Presenting a Model of Ethical Behavior in the Sale of Second-Hand Goods in the Context of Consumer-to-Consumer (C2C) E-Commerce

Extended Abstract
 
Introduction and Objectives: In the literature of Consumer-to-Consumer (C2C) electronic commerce, despite the rapid proliferation of digital platforms and the surge in peer-to-peer interactions, existing studies have predominantly focused on isolated variables such as trust, perceived risk, or customer satisfaction. Consequently, there remains a paucity of research dedicated to developing a comprehensive model of ethical behavior among sellers. Furthermore, the majority of prior scholarly work has either been situated within the context of traditional e-commerce or has primarily examined Business-to-Consumer (B2C) interactions. Such frameworks often fail to account for the unique characteristics of C2C markets, including user anonymity, the informal nature of transactions, and the prominent role of amateur participants, all of which necessitate a distinct, context-specific analysis. Moreover, a significant gap exists in understanding the ethical mechanisms governing seller behavior within the secondary (second-hand) goods market, with few studies systematically identifying the dimensions, antecedents, and consequences of such behavior within a theoretical framework. Therefore, the lack of a holistic framework to explain seller ethical behavior in C2C environments, particularly regarding second-hand goods, constitutes a critical research gap.
Against this backdrop, the primary objective of this study is to develop a comprehensive model of ethical behavior for sellers of second-hand goods within the C2C e-commerce context. Accordingly, the central research question is formulated as follows: How can a conceptual model of ethical behavior for second-hand goods sellers be explained within a C2C e-commerce framework, and what dimensions, conditions, and mechanisms influence this behavior? Given the exploratory nature of the topic and the absence of a cohesive theoretical framework, this study adopts a qualitative approach within an interpretive paradigm, utilizing Grounded Theory as the primary methodological framework.
Method: This research is applied in its objective and qualitative in nature, utilizing the systematic Grounded Theory approach developed by Strauss and Corbin (1998). This methodological framework was selected due to the exploratory nature of the topic and the necessity for an in-depth explanation of the ethical processes and mechanisms within C2C e-commerce environments. The study population comprised two distinct groups: (1) active second-hand goods sellers on C2C platforms, who act as direct participants in the phenomenon, and (2) academic and industry experts specializing in e-commerce. Participants were selected through purposive and theoretical sampling, and data collection continued until theoretical saturation was achieved. Ultimately, 16 semi-structured, in-depth interviews were conducted to allow for the exploration of emerging themes, with a specific focus on user experiences on the Divar platform. Data analysis was conducted systematically and concurrently with the collection process, following the three stages of open, axial, and selective coding using MAXQDA 2020 software. The analysis involved iterative review of transcripts, extraction of initial concepts, and aggregation into meaningful categories, allowing the conceptual model of seller ethical behavior to emerge incrementally from the data. The hallmark of this methodology lies in the flexibility of the inquiry and its focus on participants’ lived experiences, which is essential for capturing the complexities of ethical behavior in anonymous, informal digital marketplaces.
Results: This study involved 16 experts (12 male, 4 female) specializing in second-hand trading and C2C e-commerce management. The participants, predominantly aged 30-60 with advanced academic degrees, provided a robust empirical foundation based on their extensive experience in macro-level decision-making. Analytical reliability was confirmed through inter-coder agreement and test-retest methods. The qualitative findings resulted in a six-component paradigmatic model:

Contextual Conditions: Societal culture, business environment, and legal frameworks, including platform dynamics and regulatory perceptions.
Causal Conditions: Individual moral capital, altruism, and social responsibility as internal and external drivers of behavior.
Central Phenomenon: “Ethical sales behavior,” characterized by honesty, mutual respect, privacy protection, and adherence to social norms.
Strategies: Practical approaches, including empathy, risk reduction, transparency, accountability, and customer support.
Intervening Conditions: Moderating factors such as customer unawareness of legal rights, seller immorality, and user experience or learning.
Consequences: Outcomes including enhanced customer trust and loyalty, positive word-of-mouth, and strategic platform benefits.

This model comprehensively explains the complexities of ethical interactions within peer-to-peer digital marketplaces. It demonstrates how a seller’s ethical conduct, shaped by structural and individual conditions, leads to sustainable outcomes within the e-commerce ecosystem.
Discussion and Conclusions: Regarding the causal conditions, and in line with the identified themes, it is recommended that sellers of second-hand goods in C2C platforms strengthen their moral capital and altruism. To this end, they should provide truthful product information, honor their commitments, and engage with customers in an empathetic manner. Practicing empathy and paying attention to customer needs can enhance customer trust and satisfaction while reducing potential problems.
With respect to the contextual conditions, sellers are advised to align their conduct with social norms as well as platform and community rules. Awareness of customer rights and legal responsibilities makes seller behavior more transparent and trustworthy. Moreover, sellers should strive to maintain ethical and empathetic behavior in both workplace and market settings in order to reduce customers’ perceived risk and create a safer shopping experience.
In relation to the central phenomenon, ethical behavior should be institutionalized across all stages of the sales process. Honesty in pricing, respect for customers, protection of privacy, and mutual respect increase customer trust and loyalty. Sellers who uphold fairness and equity are more likely to benefit from repeat purchases and positive word-of-mouth.
As for strategies, empathy, honesty, responsiveness, and active customer support should be adopted as the main strategic orientations. For instance, sellers should respond promptly to customer messages and requests, resolve problems efficiently, and provide comprehensive guidance regarding the product. Transparency in transactions is also essential for reducing perceived risk.
Regarding intervening conditions, sellers are encouraged to rely on platform regulations and the country’s legal framework to protect customers. Compliance with legal requirements and supportive regulations enhances the credibility and empathetic nature of seller behavior and helps prevent misunderstandings and complaints.
Finally, in terms of outcomes, sellers should focus on building trust, loyalty, positive word-of-mouth, and strategic leverage. Consistent ethical conduct, proactive support, and honesty in customer interactions create positive customer experiences, foster confident purchasing, and encourage recommendations to others. In the long run, these outcomes contribute to profitability and competitive advantage.
Based on the findings, the following suggestions are proposed for C2C e-commerce platforms: strengthening user credibility systems through rating systems, trust badges, and transparent transaction histories; increasing informational transparency in advertisements by requiring standard information about product condition, authenticity, and usage terms; establishing rapid reporting and response mechanisms for ethical violations such as fraud, false information, and unfair behavior; and designing intelligent tools to warn users about transaction risks to reduce information asymmetry between buyers and sellers. Additionally, it is recommended to formulate specific regulations for C2C markets with a focus on the legal responsibility of non-professional users (amateur sellers) and to revise the penalty and enforcement system to include non-professional users.
Suggestions for Future Research: Developing the model by adding technological variables such as artificial intelligence, trust-building algorithms, and blockchain; conducting quantitative studies to test the relationships between the categories extracted in this research.
Limitations: This study was conducted qualitatively based on grounded theory, and therefore has limited statistical generalizability. The research population consisted of experts and active sellers on selected platforms, which may not cover the full diversity of C2C users. The research focused on one product group (second-hand goods and home appliances), which may limit generalizability to other product categories. The data were based on participants’ perceptions and experiences, which may be accompanied by perceptual biases.
Acknowledgements: The authors would like to express sincere gratitude to the esteemed faculty members of the Science and Research Branch of Tehran University for their invaluable support and for facilitating access to academic experts. Special thanks are extended to the distinguished professors and marketing specialists who participated in the in-depth interviews. Their profound insights, academic expertise, and practical perspectives were instrumental in the development of the conceptual model presented in this study. This research would not have reached its current depth without their generous time and scholarly contributions.
Conflict of Interest: The authors declare no conflict of interest with respect to the research, authorship, and/or publication of this article. The research was conducted independently, and the findings are based solely on the data collected from the participants. No financial or personal interests influenced the objectivity of the study.