The Dual-Driven Mechanism of “Value and Need” Influencing Consumers’ Continuous Purchase Behavior in Blind Box Consumption

Abstract

This study, grounded in the Stimulus-Organism-Response (S-O-R) model and incorporating a sustainable consumption perspective, investigates how the characteristics and marketing strategies of blind box products influence continuous purchase behavior through perceived value and perceived needs. Empirical evidence reveals that perceived needs are crucial for sustained purchases, with significant impacts from intellectual property (IP) characteristics and uncertainty, highlighting the core role of emotional resonance and experiential stimulation. In the context of sustainable consumption, long-term consumption is based on rational cognition of product value. Consumers form a dual cognitive understanding of “value” and “needs” regarding blind boxes, with these two acting as mediating variables linking antecedents and behaviors. Perceived sustainable value is increasingly becoming an important factor in decision-making. IP and economic attributes positively influence continuous purchases, while social attributes have an insignificant effect on perceived needs, reflecting the priority of individual needs recognition, with sustainable consumption pursuits gradually integrating. Identity recognition indirectly influences continuous purchases through perceived value and needs, validating the “identity–perception–behavior” logic, with sustainable consumption concepts also participating in this transmission. This research constructs an S-O-R framework suitable for blind boxes, enriching the model’s application in emerging industries. It reveals a dual-driving mechanism, providing a basis for understanding the rational logic of “irrational consumption” and the practice of sustainable consumption in the blind box field. It clarifies the priority of individual and group needs and the path of sustainable consumption. The conclusions offer references for blind box product design (strengthening IP, balancing attributes, integrating sustainable concepts), marketing (reasonable use of uncertainty, focusing on individuals, guiding sustainable behavior), and industry development (guiding rational consumption, promoting transformation, and fostering sustainable development).

1. Introduction

Blind boxes, sealed packaging containing random toys or merchandise, derive their core appeal from “unknowability” [1]. Consumers are unable to ascertain the specific product style within the box prior to purchase, relying on the element of surprise upon opening [2]. This “uncertainty” factor fuels the enjoyment of purchasing and collecting, solidifying its status as a globally popular cultural symbol in recent years [3]. The genesis of blind boxes can be traced back to the “fukubukuro” culture of late 20th-century Japan, where merchants packaged multiple products into mystery gift bags, enticing consumers to purchase items of unknown value [3]. This evolved into the “gashapon” (capsule toy) culture found in convenience stores after 2010, utilizing a random draw mechanism to stimulate desire and drive consumption. Consequently, the market size surged from 30 billion yuan in 2020 to 220 billion yuan by 2025, with a compound annual growth rate of 49%, significantly outpacing the growth of the global luxury goods market [4]. This consumption model, originating from the Japanese “fukubukuro” and “gashapon” cultures, stimulates the brain’s reward system through uncertainty, reshaping the consumption patterns of Generation Z, while also presenting issues such as overconsumption and environmental waste [5,6]. This study focuses on analyzing how the product and marketing characteristics of blind boxes influence consumers’ continued purchase intention through perceived value and perceived needs, in conjunction with S-O-R theory, and exploring how to guide responsible consumption behavior to promote the healthy development of the blind box economy.

The driving mechanism of blind boxes on consumer behavior is deeply rooted in psychological and behavioral logic [1]. From a psychological perspective, the uncertainty triggers “cognitive deprivation,” prompting consumers to alleviate discomfort through purchases [4]. Simultaneously, the low probability of hidden models (e.g., 1/144) amplifies “recency bias [7]“ and “loss aversion [8]”, fostering “collecting mania” and a gambling mentality, leading to irrational repeat purchases [9]. This behavioral effect stems from the superposition of “recency bias” and “loss aversion”: the former inclines individuals to remember recent negative experiences, while the latter causes the abandonment of behavior to be perceived as an irrational decision of “losing potential benefits” [10].

Consumer-initiated “weight-based box identification” and other cracking behaviors, along with merchants’ countermeasures, form a cycle, further reinforcing the sense of participation and satisfaction [11,12]. These psychological needs drive consumers to continuously attempt purchases in the hope of obtaining surprises and satisfaction [13]. The “like economy” on social media constructs a social feedback loop through the “three-stage propagation chain” of showing off, envy, and following trends [14]. This behavior greatly satisfies consumers’ experiential needs, not only enhancing their sense of belonging and identity but also promoting social interaction and emotional exchange [15]. The 26 million members and 58% repurchase rate of Pop Mart in 2022 validate the driving force of psychological satisfaction and social recognition on continuous consumption [16]. Furthermore, marketing strategies and value attributes jointly shape the consumption ecosystem of blind boxes [17]. Scarcity creation, hunger marketing, and IP collaborations enhance product attractiveness, while the 300–1500% premium of hidden models in the secondary market reflects both supply-demand distortion and the quantification of social capital—the prestige brought by rare models directly translates into the right to speak [15]. This value is not limited to individual psychological satisfaction; it also builds a unique consumption culture and social network through social interaction, elevating blind boxes from commodities to cultural symbols and emotional attachments, while also intensifying speculative mentality, with some consumers viewing them as investment tools [15]. The prosperity of blind boxes, on the one hand, drives the development of related industrial chains, creating numerous employment opportunities and providing new ideas for brand marketing [18]. On the other hand, for many consumers, blind boxes are not only commodities but also a cultural symbol and emotional attachment [19]. Therefore, the value significance of blind boxes is not limited to individual satisfaction and recognition but is also reflected in their dual role of social attributes and economic value.

The societal issues underlying the blind box phenomenon cannot be ignored, leading to economic burdens and ethical disputes. The bandwagon effect drives blind following [20], exacerbating the spread of consumerism [21], and unscrupulous merchants manipulate draw probabilities to harm consumer rights [22]. More importantly, over-purchasing leads to resource waste—frequent discarding of non-hidden models and the pressure of excessive packaging waste disposal, becoming an environmental burden [19]. The root of these problems lies in the blind box design’s weakening of rational judgment: uncertainty and scarcity stimulate impulsive consumption, especially impacting adolescents, making the symbolic meaning of consumption far exceed its practical value, leading to resource misallocation.

Existing research shows that the uncertainty of blind boxes has a positive impact on consumers’ purchase intention, and consumers’ emotions (such as pleasure and arousal) play a mediating role in this process [23]; although consumers’ participation in blind box products will affect their purchase intention, it only shows a negative moderating effect in specific situations (such as social, aesthetic, and interesting scenarios) [23]. In addition, blind box products can also act on consumers’ satisfaction and loyalty through multi-dimensional values (including economic value, IP value, symbolic value, social value, and psychological value), thereby affecting their purchase intention [24]. At the same time, the S-O-R model can help companies more accurately understand consumer behavior motivations and provide guidance for marketing strategy formulation: for example, by strengthening the uncertainty of blind boxes, it can stimulate consumers’ curiosity and impulsive buying behavior [1]; by optimizing product design, enhancing social attributes and interestingness, it can further enhance consumers’ purchase intention [23].

In addition, existing research based on the S-O-R model focuses on the impact of blind box product characteristics or consumer emotional experience on purchase behavior and loyalty. In view of this, this study expands the application dimension of the S-O-R model on the basis of existing results: at the stimulus (S) level, the original single stimulus factor is refined into product characteristics and marketing characteristics; at the organism (O) level, it innovatively uses perceived value and perceived needs as mediating variables, highlighting consumers’ cognition of the value and needs of blind box products, adding rational value factors compared to previous studies that focused on irrational experiences; at the response (R) level, it innovatively proposes the core indicator of “consumer continuous purchase intention”, which is different from the single purchase intention or short-term purchase behavior in previous studies. Considering that blind box products often lack practical attributes [9].

Building upon this foundation, this study aims to address two key questions. Firstly, it seeks to elucidate the influence mechanism of the consumer-driven blind box economy, spurred by blind box products, offering insights for the development of both blind box products and the consumer-driven blind box economy. Secondly, in response to the social phenomena arising from blind box products, this research endeavors to interpret the underlying logic of these phenomena from the perspective of blind box products. Through the conclusions drawn from this study, we aim to provide guidance and improve the existing blind box culture, thereby fostering the healthy development of the blind box economy. In essence, this research focuses on sustained purchase intention, supplementing the analysis with rational factors and providing insights for guiding responsible consumption. It aims to guide the public to recognize the entertainment value of blind boxes rather than their investment potential, promoting a shift from irrational exuberance to sustainable development. Therefore, this paper will systematically analyze the multidimensional drivers of consumers’ sustained purchase intention for blind box products, reveal the evolutionary logic from irrational enthusiasm to rational regulation, and explore the mechanism of blind box products on consumers’ sustained purchase intention, investigating its practical significance for promoting the sustainable development of the blind box industry.

2. Literature Review

2.1. Blind Box Features

While blind boxes are commodities, they transcend the conventional definition of products, functioning as social mediums that carry emotions and foster connections. By cultivating emotional resonance and group identification, blind boxes provide consumers with dual satisfaction during the purchasing process [23]: enjoyment from the product itself and a sense of belonging through community integration [15]. Blind box enthusiasts actively share the excitement and anticipation of unboxing moments on social media, giving rise to a unique community culture. This interaction not only strengthens individual identity but also serves as a vibrant vehicle for social and emotional exchange. The social attributes of blind boxes are closely tied to their deep integration with well-known IPs. Taking Pop Mart as an example, its collaborations with multiple brands, through IP licensing, enhance product value and market competitiveness while broadening the consumer base. This approach adds cultural significance and brand influence beyond mere commercial value [9]. The high-value nature of blind boxes is also noteworthy. Despite relatively low production costs, their selling prices are often high, with prices in the secondary market sometimes exceeding the original price. This premium reflects consumers’ high recognition of their emotional value and collectability, which is closely related to the core characteristic of blind boxes: content uncertainty [9]. The element of the unknown during purchase precisely stimulates consumers’ curiosity and desire for exploration, becoming a significant driver of purchasing behavior [23]. In essence, consumers’ enthusiasm for blind boxes is a response to their needs for self-actualization, emotional projection, and stress relief [25]. Through collecting and sharing, they gain psychological satisfaction and build broader social connections. Furthermore, the design ingenuity of blind boxes cannot be ignored. Exquisite appearances align with the aesthetic preferences of young people, while features like hidden editions and limited editions enhance the product’s fun and interactivity, further amplifying its appeal [13]. It is this combination of emotional value, cultural connotation, and unique design that has allowed blind boxes to carve out a unique and prosperous presence in the market.

2.2. Perceived Value and Needs

Perceived value is a consumer’s assessment of a product’s worth, encompassing functional, social, and economic dimensions [26]. In the context of blind box products, perceived value is further categorized into functional and social value [26]. Research indicates that perceived value serves as a mediating variable in the intention to purchase blind boxes, playing a significant mediating role [26]. Perceived needs also exert a substantial influence on blind box consumers, with factors such as uncertainty, surprise, and scarcity stimulating emotional motivations [2], including curiosity and excitement. These perceived need factors are crucial in the purchase decision-making process, with emotional motivations and experiences jointly influencing consumer purchasing behavior [2]. Consequently, both perceived value and perceived needs are pivotal in consumer behavior within the blind box context. Perceived value influences purchase intention through dimensions like functional and economic value, while perceived needs drive purchasing behavior through emotional motivations and experiences. Together, these factors constitute mediating variables in blind box consumption, offering critical insights into understanding consumer behavior in this domain.

2.3. S-O-R (Stimulus-Organism-Response) Theoretical Model

The Stimulus-Organism-Response (S-O-R) model is a psychological theory used to explain how external stimuli influence behavioral responses through an individual’s internal psychological processes (organism). This model was initially proposed by Mehrabian and Russell in 1974 [27]. The S-O-R model comprises three core components: Stimulus (S): This refers to external factors from the individual’s internal or external environment. These stimuli can be physical (e.g., visual, auditory, tactile) or psychological (e.g., emotions, cognition) [28]; Organism (O): This represents the psychological and physiological responses an individual experiences after receiving a stimulus, including cognitive processes, emotional reactions, and behavioral tendencies. The organism acts as a mediating variable connecting the stimulus and response, reflecting the individual’s subjective understanding and emotional experience of the stimulus [29]; Response (R): This refers to the behaviors exhibited by an individual following the stimulus and organism responses, including purchasing behavior, willingness to visit, loyalty, and engagement [30]. This theory is widely applied in consumer behavior research to explain how environmental stimuli influence consumers’ emotional and cognitive states, ultimately affecting their purchasing decisions [31].

The “stimulus-organism-response” (SOR) model closely aligns with the consumption process of blind boxes. The core appeal of blind box products lies in the uniqueness of “external stimuli”—the mystery of uncertainty, the emotional connection given by IPs, and the need for ostentatious sharing in social scenarios, all of which are typical categories of “stimulus (S)” in the SOR model [23]. The process by which consumers go from exposure to these stimuli to generating a sustained purchase intention inevitably involves complex internal psychological activities [1]: such as emotional fluctuations when opening the box (joy or disappointment), the cognitive obsession with hidden models, and the sense of belonging obtained through collecting behaviors, which are precisely the emotional and cognitive mediating processes that the “organism (O)” in the model focuses on [24]. The ultimate “sustained purchase intention” corresponds entirely to the output end of the model as a clear behavioral response (R). This complete link from stimulus to psychology to behavior allows the SOR model to naturally cover the entire process of blind box consumption. At the same time, the model can accommodate both rational and irrational factors in blind box consumption. Its “organism (O)” encompasses cognitive evaluation and emotional experience, which matches the design of this study that uses “perceived value” (rational) and “perceived needs” (irrational) as mediators, and can analyze the complex mechanisms of their coexistence. In addition, the model’s extensibility adapts to the research needs of “sustainable consumption.” By subdividing stimulus types and analyzing the dynamic changes in mediating variables, it can capture the impact of stimulus decay and emotional changes on sustained purchases in long-term interactions, aligning with the research on the sustainable development of the blind box industry.

3. Research Hypotheses and Models

3.1. Research Hypothesis

3.1.1. Characteristics of Blind Box Products

The IP characteristics of blind boxes influence consumer decisions through dual pathways. On the one hand, well-known IPs leverage existing fan bases to establish emotional connections, and their collaborative models can quickly attract loyal users. This emotional recognition directly translates into a positive perception of product value [9]. On the other hand, the scarcity and uniqueness of IPs create a differentiation barrier, satisfying consumers’ material needs for “collecting complete sets” while also reinforcing identity through the symbolic meaning of “owning exclusive IPs,” thereby stimulating continuous purchasing motivation [9]. Based on this, the hypothesis of this paper is:

H1a: 

IP characteristics of blind box products have a positive impact on consumer perceived value.

H1b: 

IP characteristics of blind box products have a positive impact on consumer perceived demand.

H1c: 

IP characteristics of blind box products have a positive impact on consumers’ willingness to continue purchasing.

Economic attributes are the core consideration for consumers in weighing costs and benefits. The low-price strategy of blind boxes reduces the cost of trial and error, making it easier for consumers to perceive the rationality of “payment-return,” thereby enhancing the value evaluation of the product [9]. At the same time, its economic value (such as continuous supply supported by low cost and high gross profit margin) and symbolic value (such as the social currency function of low-priced products) jointly satisfy consumers’ needs for “obtaining material and emotional satisfaction with less expenditure,” ultimately driving repeat purchases [23]. Therefore, it is deduced that:

H2a: 

Economic attributes of blind box products have a positive impact on consumer perceived value.

H2b: 

Economic attributes of blind box products have a positive impact on consumer perceived demand.

H2c: 

Economic attributes of blind box products have a positive impact on consumers’ willingness to continue purchasing.

The social attributes of blind boxes build relationship networks through community interaction. Offline exchanges, online sharing, and other behaviors not only enhance consumers’ sense of belonging (satisfying emotional needs) but also strengthen their understanding of the “social value” of the product through information exchange [9]. At the same time, community dissemination expands the influence of blind boxes, making consumers more inclined to integrate into the community through continuous purchases under group pressure and recognition needs, forming a “purchase-share-repurchase” cycle [32]. Based on this, the hypothesis of this paper is:

H3a: 

Social attributes of blind box products have a positive impact on consumer perceived value.

H3b: 

Social attributes of blind box products have a positive impact on consumer perceived demand.

H3c: 

Social attributes of blind box products have a positive impact on consumers’ willingness to continue purchasing.

Fun attributes drive consumer behavior through emotional experience. The “unboxing surprise” brought by the uncertainty of blind boxes and the immersive experience created by gamified design directly enhance the pleasure of the consumption process, making consumers perceive emotional value beyond the product itself [22,26]. This “expectation-satisfaction” cycle continuously reinforces the need for “experiencing fun again,” ultimately translating into the motivation for continuous purchases [9]. Therefore, it is deduced that:

H4a: 

The fun attribute of blind box products has a positive impact on consumer perceived value.

H4b: 

The fun attribute of blind box products has a positive impact on consumer perceived needs.

H4c: 

The fun attribute of blind box products has a positive impact on consumers’ continuous purchase intention.

3.1.2. Blind Box Marketing Strategies

Uncertainty strengthens purchasing motivation through psychological arousal. According to the information gap theory, unknown results will stimulate consumers’ curiosity, prompting them to purchase to eliminate the “information gap” [33]. At the same time, optimistic expectations make consumers interpret uncertainty as an “opportunity to obtain scarce items.” This positive cognition not only enhances the value evaluation of the product but also strengthens the perceived need to “not miss out,” ultimately driving purchasing decisions [26]. Therefore, it is deduced that:

H5a: 

Uncertainty marketing strategies have a positive impact on consumer perceived value.

H5b: 

Uncertainty marketing strategies have a positive impact on consumer perceived needs.

H5c: 

Uncertainty marketing strategies have a positive impact on consumers’ continuous purchase intention.

Experiential marketing deepens emotional connection through full-process participation. The consumption of blind boxes is not only about “obtaining goods” but also a complete process of “unwrapping-getting surprises-sharing experiences,” in which the pleasure and sense of accomplishment (emotional dimension) directly enhance consumers’ perception of product value [2]. At the same time, social sharing and collection behaviors enhance the “sense of participation,” making consumers have a higher demand for “continuously obtaining experiences,” thereby strengthening the willingness to repurchase [9,23]. In addition, consumers’ trust and satisfaction with the brand also directly affect their continuous purchasing behavior [34]. Therefore, it is deduced that:

H6a: 

Experiential marketing strategies have a positive impact on consumer perceived value.

H6b: 

Experiential marketing strategies have a positive impact on consumer perceived needs.

H6c: 

Experiential marketing strategies have a positive impact on consumers’ continuous purchase intention.

Identity marketing strategies are also of great significance in blind box consumption. Identity recognition builds brand loyalty through self-expression. Consumers convey their personality and taste by choosing specific blind boxes. This “self-symbolization” behavior satisfies the need for social recognition, making them perceive the “symbolic value” of the product [9]. At the same time, identity confirmation within the community (such as the label of “blind box enthusiasts”) will strengthen the need to “maintain identity consistency through continuous purchases,” ultimately translating into long-term loyalty to the brand [35]. Based on this, the hypothesis of this paper is:

H7a: 

Identity marketing strategies positively influence consumers’ perceived value.

H7b: 

Identity marketing strategies positively influence consumers’ perceived needs.

H7c: 

Identity marketing strategies positively influence consumers’ continuous purchase intention.

3.1.3. Perceived Value and Perceived Needs

Perceived value represents a consumer’s comprehensive assessment of a product’s “usefulness,” encompassing benefits across functional, emotional, and social dimensions [36]. When consumers believe that blind boxes offer high overall value (e.g., the emotional value of the IP, the interactive value of social engagement), they are more inclined to maintain this value acquisition through continued purchases; thus, perceived value directly and positively influences the intention to continue purchasing. From this, we deduce:

H8: 

Consumers’ perceived value positively influences continuous purchase intention.

Perceived need reflects a consumer’s subjective judgment of a product’s “necessity” [37]. When blind boxes are regarded as significant vehicles for fulfilling needs such as emotion (e.g., enjoyment), social interaction (e.g., belonging), and self-expression (e.g., identity), consumers develop the motivation to “continuously acquire to maintain need satisfaction,” thereby driving repeat purchase behavior. Based on this, the hypothesis of this paper is:

H9: 

Consumers’ perceived needs positively influence continuous purchase intention.

3.2. The Consumer Sustainable Consumption Theoretical Model of Blind Box Products Based on the S-O-R Model

Based on the analysis above, we construct the following theoretical model, as shown in Figure 1.

3.3. Questionnaire Design

The scales utilized in this study were derived from the literature of relevant scholars, and were contextually adjusted based on the specific research content. In light of this, and in conjunction with the aforementioned literature, a corresponding questionnaire was designed to validate the influence mechanisms and effects of blind box products and their marketing strategies on consumer perceived value, perceived needs, and continuous purchase intention.

The scale measuring the IP characteristics of blind box product features was adapted from Dai [9], and was measured using items (IC1–IC3). The scale for its economic attribute characteristics was adapted from Zhan [23], and was measured using items (EA1–EA3). The scale for its social attribute characteristics was adapted from Liu [32], and was measured using items (SA1–SA3). The scale for its fun characteristics was adapted from Zhang [22], and was measured using items (FA1–FA3). The scale measuring the uncertainty factors in blind box marketing strategies was adapted from Zhang [26] and Liu [33], and was measured using items (NO1–NO3). The scale measuring the experience satisfaction in blind box marketing strategies was adapted from Chen [2], and was measured using items (SE1–SE3). The scale measuring identity in blind box marketing strategies was adapted from Dai [9], and was measured using items (ID1–ID3). The scale for the mediating variable of consumer perceived value was adapted from Ratyuhono [36], and was measured using items (PV1–PV3). The scale for consumer perceived needs was adapted from Wahyuningsih [37], and was measured using items (PN1–PN3). The items for consumer continuous use intention were adapted from Sun [34], and were measured using items (CPB1-CPB3). Based on the above analysis, questionnaire design items were designed, as shown in

Table 1. Definition of variable operability and reference scales.

Construct	Items	Source
IP characteristics (IP)	IC1: I like the IP characters (such as anime and film characters) in the blind boxes. IC2: The IP in the blind boxes is unique and attracts me to purchase them. IC3: I will buy the corresponding blind box because of my love for a certain IP.	[1,9]
Economic attribute (EA)	EA1: I think blind boxes have some potential for collection appreciation. EA2: The price of the blind box matches its practical value. EA3: After purchasing a blind box, if I can get a rare version, I will feel that it is “worth the money”.	[23]
Social attribute (SA)	SA1: Purchasing blind boxes allows me to integrate into the “blind box enthusiasts” circle around me. SA2: Discussing the styles drawn in the blind boxes with others can enhance our communication. SA3: Sharing the opening video / pictures of the blind box on social platforms can attract more attention.	[32]
Fun attribute (FA)	FA1: The anticipation before opening the blind box makes me feel very interesting. FA2: The random style design of the blind box increases the fun of purchasing. FA3: The process of collecting blind boxes can make me feel relaxed.	[22]
Nondeterminacy (NO)	NO1: The uncertainty of “not knowing which version to get” makes me want to purchase more. NO2: The “low probability of hidden versions” of the blind box actually stimulates my desire to purchase. NO3: The merchants not disclosing the specific probability of winning a rare version makes this ambiguity more appealing to me, making me want to try.	[26,33]
Satisfy the experience (SE)	SE1: The online and offline pop-up stores / themed activities of the blind box can enhance my consumption experience. SE2: The opening experience of the blind box after receiving it exceeded my expectations. SE3: The promotion of new blind box information by the merchants meets my need for “novelty”.	[2]
Identity (ID)	ID1: Purchasing a certain type of blind box makes me feel like I belong to the “trendy enthusiast” group. ID2: The brand concept of the blind box aligns with my values, making me willing to support it. ID3: Having common topics with other blind box consumers makes me feel recognized.	[9]
Perceptive value (PV)	PV1: The joy brought by purchasing a blind box exceeds its price. PV2: The blind box meets my emotional and entertainment needs, making it valuable. PV3: From the perspectives of collection, social interaction, etc., the blind box is meaningful to me.	[36]
Perceived Needs (PN)	PN1: I think I have an emotional need to continue purchasing blind boxes. PN2: The blind box has become an indispensable part of my daily consumption. PN3: I will actively follow new blind box products because I need to satisfy my collection desire.	[37]
Continuous purchasing behavior (CPB)	CPB1: I will continue to purchase blind boxes of this brand/series. CPB2: I will recommend purchasing these blind boxes to others. CPB5: I plan to collect this type of blind box product for a long time.	[34]

.

Based on the above analysis, the items for questionnaire design are shown in Table 1.

3.4. Informed Consent

To ensure the comprehensiveness, authenticity, and efficiency of the survey data on consumers’ willingness to continue purchasing blind box products, this study has chosen to employ an online questionnaire survey. This decision is primarily based on two considerations: Firstly, the blind box consumer group is extensive and dispersed, encompassing various age groups, professions, and regions. It includes users who purchase through offline trendy toy stores and counters in shopping malls, as well as online consumers who rely on e-commerce platforms and community group purchases. The geographical distribution is not limited to specific cities. Offline surveys struggle to cover cross-regional, multi-channel consumers, whereas online questionnaires can overcome physical space limitations, reaching blind box users nationwide, especially in the sinking market and young consumer groups who rely on online channels. Secondly, there are significant differences in the purchase frequency and preferred types (such as trendy toy blind boxes, stationery blind boxes, and beauty blind boxes) among blind box consumers. Offline surveys are prone to data bias due to sampling scene limitations (e.g., only covering users of certain offline stores). Online questionnaires, through a combination of precise push (such as trendy toy communities and e-commerce platform users) and widespread dissemination, can more evenly cover consumers with different purchasing habits and preferences, reducing the problem of sample singularity, thereby improving the comprehensiveness and authenticity of the data. In terms of implementation standards, all respondents must meet the following criteria: 1. Adults aged 18 and above (excluding minors to comply with the compliance requirements of consumer behavior research); 2. Have experience purchasing blind box products (having purchased at least one blind box) to ensure the relevance of the survey subjects to the research topic and focus on the core research objective of “willingness to continue purchasing.” Simultaneously, before the questionnaire is launched, the system will automatically present an online informed consent form, clearly stating the survey purpose, data usage, privacy protection measures, and participant rights (such as voluntary participation and the right to withdraw at any time). Respondents must actively select the “Agree” option to enter the questionnaire filling stage. If “Refuse” is selected, the questionnaire will automatically terminate. This process replaces verbal consent with an online mandatory confirmation mechanism, which not only aligns with the convenience of online surveys but also ensures the standardization and traceability of informed consent. Therefore, online questionnaire surveys can both adapt to the characteristics of dispersed and multi-channel blind box consumers and ensure sample quality and ethical compliance through standardized processes, providing a reliable data foundation for subsequent analysis of the impact mechanism of blind box products on consumers’ willingness to continue purchasing.

4. Empirical Research

4.1. Sample Demographic Characteristics

The online questionnaire survey for this study was conducted from February to July 2025, distributing questionnaires to consumers who had purchased blind box products through online platforms. All items, in addition to basic personal information, employed a Likert scale for scoring, ranging from 1 (strongly disagree) to 7 (strongly agree). All respondents voluntarily answered the questions with informed consent and could withdraw from the survey at any time. A total of 594 samples were collected in this study. Among them, 15 invalid samples were excluded, resulting in 579 valid samples, with an effective rate of 97.4%. The criteria for invalid samples were threefold: 1. Questionnaires completed in a very short time, such as those completed within 1 min; 2. Questionnaires with consistently identical responses; 3. Multiple submissions from the same IP address, with only one selected as the questionnaire data and the rest excluded. Furthermore, the questionnaire comprised 30 questions, with 579 valid questionnaires, yielding a parameter-to-sample size ratio of 1:19.3. This sample size meets the standard proposed by Jackson, where the ratio of parameters to sample size exceeds 1:10 [38]. Therefore, the data analysis was conducted based on this standard, primarily using software such as SPSS 22.0 and Smart PLS 4.0 for processing. Descriptive statistical analysis of sample demographic variables is presented in

Table 2. Demographic profile of sample (n = 579).

Sample	Category	Number	Percentage%
Gender	Male	296	51.1
	Female	283	48.9
Age	18–24	70	12.1
	25–34	148	25.6
	35–44	211	36.4
	45–54	100	17.3
	Over 55	50	8.6
Occupation	Student	40	6.9
	Freelance or self-employed	411	71.0
	Public officials or public institutions	58	9.7
	Others	72	12.4
Frequency of purchasing blind box products	More than once a day	28	4.8
	Once a day	107	18.5
	Once a week	221	38.2
	1 to 2 times a month	165	28.5
	Less than or equal to once a month	296	51.1

.

Based on an analysis of the sample size of blind box consumer data, with 579 valid samples, the sample size effectively covers diverse groups in terms of gender, age, occupation, and purchase frequency. The gender distribution is balanced (51.1% male, 48.9% female). The age range spans from 18 to 70 years old, with the core demographic (25–44 years old) accounting for over 60%. Occupations include freelancers (71.0%), public sector employees (9.7%), students (6.9%), and other diverse types. Purchase frequency varies from “multiple times a day” to “≤1 time per month.” These 579 samples not only reflect the overall characteristics of the blind box consumer group but also support differential analyses of different subgroups (such as high-frequency and low-frequency purchasers, and middle-aged and young people versus other age groups), meeting the sample diversity requirements needed to study “consumer willingness to continue purchasing.” As a niche entertainment consumption product, the core users of blind boxes are concentrated in the middle-aged and young groups (25–44 years old accounting for 62%), and high-frequency purchasers (once a week or more) total 61.5% (4.8% + 18.5% + 38.2%). The absolute numbers of each subgroup (such as 35–44 years old, freelancers) in the 579 samples (211 people, 411 people) align with the younger consumer profile of blind box products. This also aligns with the economic characteristics of blind box products, which also encourages many blind box consumers to pursue the social activities of their added value, which is why it is not difficult to understand why there are so many freelancers. It is evident that the survey data can effectively reflect the behavioral characteristics of this niche consumer group. The sample size scale is consistent with the “non-universal” group base characteristics of blind box consumption, avoiding resource waste caused by oversampling.

4.2. Reliability and Validity Analysis

Reliability refers to the consistency of results obtained when a measurement tool is used repeatedly, encompassing the accuracy, consistency, and robustness of the measurement [39]. In this study, SPSS 22.0 software was used to calculate the Cronbach’s α values for each measurement variable. According to relevant standards, when the Cronbach’s α value of the measurement results is greater than 0.6, it indicates that the scale data has accuracy and validity [40]. As can be seen from

Table 3. Reliability analysis results (n = 579).

Dimension	Items	Collinearity Statistics (VIF)	Corrected Item-to-Total Correlation	Cronbach’s α if Item Deleted	Cronbach’s α
IC	IC1	1.779	0.662	0.756	0.817
	IC2	1.857	0.679	0.739
	IC3	1.804	0.667	0.751
EA	EA1	1.881	0.680	0.736	0.816
	EA2	1.925	0.690	0.725
	EA3	1.677	0.635	0.781
SA	SA1	1.512	0.582	0.721	0.772
	SA2	1.659	0.629	0.668
	SA3	1.601	0.609	0.690
FA	FA1	1.891	0.686	0.760	0.827
	FA2	1.842	0.676	0.770
	FA3	1.918	0.692	0.755
NO	NO1	1.672	0.634	0.767	0.811
	NO2	1.869	0.681	0.719
	NO3	1.809	0.666	0.734
SE	SE1	1.606	0.614	0.698	0.777
	SE2	1.604	0.614	0.698
	SE3	1.595	0.611	0.701
ID	ID1	1.695	0.640	0.745	0.805
	ID2	1.764	0.658	0.727
	ID3	1.759	0.657	0.728
PV	PV1	1.614	0.615	0.747	0.795
	PV2	1.812	0.669	0.689
	PV3	1.682	0.632	0.728
PN	PN1	1.719	0.645	0.774	0.817
	PN2	1.810	0.663	0.755
	PN3	1.975	0.701	0.714
CPB	CPB1	1.630	0.621	0.770	0.807
	CPB2	1.824	0.668	0.723
	CPB3	1.857	0.677	0.714

, the Cronbach’s α values of each variable in this survey data are all greater than 0.7, and the total correlation after deleting items is greater than 0.5, and the Cronbach’s α value obtained after deleting any item is not higher than the current result. This series of results indicates that all items do not need to be deleted, and also indicates that the scale used in this study has good reliability. At the same time, the variance inflation factor (VIF) is an indicator for assessing multicollinearity among independent variables, used to measure the extent to which each predictor variable is linearly explained by other variables. The higher the VIF value, the more serious the multicollinearity problem [41]. Related studies have pointed out that when the VIF exceeds 5, it indicates that there is a certain degree of multicollinearity within the measurement scale [42]; and ideally, the VIF value should be less than 3.3 [43], at which time the correlation between predictor variables is low, and the regression estimate is more stable, which is conducive to constructing a robust analysis model. As can be seen from Table 3, the VIF values of all variables are less than 3.3, indicating that there is no multicollinearity problem. Overall, the Cronbach’s α coefficient (reliability indicator) and VIF value (multicollinearity indicator) in Table 3 together indicate that the measurement scale used in this study has good reliability and no multicollinearity problem, which provides support for constructing a stable and reliable analysis model.

To ascertain whether there was sufficient correlation between the variables for factor extraction, this study employed the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity to conduct exploratory factor analysis [44]. As shown in

Table 4. Exploratory factor analysis result (n = 579).

Dimension	Items	KMO	Bartlett Sphere Test	Factor Loading	Commonality	Eigenvalue	Total Variation Explained%
IC	IC1	0.718	0	0.851	0.724	2.197	73.224
	IC2			0.862	0.743
	IC3			0.854	0.730
EA	EA1	0.713	0	0.863	0.744	2.195	73.161
	EA2			0.869	0.755
	EA3			0.834	0.695
SA	SA1	0.697	0	0.811	0.658	2.062	68.719
	SA2			0.844	0.712
	SA3			0.831	0.691
FA	FA1	0.722	0	0.863	0.745	2.231	74.350
	FA2			0.857	0.734
	FA3			0.867	0.751
NO	NO1	0.712	0	0.835	0.697	2.176	72.531
	NO2			0.864	0.747
	NO3			0.856	0.732
SE	SE1	0.703	0	0.833	0.693	2.075	69.163
	SE2			0.832	0.692
	SE3			0.830	0.689
ID	ID1	0.713	0	0.841	0.707	2.158	71.924
	ID2			0.852	0.726
	ID3			0.851	0.725
PV	PV1	0.705	0	0.827	0.684	2.130	70.987
	PV2			0.862	0.742
	PV3			0.839	0.704
PN	PN1	0.713	0	0.840	0.705	2.198	73.269
	PN2			0.853	0.727
	PN3			0.875	0.766
CPB	CPB1	0.709	0	0.828	0.685	2.166	72.189
	CPB2			0.858	0.736
	CPB3			0.863	0.745

, the KMO values for each variable ranged from 0.697 to 0.722, all exceeding the critical value of 0.5. Simultaneously, the significance levels of Bartlett’s test of sphericity were all less than 0.05 and close to 0, indicating that the sphericity test results for all variables were significant, which suggests that the data had a good foundation for factor analysis [45].

Based on this, principal component analysis was further used to perform factor analysis on each variable. The results showed that each variable extracted only one factor with an eigenvalue greater than 1, and the cumulative variance contribution rate of each variable exceeded 50%, indicating that the extracted factors could better explain each variable. In addition, the commonality of all items was greater than 0.5, and the factor loading was greater than 0.6, both within the reasonable range suggested by previous studies [46]. Therefore, this study considers that the survey results have good unidimensionality.

Through confirmatory factor analysis, this study found that the factor loadings of each item in the scale were all greater than 0.5, indicating that all items included in each variable could consistently explain the variable. This consistency not only demonstrates that the items can effectively reflect the essence of the variable but also reflects that the scale has high stability and reliability in measuring the variable [47]. Based on the factor loadings of each item, this study further calculated the composite reliability (CR) and the average variance extracted (AVE). According to relevant standards, the CR value should not be less than 0.7, and the minimum standard for the AVE value is 0.5 [48]. As can be seen from

Table 5. Convergent validity analysis results (n = 579).

Dimension	Items	Unstandardized Factor Loading	Standardize Factor Loading	SE	p-Value	AVE	CR
IC	IC1	1	0.786	-	-	0.598	0.817
	IC2	1.007	0.770	0.048	0
	IC3	0.964	0.763	0.047	0
EA	EA1	1	0.779	-	-	0.600	0.818
	EA2	1.028	0.796	0.048	0
	EA3	0.979	0.747	0.050	0
SA	SA1	1	0.699	-	-	0.532	0.773
	SA2	1.103	0.768	0.061	0
	SA3	1.009	0.719	0.059	0
FA	FA1	1	0.789	-	-	0.615	0.828
	FA2	0.965	0.751	0.048	0
	FA3	1.066	0.811	0.048	0
NO	NO1	1	0.738	-	-	0.589	0.811
	NO2	1.110	0.803	0.055	0
	NO3	1.055	0.760	0.056	0
SE	SE1	1	0.746	-	-	0.537	0.777
	SE2	0.913	0.722	0.050	0
	SE3	0.941	0.731	0.051	0
ID	ID1	1	0.753	-	-	0.579	0.805
	ID2	1.031	0.759	0.053	0
	ID3	1.041	0.771	0.052	0
PV	PV1	1	0.719	-	-	0.567	0.797
	PV2	1.094	0.793	0.056	0
	PV3	1.020	0.745	0.057	0
PN	PN1	1	0.780	-	-	0.599	0.818
	PN2	0.875	0.749	0.045	0
	PN3	0.970	0.793	0.046	0
CPB	CPB1	1	0.738	-	-	0.584	0.808
	CPB2	1.065	0.771	0.055	0
	CPB3	1.062	0.783	0.056	0

Note: 0.5 is the lowest standard for AVE and CR value > 0.7.

, the factor loadings of each item in this study are all greater than 0.5, the CR values all exceed 0.773, and the square root of AVE is greater than 0.532, which indicates that the relevant variables have good convergent validity.

The Heterotrait–Monotrait Ratio (HTMT) is an index used to assess the discriminant validity of variables within a structural equation model. A HTMT value below 0.85 is generally considered to indicate that the variables exhibit satisfactory discriminant validity [49]. It is essential to evaluate these metrics to avoid issues of multicollinearity arising from highly correlated constructs. The results indicate that all HTMT scores are within acceptable limits (≤0.85), with values ranging from 0.537 to 0.805 (

Table 6. Discriminant validity–Heterotrait ratio (HTMT) (n = 579).

Latent Variable	CPB	EA	FA	IC	ID	NO	PV	SA	SE	SP
CPB
EA	0.801
FA	0.805	0.650
IC	0.764	0.654	0.614
ID	0.735	0.602	0.614	0.560
NO	0.798	0.633	0.648	0.573	0.602
PV	0.764	0.659	0.680	0.595	0.615	0.659
SA	0.737	0.608	0.625	0.607	0.580	0.628	0.625
SE	0.729	0.585	0.574	0.537	0.559	0.584	0.590	0.564
SP	0.795	0.590	0.644	0.599	0.612	0.606	0.631	0.585	0.562

). Therefore, it can be concluded that there is sufficient evidence to support the model’s discriminant validity in this study.

Discriminant validity is employed to assess the degree of differentiation among latent variables. Following the recommendations of Fornell-Larker, a scale demonstrates satisfactory discriminant validity when all related values do not exceed 0.9 [50]. As indicated in

Table 7. Correlation coefficient and average extraction variance (n = 579).

Latent Variable	CPB	EA	FA	IC	ID	NO	PV	SA	SE	PN
CPB	0.850
EA	0.801	0.855
FA	0.814	0.823	0.862
IC	0.805	0.818	0.820	0.856
ID	0.794	0.823	0.825	0.821	0.848
NO	0.800	0.809	0.823	0.798	0.814	0.852
PV	0.795	0.819	0.817	0.812	0.804	0.809	0.843
SA	0.789	0.793	0.801	0.806	0.800	0.801	0.804	0.829
SE	0.785	0.798	0.800	0.791	0.800	0.796	0.787	0.788	0.832
PN	0.804	0.796	0.799	0.812	0.807	0.809	0.792	0.770	0.781	0.856

Note: All related values do not exceed 0.9.

, the square root of the Average Variance Extracted (AVE) for each latent variable surpasses its correlation coefficients with other latent variables, and all correlation coefficients are below 0.858. This suggests significant correlations among the variables, yet they remain distinct with clear differentiation. Consequently, the measurement model in this study exhibits robust discriminant validity.

4.3. Model Testing

SRMR is a frequently used metric in structural equation modeling (SEM) to assess the goodness of fit between the model and the data, with smaller values indicating a better fit. Research indicates that SRMR performs well in ordered factor analysis models, especially when the data distribution deviates from normality, yielding more reliable results. A SRMR value below 0.08 suggests an excellent model fit to the data [51]. Furthermore, a d-ULS value less than 0.95 indicates a good model fit with an appropriate number of free parameters [52]; the same interpretation applies to a d-G value below 0.95 [53]. NFI, with a threshold of greater than 0.8, is another indicator of good model fit, with values closer to 1 indicating a more accurate capture of the structure and relationships within the data [54]. As shown in

Table 8. Model fit measures.

Common Indices	d-ULS	d-G	SRMR	NFI
Criteria	<0.95	<0.95	<0.08	>0.8
Values	0.779	0.643	0.041	0.845

, the SRMR value in this study is 0.041, below the critical value of 0.08, indicating a good model fit. The d-ULS value of 0.779 and the d-G value of 0.643 are both less than 0.95, further validating the model fit and the rationality of the parameter settings. The NFI value is 0.845, exceeding 0.8, which suggests a high degree of model fit. Overall, the structural equation model demonstrates an ideal fit with the data.

4.4. Path Hypothesis Analysis

The hypotheses were tested using PLS-SEM (Partial Least Squares Structural Equation Modeling). Bootstrapping with 5000 resamples was employed, and a p-value less than 0.05 was considered statistically significant. The results of the hypothesis model path coefficient test, as shown in

Table 9. Hypothesis model path relationship test.

Hypothesis	Path	β Co-Efficient	T Statistics	p Values	Decision
H1a	IC → PV	0.153	3.533	***	Accept
H1b	IC → PN	0.216	5.109	***	Accept
H1c	IC → CPB	0.116	2.822	***	Accept
H2a	EA → PV	0.184	4.290	***	Accept
H2b	EA → PN	0.113	2.776	** 0.006	Accept
H2c	EA → CPB	0.102	2.266	* 0.014	Accept
H3a	SA → PV	0.156	3.521	***	Accept
H3b	SA → PN	0.041	0.914	ns, 0.361	Not Accept
H3c	SA → CPB	0.105	2.562	** 0.010	Accept
H4a	FA → PV	0.153	3.781	***	Accept
H4b	FA → PN	0.105	2.270	0.023	Accept
H4c	FA → CPB	0.153	3.460	*** 0.001	Accept
H5a	NO → PV	0.149	3.904	***	Accept
H5b	NO → PN	0.208	4.456	***	Accept
H5c	NO → CPB	0.100	2.203	* 0.028	Accept
H6a	SE → PV	0.087	2.262	* 0.024	Accept
H6b	SE → PN	0.110	2.678	** 0.007	Accept
H6c	SE → CPB	0.093	2.222	* 0.026	Accept
H7a	ID → PV	0.086	2.075	* 0.038	Accept
H7b	ID → PN	0.161	3.442	*** 0.001	Accept
H7c	ID → CPB	0.043	0.958	ns, 0.338	Not Accept
H8	PV → CPB	0.084	2.011	* 0.044	Accept
H9	PN → CPB	0.171	4.014	** 0.010	Accept

Note: Significance of p value: *** represents p ≤ 0.001, ** represents p ≤ 0.01, * represents p ≤ 0.05.

, indicate the following: IP characteristics (IC) have a positive and significant impact on Perceived Value (PV) (β = 0.153, T = 3.533, p = 0.000 < 0.05), Perceived Needs (PN) (β = 0.216, T = 5.109, p = 0.000 < 0.05), and Continuous Purchasing Behavior (CPB) (β = 0.116, T = 2.822, p = 0.005 < 0.05), thus supporting hypotheses H1a, H1b, and H1c. Economic attributes (EA) positively and significantly influence Perceived Value (PV) (β = 0.184, T = 4.290, p = 0.000 < 0.05), Perceived Needs (PN) (β = 0.113, T = 2.776, p = 0.006 < 0.05), and Continuous Purchasing Behavior (CPB) (β = 0.102, T = 2.266, p = 0.014 < 0.05), thereby supporting hypotheses H2a, H2b, and H2c. Social attributes (SA) have a positive and significant impact on Perceived Value (PV) (β = 0.156, T = 3.521, p = 0.000 < 0.05) and Continuous Purchasing Behavior (CPB) (β = 0.105, T = 2.562, p = 0.010 < 0.05), supporting hypotheses H3a and H3c, but no significant impact on Perceived Needs (PN) (β = 0.041, T = 0.914, p = 0.361 < 0.05), thus rejecting hypothesis H3b. Fun attributes (FA) positively and significantly influence Perceived Value (PV) (β = 0.153, T = 3.781, p = 0.000 < 0.05), Perceived Needs (PN) (β = 0.105, T = 2.270, p = 0.023 < 0.05), and Continuous Purchasing Behavior (CPB) (β = 0.153, T = 3.460, p = 0.001 < 0.05), supporting hypotheses H4a, H4b, and H4c. Nondeterminacy (NO) has a positive and significant impact on Perceived Value (PV) (β = 0.149, T = 3.904, p = 0.000 < 0.05), Perceived Needs (PN) (β = 0.208, T = 4.456, p = 0.000 < 0.05), and Continuous Purchasing Behavior (CPB) (β = 0.100, T = 2.209, p = 0.028 < 0.05), supporting hypotheses H5a, H5b, and H5c. Satisfying the experience (SE) positively and significantly influences Perceived Value (PV) (β = 0.087, T = 2.262, p = 0.024 < 0.05), Perceived Needs (PN) (β = 0.110, T = 2.678, p = 0.007 < 0.05), and Continuous Purchasing Behavior (CPB) (β = 0.093, T = 2.222, p = 0.026 < 0.05), supporting hypotheses H6a, H6b, and H6c. Identity (ID) has a positive and significant impact on Perceived Value (PV) (β = 0.086, T = 2.075, p = 0.038 < 0.05) and Perceived Needs (PN) (β = 0.161, T = 3.442, p = 0.001 < 0.05), supporting hypotheses H7a and H7b, but no significant impact on Continuous Purchasing Behavior (CPB) (β = 0.043, T = 0.958, p = 0.338 < 0.05), thus rejecting hypothesis H7c. Perceived Value (PV) positively and significantly influences Continuous Purchasing Behavior (CPB) (β = 0.084, T = 2.011, p = 0.044 < 0.05), supporting hypothesis H8. Perceived Needs (PN) positively and significantly influences Continuous Purchasing Behavior (CPB) (β = 0.171, T = 4.014, p = 0.010 < 0.05), supporting hypothesis H9.

The results of hypothesis testing are shown in the above table, as shown in Figure 2.

5. Discussion

The sustained purchasing intention of consumers directly impacts the sustainable development of blind box products and the blind box economy, given their rapid growth. The emergence of blind box products has led to certain social issues and misunderstandings within the current social environment. Therefore, studying consumers’ sustainable purchasing intention for blind box products is crucial for promoting their sustainable development. In response to some consumers’ misunderstandings of blind box products, this paper will explore the influence mechanism on consumers’ sustainable purchasing intention based on the S-O-R model, combined with the characteristics of blind box products, marketing strategies, perceived value, and perceived needs. Empirical analysis will be conducted on the collected sample data using a structural equation model, as detailed below:

Based on the hypothetical model data, perceived needs (PN) have the most significant impact on consumers’ continuous purchase behavior (CPB) among all variables (T = 4.014), indicating that consumers’ recognition of perceived needs is the core factor determining their continuous purchases. The data also show that IP characteristics (IC) (T = 5.109), uncertainty (NO) (T = 4.456), and economic attributes (EA) (T = 4.290) all significantly impact perceived needs (PN) and perceived value (PV), according to the view that “the higher the T-value, the greater the significance” [55]. The impact of IP characteristics on perceived needs is particularly significant, followed by uncertainty, which means that the IP attributes of products (such as cultural connotations and brand symbols) and the emphasis on uncertainty in marketing (such as random experiences and scarcity) are more likely to trigger consumers’ emotional resonance and needs, thereby strengthening their continuous purchasing intention. The view that IP-linked products enhance consumers’ value perception, thereby influencing their purchasing decisions, is consistent with Huang’s findings [56]. The verification of uncertainty in marketing strategies on consumers’ sustainable purchasing intention further highlights the innovation and practical significance of this study. Furthermore, unlike models in some studies that directly link a single attribute to purchasing behavior, this paper uses perceived value and perceived needs as mediating variables, connecting multi-dimensional antecedents such as IP characteristics and economic attributes with continuous purchase behavior. This highlights the key role of consumers’ dual cognition of product “value” and “needs” in consumption decisions—both focusing on whether the product can meet actual needs and whether it can convey self-identity or social signals. This design effectively reveals the complex psychological mechanisms behind consumer behavior, thereby validating the rationality of setting the two mediating variables.

Antecedent variables such as IP characteristics, economic attributes, and hedonic attributes all significantly influence perceived value and perceived needs. In terms of data significance, the path by which IP characteristics affect perceived needs (T = 5.109) has the most prominent impact on continuous purchase behavior, while the hypothesis regarding the influence of social attributes (SA) on perceived needs (T = 0.914, p = 0.361) is not supported. This indicates that users’ demand cognition based on product characteristics has a clear and stable driving effect on continuous purchases, whereas the influence of social attributes has boundaries. This may be because, in the current consumption scenario, users are more concerned with the product’s association with themselves rather than the social attributes at the group level, or because social attributes need to indirectly affect perceived needs through more complex intermediary chains (such as word-of-mouth communication). The viewpoint in this result, that the demand cognition formed by product characteristics drives continuous purchases, is consistent with Edward’s view that consumers’ cognition of product characteristics (such as whether the product meets their needs and whether it is unique) affects their continuous purchase behavior [57]. At the same time, the viewpoint that users are more concerned with the product’s association with themselves rather than the social attributes at the group level echoes Bhattacharya’s view that consumers are more concerned with obtaining self-identity from the product [35]. This suggests that consumers are more inclined to satisfy their self-needs (such as self-realization and self-identity) through products, rather than driving consumption behavior through social attributes (such as a sense of belonging). In continuous purchase decisions, consumers value the product’s value (such as cost-effectiveness brought by economic attributes) and also rely on the emotional and identity recognition brought by perceived needs (such as cultural preferences conveyed by IP characteristics). Although social attributes do not significantly affect emotional needs, their significant positive effects on perceived value (T = 3.521) and continuous purchase behavior (T = 2.562) validate their necessity as antecedent variables. This design breaks through the limitations of traditional research focusing on a single attribute and reveals the driving mechanism of consumer behavior from multiple dimensions (practical and emotional), especially by incorporating variables such as “uncertainty” and “hedonic attributes,” capturing the importance of “experience” and “entertainment” in current consumption, reflecting the innovation of the research.

Identity (ID) indirectly influences continuous purchase behavior by affecting perceived value (T = 2.075) and perceived needs (T = 3.442), but has no direct significant impact on continuous purchase behavior (T = 0.958, p = 0.338). This suggests that identity needs to influence actual purchase behavior through value perception, rather than directly driving decisions. Existing literature has limited discussion on the indirect impact path of identity on continuous purchase behavior. This paper takes multi-attribute products as the research object and verifies that identity influences continuous purchase through shaping users’ judgment of product value and interpretation of their own needs, thereby expanding new empirical support for related theories. Relevant studies mainly explore the relationship between identity and consumer behavior, consumption patterns, and lifestyles [58]. Among the various attribute dimensions, except for the social attribute, which has no significant impact on perceived needs, IP characteristics, economic attributes, interesting attributes, uncertainty, and experience satisfaction are all significantly related to continuous purchase behavior. The direct impact of perceived needs on continuous purchase (T = 4.014) is stronger than that of perceived value (T = 2.011), indicating that in the current consumption context, product needs drive consumers’ long-term choices more than value, which also fully reflects the “blind box attribute” characteristics of blind box products. The reason for the insignificant impact of social attributes may be that: respondents’ perception of the social value of the product is relatively vague, and the description in the item about “discussing the styles drawn from the blind box with others can enhance communication” has not effectively reached their core needs; or in this consumption scenario, the priority of individual-level needs recognition is higher than that of group-level social attributes. Similar views that individuals take precedence over groups have also been reached in related studies. For example, some scholars believe that individual self (rather than relationships or collectives) and individual identity have motivational priority, and that individuals’ responses to threats and enhancements are more strongly directed towards the individual self rather than the collective self [59]. This supports the view of this study that the priority of individual-level needs recognition is higher than that of group-level. Similarly, some scholars’ research holds the view that the group level takes precedence over individual needs, for example, in the environmental field, group identity takes precedence over individual identity [60]. Therefore, from the conclusions of this study and the comparison of related studies, the priority of individuals and groups is determined according to the specific circumstances of different types, rather than being absolutely established.

This study offers a theoretical contribution to the understanding of consumer repurchase behavior in multi-attribute blind box products. By incorporating IP characteristics and economic attributes as antecedent variables, and perceived value and perceived needs as mediating variables, this research systematically investigates their impact on continuous purchase behavior. Furthermore, the inclusion of variables such as identity enhances the model’s predictive stability. This approach not only enriches the “attribute-perception-behavior” chain within consumer behavior theory but also provides targeted insights for businesses to optimize product design (e.g., strengthening IP symbols, balancing value and emotional significance) and marketing strategies (e.g., emphasizing identity, enhancing user experience).

6. Conclusions and Suggestions

This study, based on the S-O-R model, investigates the mechanism by which blind box product features and marketing strategies influence continuous purchase behavior through perceived value and perceived needs. The main conclusions are as follows: Perceived need is the most critical factor influencing consumers’ continuous purchase of blind boxes, with IP characteristics and uncertainty having a particularly significant impact on perceived needs, highlighting the core role of emotional resonance and experiential stimulation in long-term consumption. Consumers form a dual cognitive understanding of the “value” and “need” of blind boxes, which jointly mediate the relationship between product attributes and continuous purchase behavior, breaking through the traditional understanding of single-attribute-driven behavior. IP characteristics, economic attributes, and other factors all have a significant positive impact on continuous purchase behavior, but social attributes do not significantly affect perceived needs, reflecting that individual needs are prioritized over group social attributes in blind box consumption. Identity recognition needs to indirectly influence continuous purchase behavior through perceived value and perceived needs, verifying the “identity–perception–behavior” transmission logic and expanding the relevant theoretical field. Based on the above, the following practical suggestions are proposed: In product design, IP characteristics should be strengthened to enhance emotional connection, and economic and fun attributes should be balanced to take into account both value and experience. In marketing strategies, uncertainty needs to be reasonably utilized, and transparent rules should be used to reduce consumers’ resistance. At the same time, focus on individual needs, highlight appeals such as “self-satisfaction,” and weaken group social attribute guidance. In terms of industry development, rational consumption should be guided, and perceived value should be enhanced by improving product quality. Social attribute marketing should be standardized to reduce the risk of irrational consumption. Membership systems can also be used to strengthen identity recognition and reduce short-term speculative purchases, promoting the blind box economy from “traffic dependence” to “value-driven” transformation and achieving sustainable development.

6.1. Theoretical Contributions

This study holds multifaceted theoretical value, extending the application of existing models, elucidating consumption-driving mechanisms, and offering an in-depth perspective on the insignificant impact of social attributes on perceived needs. Firstly, at the theoretical level, the introduction of the S-O-R model into the blind box consumption domain transcends its traditional application scenarios, validating its explanatory power in emerging consumption formats and providing a model reference for similar studies. This perspective broadens the application of the S-O-R model, which has been utilized in various fields such as retail, online shopping, virtual reality, and consumer behavior [61]. Secondly, it reveals a dual-driving mechanism of “value” and “need,” breaking the limitations of traditional single-focus on functional or emotional value, and supplementing new empirical evidence for consumption motivation theory. This empirical study aligns with Sheth’s theory of consumption value [62] and expands into new empirical research. Thirdly, the supplemented variable relationship evidence has theoretical completeness: it verifies the strong driving effect of IP characteristics on perceived needs, supporting brand equity theory; it incorporates “uncertainty” and confirms its role, enriching the theory of perceived risk and value; and it clarifies the indirect path of identity recognition, refining the theory of consumer self-identification [35]. Fourthly, it clarifies that individual needs take precedence over group social attributes, providing a new case for the study of consumption motivation context dependence, contrasting with Belk’s research [63], which emphasizes the dominant role of group social interaction. The finding that social attributes have an insignificant impact on perceived needs warrants attention. The reasons include blind box consumption emphasizes individual emotional sustenance and the satisfaction of collecting desires, rather than social recognition or social interaction; the collection attribute makes consumers focus more on individual preferences and collection progress, weakening the influence of social attributes; and community exchanges are mostly for interest sharing, not the main driver of consumption. Furthermore, the extension of theoretical research also provides guidance for the marketing strategies of blind box companies, suggesting more focus on individual needs and emotional value satisfaction, such as strengthening IP creation and product uniqueness design.

6.2. Practical Contributions

In practical applications, blind box enterprises need to translate theoretical guidance into feasible operational plans, especially in balancing “uncertainty” with ethical marketing and optimizing product design to guide sustainable consumption. This can be approached through specific pathways: In balancing “uncertainty” with ethical marketing, enterprises can set boundary thresholds for “uncertainty.” By using data to measure consumers’ tolerance for the “unobtained feeling,” for example, setting the hidden model draw probability of a single series of blind boxes to no less than 1/100, and displaying real-time probabilities in the purchase page in the form of dynamic charts (e.g., “327 people have purchased, and the hidden model has been drawn 2 times”), and at the same time launching a “guaranteed mechanism,” stipulating that when consumers accumulate a certain number of purchases (such as 20) without drawing the hidden model, they can directly redeem it with the purchase record, which both retains the surprise of the unknown and avoids overconsumption caused by “gambling psychology”; it can also establish a “transparent traceability” system, using blockchain technology to record the production and circulation data of each blind box. Consumers can scan the code to view the product’s production batch, quality inspection report, and the style distribution of blind boxes sold in the same batch. For the second-hand trading market, the platform can access official traceability data to crack down on the act of counterfeiting rare blind box products, weaken speculative consumption motives through information symmetry, and enhance consumers’ ethical trust in the brand. In product design, taking into account demand and sustainable consumption, modular product design can be adopted, disassembling blind box products into basic modules and personalized modules. For example, the body of a trendy toy blind box is a universal basic model, and the head and accessories are replaceable modules. Consumers can purchase modules separately, which both meets the demand for “collecting different styles” and reduces waste caused by repeatedly purchasing complete products. At the same time, it can try to launch an “old module recycling program,” and the recycled modules are disinfected and repackaged for sale, giving the product a second life; it can also try to establish a “consumption-environmental protection” linkage mechanism, marking the carbon emissions in the production process of each blind box. After consumers accumulate a certain number of purchases, the brand plants the corresponding number of trees in the name of the consumer (and provides an electronic certificate for verification). For “hidden models,” set up an “environmental protection exchange channel”—consumers can donate 3 complete, unopened idle blind boxes (donated to public welfare organizations by the brand) to directly exchange for 1 hidden model, which both reduces the impulse to over-purchase to draw hidden models and promotes the reuse of idle resources. Therefore, through the above specific measures, blind box enterprises can both retain the core appeal of the product and find a balance between commercial interests and social responsibility, gradually guiding the industry to transform from “traffic-driven” to “sustainable value-driven.”

6.3. Suggestions

This study systematically investigates the sustained purchasing behavior of blind box consumers, while acknowledging areas for future development. Regarding the sample, this research encompasses consumers from diverse regions and income levels, with a higher proportion of freelancers and younger respondents. This phenomenon can be attributed to two factors: the prevalence of youth-oriented consumption in blind box products and the societal trend of young consumers pursuing the added value associated with these products. Consequently, the overrepresentation of freelancers is understandable. Future research should incorporate consumers from various occupational groups (e.g., employed individuals, students) and age groups (e.g., middle-aged, elderly) to explore potential significant differences in consumption attitudes and purchase motivations, thereby broadening the study’s generalizability. Subsequent studies should comprehensively reflect the behavioral mechanisms of blind box consumers across different demographics.

From a variable perspective, the current research does not include potential moderating variables with negative impacts, such as “addiction” and “collection motivation intensity.” Future research can incorporate these variables to comprehensively address the influence mechanisms between the ethical attributes of blind box products and consumer behavior, thereby enhancing the study’s comprehensiveness. Furthermore, due to the cross-sectional data used in this study, the tracking of long-term changes in consumer purchasing behavior is limited. Future longitudinal studies can be conducted to reveal the dynamic evolution of variable relationships over time, providing a better understanding of the long-term patterns of consumer purchasing behavior.

In addition, the following directions for future research are proposed: First, conduct cross-cultural comparative studies. Given potential differences in consumers’ perceptions of IPs and uncertainty across different cultural backgrounds, comparing consumer behavior across various countries or regions can provide new perspectives and directions for expanding this theory. Second, investigate the consumer behavior mechanisms of digital blind boxes (e.g., non-fungible tokens, virtual blind boxes in gamified applications). With the development of the digital economy, digital blind boxes are becoming a new hotspot in the consumer market. Studying the purchase motivations and sustained purchasing behavior of their consumers can make the research more relevant to the times. Third, continue to advance longitudinal studies of consumer behavior, tracking changes in consumer purchasing behavior over the long term, and providing more targeted references for businesses in formulating long-term marketing strategies.