Technology-Enabled Cross-Platform Disposal of Idle Clothing in Social and E-Commerce Synergy: An Integrated TPB-TCV Framework

Abstract

This study integrates the Theory of Planned Behavior and the Theory of Consumption Values through a mixed-methods approach (structured interview and structural equation model) to investigate cross-platform disposal behaviors for idle clothing on social media and second-hand platform ecosystems. The study reconstructs traditional theoretical variables: psychological motivation dimension (platform-enabled green attitude, social circle environmental demonstration, and cross-platform behavioral control) and perceived value dimension (functional integration value perception, socialized emotional empowerment, and community identity value). Key findings: Cross-platform behavioral control is the strongest predictor of behavioral intention. In the value dimension, emotional value has the strongest direct impact on disposal intentions, functional integration is key to enhancing behavioral control, and community identity value most significantly impacts the platform-enabled green attitude and the social circle environmental demonstration. Finally, proposing a governance framework of “technological empowerment–emotional resonance–identity motivation”, offering theoretical foundations for optimizing platform interoperability and formulating digital environmental policies.

1. Introduction

Municipal solid waste generated globally has exceeded 2 billion tons per year [1], of which waste textiles have dual attributes of resource and pollution, and the recovery rate of the textile industry as the third largest pollution industry is less than 1%, highlighting the urgency of waste textiles management [2]. As the world’s largest textile producer and consumer, China faces acute serious challenges: the historical accumulation of waste textiles exceeds 400 million tons, with annual growth of 20 million tons [3,4]. Traditional landfill and incineration disposal methods not only waste resources but also cause environmental pollution, such as the leakage of macroplastic and the release of dioxin and other persistent toxic pollutants, posing a long-term threat to ecosystems and public health [5,6]. Although the Chinese government has explicitly included a 30% recycling rate for waste textiles in 2030 [7], a “high retention–low circulation” paradox persists in reality: 40% of consumers choose to hoard used clothing, while national recycling rate is maintained at 15% [8,9]. This dilemma needs to be resolved by deconstructing decision-making psychology at the micro level. In this context, academics have begun to pay attention to the role of digital technology in reshaping environmental behavior, and there have been studies exploring the mechanisms of disposal behavior in the context of social media or e-commerce platforms, but the synergistic effect of social media and e-commerce platforms has been neglected. This direction is highly compatible with the focus of emerging e-commerce research on the exploration of technology-enabled sustainable consumption.

The emergence of social media and its synergy with e-commerce platforms has provided new paths for the dissemination and transformation of environmental behavior. User-generated content (UGC), as the core carrier of social media, reshapes the value perception and disposal path of idle clothing through a threefold mechanism: Firstly, in value visualization, users visualize the implicit attributes of clothing, e.g., aesthetic value and emotional memory through pictures and textual notes, dynamically influencing the consumers’ perceived value assessment [10]. Secondly, in normative visualization, algorithmic recommendation systems provide new venues for normative influence [11]. Algorithmic targeted recommendation of environmental content transforms green disposal from private behavior to community consensus. Thirdly, in behavior demonstration, UGC platform users share disposal experiences from second-hand platforms, forming replicable behavioral templates of green disposal through community interaction [12]. The synergistic ecology of UGC platforms represented by REDnote (320 million monthly active users, 90% UGC content) and second-hand trading platforms represented by Xianyu (over 500 million users, average daily transaction volume exceeding CNY 1 billion) provides an ideal scenario for observing this mechanism [13,14]. For example, the “Idle Fish Partner” activity incentivizes users to create second-hand trading tutorials; although focusing on interest categories and local services, its core logic of activating the circulation of idle can be borrowed from the green disposal of clothing, reflecting the generality of the synergy between social networking and e-commerce in cracking the dilemma of idle resources. A comparison of single-platform and cross-platform disposal behaviors is shown in

Table 1. Comparison of single-platform and cross-platform disposal.

Comparison Dimension	Traditional Single-Platform Disposal	Cross-Platform Synergistic Disposal	Theoretical Significance
Psychological motivation	Driven by economic rationality	Cognitive–emotional–utility synergistically driven (three synergistic effects of UGC: cognitive regulation, emotional resonance, and item utility evaluation)	Breaking through rational choice theory, integrating TPB and TCV for a more comprehensive understanding of the psychological mechanisms of cross-platform online disposal
Decision-making path	Linear path	Spiral path (content generation–community interaction–cross-platform behavior–content regeneration)	Revealing the self-reinforcing logic of user behavior in the cross-platform ecosystem
Technology involved	Instrumental support	Collaborative ecological empowerment (disposal experience in UGC, lightweight interactions and commodity data integration in second-hand trading platforms)	Redefining “perceived behavioral control” to make TPB more suitable for the characteristics of technology–behavior coupling in the digital ecosystem
Influence	Private transactions are predominant	Social impact of environmental behavior (online disposal behavior is spread by UGC to create a demonstration effect of environmental behavior)	Expanding the influence of social norms and focusing on the synergistic effect of multi-platform technology

.

Current research exhibits theoretical gaps in explaining idle clothing disposal behaviors. Although the Theory of Planned Behavior (TPB) and the Theory of Consumption Value (TCV) are complementary in explaining pro-environmental behaviors—TPB emphasizes the direct drive of psychological motivation [15] and TCV focuses on multidimensional value trade-offs [16]—their integration is still underdeveloped. Evidence suggests that value dimensions can indirectly influence behavioral intentions through TPB variables [17], and UGC features can affect decision-making by reshaping perceived value [10]. However, limitations persist: Firstly, it mainly focuses on green purchasing behaviors [18], with insufficient attention to disposal practices under the synergistic effect of UGC platforms and second-hand platforms. Secondly, the analysis of social media influence pathways mainly focuses on the single-dimensional influence of interaction or algorithmic recommendation [19,20] and fails to reveal the psychological value interaction mechanism of cross-platform behavior transmission. Based on this, this study constructs an integrated TPB-TCV model to elucidate the value-psychological mechanism underlying cross-platform green disposal on social media UGC platform and second-hand trading platform ecosystems. Specifically, this study attempts to reveal how UGC platforms influence behavioral intention through dynamic cognitive construction (platform-enabled green attitude), interaction and algorithmic mediation norms (social circle environmental demonstration), technology enabling control (cross-platform behavioral control), and reconstructed perceived value, as well as how functional integration value, socialized emotional empowerment, and community identity drive decision-making through cross-platform synergy.

This study provides theoretical insights into the complex mechanism of idle clothing disposal in the digital ecosystem and offers a theoretical basis for platforms to optimize cross-platform interoperability design and formulate digital environment strategies, aiming to mobilize the public to participate in the practice of idle item recycling and alleviate environmental pressure. At the individual level, green disposal not only creates economic value and frees up space but also provides a sense of environmental achievement. It transforms the disposal process into a positive experience and a way to realize self-worth. Ultimately, achieving a win-win situation for environmental benefits and citizens’ well-being.

2. Theoretical Foundations and Literature Review

2.1. Theory of Planned Behavior and Theory of Consumption Value

The Theory of Planned Behavior (TPB) posits that behavioral intention—an antecedent variable of actual behavior—is shaped by three factors: attitudes (ATT), subjective norms (SN), and perceived behavioral control (PBC) [15]. The theory has been widely validated in environmental behavior studies, including waste recycling [21] and sustainable retail [22]. However, TPB shows some limitations in explaining digital environmental behaviors: Firstly, there is scarce research on clothing disposal behaviors in developing economies [23]. Secondly, traditional TPB assumes that the core variables are static and stable [24], ignoring how social media dynamically reshapes attitudes and norms [25]. Thirdly, based on TPB, the impact of social platforms technical features (algorithm recommendation and tool empowerment) on users’ pro-environmental psychology still needs to be further explored [26].

The Theory of Consumption Value (TCV) analyzes decision-making through multiple value dimensions. Consumers evaluate perceived value by balancing product utility against acquisition costs, forming the foundation of decisions [27]. Sheth, Newman, and Gross [16] further deconstructed perceived value into functional, emotional, and social values, laying the theoretical foundation for subsequent research. TCV has been successfully applied to green consumption and e-waste recycling behavior [28,29]. However, there are still limitations in TCV application in collaborative social and e-commerce scenarios. On the one hand, the existing cross-study of UGC and TCV focuses on the value assessment in green purchasing [10] and does not explain the value evolution mechanism in the idle clothing disposal stage. On the other hand, in green disposal, the pathway of how UGC interaction and algorithmic recommendation drive behavioral motivation through multidimensional value is unclear. For example, users’ emotional attachment to possessions may inhibit disposal intentions [30]. However, the path for social platforms to dissolve such barriers through emotional reconfiguration is unclear.

Therefore, the study integrates TPB and TCV to develop a “value perception–psychological motivation–disposal behavior” model, specifically examining users’ dynamic decision-making mechanisms in collaborative ecosystems of social media and e-commerce platforms.

2.2. Qualitative Research and Scenario-Based Variable Reconstruction

2.2.1. Qualitative Research

In order to break through the explanatory limitations of traditional theoretical variables in social media and e-commerce contexts, this study employs a qualitative research method to investigate the underlying logic of users’ cross-platform idle clothing green disposal behavior. Based on the characteristics of the synergistic scenarios of social UGC platforms (e.g., REDnote) and second-hand trading platforms (Xianyu), we adopted the structured interview method and designed a semi-structured interview outline (Appendix A) containing seven core dimensions, e.g., value perception, psychological motivation, and behavioral triggers. Firstly, we start with cognitive triggering questions (Question 1) and then use questions to ask respondents about the impact of perceived social norms (Question 2) and their experience of operational difficulties (Question 3) to construct a behavior-driven framework. On this basis, the evolution of perceived value in the decision-making process is tracked through multidimensional value cognition questions (Questions 4, 5, and 6). Finally, we use behavioral recall incentive and motivation questions to infer the behavioral intentions of the respondents (Question 7). We systematically collected data from initial content exposure to cross-platform disposal behavior through one-on-one in-depth interviews (30–45 min per session).

Given that users of UGC platforms and second-hand trading platforms are concentrated in youths under 35 [31,32], the study limited the age of respondents to this range. Stratified sampling was used to cover users from tier 1 to 4 cities to ensure heterogeneous characterization of geographic distribution, economic level, and behavioral patterns. The 32 respondents were recruited with behavioral records of clothes disposal through second-hand disposal platforms at least three times in the past year and possessing social media sharing experience. We provided the interviewee with an outline before the interview to prepare in advance, thereby improving the quality of the interview. All interviews were recorded and transcribed word for word with consent. To ensure reliability and validity, the triangulation method was used to cross-compare interview texts, second-hand platform behavior logs (e.g., Xianyu records), and social media UGC content (e.g., REDnote notes). Three relevant professional graduate students were invited to independently code part of the text, and two field professors reviewed the coding results, laying a solid empirical foundation for the theoretical model.

NVivo was used to code and label the interview data. In the open coding stage, the 280,000-word interview text was broken down paragraph by paragraph, focusing on the key expressions of user descriptions of cross-platform disposal behavior. Through repeated comparison and merging of repeated semantic units, 12 initial concepts such as “content attitude reinforcement” and “light-interaction constraint” were extracted; in the main axial encoding stage, 6 core categories were formed through association analysis and clustering of initial concepts (see

Table 2. Qualitative research and scenario reconstruction result.

Traditional Variable	Scenario-Based Variable	Initial Concepts	Scenario-Based Variable Definition
Attitude (ATT)	Platform-enabled green attitude (PEGA)	Content attitude reinforcement	A dynamic environmental behavior evaluation system formed by users through content interaction (e.g., liking environmental notes) on social platforms (e.g., REDnote) and disposal practices (e.g., one-click resale function) on second-hand platforms (e.g., Xianyu).
		Technology attitude transformation
Subjective norms (SN)	Social circle environmental demonstration (SCED)	Light-interaction constraint	Algorithmic recommendation mechanisms and community interaction behavior jointly construct new social norms. Users form the perception of “majority agreement” through high-frequency exposure to green disposal content and internalize the norms through lightweight interactions.
		Algorithm norms-construction
Perceived behavioral control (PBC)	Cross-platform behavioral control (CPBC)	Tool synergy utility	Users’ assessment of the difficulty of implementing green disposal behaviors using two-platform collaborative tools (e.g., REDnote tutorials and Xianyu fast recycling).
		Operational friction perception
Perceived functional value (PFV)	Functional integration value perception (FIVP)	Decision knowledge Integration	Users integrate the value of social media content (e.g., disposal experience) with the value of second-hand platform tools (e.g., market data) to perceive the practical utility of a product or behavior.
		Tool efficiency integration
Perceived emotional value (PEV)	Socialized emotional empowerment (SEE)	Collective emotional resonance	Users form emotional perceptions of products or behaviors through UGC with emotion (e.g., the topic of “donating idle clothing during graduation season”) and algorithmic recommendation mechanisms.
		Algorithm emotional priming
Perceived social value (PSV)	Community identity value (CIV)	Virtual identity recognition	Users construct digital identities through lightweight interactions (e.g., liking sustainable life tags) and content imitation.
		Content-imitation perception
Clothing disposal intention (CDI)	Cross-platform collaborative disposal intention (CPCDI)	-	The behavioral tendency of users in the dual-platform collaborative ecology.

). For example, “content attitude reinforcement” and “technology attitude transformation” are classified as attitude dimensions.

2.2.2. Scenario-Based Variable Reconstruction

Qualitative research revealed that traditional theoretical variables present contextualized features such as dynamic decision-making, socialization, and technological intermediation in the synergistic scenarios of social UGC platforms and second-hand trading platforms. For example, traditional attitudes tend to focus on static evaluations, while the formation of attitudes in user descriptions relies on the dynamic collaboration between social platform content interaction and second-hand platform technology practices, resulting in attitude changes. Thereby, “content attitude reinforcement” and “technology attitude transformation” are integrated to reconstruct attitude variables. The initial concept and reconstruction variable definitions are shown in Table 2. Therefore, the core variables of TPB (attitude, subjective norm, and perceived behavioral control) are reconstructed as platform-enabled green attitude (PEGA), social circle environmental demonstration (SCED), and cross-platform behavioral control (CPBC), respectively. Similarly, TCV dimensions (functional, emotional, and social values) also face the challenge of scenario adaptation and are reconfigured as functional integration value perception (FIVP), socialized emotional empowerment (SEE), and community identity value (CIV). This variable reconstruction demonstrates that the technical characteristics of the platform have transcended the traditional tool attributes, embedded in the formation mechanism of users’ psychological motivation, and become a key contextual element in shaping green disposal behavior.

3. Research Model and Hypothesis

3.1. TPB-Based Hypothesis Expansion

The Theory of Planned Behavior defines three core constructs: attitudes (ATT) reflect personal evaluations of specific behaviors, subjective norms (SN) embody the perception of social pressure, and perceived behavioral control (PBC) assesses the perceived difficulty of performing the behavior [15]. In the synergistic scenario of the social UGC and second-hand trading platforms, this study reveals the remodeling effect of the platform’s technical characteristics on the traditional decision-making path through variable reconstruction.

ATT is reconstructed as platform-enabled green attitude (PEGA), referring to users’ holistic evaluations of idle clothing disposal behavior through social UGC platform content interaction (e.g., liking idle clothing resale content) and second-hand platform function experience (e.g., “one-click resale” of Xianyu). This dynamic evaluation system has the characteristic of cognitive iteration, and each cross-platform operation may strengthen the existing attitude. As interviewee F02 stated, “Bloggers use Xianyu to resell used clothes effortlessly, which is environmentally friendly and interesting. I’m inspired to try selling my old coat.” Previous research confirms that environmental attitudes are the key factor influencing clothing recycling [33], and social media can affect environmental behaviors by enhancing users’ environmental awareness [34], therefore proposing the following:

H1a. 

Platform-enabled green attitude (PEGA) positively influences cross-platform collaborative disposal intention (CPCDI).

SN is reconstructed as a social circle environmental demonstration (SCED), emphasizing the role of algorithmic recommendations and community interactions in reshaping normative perceptions. Previous research indicated that the platform’s multi-stakeholder recommendation system is a “social planner” that reinforces social norms [20]. This algorithmic recommendation of green disposal content not only enhances the visibility of the environmental behavior but also establishes behavioral reference networks through lightweight interactions (e.g., collection and comments), further motivating individual green behavioral tendencies. As interviewee F09 mentions, “Seeing daily recommendations about recycling made me feel disconnected from the community if ignored these…eventually I joined in.” Therefore, we hypothesized the following:

H1b. 

Social circle environmental demonstration (SCED) positively influences cross-platform collaborative disposal intention (CPCDI).

Perceived behavioral control (PBC) is reconstructed as cross-platform behavioral control (CPBC). Its role is based on cognitive offloading theory [35], where disposal tutorials in social media tutorials can reduce the cognitive load of users’ decision-making. Second-hand platforms can shorten the transaction process and provide convenience (e.g., the “one-click resale” function) [36]. Together, they reduce behavioral friction. As expressed by interviewee F03, “The tutorial-guided process feels like a game—clear instructions at each step make reselling clothes effortless.” Therefore, we hypothesize the following:

H1c. 

Cross-platform behavioral control (CPBC) positively influences cross-platform collaborative disposal intention (CPCDI).

3.2. TCV-Based Hypothesis Expansion

3.2.1. Perceived Value and Cross-Platform Collaborative Disposal Intention

The Theory of Consumption Value provides a multidimensional perspective for analyzing idle clothing disposal behavior through the framework of functional, emotional, and social values [16]. However, traditional frameworks inadequately explain the dynamic evolution of value perceptions in social and e-commerce contexts. This study reveals the differentiated roles of different value dimensions in cross-platform collaborative disposal through systematic variable reconstruction.

Traditional functional value (PFV) emphasizes product utility. It is reconstructed as functional integration value perception (FIVP), which emphasizes that users develop comprehensive assessments of items’ utility by integrating experiential content from social UGC platforms and transaction data from second-hand platforms. Value assessment supported by multi-source data can reduce decision uncertainty [37]. Specifically, firstly, skills from UGC platforms (e.g., resale experience sharing) and transaction data from second-hand platforms (e.g., transaction price) provide complementary information; secondly, cross-platform multi-source data validation reduces users’ perception of the transaction risk; lastly, visualized success in disposal cases further optimizes users’ behavioral expectations. As interviewee F06 described, “When I resell T-shirts, by following REDnote resale guides and checking Xianyu price trends for similar T-shirts, I sold mine quickly.” This technology-enhanced utility assessment may promote sustainable behavior, and the following is therefore hypothesized:

H2a. 

Functional integration value perception (FIVP) positive influences cross-platform collaborative disposal intention (CPCDI).

PEV is reconstructed as socialized emotional empowerment (SEE), capturing UGC-driven emotional activation mechanisms. While emotional attachment to possessions may inhibit disposal willingness [30], social platforms achieve an emotional value creative transformation through content co-creation: UGC usually contains abundant and authentic emotional content [38], which can trigger emotional resonance according to the emotional contagion theory [39]. Platform algorithms amplify this emotional effect [40], forming a transmission chain of “emotional transmission–social learning–behavioral imitation”. Participant F02 exemplified this: “Seeing the stories of moms donating their babies’ clothes touched me, and then I also decided to donate my daughter’s clothes.” Established research suggests that highly empathic individuals are more inclined to pro-environmental behaviors [41]; thus, we proposed the following:

H2b. 

Socialized emotional empowerment (SEE) positively influences cross-platform collaborative disposal intention (CPCDI).

PSV is reconstructed as community identity value (CIV), reflecting that users construct implicit identities by engaging in community interactions. Interactions on UGC platforms are the outward manifestation of users’ social identities [42]. Algorithmic systems categorize users into specific interest-based communities by identifying users’ green disposal behavioral characteristics, subsequently continuously promoting disposal practice content. According to social identity theory [43], users actively internalize group norms to maintain community membership, which may enhance green disposal tendencies. As stated by respondent F07, “Liking green disposal posts increased similar recommendations, making me feel I should also participate in resale.” Social Comparison Theory further explains the mechanism [44]: when users perceive peers’ environmental practices as more frequent than their own, cognitive dissonance pressure will motivate them to achieve identity accommodation through behavioral imitation. Therefore, we hypothesize the following:

H2c. 

Community identity value (CIV) positively influences cross-platform collaborative disposal intention (CPCDI).

3.2.2. Perceived Value and Platform-Enabled Green Attitude

The Theory of Consumption Value reveals that perceived value influences environmental attitudes through cognitive reconfiguration [17]. However, its mechanism exhibits unique contextual characteristics in social and e-commerce scenarios.

Traditional functional value focuses on product utility, which is reconfigured as a cross-platform technology-enabled resource evaluation. Users form perceptions of the resource potential of idle clothing by integrating social UGC platform disposal experiences with second-hand platform market data, while individuals believe that items that still have functional value should not be wasted [17]. This cognitive shift occurs through three stages: first, cross-platform online disposal utility (e.g., economic returns from resale) dismantles “used clothing as waste” perceptions; second, platform algorithms reinforce idle clothing resource attributes by the visualization and expansion of green disposal cases; and lastly, sustained exposure to green information contributes to establishing a stable cognitive framework of environmental protection. As interviewee F11 mentioned, “Xianyu pricing guides and REDnote tutorials transformed my old clothes from burdens to resources, which is profitable and environmentally friendly.” Thus, we hypothesize as follows:

H3a. 

Functional integration value perception (FIVP) positively influences platform-enabled green attitude (PEGA).

Emotional value is reconfigured as a memory and emotion activation process triggered by UGC. Green disposal content on UGC platforms (e.g., the “donating used clothes during graduation season” topic) stimulates users’ emotional resonance through the emotional contagion theory [39]. The platform’s algorithms form a memory reinforcement loop by recommending similar emotional content, transforming individual attachment into environmental responsibility. F09 stated, “The user’s idle commemorative t-shirt donation story reminds me of the past and makes me realize idle clothes should be repurposed, like donations.” Some research confirms that emotional connections can motivate individuals to adopt eco-friendly behaviors [45]; therefore, we proposed the following:

H3b. 

Socialized emotional empowerment (SEE) positively influences platform-enabled green attitude (PEGA).

Community identity value (CIV) reshapes environmental attitudes through technology-enabled identity construction. Platform algorithms label identities based on user behavioral data (e.g., frequency of interaction with environmental contents) and reinforce green identities by continuously pushing similar content through echo chamber effects [46]. According to social identity theory [43], users actively internalize group norms to maintain community membership, which incorporates green dispositional behaviors into their self-concept. Meanwhile, the need for alignment between self-concept and behavior may translate into stable positive evaluations of green disposition. As stated by interviewee F11, “Liking green disposal notes led to more recommendations, exposure to these content made me feel part of it, feel this behavior was meaningful.” Therefore, we hypothesize as follows:

H3c. 

Community identity value (CIV) positively influences platform-enabled green attitude (PEGA).

3.2.3. Perceived Value and Social Circle Environmental Demonstration

Social circle environmental demonstration (SCED) is a synergistic result between perceived value and platform technical characteristics. The role of different perceived values on SCED in social and e-commerce scenarios presents contextualized features and differences.

Functional integration value perception (FIVP) reconstructs normative cognition through technology-enabled utility visualization. When users integrate the social platform disposal experience (e.g., REDnote old clothes resale skills) with the second-hand platform market data (e.g., Xianyu historical transaction price), users recognize the resource potential of idle clothes, which may lead to fostering environmental awareness [17]. In this process, the platform algorithm continuously optimizes the content delivery strategy based on user behavior, exposing users to sustainable practices to establish group behavioral perception. As interviewee F12 noted, “REDnote recommends highly praised idle clothes disposal tutorials… Finding value in old clothes, and I think everyone does it.” This algorithm-amplified behavioral visibility prompts users to internalize widely accepted environmental practices as behavioral norms [47]. Therefore, we hypothesize the following:

H4a. 

Functional integration value perception (FIVP) positive influences on social circle environmental demonstration (SCED).

Socialized emotional empowerment (SEE) reshapes normative cognition through the mechanism of emotional connection and algorithmic synergy: emotional symbols in UGC (e.g., old clothes stories and feedback from grantees) resonate, and the platform recommendation system homogenizes cognitive norms by repetitively delivering similar content [20]. When platform algorithms translate emotional interaction data into recommendation signals, the long-term effect may reinforce the belief that “green disposal is a community norm”. This mechanism, within the framework of social identity theory [43], drives users to acquire group belonging through behavioral mimicry, as stated by interviewee F09: “Suit resale notes evoke my memories, and after liking them, I receive more recommendations and feel that the resale is a consensus.” Thus, we hypothesize the following:

H4b. 

Socialized emotional empowerment (SEE) positive influences on social circle environmental demonstration (SCED).

Community identity value (CIV) continuously reinforces social circle environmental demonstration through technology-enabled identity reinforcement loops. According to the recommendation system process [48], the platform algorithm prioritizes delivering green disposal content when users are labeled as environmentalists through lightweight interactions with green content. Then, it dissolves users’ cognitive standard deviation within the community through continuous content exposure. This process aligns with social identity theory’s group belonging mechanism [43], as described by interviewee F08: “Liking the door-to-door recycling content… pushed more related content…feeling like I was involved, disposal behavior is socially acceptable.” Therefore, we hypothesize as follows:

H4c. 

Community identity value (CIV) positive influences on social circle environmental demonstration (SCED).

3.2.4. Perceived Value and Cross-Platform Behavioral Control

Traditional perceived behavioral control emphasizes the self-assessment of the ability to perform behaviors. In social UGC and second-hand platform collaborative scenarios, different dimensions of perceived value enhance user cross-platform behavioral control (CPBC) through differentiated paths.

Functional integration value perception (FIVP) enhances behavioral control through cross-platform data integration. UGC is considered more credible because its creators are perceived to comprehensively feedback both positive and negative feelings based on their personal experiences [49]. Exposure to successful cases of others’ green solutions on the UGC platform makes it easy to convince users of the feasibility of these approaches, while combined with second-hand platforms’ market data to validate economic returns, users can systematically assess the actual utility and implementability of behavior. This cross-platform information complementary mechanism can reduce behavioral uncertainty and strengthen users’ behavioral control. As interviewee F07 stated, “Learning to display outdated dresses on REDnote and using Xianyu to assist with pricing… make resale or rental smoother.” Thus, we hypothesize the following:

H5a. 

Functional Integration Value Perception (FIVP) positive influences on cross-platform behavioral control (CPBC).

Socialized emotional empowerment (SEE) translates emotional resonance into behavioral confidence through algorithm-driven recommendation. Emotional cues in green disposal content in UGC platforms (e.g., feedback on used clothing donations) stimulate user resonance, and algorithmic recommendations of similar content reinforce this effect. When users perceive the social value of their behaviors, they develop a sense of environmental mission, which enhances confidence in their ability to perform the behavior. As interviewee F04 expressed, “Seeing other mothers donating baby clothes on Xianyu and receiving feedback from recipients moved me and increased my confidence in using the platform to dispose of my sons’ clothes.” Research confirms that positive affective states enhance individuals’ sense of behavioral mastery [50]. Thus, we hypothesize the following:

H5b. 

Socialized emotional empowerment (SEE) positive influences on cross-platform behavioral control (CPBC).

Community identity value (CIV) forms the perception of behavioral control through algorithmic feedback mechanisms. Users’ interactive behaviors on social platforms (e.g., commenting and liking content) constitute the outward signs of digital identity [42], and platform algorithms analyze these behavioral data to continuously recommend matching disposal content, forming the perception of “replicable behavior”. As interviewee F15 states, “Liking highly interactive online recycling notes… receiving more and detailed tutorials convinced me I could execute recycling actions effectively.” Therefore, we present the following hypothesis:

H5c. 

Community identity value (CIV) positive influences on cross-platform behavioral control (CPBC).

The research model is shown in Figure 1.

4. Research Methodology

4.1. Questionnaire and Procedures

This study developed an initial measurement scale for cross-platform green disposal behavior using a three-stage approach: Firstly, translate the existing mature research items into Chinese. Secondly, invite 2 professors and 3 graduate students to form a focus group to review the sentences, ensure semantic clarity, and revise the wording accordingly. Finally, evaluate the effectiveness of the measurement items in the pilot study and make content revisions. The questionnaire includes the following core variables: (1) research background and operational definition of “idle clothes”; (2) case descriptions of cross-platform disposal practices (resale/recycling/donation/renting); (3) latent variable measurement covers platform-enabled green attitude (PEGA), social circle environmental demonstration (SCED), cross-platform behavioral control (CPBC), functional integration value perception (FIVP), socialized emotional empowerment (SEE), community identity value (CIV), and cross-platform collaborative disposal intentions (CPCDI), with specific items detailed in Appendix B. All constructs were measured using a 7-point Likert Scale (1 = strongly disagree, 7 = strongly agree).

Based on the advantages of the questionnaire method in elucidating behavioral mechanisms [51], this study collected data through Credamo, a professional research platform. Data were collected from June to August 2024. Chinese netizens who met the following criteria were screened: (1) being a common user of REDnote and Xianyu; (2) having experience interacting with environmental protection content on social platforms (e.g., old clothing recycling and donation). Participants received a compensation of CNY 4–6 to ensure response quality. Out of 2015 distributed questionnaires, 1520 valid responses were retained (75.4% validity rate).

The demographic characteristics of the sample (Figure 2) show a balanced gender distribution (47.96% male, 52.04% female), a concentration of age under 40 (81.37%). Participants with college/bachelor’s degrees constituted 40.72%, while 60.26% were married, 69.28% living in cities and towns, and 54.6% reported a monthly disposable income of ≥CNY 4000. Compared with the 55th China Internet Development Status Statistical Report [52], the gender ratio (national male internet users: 51.1%) and the urban–rural structure (national urban internet users: 71.8%) are representative. Although the sample shows youthfulness, high education, and high-income levels, the age distribution mirrors the user profile of the target platforms (85% of REDnote’s users are aged 18–35 [31]), and the survey urban concentration of respondents likely leads to high income and education levels. Furthermore, the sample aligns with the user profile of Credamo [53]. It confirms the representativeness of the questionnaire data in capturing the behavioral mechanisms of users on Chinese social media and second-hand trading platforms.

4.2. Non-Response Bias and Common Method Bias

Non-response bias was assessed using T-tests between early (first ten days) and late (final ten days) respondents’ demographics [54]. The results showed no significant differences in demographic characteristics between the two groups, suggesting minimal non-response bias. For common method bias, Harman’s single-factor test [55] identified seven factors with eigenvalues exceeding 1, and the largest factor variance explained was 11.45%, below the critical threshold of 50% [56], indicating that the CMB was not significant.

4.3. Statistical Analysis

This study employs Structural Equation Modeling (SEM) and Partial Least Squares (PLS) for data analysis, which is suitable for non-normally distributed data and small-sample studies [57]. It can effectively address complex models and theory development demands [58]. Given these methodological advantages, SmartPLS 4.1.0.3 software was used for model estimation and validation.

5. Data Analysis and Results

5.1. Measurement Model Analysis

The study used a two-stage approach to systematically assess the reliability and validity of the measurement model. The reliability test showed (

Table 3. Confirmatory factor analysis.

Construct	Indicator	Standardized Loading	Cronbach’s a	Composite Reliability	AVE
FIVP	FIVP1	0.819	0.797	0.799	0.712
	FIVP2	0.827
	FIVP3	0.884
SEE	SEE1	0.797	0.783	0.789	0.699
	SEE2	0.810
	SEE3	0.899
CIV	CIV1	0.833	0.804	0.805	0.719
	CIV2	0.829
	CIV3	0.882
PEGA	PEGA1	0.850	0.788	0.790	0.702
	PEGA2	0.814
	PEGA3	0.849
SCED	SCED1	0.883	0.856	0.861	0.776
	SCED2	0.865
	SCED3	0.896
CPBC	CPBC1	0.809	0.786	0.789	0.700
	CPBC2	0.833
	CPBC3	0.867
CPCDI	CPCDI1	0.752	0.729	0.730	0.552
	CPCDI2	0.781
	CPCDI3	0.733
	CPCDI4	0.703

) that Cronbach’s α ranged from 0.729 to 0.804, and the combined reliability (CR) ranged from 0.730 to 0.861, all exceeding the recommended threshold of 0.7 [59], showing that the scale has high internal consistency. The validity is evaluated through convergent and discriminant validity. For convergent validity, the standardized factor loadings of each measurement item ranged from 0.703 to 0.899, and the average variance extracted (AVE) ranged from 0.552 to 0.766, which met the criteria of factor loadings > 0.7 and AVE > 0.5 [57]. For discriminant validity, we used the Fornell–Larcker criterion [60] and the square root of the AVE of each latent variable (diagonal value) exceeded its correlation coefficient with the other variables (non-diagonal value), confirming distinct conceptual boundaries (see

Table 4. Descriptive statistics and correlations.

	MEAN	SD	FIVP	SEE	CIV	PEGA	SCED	CPBC	CPCDI
FIVP	5.51	1.147	0.844
SEE	5.48	1.055	0.438	0.836
CIV	5.57	1.065	0.408	0.544	0.848
PEGA	6.05	1.056	0.386	0.444	0.476	0.838
SCED	5.77	1.083	0.389	0.379	0.428	0.442	0.881
CPBC	5.43	1.178	0.468	0.464	0.465	0.470	0.395	0.837
CPCDI	5.65	1.202	0.511	0.544	0.537	0.603	0.507	0.644	0.743

Note: Values in the diagonal row (bold) are the square roots of the AVEs and the others are the correlations between constructs.

).

5.2. Structural Model Analysis

We validated our hypotheses using bootstrapping with 1520 observations and 5000 subsamples, ensuring reliable testing [57]. The results are summarized in

Table 5. Structural model result.

Hypothesis	Path Estimate	Standard Error	t-Value	Hypothesis Supported
H1a: PEGA → CPCDI	0.244 ***	0.024	10.151	Y
H1b: SCED → CPCDI	0.137 ***	0.023	6.054	Y
H1c: CPBC → CPCDI	0.312 ***	0.024	13.163	Y
H2a: FIVP → CPCDI	0.120 ***	0.022	5.353	Y
H2b: SEE → CPCDI	0.135 ***	0.022	6.081	Y
H2c: CIV → CPCDI	0.095 ***	0.022	4.255	Y
H3a: FIVP → PEGA	0.176 ***	0.027	6.462	Y
H3b: SEE → PEGA	0.209 ***	0.029	7.169	Y
H3c: CIV → PEGA	0.290 ***	0.032	9.093	Y
H4a: FIVP → SCED	0.221 ***	0.029	7.562	Y
H4b: SEE → SCED	0.139 ***	0.029	4.758	Y
H4c: CIV → SCED	0.262 ***	0.031	8.488	Y
H5a: FIVP → CPBC	0.278 ***	0.027	10.112	Y
H5b: SEE → CPBC	0.214 ***	0.031	6.896	Y
H5c: CIV → CPBC	0.236 ***	0.031	7.632	Y
Indirect effect	Path Estimate		Confidence intervals
FIVP → PEGA → CPCDI	0.043 ***		(0.029, 0.060)
FIVP → SCED → CPCDI	0.030 ***		(0.019, 0.044)
FIVP → CPBC → CPCDI	0.087 ***		(0.066, 0.109)
SEE → PEGA → CPCDI	0.051 ***		(0.035, 0.071)
SEE → SCED → CPCDI	0.019 ***		(0.011, 0.031)
SEE → CPBC → CPCDI	0.067 ***		(0.046, 0.088)
CIV → PEGA → CPCDI	0.071 ***		(0.052, 0.097)
CIV → SCED → CPCDI	0.036 ***		(0.023, 0.053)
CIV → CPBC → CPCDI	0.074 ***		(0.053, 0.096)
GOF:0.647	Total variance explained	R2	Q2
	PEGA	0.297	0.207
	SCED	0.249	0.191
*** p < 0.001	CPBC	0.337	0.233
	CPCDI	0.602	0.329

.

The model explanatory and predictive power were evaluated via R² and Q² indicators. The cross-platform collaborative dispositional intentions (CPCDI) R² was 0.602, indicating that the model explains 60.2% of the behavioral variance, reflecting strong predictive capability [57]. According to the evaluation criteria of the Q² value [61], the CPCDI Q² was 0.329, surpassing the 0.35 threshold, thereby confirming the strong predictive relevance of the model. These results support the applicability of the theoretical framework in digital scenarios.

Variance inflation factor (VIF) were examined for diagnosis to avoid multi-collinearity interference. The VIF values of all variables are below the critical threshold of 3.3 [62], indicating no significant collinearity issues. Additionally, overall model fit was assessed by the goodness-of-fit (GOF) indicators. Following [63]’s formula (GOF = √(mean AVE × mean R²)), the model’ GOF value was 0.647, which exceeds the large effect size threshold of 0.61 [64], demonstrating the excellent model fit.

The study confirmed that platform-enabled green attitude (PEGA, β1a = 0.244, p < 0.001), social circle environmental demonstration (SCED, β1b = 0.137, p < 0.001), and cross-platform behavioral control (CPBC, β1c = 0.312, p < 0.01) had a significant positive effect on cross-platform collaborative disposal intention (CPCDI), supporting H1 (a,b,c). Among the perceived value dimensions, function integration value perception (FIVP, β2a = 0.120, p < 0.001), socialized emotional empowerment (SEE, β2b = 0.135, p < 0.001), and community identity value (CIV, β2c = 0.095, p < 0.01) also exhibited direct positive effects on CPCDI, validating H2 (a,b,c). Among these, CPBC has the strongest impact, suggesting that technology-enabled process simplification is the core force for behavior, while SEE and SCED have comparable direct impacts on CPCDI.

The analysis further examines the effects of perceived value dimensions on three core TPB indicators:

(1) Influence on platform-enabled green attitude (PEGA): Community identity value (CIV, β3c = 0.290, p < 0.01) exerted the strongest influence, followed by socialized emotional empowerment (SEE, β3b = 0.209, p < 0.001) and function integration value perception (FIVP, β3a = 0.176, p < 0.001). This suggests that the identity formed through environmental community interactions can be deeply internalized to evaluate cross-platform green behaviors.

(2) Influence on social circle environmental demonstration (SCED): The contribution of CIV (β4c = 0.262, p < 0.01) and FIVP (β4a = 0.221, p < 0.001) was significantly higher than that of SEE (β4b = 0.139, p < 0.001), which suggests that community identity and information integration jointly construct normative pressure.

(3) Effect on cross-platform behavioral control (CPBC): The role of FIVP (β5a = 0.278, p < 0.001) was the most critical predictor, followed by CIV (β5c = 0.236, p < 0.01) and SEE (β5b = 0.214, p < 0.001). This suggests that operational convenience due to functional integration is a central driver of perceived behavioral control.

The above results support all hypotheses (H3–H5) while implying a chain transmission mechanism of perceived value to psychological motivation.

5.3. Indirect Effect Test

Although the research hypothesis focuses on the direct influence of perceived value and TPB variables on cross-platform disposal behaviors, SEM revealed a significant mediating effect. This suggests that users’ decision-making undergoes a multi-stage transformation in the collaborative scenario of social and e-commerce platforms: value assessment–psychological motivation–cross-platform behavior. The indirect effect can more completely portray the dynamic mechanism.

Table 5 shows that functional integration value perception (FIVP), socialized emotional empowerment (SEE), and community identity value (CIV) have differential indirect effects on cross-platform collaborative disposal intention (CPCDI) through platform-enabled green attitude (PEGA), social circle environmental demonstration (SCED), and cross-platform behavioral control (CPBC): FIVP transmits indirect effects through PEGA (β = 0.043), SCED (β = 0.030), and CPBC (β = 0.087), with a total effect of 0.280; SEE showed positive indirect effects through PEGA (β = 0.05), SCED (β = 0.019), and CPBC (β = 0.067), with a total effect of 0.272; CIV showed a positive indirect effect through PEGA (β = 0.071), SCED (β = 0.036), and CPBC (β = 0.074), with a total effect of 0.276.

To further determine the nature of the mediating effect, the variance explanation ratio (VAF = indirect effect/total effect × 100%) was calculated to assess the mediation strength. The results showed that the VAF values for FIVP, SEE, and CIV were 57.14%, 50.37%, and 65.58%, respectively, indicating the presence of partial mediation effects (20% ≤ VAF ≤ 80%). CIV has the strongest indirect effect, suggesting that the effect of community identity value on behavioral intention relies more on the chain transmission of psychological motivation.

6. Discussion

By integrating TPB and TCV, this study systematically analyzes the users’ idle clothing cross-platform disposal behavior mechanism under the synergistic ecology of social UGC platforms (e.g., REDnote) and second-hand trading platforms (e.g., Xianyu), aiming to solve the practical predicament of “high retention–low circulation” of used textiles in China. Based on structured interviews, the study reconstructs theoretical variables and constructs a three-dimensional model of “value perception–psychological motivation–cross-platform behavior”. The SEM results demonstrate the integrated model has a higher explanatory power (R² = 60.2%), which is significantly better than a single theoretical framework (TPB: R² = 43.8%; TCV: R² = 56.2%), which confirms the key role of simultaneously grasping psychological motivation and value perception in promoting the transformation of idle clothing from “hoarding” to “circulation”, responds to the academic community’s exploration demand for technology-driven sustainable consumption mechanisms, and provides theoretical support for solving the practical problem of insufficient green disposal practices.

6.1. TPB and Cross-Platform Collaborative Disposal

It was found cross-platform behavioral control (CPBC) was the strongest predictor of users’ disposal intention (β = 0.312), and its influence surpasses platform-enabled green attitude (PEGA, β = 0.244) and social circle environmental demonstration (SCED, β = 0.137). This finding is consistent with conclusion of a previous study on the critical role of perceived behavioral control on recycling behavior [65]. Green behavior has a high effort attribute [66], which directly points out that one of the important reasons why consumers hoard old clothes is that they do not know how to dispose of them and green disposal is too troublesome, but the dual-platform functional collaboration (e.g., REDnote tutorial guide and Xianyu pricing information) significantly reduces this attribute through process scripting and cognitive offloading. In contrast, SCED has the weakest explanatory power due to the anonymity and ease of manipulation of UGC, which may lead users to question the authenticity of content [49]. This may weaken the internalization of norms, making it difficult for green disposal to shift from private behavior to community consensus. As interviewee F19 said, “When similar content dominates my feed, I question the commercial motives rather than authentic environmental advocacy.”

Based on the above findings, this study suggests that social UGC platforms should utilize algorithms to accurately identify environmentally conscious users and deliver disposal tutorials (e.g., Xianyu resale tutorials) among targeted users, or embed cross-platform green data dashboards in the platform (e.g., Xianyu carbon credits). These measures enhance behavioral control by providing actionable guidance or dynamic normative information [67]. In addition, a cross-platform environmental incentive system is designed to enable users to accumulate points or receive traffic incentives for their environmental interactions on REDnote and transactions on Xianyu (e.g., Traffic tilt on REDnote, Xianyu payment deduction coins), encouraging users to proactively complete green disposal through cross-platform collaboration.

6.2. TCV and Cross-Platform Collaborative Disposal

6.2.1. Direct Impact of Perceived Value

The three dimensions of perceived value differentially influence cross-platform collaborative disposal behaviors. Socialized emotional empowerment (SEE) demonstrated the strongest direct effect (β = 0.135), followed by functional integration value perception (FIVP, β = 0.120) and community identity value (CIV, β = 0.095). This indicates that in social and commerce ecosystems, SEE’s immediate behavioral activation outweighs the gradual influences of utility evaluation or social identification, consistent with findings on emotional value dominance in green consumption [68]. An individual’s emotional attachment to items is a key factor in suppressing their willingness to green disposal [30], and the leading role of SEE precisely provides a breakthrough to solve the predicament of “emotional hoarding”. The superior effect of SEE stems from the synergy between UGC authentic emotional content and algorithmic amplification: the highly interactive nature of UGC facilitates emotional resonance [38], then platform algorithms further amplify this emotional effect and prompt users to imitate the behavior [40]. Previous studies have also shown highly empathic individuals are more willing to engage in environmental behaviors [41].

Previous studies show that perceived social value dominates redistribution willingness for smartphones [17], while only functional value determines green cosmetic purchases [28]. This discrepancy may stem from two factors: in product type, standardized products rely on utility assessment, while items with strong emotional attributes (e.g., clothing) are more likely to trigger emotional drive; in platform ecology, traditional TCV studies examine general consumption scenarios, whereas the “social and e-commerce” synergistic ecosystem reconstructs value transmission pathways by connecting emotional content, which therefore enhances the efficiency of transforming emotional value into behavior with the immediacy of emotion.

The study further revealed that functional integration value perception (FIVP) exerted the strongest direct effect on cross-platform behavioral control (CPBC) (β = 0.278). The core of functional value lies in utility assessment, and its mechanism reflects the instrumental mediation effect of technological empowerment: Users assess behavioral feasibility by acquiring disposal strategies from UGC platforms and market data from secondhand platforms. This cross-platform information synergy reduces decision complexity through cognitive offloading, thereby enhancing users’ sense of control over the smooth disposal of idle clothing and addressing the pain points of hoarding clothing due to complex operations. This finding is consistent with studies on new business model adoption [69]. Further, in the cross-platform collaborative ecosystem, this functional integration is transformed into users’ willingness to practice green disposal by breaking down information barriers.

Based on the above findings, this study puts forward suggestions: Firstly, strengthen emotional utility—UGC platforms should build an emotion sign recognition model and prioritize cases with emotional content (e.g., the “Clothes Rebirth Story”) and design topic and labels like a “green sense of accomplishment” to encourage users to share the emotional motivation behind their behavior. Both jointly motivate and trigger users’ willingness to dispose. Secondly, advance functional and technical integration—embedding the second-hand platform functional interface in the UGC platform (e.g., embedding Xianyu’s HTML5 page or small app into REDnote). Gradually achieve platform API cooperation and realize one-click redirection from REDnote to Xianyu for resale, thereby enhancing operational smoothness and lowering action barriers to promote users’ active participation in circular disposal practices.

6.2.2. Indirect Effects of Perceived Value

Although the research hypotheses focused on the direct effects of reconstructed perceived values and TPB core variables on cross-platform disposal behaviors, SEM analysis revealed significant indirect paths. These unanticipated mediating effects suggest that in dual-platform ecology, the influence of perceived value on behavioral intention needs to be realized through the chain conduction of psychological motivation, confirming that the influence of perceived value on behavior may be moderated by individual differences, situational dynamics, and psychological factors [70]. Notably, perceived values’ indirect effects surpassed direct effects. Community identity value (CIV) demonstrated particularly prominent mediation, with its indirect effect approximately twice the direct effect. It reflects that many consumers lack the intrinsic motivation for continuous disposal because they have not included environmentalism in their self-identity perception. This discovery provides a more precise perspective for understanding the gap between users’ cross-platform disposal intentions and behaviors.

The strong mediating effect of CIV reveals that social value perception needs to be synergized with psychological motivation to achieve better behavioral transformation. UGC platforms’ community features reshape identity anchoring for environmental behaviors. User identities are reconstructed through lightweight interactions with green disposal content [42], potentially being labeled as environmentalists. Firstly, community identity is transformed into self-value recognition through platform-empowered green attitudes. Secondly, the social circle environmental protection demonstration forms group norms of “majority participation” through algorithmic recommendation of high-exposure cases. And lastly, cross-platform behavioral control reduces action thresholds via process simplification. In contrast, the value of functional integration relies on rational utility assessment, and socialized emotional empowerment relies on instantaneous emotional feedback, both of which lack the in-depth internalization effect of identity on behavior.

Therefore, this study suggests building a cross-platform identity symbol system. Through authorization agreements, synchronize the environmental protection achievements of second-hand platforms (e.g., digital badges) to the personal homepage of UGC platforms, or initiate activities to encourage users to share the green achievement posters of second-hand platforms on UGC platforms, forming cross-platform identity markers. Moreover, build a collaborative space for communities in the UGC platform, establish vertical communities (e.g., an old clothing disposal mutual aid group), provide disposal experience and tools (e.g., Xianyu resale template), and transform individual identity into collective action, thereby enhancing the willingness and behavioral transformation of idle clothing disposal through the indirect effect of community identity value.

6.2.3. Total Impact of Perceived Value

It was found that the total effects of functionally integrated value perception (FIVP), socialized emotional empowerment (SEE), and community identity value (CIV) on cross-platform collaborative dispositional behavioral intentions (CPCDI) were 0.280, 0.272, and 0.276, respectively, and that, although their direct effects were weaker than those of platform empowerment of green attitudes (PEGA), social circle environmentally friendly demonstration (SCED), and cross-platform behavioral control (CPBC), the total effect significantly surpassed the former two (PEGA total effect = 0.241; SCED total effect = 0.208). This finding reveals that users’ cross-platform disposition behavior choices in the collaborative ecology of social e-commerce are not only driven by immediate psychological motives but also rooted in the process that functional integration lowers operational thresholds, emotional resonance resolves emotional attachment, and identity value transfer strengthens continuous motivation.

The platform can bridge the gap between willingness and behavior towards green disposal of idle clothing through multidimensional value collaboration and layered implementation strategies. On the one hand, it can develop a cross-platform environmental points/identity system and optimize emotional content algorithms to mobilize users’ motivation and willingness to participate in green disposal. On the other hand, the initial model of zero cost virtual incentives (e.g., environmental badges) and lightweight technology integration (e.g., embedded H5 pages) is adopted, relying on user-generated content to reduce costs. In the later stage, we will enhance the incentive value through brand cooperation, embed mini programs, deepen API integration, and use traffic conversion and policy subsidies to cover long-term investment, ensuring the feasibility of suggestions.

7. Conclusions and Limitations

This study systematically analyzes the driving mechanisms of cross-platform idle clothing disposal behaviors in social and e-commerce ecosystems through an integrated TPB-TCV theoretical framework and mixed-methods approach. Traditional constructs were contextually reconstructed through qualitative analysis: In the psychological motivation dimension, attitude, subjective norms, and perceived behavioral control are transformed into platform-enabled green attitude green attitude, social circle environmental demonstration, and cross-platform behavioral control, respectively. In the perceived value dimension, perceived functional, emotional, and social value are reconstructed as functional integration value perception, socialized emotional empowerment, and community identity value, respectively. The quantitative validation of SEM confirmed all hypotheses, and the model’s explanatory power was significantly better than a singular theoretical framework. It is found that cross-platform behavioral control is the strongest predictor of behavioral intention, driven by operational simplification through dual-platform tool synergy; functional integration value perception is the key antecedent of cross-platform behavioral control, highlighting cross-platform information integration’s critical role in decision feasibility. Meanwhile, among perceptual values, the community identity value has the most significant impact on platform-enabled green attitude and social circle environmental demonstration, revealing the mechanism of identity’s persistent influence on green behaviors in digital communities. These findings overcome the reliance on a single psychological motivation or static value perception in traditional environmental behavior research and elucidate how multidimensional perceived value evolves into psychological motivation and behavioral intention driven by technology empowerment. The findings also clarify how technological empowerment catalyzes the transformation of multidimensional perceived value into behavioral motivation, providing a theoretical foundation for optimizing platform interoperability and formulating digital environment policies and promoting the improvement of environmental well-being in the e-commerce collaborative ecosystem.

This paper also has limitations: Firstly, the reliance on self-reported data may lead to social expectation bias. Future studies could utilize platform behavioral logs to enhance data validity. Secondly, the study focuses on general disposal behaviors without distinguishing the impact on specific behavior (resale/donation/recycling/renting), and comparative analyses of distinct disposal types should be conducted in the future. Finally, the sample of this study focuses on Chinese users, and cross-cultural validation is recommended to assess the generalizability of the findings.