceived entertainment, and perceived interactivity of short video advertisements significantly affect the immersion experience. Conversely, convenience, perceived entertainment, and media richness significantly influence users’ flow experience.
These findings align with recent studies. For instance, Wang’s research suggests that a convenient and swift short video ad experience can enhance users’ flow experience, and user-friendly operations can improve users’ flow and immersion (Wang et al. 2022). Short video ads providing convenience features like quick purchase links or one-click ordering may encourage consumers to purchase household products by lowering purchase process barriers.
Social influence significantly impacts short video users’ willingness to share, watch, and create short videos (Zheng 2023). Social support and influence can affect consumers’ emotions and product perceptions, influencing consumption willingness (Dahl 2013). Product endorsements by celebrities or usage by the user’s friends and family can also increase product familiarity and purchase willingness.
The study also reveals that media richness and perceived interactivity significantly influence users’ willingness to use short video applications and the consumption behaviors generated while watching these videos. These findings corroborate previous research conclusions. For example, Xiang and Chae (2022) investigated the effects of five dimensions of perceived interactivity on users’ consumption and usage persistence intention on short video platforms. Studies have shown that the perceived interactivity of short videos may facilitate consumers’ interaction with the product, enhancing their product interest and purchase intention (Li 2019; Xiang and Chae 2022).
Additionally, the perceived entertainment of short videos may attract consumers to watch them and create a desire to purchase during the viewing process (Cheng et al. 2022; Lin et al. 2022). For example, if short videos display household products in a fun or engaging way, consumers may feel that purchasing these products will bring happiness and satisfaction. Sriram et al. (2021) explored the impact of social media advertisements on consumers’ purchase intentions, finding that creative features, engaging details, emotional appeals, and celebrity endorsements all impacted the evaluation of social media advertisements.
These results reveal that immersion and the flow experience directly and significantly influence home consumption intentions. Moreover, data suggest that immersion indirectly affects the flow experience. This relationship between immersion and the flow experience aligns with previous consumer behavior studies (Mohsin et al. 2017; Zheng 2023). The study also found that when short video users experienced a strong telepresence and flow experience, their interest in the home furnishings displayed in the short video increased. Telepresence and flow experiences can also boost users’ trust in home furnishings. When users feel they are in the scene depicted in the short video, they may perceive the information provided as more authentic and reliable. This trust promotes users’ purchase willingness. Ultimately, telepresence and the flow experience can enhance the shopping experience. When users feel immersed while browsing short videos on home furnishings, they may find the shopping process more enjoyable. This reaffirms previous research suggesting that creating telepresence and flow experiences can reduce uncertainty and psychological distance between consumers and merchants, playing a crucial role in shaping consumer behavior and purchase intentions (Wu et al. 2014; Zheng 2023). The flow experience may also positively impact video users’ impulse shopping intentions (Dong et al. 2022).
Practical Implications
This study has multiple practical implications that will help practitioners in the furniture industry formulate their advertising strategies more accurately. First, the results of this study indicate that the five measures significantly influence furniture purchase intention. This finding provides valuable information for advertising marketers in the furniture industry to more effectively tailor the content and format of their ads to the study’s findings, ensuring that the ads excel in social impact, entertainment, and interactivity to better engage potential buyers. Companies can allocate resources in a more targeted manner. They can optimize the ad production process to maximize the effectiveness of their ads. Examples are as follows:
User reviews and sharing: Highlight in advertisements the positive reviews and shared experiences of other consumers with the product. This helps to build a sense of social identity, making it easier for potential purchasers to trust other people’s opinions of the product and, as a result, be more likely to make a purchase.
Creative storyline: Create a compelling storyline and incorporate attractive elements, such as fun, humor, or engaging content, to make the ad more attractive and entertaining. Viewers are more willing to watch and interact with the advertisement.
Interactive elements: Add interactive elements, such as voting, commenting, lucky draw, etc., to encourage viewers to participate in the content of the advertisement actively. This not only increases user participation but also enhances the attractiveness of the advertisement.
Purchase links and coupon codes: Ensure that advertisements contain easy-to-find purchase links or coupon codes so potential purchasers can quickly buy. Providing a convenient way to buy usually improves conversion rates.
Multimedia content: Make full use of various media elements, such as images, video, sound, etc., to increase the diversity of advertising. This can make the advertisement more compelling and provide more information to trigger the interest of potential buyers.
Finally, the results of this study are also important references for other studies in similar industries. Researchers in other fields can draw on the methodology of this study to examine advertising influences in different product or service categories.
Limitations and Future Research Directions
First, it is worth noting that the respondents in this study were mainly from China, yet short-form video advertising has become a global phenomenon. Therefore, future research could consider the impact of different cultural contexts on users, which may require a cross-national multi-sample research project. Second, the field of short-video advertising is in an evolving stage, and it has begun to explore the integration of innovations with technologies such as virtual reality (VR) and augmented reality (AR). Therefore, further in-depth research on this field’s development trends and influencing factors is needed. Third, although this study has considered some influencing factors of short video advertising, there are still some limitations. Future research can further explore the full impact of moderating variables, such as gender, age, geography, color, and personality traits, on the willingness to consume household goods. Fourth, this study used stratified sampling for data collection, which may also impact the generalizability of the findings. Future studies may consider other sampling techniques and increase the sample size to improve the accuracy of the findings.
CONCLUSIONS
- This study reveals that users’ flow and telepresence experiences are significantly influenced by five key factors in short video advertisements: social impact, perceived entertainment, perceived interactivity, convenience, and media richness. These experiences, in turn, substantially affect their willingness to purchase home furnishings.
- The findings underscore the pivotal role of short-form video advertising in stimulating furniture sales and bolstering economic growth.
ACKNOWLEDGMENTS
The authors are grateful for the support of Nanjing Forestry University.
Data Availability Statement
The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.
Conflicts of Interest
The authors declare no conflict of interest.
Author Contributions
Hongli Zhang was the main contributor to this work, with help from the remaining authors. All authors have read and agreed to the published version of the manuscript.
REFERENCES CITED
Antoniadis, I. I., Saprikis, V. S., and Karteraki, E. Ε. (2019). “Consumers’ attitudes towards advertisement in YouTube,” Strategic Innovative Marketing and Tourism: 7th ICSIMAT, Athenian Riviera, Greece, pp. 253-261. DOI: 10.1007/978-3-030-12453-3_29
Balog, A., and Pribeanu, C. (2010). “The role of perceived enjoyment in the students’ acceptance of an augmented reality teaching platform: A structural equation modelling approach,” Studies in Informatics and Control 19(3), 319-330. DOI: 10.24846/v19i3y201011
Boomsma, A. (1987). “The robustness of maximum likelihood estimation in structural equation models,” in: Structural Modeling by Example, P. Cuttance, and R. Ecob (eds.), Cambridge University Press, Cambridge, UK, pp. 160-188. DOI:10.1017/CBO9780511601118.010
Burnsed, K. A, and Hodges, N. J. (2014). “Home furnishings consumption choices: A qualitative analysis,” Qualitative Market Research: An International Journal 17(1), 24-42. DOI: 10.1108/QMR-11-2011-0022
Chen, L., Rashidin, M. S., Song, F., Wang, Y., Javed, S., and Wang, J. (2021). “Determinants of consumer’s purchase intention on fresh e-commerce platform: Perspective of UTAUT model,” Sage Open 11(2), article ID 21582440211027875. DOI: 10.1177/21582440211027875
Cheng, X., Dale, C., and Liu, J. (2007). “Understanding the characteristics of internet short video sharing: YouTube as a case study,” arXiv (preprint), arXiv:0707.3670.
Cheng, Z., Shao, B., and Zhang, Y. (2022). “Effect of product presentation videos on consumers’ purchase intention: The role of perceived diagnosticity, mental imagery, and product rating,” Frontiers in Psychology 13, article ID 812579. DOI: 10.3389/fpsyg.2022.812579
Chu, S.-C., and Kim, Y. (2017). “The influence of perceived interactivity of social media advertising and voluntary self-disclosure on attitudes and intentions to pass-along,” in: Advertising and Branding: Concepts, Methodologies, Tools, and Applications, IGI Global, PA, USA, pp. 1388-1405. DOI: 10.4018/978-1-5225-1793-1.ch064
Csikszentmihalyi, M. (1988). “The flow experience and its significance for human psychology,” Optimal Experience: Psychological Studies of Flow in Consciousness 2, 15-35. DOI: 10.1017/CBO9780511621956.002
Cui, Y., Zhu, J., and Liu, Y. (2022). “Exploring the social and systemic influencing factors of mobile short video applications on the consumer urge to buy impulsively,” Journal of Global Information Management (JGIM) 30(1), article ID 314226. DOI: 10.4018/jgim.314226
Daft, R. L., and Lengel, R. H. (1986). “Organizational information requirements, media richness and structural design,” Management Science 32(5), 554-571. DOI: 10.1287/mnsc.32.5.554
Dahl, D. (2013).”Social influence and consumer behavior,” Journal of Consumer Research 40(2), iii-v. DOI: 10.1086/670170
Dong, W.-W., Wang, Y.-Q., and Qin, J. (2022). “An empirical study on impulse consumption intention of livestreaming e-commerce: The mediating effect of flow experience and the moderating effect of time pressure,” Frontiers in Psychology 13, article ID 1019024. DOI: 10.3389/fpsyg.2022.1019024
Dou, Z., and Zhang, Y. (2023). “The influence of short video advertisements on consumers’ purchase intention,” Journal of Education, Humanities and Social Sciences 13, 269-274. DOI: 10.54097/ehss.v13i.7912
Draper, J. V., Kaber, D. B., and Usher, J. M. (1998). “Telepresence,” Human Factors 40(3), 354-375. DOI: 10.1518/001872098779591386
Ferreira, L., Oliveira, T., and Neves, C. (2023). “Consumer’s intention to use and recommend smart home technologies: The role of environmental awareness,” Energy 263, article ID 125814. DOI: 10.1016/j.energy.2022.125814
Fishbein, M., and Ajzen, I. (1977). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Penn State University Press, PA, USA.
Fornell, C., and Larcker, D. F. (1981). “Evaluating structural equation models with unobservable variables and measurement error,” Journal of Marketing Research 18(1), 39-50. DOI: 10.1177/002224378101800104
Gao, W., Liu, Y., Liu, Z., and Li, J. (2018). “How does presence influence purchase intention in online shopping markets? An explanation based on self-determination theory,” Behaviour and Information Technology 37(8), 786-799. DOI: 10.1080/0144929X.2018.1484514
Ge, J., Sui, Y., Zhou, X., and Li, G. (2021). “Effect of short video ads on sales through social media: The role of advertisement content generators,” International Journal of Advertising 40(6), 870-896. DOI: 10.1080/02650487.2020.1848986
Guo, X., and Deng, F. (2022). “Short video audience identification data recommended by multiple neural network algorithms,” in: The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy: SPIoT-2021 Volume 1, Gyeonggi-do, Korea, pp. 1042-1050. DOI: 10.1007/978-3-030-89508-2_135
Hair, Jr, J. F., Sarstedt, M., Hopkins, L., and Kuppelwieser, V. G. (2014). “Partial least squares structural equation modeling (PLS-SEM), an emerging tool in business research,” European Business Review 26(2), 106-121. DOI: 10.1108/EBR-10-2013-0128
Hidayatullah, S., Ardianto, Y. T., Octvie H. A., Rachmawati, I. K., and Alvianna, S. (2020). “Performance expectancy, effort expectancy, social influence on behavioral to use through behavioral intention in using mobile banking in Malang,” in: 5th ICGSS International Conference of Graduate School on Sustainability, Universitas Merdeka, Malang, Indonesia, pp. 272-276.
Huang, E. (2012). “Online experiences and virtual goods purchase intention,” Internet Research 22(3), 252-274. DOI: 10.1108/10662241211235644
Khatimah, H., and Halim, F. (2014). “Consumers’ intention to use e-money in Indonesia based on Unified Theory of Acceptance and Use of Technology (UTAUT),” American-Eurasian Journal of Sustainable Agriculture 8(12), 34-40.
Kim, J., and Lennon, S. J. (2013). “Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention: Based on the stimulus‐organism‐response model,” Journal of Research in Interactive Marketing 7(1), 33-56. DOI: 10.1108/17505931311316734
Koo, Y.-S., and Youn, C. (2021). “Analysis of home furnishing trends caused by the COVID-19 pandemic,” International Journal of Costume and Fashion 21(2), 80-90. DOI: 10.7233/ijcf.2021.21.2.080
Landis, R. S., Beal, D. J., and Tesluk, P. E. (2000). “A comparison of approaches to forming composite measures in structural equation models,” Organizational Research Methods 3(2), 186-207. DOI: 10.1177/109442810032003
Li, C. C. (1975). Path Analysis – A Primer, The Boxwood Press, New York, NY, USA.
Li, M.-H. (2019). “Exploring short video application users’ visit intention: Applying the stimulus-organism-response model,” Asian Social Science 15(12), 8-19. DOI: 10.5539/ass.v15n12p8
Lin, B., Chen, Y., and Zhang, L. (2022). “Research on the factors influencing the re-purchase intention on short video platforms: A case of China,” PloS One 17(3), article ID e0265090. DOI: 10.1371/journal.pone.0265090
Liu, Y., and Zheng, S. (2022). “Factors affecting consumers’ purchase intention for agriculture products omni-channel,” Frontiers in Psychology 13, article ID 948982. DOI: 10.3389/fpsyg.2022.948982
McMillan, S. J., and Hwang, J. -S. (2002). “Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity,” Journal of Advertising 31(3), 29-42.
Mehrabian, A., and Russell, J. A. (1974). An Approach to Environmental Psychology, The MIT Press, Cambridge, MA, USA.
Miller, N. J., Schofield-Tomschin, S., and Kim, S. (1998). “Consumers’ apparel and home furnishings inshopping behavior in rural communities,” Clothing and Textiles Research Journal 16(4), 157-166. DOI: 10.1177/0887302X9801600402
Mohsin, A., Lengler, J., and Chaiya, P. (2017). “Does travel interest mediate between motives and intention to travel? A case of young Asian travelers,” Journal of Hospitality and Tourism Management 31, 36-44. DOI: 10.1016/j.jhtm.2016.08.003
Onaolapo, S., and Oyewole, O. (2018). “Performance expectancy, effort expectancy, and facilitating conditions as factors influencing smart phones use for mobile learning by postgraduate students of the University of Ibadan, Nigeria,” Interdisciplinary Journal of e-Skills and Lifelong Learning 14(1), 95-115. DOI: 10.28945/4085
Rangaswamy, E., Nawaz, N., and Changzhuang, Z. (2022). “The impact of digital technology on changing consumer behaviours with special reference to the home furnishing sector in Singapore,” Humanities and Social Sciences Communications 9(1), 1-10. DOI: 10.1057/s41599-022-01102-x
Sair, S. A., and Danish, R. Q. (2018). “Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers,” Pakistan Journal of Commerce and Social Sciences (PJCSS) 12(2), 501-520.
Sally, J. M., and Jang-Sun, H. (2002). “Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity,” Journal of Advertising 31(3), 29-42. DOI: 10.1080/00913367.2002.10673674
Sheng, X., Zeng, Z., Zhang, W., and Hu, Y. (2022). “Vlogger’s persuasive strategy and consumers’ purchase intention: The dual mediating role of para-social interactions and perceived value,” Frontiers in Psychology 13, article ID 1080507. DOI: 10.3389/fpsyg.2022.1080507
Smith, R. L., and Naylor, J. (1987). “A comparison of maximum likelihood and Bayesian estimators for the three-parameter Weibull distribution,” Journal of the Royal Statistical Society Series C: Applied Statistics 36(3), 358-369. DOI: 10.2307/2347795
Song, Z., Liu, C., and Shi, R. (2022). “How do fresh live broadcast impact consumers’ purchase intention? Based on the SOR theory,” Sustainability 14(21), article ID 14382. DOI: 10.3390/su142114382
Sriram, K. V., Namitha, K. P., and Kamath, G. B. (2021). “Social media advertisements and their influence on consumer purchase intention,” Cogent Business and Management 8(1), article ID 2000697. DOI: 10.1080/23311975.2021.2000697
Thorndike, E. L. (1898). “Animal intelligence,” Nature 58(1504), 390-390. DOI: 10.1038/058390b0
Tian, K., Xuan, W., Hao, L., Wei, W., Li, D., and Zhu, L. (2022). “Exploring youth consumer behavior in the context of mobile short video advertising using an extended stimulus-organization-response model,” Frontiers in Psychology 13, article ID 933542. DOI: 10.3389/fpsyg.2022.933542
Venkatesh, V., and Davis, F. D. (2000). “A theoretical extension of the technology acceptance model: Four longitudinal field studies,” Management Science 46(2), 186-204. DOI: 10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). “User acceptance of information technology: Toward a unified view,” MIS Quarterly 2003, 425-478. DOI: 10.2307/30036540
Wang, Hailiang,et al. (2020). “Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF,” International Journal of Medical Informatics 139, article 104156. DOI: 10.1016/j.ijmedinf.2020.104156
Wang, X., Yu, Y., Zhu, Z., and Zheng, J. (2022). “Visiting intentions toward theme parks: Do short video content and tourists’ perceived playfulness on TikTok matter?,” Sustainability 14(19), article ID 12206. DOI: 10.3390/su141912206
Wu, C. H.-J., Li, H.-J., and Chiu, C.-W. (2014). “Understanding consumer responses to travel websites from online shopping value and flow experience perspectives,” Tourism Economics 20(5), 1087-1103. DOI: 10.5367/te.2013.0326
Xiang, Y., and Chae, S. W. (2022). “Influence of perceived interactivity on continuous use intentions on the Danmaku video sharing platform: Belongingness perspective,” International Journal of Human-Computer Interaction 38(6), 573-593. DOI: 10.1080/10447318.2021.1952803
Xiong, X.-Q., Guo, W.-J., Fang, L., Zhang, M., Wu, Z.-H., Lu, R., and Miyakoshi, T. (2017). “Current state and development trend of Chinese furniture industry,” Journal of Wood Science 63, 433-444. DOI: 10.1007/s10086-017-1643-2
Xiong, X.-Q., Yuan, Y.-Y., Fang, L., Liu, H., and Wu, Z.-H. (2018). “Status and development trends of intelligent manufacturing in China’s furnishings industry,” Forest Products Journal 68(3), 328-336.
Xu, X., Hua, Y., Wang, S., and Xu, G. (2020). “Determinants of consumer’s intention to purchase authentic green furniture.” Resources, Conservation and Recycling 156, article ID 104721. DOI: 10.1016/j.resconrec.2020.104721
Yang, K.-C., Huang, C.-H., Yang, C., and Yang, S. Y. (2017). “Consumer attitudes toward online video advertisement: YouTube as a platform,” Kybernetes 46(5), 840-853. DOI: 10.1108/K-03-2016-0038
Yang, S., Zhao, Y., and Ma, Y. (2019). “Analysis of the reasons and development of short video application – Taking Tik Tok as an example,” in: Proceedings of the 2019 9th International Conference on Information and Social Science (ICISS 2019), Manila, Philippines, pp. 12-14.
Zhao, J., and Wang, J. (2020). “Health advertising on short-video social media: A study on user attitudes based on the extended technology acceptance model,” International Journal of Environmental Research and Public Health 17(5), article 1501. DOI: 10.3390/ijerph17051501
Zheng, C. (2023). “Research on the flow experience and social influences of users of short online videos: A case study of DouYin,” Scientific Reports 13(1), article 3312. DOI: 10.1038/s41598-023-30525-y
Zhou, C.-M., Wang, Q.-Y., Kaner, J., and Lv, Y.-X. (2023). “Wooden door preferences based on lifestyle theory and consumer behaviour theory,” BioResources 18(1),1616-1636. DOI: 10.15376/biores.18.1.1616-1636
Zhu, G., Jiang, S., and Li, K. (2022). “A moderated mediation mechanism underlying the impact of website telepresence on purchase intention – Evidence from Chinese female college student customers,” Frontiers in Psychology 13, 902414-902414. DOI: 10.3389/fpsyg.2022.902414
Article submitted: November 20, 2023; Peer review completed: February 11, 2024; Revised version received and accepted: February 22, 2024; Published: March 6, 2024.
DOI: 10.15376/biores.19.2.2639-2659