A study on the impact of perceived financial constraints on Chinese consumer preferences for livestreaming scenarios

doi:10.21203/rs.3.rs-4712811/v1

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A study on the impact of perceived financial constraints on Chinese consumer preferences for livestreaming scenarios

https://doi.org/10.21203/rs.3.rs-4712811/v1

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In recent years, China’s economic growth rate has slowed down, the consumption level has increased, the financial pressures on people have risen, and more and more consumers feel financial constraints. Through two experiments, this study explored the impact of the sense of financial constraint on consumers’ livestreaming scene preferences and the dual roles of mediation and moderation of their flow experience. Experiment 1 used a one-way completely randomized design to measure the sense of financial constraint and initially verified that consumers in a state of financial constraint reduce their browsing preferences for artificially constructed types of livestreaming scenes. Experiment 2 used a two-by-two completely randomized design to confirm that a sense of financial constraint reduces consumers’ browsing preference for artificially constructed livestreaming scenes and reduces the mediating and moderating roles of flow experience on the sense of financial constraint and consumers’ browsing preference for artificially constructed scenes. This study not only enriches the related research on the sense of financial constraint in the field of consumer psychology but also complements and improves the research on e-commerce livestreaming and provides certain reference suggestions for e-commerce enterprises’ scene selection and consumers’ pursuit of individual happiness.

Biological sciences/Psychology

Biological sciences/Psychology/Human behaviour

sense of financial constraint

livestreaming scenarios

browsing preferences

flow experience

According to data from the China Internet Network Information Center (CNNIC), the e-commerce industry has been highly competitive in recent years. As of December 2023, China’s online shopping user scale reached 915 million people, accounting for 83.8% of the overall number of Internet users. The incremental user scale has reached the upper limit. Converting the stock market into an incremental market is a constant challenge that live e-commerce enterprises now face¹. Live e-commerce has been booming since 2016, the live e-commerce market size reached CNY(Chinese Yuan) 4.92 trillion in 2023, and the competition for user traffic in the field of live e-commerce has become increasingly heated. Relevant data show that live order users account for 66.2% of the users watching live broadcasts, and the role of consumer behavior for merchants and platforms is becoming more and more significant. Chen Rui et al.² stated that live broadcast e-commerce can generate large-scale traffic by leveraging the richness of shopping sites, a large number of merchants, and a stable flow of customers. Therefore, tapping users’ potential demand, creating demand, and promoting consumption have become topics of the times in the e-commerce industry, and the importance of indicators such as user viewing hours and user stickiness has increased. Against the background of the large volume of the live e-commerce market, the overall scale of live e-commerce users still has ample room for growth. The market is expected to further explore the value of traffic by using live broadcasting, advertising, and consumer psychology as the main means to release more revenue space and profitability.

At the same time, in the context of economic development and consumer diversification, the financial pressures on people have also risen, and more and more middle- and high-income people also feel financial constraints. A significant portion of Americans who appear to be “middle class” also consider themselves financially vulnerable and are pessimistic about their ability to earn USD 2000 per month³. Thus, the sense of financial constraint is a widespread psychological feeling. The feeling of financial constraint refers to an individual’s perception that his or her financial situation limits his or her desire to spend money⁴.

Livestreaming e-commerce has changed the retail business environment and established major sales channels by showing products and interacting with customers in real time through live video streaming⁵. As a component of today’s Internet business practices, live e-commerce is a natural fit with today’s situation. Live e-commerce connects merchants, products, anchors, and consumers and constructs an interactive space for users with different needs. Through the construction of the live setting, consumers perceive the anchor and the products and thus experience a more intuitive, three-dimensional, and rich knowledge of the goods. Tong J. et al.⁶ found through empirical analysis that live e-commerce’s vividness, interactivity, and authenticity enhance the consumer’s willingness to buy by influencing the consumer’s sense of immediacy and trust. Based on the rapid development of live e-commerce and the important influence of the sense of financial constraints, this paper will explore the influence of the sense of financial constraints on consumers’ livestreaming preferences.

Reviewing the existing literature, we can observe that current scholarly research on the sense of financial constraints and the impact of the sense of financial constraints on consumer behavior is on the low side, and research on e-commerce livestreaming scenes or settings is also relatively scarce. Articles related to the sense of financial constraints mainly analyze and verify the assumptions from the perspectives of formative causes and action mechanisms and, ultimately, explore how individuals cope with them in order to enhance their sense of well-being, with the most notable studies focusing on resource scarcity. The research on live e-commerce shows rapid growth with the booming development of the e-commerce industry, but in this aspect of live e-commerce, scholars at home and abroad mostly carry out research from the perspectives of scene theory, communication mode, marketing strategy, etc., which is yet to be enriched by the research on the impact of the live setting on consumer behavior. Therefore, this study enriches the related research on the sense of financial constraints in the field of consumer psychology and proves that the dual roles of mediation and moderation played by flow experience impact the sense of financial constraints on consumer behavior. At the same time, this study divides e-commerce livestreaming scenes into artificially constructed livestreaming scenes and origin-source livestreaming scenes, which complements and improves the research on e-commerce livestreaming and provides certain reference suggestions for e-commerce enterprises’ scene selection and consumers’ pursuit of individual happiness.

Sense of financial constraint

The sense of financial constraint refers to an individual’s feeling that the current financial situation limits his or her desired consumption⁴. As a subjective psychological state, the sense of financial constraint does not necessarily mean that the individual is financially constrained. When an individual’s desire to consume exceeds his or her financial ability, then he or she will have a sense of financial constraint.

Currently, domestic research on the sense of financial constraints is in its infancy, with few studies investigating financial constraints and its impact on consumer behavior. Foreign research on how financial constraints affect consumer behavior generally include four aspects: resource scarcity, choice limitation, social comparison, and environmental uncertainty⁷. Resource scarcity focuses on money, choice constraints focus on products and services, social comparison focuses on how to establish connections with others, and environmental uncertainty focuses on the consumption environment. Resource scarcity makes consumers susceptible to being captured by scarcity cues and sacrificing attention to other cues in the process of identifying decision targets⁸ which, in turn, produces a double-edged sword effect. An Xianru et al.⁹ explained the double-edged sword effect of consumer behavior from three levels: cognitive, behavioral, and emotional. They argued that resource scarcity does more harm than good to consumers in the long run. These impacts can be explained in detail: as scarcity leads to a shift in consumers’ attention¹⁰ where their attention is drawn to scarce resources, they become more concerned about money and the price of goods and services and, for example, focus more on price concessions before consumption. This state also limits the choice of products and services that consumers want and leads them to accept a smaller range of choices. In addition, the environmental uncertainty triggered by financial constraints leads to a sense of self-insecurity that may increase concerns about the lasting effects of consumption. At the same time, the double-edged sword effect can have an impact on the whole consumption process; for example, focusing on the use of scarce resources due to their scarcity can have actual or potential positive impacts on the consumer, while, on the other hand, it may be easy to ignore other important information or information related to the future, resulting in short-sightedness and other negative consequences.

The concept of the sense of financial constraint originates from the study of resource scarcity in the fields of economics, sociology, psychology, and consumer behavior and has an important impact on consumer behavior. Consumers’ sense of financial constraint mainly comes from the scarcity of monetary resources; for example, the scarcity of money will cause consumers to experience unpleasant emotions¹¹; consumers will use efficiency planning and prioritization planning strategies to cope with the scarcity of resources¹²; consumers will be affected by anxiety, self-efficacy, and their social environment; and this will prevent them from choosing green products¹³. The sense of financial constraints has an important impact on an individual’s cognitive and consumption decisions. Studies have shown that a sense of financial constraint causes consumers to pursue scarce goods¹⁴, reduces consumer diversity of choice¹⁵, cause consumers to focus on a greater range of discounts¹⁶, causes consumers to appreciate information framed in a positive way¹⁷, increases consumer preference for physical consumption¹⁸, reduces consumer happiness from purchases¹⁹, enhances consumer brand extension evaluations²⁰, etc.

E-commerce Livestreaming Scene

Live e-commerce is an e-commerce model that utilizes interactive social media to facilitate online transactions and enhance the online shopping experience of consumers²¹. Domestic live e-commerce can be divided into two main modes. One is the “e-commerce + live” mode, that is, the use of traditional e-commerce platforms for live broadcasting, such as Taobao live and Jingdong live; the other is the “live + e-commerce” mode, that is, when social communication platforms to carry out live broadcasting with consumer goods, such as Tiktok live, RED live, and WeChat Channels live. At present, the development of live e-commerce in China is very mature, and related research can be divided into four aspects: live shopping platforms, products, consumers, and anchors. Jiao Yuanyuan et al.²² showed that the functional convenience and remote perception of e-commerce platforms affect the formation of customer stickiness. Hu and Chaudhry²³ suggested that live e-commerce has the main advantage of realizing scenario-based sales. Zhong Tao²⁴ argued that livestreaming has a rich variety of products and that livestreaming e-commerce is a new way to realize the “unity of product effect”. Cai et al.²⁵ investigated the relationship between hedonic motivation and utilitarian motivation and consumers’ willingness to purchase. Wongkitrungrueng and Assarut²⁶ argued that the symbolic value perceived by consumers in livestreaming directly affects the customer’s engagement behavior. Lixia Lu²⁷ investigated the influence of anchor characteristics on consumer purchase intention in e-commerce live broadcasting platforms based on social presence and flow experience. Zhou Li and Shen Pengyi²⁸ analyzed the behavior of customer participation in e-commerce live broadcasting based on e-commerce live broadcasting platforms and customer operant resources.

Regarding the scene categories of e-commerce livestreaming, scholars have made the following classifications: Yan Daocheng and Li Fei²⁹ classified e-commerce scenes into the restoration of offline store scenes, the fictionalization of social scenes, and the merger of front and backstage landscapes. Wang Jiahang and Zhang Shuainan³⁰ classified e-commerce scenes into the restoration of offline store scenes, the fictionalization of social scenes, and the merger of front and backstage landscapes. The research of Wang Jiahang and Zhang Shuainan³¹ summarized the three frame types of e-commerce live broadcasting scenes as the anchor private scene, shopping proscenium scene, and production traceability scene. Ye Qiaonan³² summarized the scene types as virtual online consumption scene, artificially constructed usage scene, and instant social interaction scene. Based on the above research, this paper categorizes e-commerce livestreaming scenes into artificially constructed live broadcasting scenes and production-source live broadcasting scenes.

Artificially constructed live broadcast scenes refers to a livestreaming space built by means of artificial organization, from the room background, signage, flow charts, lighting, sound effects, and other aspects of artificial design layout such as building a set table, inserting a video, planning the marketing theme, and other ways to sell goods.

Origin-source livestreaming scenes refers to a direct live broadcast at the origin of the product or production site. Live broadcast will appear in the production or selection of the product scene in order to show the origin of the product, growth environment, production process, and other information. This type of live broadcasting room is mostly based on the origin of the source as a selling place, through the strengthening of the attributes of the origin of the goods sold.

In addition, scholars have carried out a great deal of research on user behavior in e-commerce livestreaming scenes. Gong Xiaoxiao et al.³³ analyzed the mechanism of action between ambient cues of livestreaming scene—flow experience—and flow impulse consumption willingness. Chen Yingxin et al³⁴ investigated the interaction mechanism affecting the construction of customers’ sense of presence in live webcast shopping. Jia Yi³⁵ argued that various types of consumption under e-commerce scenario dissemination endow users with increased modes of expression. Xu et al.³⁶ investigated the influence of consumer cognition and emotional state on their shopping and social behavior in e-commerce livestreaming. Liu Yang et al.³⁷ constructed a research model based on the Stimulus–Organism–Response (SOR) theory and empirically analyzed and verified the role of live webcast shopping features on consumers’ purposeful and impulsive purchases. Qing et al.³⁸ revealed the paths by which the quality of live broadcast e-commerce (quality of service, quality of information, and quality of the system) affects consumers’ willingness to purchase. Shi et al.³⁹ utilized the SOR model to study the effects of live broadcast e-commerce atmosphere cues on consumers’ impulsive buying behavior.

When consumers become aware of financial constraints as a problem, they take proactive countermeasures to reduce their negative impact. The higher prices of goods sold in livestreams, which are mainly artificially constructed, make overspending less acceptable to less well-off consumers, who are prone to develop a resistance to it. Consumers become more cautious and selective to cope with scarcity of resources due to limited choices. At the same time, artificially constructed live rooms are carefully set up to create an atmosphere of excitement, which can lead to impulsive purchasing behavior, and consumers do not necessarily enjoy the benefits of goods and services in the coming period. The “focus on dividends” may make consumers pay lower purchase prices and actively seek scarce goods in origin-source-type live rooms; the “burden of peeping” causes consumers to ignore the more frequent promotional activities and greater promotional efforts in the artificially constructed-type live rooms. Therefore, the following hypothesis is proposed:

H1 A sense of financial constraint reduces consumer preference for artificially constructed live scenes compared to origin-source live scenes.

Mediating and moderating effects of flow experience

Flow experience refers to an individual’s complete immersion in an activity, i.e., creating a sense of time distortion, ignoring the surrounding environment, focusing attention completely on the present moment, and obtaining a feeling of pleasure in one’s mood⁴⁰. Studies have shown that when people are in the state of flow experience, they are attracted to the present, highly focused, and automatically filter irrelevant information. Among these behaviors, perceived control has a significant impact on an individual’s flow experience and is defined as the feeling of being unrestricted or free to act in a variety of ways in specific situations and environments⁴¹. Koufaris⁴² defined perceived control as the level of control that an individual has over his or her environment and behavior. Individuals in a state of flow can control their behavior and environment, and this sense of control has a long duration. Since flow activities have clear rules, people who adopt an activity may temporarily forget their identity and its problems; e.g., internet users are more likely to have a flow experience⁴³ which encourages users to continue browsing and purchasing, and even leads to impulse buying⁴⁴, and the flow experience is affected by the online service scenario⁴⁵, which then promotes impulse buying’s willingness to arise. Bao et al.⁴⁶ also showed that the interrelationship between the flow experience and serendipity and trust motivates online impulse buying. Yin J. et al.⁴⁷ proposed a comprehensive model to explain the mechanism that influences consumers’ purchase intention in live shopping based on the theory of flow.

Self-regulation theories about resource scarcity⁴⁸ can effectively explain the association between the experience of flow and the sense of financial constraint. When individuals are at a high level of resource variability (the degree to which the level of resource scarcity can be changed through effort), they realize that they are capable of solving the resource scarcity situation and will take direct measures to obtain the scarce resources, for example, increasing the utilization of the scarce resources in consumption to reduce the depletion of the scarce resources. When individuals are at a low level of resource variability, they are less able to address resource scarcity, feel a stronger sense of threat, and defuse the disadvantage by seeking other positive feelings to compensate for the negative impact, such as attempting to seek a sense of control during consumption or using the product creatively after consumption. Because resource scarcity under low variability is distasteful, the experience of resource scarcity is sometimes accompanied by conscious negative feelings. Consumers adapt to resource scarcity by spending a greater proportion of their financial resources on necessities⁴⁹. Artificially constructed livestreaming rooms often attract consumers to participate in live broadcasting by means of elaborate scene construction, the motivational drive of the anchor, instant interactive entertainment, and diversified content provision, thus improving consumers’ flow experience and inducing them to perceive the reliability of goods and, as a result, devote more attention to the live broadcasting room.

In this paper, we introduce the flow experience as a mediating variable by linking it to consumers’ purchasing attitudes, intentions, and behaviors. When consumers feel financial constraints, negative emotions such as anxiety and restlessness are closely related to lower levels of flow experience, while a strong flow experience felt by consumers—which leads to a loss of the sense of time and an increase in positive emotions—will allow them to immerse themselves in live broadcasts, forget about the existence of the external environment, increase their sense of control, and, as a result, will produce impulsive consumption intentions, which is more obviously reflected in artificially constructed live broadcasting rooms. In addition, further dividing the flow experience into different levels can also play a moderating role. For example, when the flow experience is low, consumers will adopt hedonic and instrumental emotion regulation strategies⁷, the former aiming to motivate behaviors toward the pursuit of pleasure and the latter, i.e., giving up pleasure for other important goals. In hedonic emotion regulation, if consumers set the goal of pursuing pleasure, they will be prone to avoidant behaviors⁹ and may react negatively to the original artificial class of live interactions, whereas in instrumental emotion regulation, consumers are more likely to look for emotions in the environment that can convey information about themselves or the world around them in order to obtain compensation^50,48 and thus directly narrow the gap between the current level of resources and the desired level of resources, thereby reducing their concern about the current level of resources and the desired level of resources. Conversely, individuals with a high flow experience become more immersed in livestreams and develop impulsive consumption intentions even if they are in a poor resource situation such as scarcity of money; higher perceived control and identity amnesia lead them to believe that they have the power to change this situation⁵¹. In addition to being inherently pleasurable, high flow experiences have been shown to trigger more positive emotions⁵² and higher life satisfaction⁵³; thus, consumers in this state are less affected by a sense of financial constraint.

Before considering analyzing a variable as a moderator or mediator, the analysis must make sense from a disciplinary theoretical or empirical common-sense perspective⁵⁴. There are many instances in the existing literature where a particular variable acts as both a moderator and a mediator. For example, Rabenu et al.⁵⁵ explored the dual role of human resource management (HRM) strengths as a moderator and mediator in the relationship between HRM practices and organizational innovation. Tian⁵⁶ examined just-world beliefs as a mediator and moderator variable in the relationship between negative life events and life satisfaction among college students. McKeen et al.⁵⁷ demonstrated that positive thoughts serve as a mediator and moderator variable in the relationship between adverse childhood experiences and depression as a mediating and moderating variable. In summary, different perspectives on the experience of mindfulness flow have both mediating and moderating effects between the effects of the sense of financial constraints and consumers’ preferences for browsing artificial types of scenes. If it is believed that the sense of financial constraints affects the flow experience, which, in turn, affects consumers’ artificial scene browsing preferences, then the flow experience can be analyzed as a mediating variable; if it is believed that the sense of financial constraints has a greater impact on consumers’ artificial scene browsing preferences, flow experience is a moderating variable at this point. Accordingly, this study proposes the following hypotheses:

H2a Flow experience mediates between the sense of financial constraints and preferences for browsing live scenes of the artificially constructed type.

H2b Flow experience mediates the relationship between financial constraints and preference for artificially constructed livestreaming scenes. Individuals with lower flow experience reduce their preference for artificially constructed scenes in financial constraint situations compared to individuals with higher flow experience.

Research framework

In this paper, we classify livestreaming scenes into two types, namely, the artificially constructed type and the origin-source type, and explore the impact of the sense of financial constraints on consumers’ livestreaming scenario preferences, as well as the mediating and moderating roles of their flow experience through two online experiments in the context of the reality that consumers generally feel financial constraints. The research framework of this study is shown in Fig. 1. The specific groupings of the two experiments are shown in Table 1.

Table 1

Experimental groupings.
Experiment	Groups	Sense of financial constraint	Livestreaming Scene Types
Experiment 1	Group 1	Financial constraints group
Experiment 1	Group 2	Control groups
Experiment 2	Group 1	Financial constraints group	Artificially constructed group
	Group 2	Financial constraints group	Origin-source group
	Group 3	Control groups	Artificially constructed group
	Group 4	Control groups	Origin-source group

Experiment 1

Experiment 1 used an online experiment to present subjects with three different livestreaming scenarios, each containing a artificially constructed scenario and an origin-sourced scenario, with the purpose of initially exploring the influence of financial constraints on consumers’ livestreaming scene preferences.

Method

Our study was obtained ethical approval from the Interim Ethical Committee of the Department of Business of Wuhan Business University.In accordance with the ethical principles outlined in the Declaration of Helsinki,all participants provided informed consent before participating in the study.The anonymity and confidentiality of the participants were guaranteed,and participation was completely voluntary.

Participants

In this experiment, an online questionnaire was distributed through the Credamo platform, and subjects were paid CNY 2 for completing the questionnaire. A total of 330 subjects were recruited and randomly assigned to two experimental scenarios: the financial constraint group and the control group. Invalid questionnaires were excluded according to the following criteria: the response time was less than or equal to 100 seconds; the writing task did not meet the requirements of the question, or AI wrote it on behalf of the subject; and the reverse question was filled in incorrectly. After screening, 256 valid questionnaires were finally obtained, and the recovery rate of the questionnaires was 77.6%. The numbers of the financial constraint group and the control group were 130 and 126, respectively. The age of the subjects ranged from 18 to 66 years old, with a mean age of 30.32 years old (SD = 7.43), and the subjects were predominantly female, accounting for 69.1% of the overall sample. In terms of the frequency of watching live e-commerce, 46.1% of the subjects watched it, on average, two to three times per week, and 35.5% of the subjects watched it, on average, four to six times per week. Overall, the subjects were knowledgeable about live e-commerce, which was in line with the purpose of the study.

Procedure

Experiment 1 adopts a one-way completely randomized design, with sense of financial constraint as the independent variable and consumer browsing preference as the dependent variable, and mainly explores the effect of sense of financial constraint on the preference for an artificially constructed type of livestreaming scenario versus an origin-source type of livestreaming scenario. This experiment was randomly divided into two scenarios, a financial constraint group and a control group, and the specific process took place in three parts: the first part asked for the subjects’ basic information such as gender, age, and frequency of watching live e-commerce. The second part asked the subjects to complete a writing task, followed by filling out a test questionnaire on their sense of financial constraint. The third part asked subjects to hypothetically make browsing choices for three sets of livestreaming scenarios under their actual financial situation. Before the formal experiment, a pre-survey was used to select the scenes and products in the hypothetical browsing livestreaming task.

Materials

The variables were measured in this study using a seven-point Likert scale, and details of the variables and measurement question items are shown in Table 2.

Table 2

Study variables and measurement items.
Research variables	Measurement items	Sources
Sense of financial constraint	1. At this moment, you feel financial constraints 2. At this moment, the extent to which you feel financially constrained is	Tully et al,⁴
Consumer browsing options	If you now had to choose between the following two livestreaming scenarios, the one you would consider viewing would be
Livestreaming scene types	Based on the previously read definitions, do you believe that the above live broadcasts
Consumer browsing preferences	1. Whether you would like to browse the above live broadcasts 2. Whether you would like to buy the product in the above live chat room
Flow experience	1. While watching a livestream, you often ignore what’s happening around you 2. You feel in control of your own actions while watching a livestream	Lixia, ²⁷

Manipulation of the sense of financial constraints

The manipulation of financial constraints in this paper draws on the approach of Tully et al.⁴ by focusing on the manipulation of subjective feelings, which aims to cause subjects to experience resource scarcity through imagination, recall, etc., and to control for feelings of financial constraints by asking subjects to write short essays involving financial stress. Thus, for the financial constraint group, we asked them to complete a writing task on economic stress, while the control group wrote eight objective facts. The specific manipulation materials for the two groups were as follows. The reading material for the financial constraint group stated that “Everyone may face financial stress in their lives, and perhaps you have experienced a certain amount of tension or anxiety because you feel that your financial situation is limiting your consumption needs. Please recall and describe this experience and feeling as thoroughly as possible and analyze the causes of your financial stress (at least 80 words).” The reading material for the control group stated the following: “Write 8 facts that you know (e.g., the sun rises in the east and sets in the west every day. Total words in the text should be at least 80 words).” The sense of financial constraint was tested by completing two questionnaire items, “At this moment, you feel financially constrained” (1 = strongly agree, 7 = completely disagree), and “At this moment, to what extent do you feel financially constrained?” (1 = very weakly, 7 = very strongly). The former was reverse scored and was used to screen for seriousness of response, with lower scores on Item 1 indicating a feeling of financial constraints and higher scores on Item 2 indicating a stronger feeling of financial constraints.

Measurement of consumer browsing options

Subjects’ browsing choices were measured through a hypothetical live broadcast browsing task in which subjects were required to make browsing choices for three groups of live broadcast scenarios under their own actual economic circumstances (1 = definitely artificially constructed type of live broadcast scenarios, and 7 = definitely origin-source type of live broadcast scenarios). Before the start of the formal experiment, we carried out a pre-survey to select a suitable live broadcast as the material for Experiment 1; that is, we prepared 20 live broadcast clips (including 14 specific products), 10 each of the two types of live broadcast scenes. Through the form of a questionnaire, we explored the classification of these live scenes in the minds of consumers and the willingness to browse the live room. The specific livestreaming scenes included laundry detergent, sneakers, clothing, paper towels, iron pots, kiwis, pastries, milk, brine, stationery, shower gel, laptops, snack nuts, and cooked beef brisket. In the questionnaire about the types of livestreaming scenarios, subjects first read the definitions of artificially constructed versus origin-sourced livestreaming scenarios, and then completed a one-item question, “What do you think of the above livestreaming scenarios” (1 = entirely artificially constructed livestreaming scenarios, 7 = entirely origin-sourced livestreaming scenarios). In the questionnaire on the willingness to browse the live broadcasting room, each live broadcasting scene and the product as a whole was summarized as a “live broadcasting room”, and the measurement item was “Your willingness to browse the above live broadcasting room is” (1 = very unwilling, 7 = very willing). Subsequently, through the one-sample t-test, three groups of scenes with significant differences in the classification of live broadcast scenes were selected as the live broadcast scenes that consumers could easily distinguish from each other and matched with the willingness to browse the above live broadcasts as the formal material of Experiment 1. The three groups of live broadcast scenes were the following: laundry detergent and stationery, clothing and iron pots, and snack nuts and milk. The specific values are shown in Table 3.

Table 3

Scoring of Live Scene Types.
Products	M _{Artificially constructed type}	M _{Browsing Willingness}
Laundry detergent	5.83	4.27
Stationery	3.88	4.27
Clothing	5.46	4.06
Iron cooker	3.51	4.03
Snacks and nuts	5.55	4.41
Milk	2.86	4.47

Results

Financial constraint sense manipulation test

The scores of the two questions answered by the subjects in completing the writing task were used as an indicator of whether the manipulation was successful. Financial Test I was a reverse test, i.e., the lower the score, the more financial constraints were felt by the subjects; in Financial Test II, the higher the score, the stronger the financial constraints felt by the subjects.

Independent samples t-tests showed significant differences in the scores of the financial constraints and control groups: in Question 1, M _{Financial constraints group} = 2.28, M _{Control group} = 3.60, t(254) = -6.75, p = 0.000 < 0.05; and in Question 2, M _{Financial constraints group} = 5.95, M _{Control group} = 3.58, t(254) = 13.25, p = 0.000 < 0.05, indicating that the manipulation of financial constraints was effective.

Impact of the sense of Financial Constraints on Preferences for Livestreaming Scene Types.

Experiment 1 used analysis of variance (ANOVA) to explore the effect of a sense of financial constraints on scene type browsing preferences, with scene pairing as the within-group variable and financial constraints as the between-group variable. The results showed that the main effect of a sense of financial constraints was significant (F(1,254) = 35.31, p = 0.000 < 0.05, η² = 0.12), which confirmed Hypothesis 1, that consumers under conditions of financial constraints would decrease their browsing preferences for artificially constructed types of livestreaming scenes. Using the average of the class of artificially constructed scenes’ browsing preference scores for the three groups of livestreaming scenes as the dependent variable, it was found (see Fig. 2) that the financial constraints group had significantly lower browsing preferences for artificially constructed scenes (M _{Financial constraints group} = 2.44, SD = 1.24) than the control group (M _{Control group} = 3.52, SD = 1.64). An independent samples t-test indicated a significant difference in scene scoring between the two groups (t(254) = -5.92, p = 0.000 < 0.05), again indicating that consumers subject to financial constraints reduced their browsing preference for artificially constructed live scenes.

Discussion

Experiment 1 confirmed that consumers who felt financial constraints reduced their browsing preferences for artificially constructed class scenes.

However, Experiment 1 also left two questions open. First, although the results of the study proved that the preference for artificially constructed scenes was significantly lower in the financially constrained group than in the control group, it is also possible that the feeling of financial constraints increased consumers' browsing preference for scenes in the origin source category, since the study was asking subjects to choose between artificially constructed live streaming scenes and origin source live streaming scenes. Second, although browsing preferences for each group of live streaming scenarios were matched prior to the start of the study, the specific content of the live streaming scenarios may still have had an impact on the results.

In summary, Experiment 2 will address these two issues with further improvements.

Experiment 2

Experiment 2 used a completely randomized two (financial constraints group vs. control group) by two (artificially constructed livestreaming scenes vs. origin-source livestreaming scenes) design. Experiment 2 has two purposes: one is to describe the same livestreaming scene in two different ways to exclude the effect of the livestreaming scene type itself, as well as to explore the direction in which the sense of financial constraints affects the artificially constructed livestreaming scene and the origin-sourced livestreaming scene and to test Hypothesis 1 again. The other purpose is to verify the mediating and moderating role of the flow experience.

Method

Participants

Same as Experiment 1, Experiment 2 distributed online questionnaires through the Credamo platform and recruited a total of 354 subjects.

Same as Experiment 1, Experiment 2 distributed online questionnaires through the Credamo platform and recruited a total of 354 subjects, who were randomly assigned to two (financial constraint group vs. control group) by two (artificially constructed livestreaming scenes vs. origin-source livestreaming scenes) scenes for a total of four experimental scenes. After screening, 288 valid questionnaires were finally obtained, with a questionnaire recovery rate of 81.4%. Among them, the age of the subjects ranged from 19 to 58 years old, with an average age of 30.00 years old (SD = 7.56); the subjects were mainly female, with 183 females, accounting for 63.5% of the overall sample.

Procedure

Experiment 2 used sense of financial constraint and live scene type as independent variables; sense of financial constraint was divided into two levels (financial constraint group and control group), and live scene type was divided into two levels (artificially constructed type of live scene and origin-source type of live scene). Subjects were randomly assigned to one of the four groups. The experimental procedure was divided into three parts. The first part was the same as Experiment 1, requiring subjects to answer basic information. The second part required subjects to complete a writing task and then asked them to answer questions from the financial constraint manipulation test, after which the subjects’ experience of livestreaming was measured. The third part required subjects to read the definitions of artificially constructed scenarios and origin-source scenarios and then asked subjects to read a description of a scenario, followed by completing the browsing preference manipulation and measurement.

Materials

Manipulation of the sense of financial constraints

Subjects completed the same writing task and corresponding manipulation test as in Experiment 1.

Manipulation of live scene types

The live scene type was manipulated by describing the same live broadcast in two different ways. For Experiment 2, the livestreaming scene of shower gel was selected, and a pre-experiment was carried out before the start of the formal experiment in order to guide the subjects in their choice. The definitions of the two types of livestreaming scenarios were first explained, and different ways of describing the shower gel livestreaming scenario were adopted in which subjects were assigned to read different texts and answer the following two questions: “What do you think of the above livestreaming room that you viewed” (1 = completely artificially constructed livestreaming scenario, 7 = completely origin-sourced livestreaming scenario) and “How much do you like the above livestream” (1 = not at all, 7 = very much). The results showed that the subjects who read the textual material of the origin-source group thought that the live room of the shower gel was more in line with the origin-source type of the live scene than the subjects who read the textual material of the man-made construction group (M _{Artificially Constructed Group} = 3.66, SD = 1.77, M _{Origin − Source Group} = 4.60, SD = 1.68, t(138) = -3.23, p = 0.002 < 0.05), but the subjects’ opinion about the live room’s favoritism did not differ (M _{Artificially Constructed Group} = 4.31, SD = 1.22, M _{Origin − Source Group} = 4.56, SD = 1.11, t(138) = -1.23, p = 0.22). The two different types of descriptive material for the shower gel live scene are as follows:

(a) “Artificial scene group” reading materials: this is the body lotion live studio; the background is manually inserted into the video, and the anchor is in front of the video background to demonstrate the products live.

(b) “Origin scene group” reading materials: this is the body lotion live room; the background is the body lotion processing production line, and the anchor is live with the products.

Based on the above text material, our subjects were prompted to answer the following question: “According to the definition of the previous reading, do you think that the above live room was” (1 = a completely artificially constructed construction of a live scene, 7 = a completely origin-sourced live scene); the average score of the question item was used as a manipulation test for the type of live scene.

Consumer Browsing Preference Measurement

Consumer browsing preferences were measured by measuring the subjects’ willingness to browse live clips and their willingness to purchase the products in the livestream. This section of the questionnaire consisted of two questions: “Are you willing to browse the above live broadcast”, and “In the above live broadcast, are you willing to purchase the product” (where 1 = not at all, 7 = very willing). Higher mean scores for both questions indicated higher browsing preferences.

Measurement of the flow experience

In this study, the measurement of subjects’ experience of flow was carried out according to the work of Lu Lixia²⁷ and combined with the actual research topic of this paper. Finally, the two aspects of attention and perceived control were selected for the scale rating of the subjects. The two question items were as follows: “When watching live broadcasts, you often ignore what is happening around you”, and “When watching live broadcasts, you feel in control of your actions” (where 1 = not at all, 7 = very much).

Results

Financial constraint sense manipulation test

The results of Experiment 2 showed that there was a significant difference between the scores of the financial constraint and control groups: in Question 1, M Financial constraints group = 2.90, M _{Control group} = 3.90, t(286) = -4.94, p = 0.000 < 0.05; in Question 2, M Financial constraints group = 5.93, M _{Control group} = 3.81, t(286) = 13.14, p = 0.000 < 0.05, indicating that the manipulation of financial constraint was successful.

Live Livestreaming Type Manipulation Examination

The average score of the question items was used to verify the success of the manipulation. Independent samples t-tests indicated significant differences in scene scoring across groups, with the origin-source group perceiving the origin-source live scene of the bath bombs (M _{Artificially Constructed group} = 2.13, SD = 1.74) to be significantly higher than that of the artificially constructed group (M _{Origin − Source Group} = 6.15, SD = 1.06), t(286) = -23.75, p = 0.000 < 0.05, suggesting that the live-scene-type manipulation was effective.

Impact of the sense of Financial Constraints on Preferences for Livestreaming Scene Types

Experiment 2 used a two (financial constraint group vs. control group) by two (artificially constructed class live scene vs. origin-source live scene) ANOVA to explore the effects of the sense of financial constraint, type of live scene, and the interaction between the two on consumer browsing preferences. The results showed (see Fig. 3) that the main effect of a sense of financial constraint was significant (F(1,284) = 10.25, p = 0.002, η² = 0.035), that the main effect of the type of livestreaming scene was significant (F(1,284) = 77.29, p = 0.000, η² = 0.214), and that the interaction between a sense of financial constraint and the type of livestreaming scene was not significant (F(1,284) = 2.75, p = 0.098, η² = 0.010).

The mediating role of the flow experience.

Before exploring the relationship between the variables, Pearson’s correlation coefficient analysis was used to analyze the variables, and Table 4 shows that there was a good correlation between the variables.

Table 4

Pearson correlation analysis.
	Sense of Financial Constraint	Artificially Constructed Class of Scene Browsing Preferences	Flow Experience
Sense of financial constraint	1
Artificially constructed class of scene browsing preferences	0.244**	1
Flow experience	0.187*	0.428**	1
Note: * indicates P<0.05, ** indicates P<0.01.

The data from the group of artificially constructed class scenes were selected, and the SPSS process plug-in was used to conduct the mediation effect test, with the grouping of the sense of financial constraints as the independent variable, the -flowexperience as the mediating variable, and the browsing preference of artificially constructed class of live scenes as the dependent variable. This process was included in Process Model 4 with a Bootstrap Sample of 5000 and a confidence interval of 95%. The results showed (see Table 5) that the sense of financial constraints had a significant predictive effect on the flow experience (β = 0.37, t = 2.25, p = 0.03 < 0.05), and the predictive effect of financial constraints on the browsing preference for the artificially constructed class of live scenarios was still significant after incorporating flow experience as a mediator variable into the model (β = 0.47, t = 2.21, p = 0.03 < 0.05). Further, the flow experience was a significant predictor of browsing preference for artificially constructed classes of livestreaming scenes (β = 0.55, t = 5.17, p = 0.000 < 0.001).

Table 5

Prediction of artificially constructed scene browsing preferences by sense of financial constraints and flow experiences.
Variables		Artificially Constructed Scene Browsing Preferences		Flow Experience		Artificially Constructed Scene Browsing Preferences
Variables		β	t	β	t	β	t
Independent variable	Sense of financial constraint	0.47^*	2.21	0.37^*	2.25	0.67	2.97
Intermediary variable	Flow experience					0.56^***	5.17
R²		0.21		0.04		0.06
F		18.59		5.06		8.85
Note: * indicates P<0.05, indicates P<0.01, * indicates P<0.001.

The results of the mediation effect analysis (see Table 6) show that the bootstrap and the 95% confidence interval for the mediation effect of the flow experience is [0.03, 0.43], the Boot LLCI and the Boot ULCI did not include 0, and the mediation effect is significant, with an effect size Boot SE of 0.20. In addition, after controlling for the flow experience, the effect of financial constraints on the browsing preference of the artificially constructed class of livestreaming scenes is still significant, with the bootstrap and the 95% confidence interval of [0.03, 0.05], the Boot LLCI and the Boot ULCI did not include 0, indicating that the sense of control partially mediates the relationship between financial constraints and willingness to purchase physical consumption, confirming hypothesis H2a.

Table 6

An analysis of the mediating effects of flow experiences.
	β	Boot SE	Boot LLCI	Boot ULCI	Percentage of Total Effect
Total effect	0.67	0.22	0.22	1.11
Direct effect	0.47	0.21	0.05	0.89	70.1%
Intermediary effect	0.20	0.10	0.03	0.43	29.9%

The data of the origin-source-type scene group were selected and the SPSS process plug-in was used to test the mediating effect, with the financial constraints sense grouping as the independent variable, the flow experience as the mediator variable, and the browsing preference of the origin-source-type live scene as the dependent variable, which was included in the Process Model 4 with a bootstrap sample of 5000 and a confidence interval of 95%. The results showed that the 95% confidence interval was [–0.04, 0.37], the Boot LLCI and the Boot ULCI include 0, and the mediating effect was not significant.

Simple effects analyses showed that subjects in the financial constraints group had significantly lower browsing preferences for livestreaming scenarios of the artificially constructed type than those in the control group (M _{Financial constraints group} = 4.00, SD = 1.47, M _{Control groups} = 4.67, SD = 1.20, F(1,284) = 8.85, p = 0.003, η² = 0.059). In contrast, there was no significant difference in browsing preferences between the financial constraints group and the control group in the livestreaming scenarios in the origin-source type (M _{Financial constraints group} = 5.44, SD = 1.07, M _{Control groups} = 5.65, SD = 0.86, F(1,284) = 1.75, p = 0.189, η² = 0.012).

The role of the sense of financial constraint was evident in two different scene types. When comparing the data for the financial constraint group, M _{Artificially Constructed group} = 4.00, SD = 1.47, M _{Origin − Source Group} = 5.44, SD = 1.07, F(1,284) = 45.39, p = 0.000, and η² = 0.242. Similarly, in the control group, M _{Artificially Constructed group} = 4.67, SD = 0.20, M _{Origin − Source Group} = 5.65, SD = 0.86, F(1,284) = 31.92, p = 0.000, and η² = 0.184. Consumers’ browsing preferences for livestreaming scenes of the artificially constructed type were significantly lower than those of the origin-source type, which is consistent with the three groups in Experiment 1. There is consistency in the results of livestreaming scene selection, but furthermore, it can be found that the sense of financial constraints reduces consumers’ browsing preference for livestreaming scenes of the artificially constructed type. Therefore, the above results support hypothesis H1.

The moderating role of the flow experience.

The mean scores of the two question items of the flow experience were selected as a measure of the moderating effect, with a lower mean score representing a lower degree of flow experience. The SPSS process plug-in was used to test the moderating effect, with the grouping of the sense of financial constraints as the independent variable, the browsing preference of the artificially constructed types of live scenes as the dependent variable, and the flow experience as the moderating variable, which was included in the Process Model 1, with a bootstrap sample of 5000 and a 95% confidence interval, and combined with the hierarchical regression to calculate the moderating effect. As shown in Table 7, the amount of change in the R² is significant (p = 0.031 < 0.05), the moderating effect exists, and the interaction term is significant, indicating that the flow experience plays a moderating role between the sense of financial constraints and the browsing preference for artificially constructed scenes, thereby validating hypothesis H2b.

Table 7

A test of the moderating effect of the flow experience.
Predictor Variables	Outcome Variable
	Browsing Preferences			Browsing Preferences
	Beta	t	p	Beta	t	p
Sense of Financial Constraint Subgroup	0.170	2.214	0.028	1.119	2.527	0.014
Flow Experience	0.396	5.169	0	0.876	3.760	0.001
Interaction Term				-1.152	-2.176	0.031
F	18.593 0.211			14.307
R²	18.593 0.211			0.237

To further explore the moderating effect, Fig. 4 plots the slope of the moderating effect of flow experience on the perception of financial constraint and browsing preference for artificially constructed scenes. The results show that under low flow experience, financial constraints have a significant effect on browsing preference for artificially constructed scenes (p = 0.002 < 0.05); i.e., the browsing preference for artificially constructed scenes of consumers with a sense of financial constraints is significantly lower than that of the control group. Under high flow experience, financial constraints have no significant effect on browsing preference for artificially constructed scenes (p = 0.959 > 0.05); i.e., there is no significant difference in browsing preference for artificially constructed scenes between the financial constraints group and the control group.

This study investigates the impact of a sense of financial constraint on consumers’ livestreaming scene preference and the moderating role of flow experience. Through two experiments, the main conclusions drawn from the validation are as follows: the sense of financial constraint reduces consumers’ preference for artificially constructed livestreaming scenes, and the flow experience plays the dual roles of mediation and moderation between the sense of financial constraint and preference for artificially constructed livestreaming scene browsing.

Experiment 1 presented subjects with a hypothetical livestream browsing task in which they were asked to make browsing choices among three sets of livestreaming scenes, each of which contained a scenario in the artificially constructed class of scenarios and a scenario in the origin-source class of scenarios. The results showed that subjects experiencing financial constraints reduced their browsing preferences for livestreaming scenes of the artificially constructed type. Experiment 2 makes relevant improvements on the basis of Experiment 1, describing the same livestreaming scene in two different ways, guiding subjects to think about their browsing intention for this livestreaming room in the framework of the artificially constructed livestreaming scene or the origin-sourced livestreaming scene, and completing the measurement of their browsing preference. The results show that subjects’ browsing preference for the artificially constructed scenario is significantly lower than that for the origin-source scenario, but the browsing preference for the artificially constructed scene is significantly lower for the subjects experiencing financial constraints, which indicates that the sense of financial constraints reduces browsing preference for an artificially constructed scene. Consumers in a state of financial constraint lack the resources to freely spend their money on a wide range of choices due to the effects of resource scarcity and choice constraints⁵⁸, which is consistent with the findings of scholars. In addition, Experiment 2 shows that consumers’ perceptions of livestreaming scene types are diverse, and there are differences in their choices when considering their choices among different scene types.

Experiment 2 also explored the mediating and moderating role of flow experience on the above effects, confirming the mediating role of flow experience between the sense of financial constraints and browsing preference for artificially constructed live scenes and confirming that lower flow experience resulted in lower browsing preference for artificially constructed scenes among consumers who felt financial constraints. The sense of financial constraint directly affects consumers’ flow experience, and the level of flow experience affects their consumption behavior from both direct and indirect perspectives, in line with the positive correlation between flow experience and purchase intention confirmed by many studies^59,60,61. Furthermore, in the e-commerce livestreaming environment, the impact of flow experience on artificially constructed livestreaming scenes is more obvious. Based on the self-regulation theory of resource scarcity, individual arousal and sense of control are reduced in the state of low flow experience, and individuals reduce the adverse effects of resource scarcity by narrowing the gap with the desired situation. Hsu C. L. et al. demonstrated ⁴⁴ that the relationship between the flow experience and online shopping behaviors is moderated by consumer characteristics, that there is a strong correlation between the flow experience and sustained attention⁶², and that these effects make it easier for individuals in a flow experience to focus on the consumption process. Therefore, a higher flow experience reduces the influence of the sense of financial constraint on browsing preferences for artificially constructed scenes, which allows consumers to normalize their browsing preferences.

In this paper, we categorized livestreaming scenes into two categories: artificially constructed and origin-sourced scenes. In the context of the reality that consumers generally feel financial constraints, two experiments were conducted to explore the impact of the sense of financial constraints on consumers’ livestreaming scene preferences, as well as the mediating and moderating roles of their flow experience. This study contributes to the existing literature in the following ways. First, it explored the impact of the sense of financial constraint on consumer psychology and consumer behavior and related this impact to live e-commerce scenes, filling an important gap in the existing literature. Second, under the current situation of the booming industry of live e-commerce in China, using the live broadcasting scene as the research object enriches the original research in the field of e-commerce on the four aspects of e-commerce platforms, products, consumers, and anchors and provides a new research perspective on the scenes used in live e-commerce broadcasting.

Most e-commerce enterprises are currently strengthening the planning and construction of live broadcasting rooms, but in the context of the reality that consumers generally feel financial constraints, enterprises should pay more attention to the adverse effects of artificially constructed scenes and the value of origin-based scenes. E-commerce enterprises need to tap into the emotional value and life experience in the live broadcasting scene to reduce the anxiety and uneasiness that the sense of financial constraints brings to consumers and to take user browsing behavior into consideration in order to enhance user loyalty and encourage purchase conversion. From the perspective of consumers, consumers need to consider the impact of financial constraints when watching live broadcasts, pay attention to the personal experience of flow, and rationally choose to browse and consume. Live e-commerce is mostly a “wake-up call”: consumers should fully consider their personal behavior in the process of browsing live products, combined with personal economic conditions and the actual needs of multi-angle assessments of consumption choices, and increase the repeatability of their purchases and focus on the availability of consumption choices in order to obtain long-term benefits, thereby preventing impulsive consumption triggered by live e-commerce broadcasting or an elevated flow experience.

Summary

This study explored the impact of a sense of financial constraint on consumers’ livestreaming scene preferences and the moderating effect of their flow experience through two experiments. Experiment 1 used a one-way completely randomized design to measure the sense of financial constraint and initially verified that consumers in a state of financial constraint reduce their browsing preference for artificially constructed types of livestreaming scenes. Experiment 2 used a two-by-two completely randomized design to verify that a sense of financial constraint reduces consumers’ browsing preference for artificially constructed scenes, as well as verifying the dual roles of flow experience in mediating and moderating the effect of a sense of financial constraint on consumers’ browsing preference for livestreaming scenes.

Although we combed the important literature at home and abroad during the research process, the domestic research on the sense of financial constraints in the field of consumer psychology is on the low side, and at the same time, due to the rapid development of live broadcast e-commerce in the past two years, there is a lag in the academic research on live broadcast e-commerce and live broadcasting scenarios. Therefore, there are some deficiencies in this study that need to be explored and addressed. First of all, the live broadcast scene selection has not yet been divided into product categories or the specifics of the live broadcast room, and differences in gender and consumption habits may cause consumers to have different emotional attitudes and behavioral decisions. Therefore, in the future, we can further classify and refine the e-commerce live broadcast platform, anchor, and product type and study how the live broadcast scene affects consumer browsing preferences. Secondly, this study only selected the flow experience as the mediating and moderating role of the study. There may be other influencing factors that impact the consumer’s livestreaming scene browsing preference, such as social presence, impulsive purchase willingness, and perceived value. At the same time, the measurement dimensions of the flow experience should be deeper, and there is a need to continue to improve and add new influencing variables for research and analysis.

Competing interests

The authors declare no competing interests.

Additional information

Correspondence and requests for materials should be addressed to Y.Z.

Funding

This research was supported by Hubei Provincial Education Science Planning Project(Grant Number. 2023GB083).

Author Contribution

Conceptualization: Y.Z., J.X.; methodology: Y.Z.; formal analysis and investigation: Y.Z. and X.D.; writing—original draft preparation: Y.Z., X.D. ; writing—review and editing: Y.Z., X.D.; funding acquisition: Y.Z.; Supervision: Y.Z. All authors have read and agreed to the published version of the manuscript.

Data Availability

The datasets generated and analysed during the current study are not publicly available due to limitations of university policy and anonymity of the questionnaire we conducted, but are available from the corresponding author on reasonable request.

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No competing interests reported.

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A study on the impact of perceived financial constraints on Chinese consumer preferences for livestreaming scenarios

Status:

Version 1

Abstract

Figures

Introduction

Hypotheses development and theoretical framework

Sense of financial constraint

E-commerce Livestreaming Scene

Mediating and moderating effects of flow experience

Research framework

Experiment 1

Participants

Procedure

Materials

Manipulation of the sense of financial constraints

Measurement of consumer browsing options

Results

Financial constraint sense manipulation test

Discussion

Experiment 2

Participants

Procedure

Materials

Manipulation of the sense of financial constraints

Manipulation of live scene types

Consumer Browsing Preference Measurement

Measurement of the flow experience

Results

Financial constraint sense manipulation test

Live Livestreaming Type Manipulation Examination

Impact of the sense of Financial Constraints on Preferences for Livestreaming Scene Types

General discussion

Summary

Declarations

Competing interests

Additional information

Funding

Author Contribution

Data Availability

References

Additional Declarations

Status:

Version 1