Future research directions in buyer-seller relationships within live shopping marketplaces
| Research area/theme | Observed insight from current study | Future research question/direction | Potential methodological approach |
|---|---|---|---|
| Commitment–trust theory in live contexts | Commitment appears more provisional and performance-sensitive than original CTT specifies; trust is dynamically calibrated in real time | How does the live, synchronous, entertainment-focused nature of this context transform the definitions of “commitment” and “trust”? Does commitment become more conditional when continuously evaluated through performance? How does witnessed behavior affect trust formation? | Longitudinal ethnographic observation of streamer–viewer interactions; repeated interviews tracking relationship trajectories; experience sampling during live streams |
| Platform governance and multi-sided dynamics | Marketplace functions as a trust intermediary; platform failures attributed to sellers by association; dual-role users develop sophisticated trust assessments | How do specific governance mechanisms (reputation systems, dispute resolution, algorithmic visibility and fee structures) moderate CTT antecedent–outcome relationships? What are distinctive dynamics of multi-sided platforms where users occupy multiple roles? How do network effects operate in live commerce communities? | Comparative case studies of platforms with contrasting governance models; natural experiments following governance changes; social network analysis of community structures |
| Consumer vulnerability and dark patterns | Explicit user reports of addiction, FOMO exploitation and unregulated gambling mechanics; users mentioning mystery boxes expressed financial regret | What are the prevalence and severity of compulsive buying in live shopping? How do platform design features (mystery boxes, countdown timers and social pressure) exploit cognitive biases among vulnerable populations (youth, compulsive buyers and financially constrained households)? What regulatory interventions would effectively constrain harmful patterns? | Large-scale prevalence surveys; in-depth interviews with vulnerable users; experimental testing of design feature effects; interdisciplinary collaboration with consumer policy and legal scholars |
| Cross-cultural dynamics | Findings based on English-language reviews from predominantly Western users; live shopping is massively prevalent in Asian markets | Do identified relational mechanisms hold in Asian markets where live shopping is structurally embedded in social media and super-apps? How do cultural variations in collectivism, uncertainty avoidance and communication norms shape trust and commitment expression? How do different regulatory environments affect acceptance of chance-based mechanics? | Cross-cultural comparative studies using parallel data collection across multiple countries; culturally adapted measurement instruments; collaboration with international research teams |
| Temporal dynamics and relationship evolution | Cross-sectional data captures relational states at single points; users describe relationship development (“from buyer to seller”) | How do buyer–seller relationships evolve over time? What are critical junctures where relationships intensify or fracture? How does accumulation of interactional capital modify CTT mechanism operation? How do users navigate the transition from novice to experienced participant? | Longitudinal diary studies; repeated interviews over 12–24 months; platform trace data analysis tracking interaction sequences, purchase patterns and community participation |
| Emerging technologies and relational outcomes | Platform features shape relational possibilities; device-based variation in experience | What role do emerging technologies (AI recommendations, AR/VR try-on and algorithmic curation) play in shaping trust and commitment? How do they interact with human relational processes? Can AI detect emerging trust issues in real time? | Design science research; experimental manipulation of feature availability; platform collaboration for A/B testing; machine learning analysis of interaction patterns |
| Research area/theme | Observed insight from current study | Future research question/direction | Potential methodological approach |
|---|---|---|---|
| Commitment–trust theory in live contexts | Commitment appears more provisional and performance-sensitive than original | How does the live, synchronous, entertainment-focused nature of this context transform the definitions of “commitment” and “trust”? Does commitment become more conditional when continuously evaluated through performance? How does witnessed behavior affect trust formation? | Longitudinal ethnographic observation of streamer–viewer interactions; repeated interviews tracking relationship trajectories; experience sampling during live streams |
| Platform governance and multi-sided dynamics | Marketplace functions as a trust intermediary; platform failures attributed to sellers by association; dual-role users develop sophisticated trust assessments | How do specific governance mechanisms (reputation systems, dispute resolution, algorithmic visibility and fee structures) moderate | Comparative case studies of platforms with contrasting governance models; natural experiments following governance changes; social network analysis of community structures |
| Consumer vulnerability and dark patterns | Explicit user reports of addiction, | What are the prevalence and severity of compulsive buying in live shopping? How do platform design features (mystery boxes, countdown timers and social pressure) exploit cognitive biases among vulnerable populations (youth, compulsive buyers and financially constrained households)? What regulatory interventions would effectively constrain harmful patterns? | Large-scale prevalence surveys; in-depth interviews with vulnerable users; experimental testing of design feature effects; interdisciplinary collaboration with consumer policy and legal scholars |
| Cross-cultural dynamics | Findings based on English-language reviews from predominantly Western users; live shopping is massively prevalent in Asian markets | Do identified relational mechanisms hold in Asian markets where live shopping is structurally embedded in social media and super-apps? How do cultural variations in collectivism, uncertainty avoidance and communication norms shape trust and commitment expression? How do different regulatory environments affect acceptance of chance-based mechanics? | Cross-cultural comparative studies using parallel data collection across multiple countries; culturally adapted measurement instruments; collaboration with international research teams |
| Temporal dynamics and relationship evolution | Cross-sectional data captures relational states at single points; users describe relationship development (“from buyer to seller”) | How do buyer–seller relationships evolve over time? What are critical junctures where relationships intensify or fracture? How does accumulation of interactional capital modify | Longitudinal diary studies; repeated interviews over 12–24 months; platform trace data analysis tracking interaction sequences, purchase patterns and community participation |
| Emerging technologies and relational outcomes | Platform features shape relational possibilities; device-based variation in experience | What role do emerging technologies ( | Design science research; experimental manipulation of feature availability; platform collaboration for A/B testing; machine learning analysis of interaction patterns |
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