Pub Date : 2025-05-21DOI: 10.1016/j.elerap.2025.101504
Peng-Chu Chen, Ran Tao
This study examines the interaction between soft and hard information in peer-to-peer (P2P) markets, utilizing a survey of 245 participants who evaluated 199 stylized loan requests. The findings reveal that providing both soft and hard information significantly improves funding decisions compared to relying solely on hard information. Soft information enables lenders to identify and support promising borrowers with strong, though marginally insufficient, hard information, while poor hard information effectively mitigates the risk of misinformation. We observe that ambiguity diminishes the influence of soft information, whereas hard information reflecting loan popularity amplifies it through confirmation bias. Consequently, the absence of soft information may impede lenders’ ability to recognize potentially successful borrowers. To ensure the reliability of soft information, P2P platforms should actively monitor its quality and dynamically adjust its prominence. In markets where soft information is generally aligned with borrower quality, platforms may consider de-emphasizing hard data or reducing ambiguity. Conversely, in markets with misaligned soft information, incorporating free-form text and prioritizing hard information can enhance decision-making. These insights offer actionable recommendations for P2P platforms to optimize information presentation and improve loan assessment.
{"title":"Information and funding decisions in peer-to-peer markets: An exploratory study","authors":"Peng-Chu Chen, Ran Tao","doi":"10.1016/j.elerap.2025.101504","DOIUrl":"10.1016/j.elerap.2025.101504","url":null,"abstract":"<div><div>This study examines the interaction between soft and hard information in peer-to-peer (P2P) markets, utilizing a survey of 245 participants who evaluated 199 stylized loan requests. The findings reveal that providing both soft and hard information significantly improves funding decisions compared to relying solely on hard information. Soft information enables lenders to identify and support promising borrowers with strong, though marginally insufficient, hard information, while poor hard information effectively mitigates the risk of misinformation. We observe that ambiguity diminishes the influence of soft information, whereas hard information reflecting loan popularity amplifies it through confirmation bias. Consequently, the absence of soft information may impede lenders’ ability to recognize potentially successful borrowers. To ensure the reliability of soft information, P2P platforms should actively monitor its quality and dynamically adjust its prominence. In markets where soft information is generally aligned with borrower quality, platforms may consider de-emphasizing hard data or reducing ambiguity. Conversely, in markets with misaligned soft information, incorporating free-form text and prioritizing hard information can enhance decision-making. These insights offer actionable recommendations for P2P platforms to optimize information presentation and improve loan assessment.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"72 ","pages":"Article 101504"},"PeriodicalIF":5.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-19DOI: 10.1016/j.elerap.2025.101511
Chenchen Zhao , Jianghua Wu , Yuhong He
The posterior price guarantee (PG) strategy, leveraging randomized pricing, has gained widespread adoption among retailers. Under this strategy, retailers operating within an infinite timeframe assure consumers that they will refund the price difference if the product is purchased prior to the price reduction. Consumers exhibit heterogeneity in terms of their valuation, patience, and concerns regarding PG. This study examines how consumer purchasing strategies impact the effectiveness of the PG strategy. Specifically, we examine how the PG strategy affects the retailer’s pricing, promotion probability, and the duration of the PG period. Our findings reveal that the PG strategy compels the retailer to decrease the probability of promotions and enhance their depth, which negatively impacts consumer surplus. Furthermore, we identify the optimal length of the PG period, which is contingent upon consumer characteristics and the nature of the product.
{"title":"Posterior price guarantee strategy with randomized pricing in electronic commerce","authors":"Chenchen Zhao , Jianghua Wu , Yuhong He","doi":"10.1016/j.elerap.2025.101511","DOIUrl":"10.1016/j.elerap.2025.101511","url":null,"abstract":"<div><div>The posterior price guarantee (PG) strategy, leveraging randomized pricing, has gained widespread adoption among retailers. Under this strategy, retailers operating within an infinite timeframe assure consumers that they will refund the price difference if the product is purchased prior to the price reduction. Consumers exhibit heterogeneity in terms of their valuation, patience, and concerns regarding PG. This study examines how consumer purchasing strategies impact the effectiveness of the PG strategy. Specifically, we examine how the PG strategy affects the retailer’s pricing, promotion probability, and the duration of the PG period. Our findings reveal that the PG strategy compels the retailer to decrease the probability of promotions and enhance their depth, which negatively impacts consumer surplus. Furthermore, we identify the optimal length of the PG period, which is contingent upon consumer characteristics and the nature of the product.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"72 ","pages":"Article 101511"},"PeriodicalIF":5.9,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-16DOI: 10.1016/j.elerap.2025.101509
Xin Tian , Bochao Yan , Xiaohui Zhou , Yinyun Yan
Logistics plays a crucial role in the operations of e-commerce platforms, but few studies have directly investigated its influence on consumer purchase frequency. While some research indicates a significant positive relationship between logistics performance and consumer satisfaction, relying solely on satisfaction scores to predict future purchasing behavior may lead to the “customer satisfaction trap.” This study empirically examines the impact of logistics performance on consumer purchase frequency using data from e-commerce platforms specializing in cross-border luxury goods. Leveraging detailed consumer purchase data, we circumvent the pitfalls of the “customer satisfaction trap.” Our analysis reveals surprising insights into how cross-border shipping times affect future purchasing behavior and how the rigorous quality inspection processes for luxury goods influence consumer decisions. By linking consumer order records with logistics completion and merchant processing efficiency, we uncover the nuanced effects of logistics performance on consumer behavior. Our findings suggest that delivery delays and extended transit times negatively impact purchase frequency, particularly when coupled with increased shipping costs, although this negative effect is somewhat attenuated in the context of cross-border shipping. Intriguingly, we observe a positive relationship between increased order processing time and consumer purchase frequency, indicating that consumers prioritize quality assurance, even if it entails longer wait times for product inspection.
{"title":"Impact of logistics delivery performance on consumers’ future purchase behavior: Evidence from an e-commerce platform in China","authors":"Xin Tian , Bochao Yan , Xiaohui Zhou , Yinyun Yan","doi":"10.1016/j.elerap.2025.101509","DOIUrl":"10.1016/j.elerap.2025.101509","url":null,"abstract":"<div><div>Logistics plays a crucial role in the operations of e-commerce platforms, but few studies have directly investigated its influence on consumer purchase frequency. While some research indicates a significant positive relationship between logistics performance and consumer satisfaction, relying solely on satisfaction scores to predict future purchasing behavior may lead to the “customer satisfaction trap.” This study empirically examines the impact of logistics performance on consumer purchase frequency using data from e-commerce platforms specializing in cross-border luxury goods. Leveraging detailed consumer purchase data, we circumvent the pitfalls of the “customer satisfaction trap.” Our analysis reveals surprising insights into how cross-border shipping times affect future purchasing behavior and how the rigorous quality inspection processes for luxury goods influence consumer decisions. By linking consumer order records with logistics completion and merchant processing efficiency, we uncover the nuanced effects of logistics performance on consumer behavior. Our findings suggest that delivery delays and extended transit times negatively impact purchase frequency, particularly when coupled with increased shipping costs, although this negative effect is somewhat attenuated in the context of cross-border shipping. Intriguingly, we observe a positive relationship between increased order processing time and consumer purchase frequency, indicating that consumers prioritize quality assurance, even if it entails longer wait times for product inspection.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"72 ","pages":"Article 101509"},"PeriodicalIF":5.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-15DOI: 10.1016/j.elerap.2025.101510
Xingpeng Xu , Qingfeng Zeng , Ri Na , Weiguo Fan
It is known that streamers play a special role in live streaming commerce, but there is a huge discrepancy in sales performance resulting from different characteristics of streamers. This study applies social influence theory to systematically analyze how streamer characteristics interact to affect sales performance. Using a unique dataset of 120,794 live streaming records from 597 streamers on Douyin platform, we establish a fixed effects model with unbalanced panel data. The results show that previous sales have strong momentum effects. Total views, number of live commercial products and live streaming duration all have a positive impact on sales volumes. Heterogeneity analysis reveals significant differences across identity types, industry types, and authentication statuses, with celebrities, streamers from entertainment and leisure sectors, and unverified streamers showing notably stronger gains. These findings provide empirical evidence to guide streamers and platforms in optimizing marketing strategies in the competitive live streaming commerce.
{"title":"Unveiling the influence of streamer characteristics on sales performance in live streaming commerce","authors":"Xingpeng Xu , Qingfeng Zeng , Ri Na , Weiguo Fan","doi":"10.1016/j.elerap.2025.101510","DOIUrl":"10.1016/j.elerap.2025.101510","url":null,"abstract":"<div><div>It is known that streamers play a special role in live streaming commerce, but there is a huge discrepancy in sales performance resulting from different characteristics of streamers. This study applies social influence theory to systematically analyze how streamer characteristics interact to affect sales performance. Using a unique dataset of 120,794 live streaming records from 597 streamers on Douyin platform, we establish a fixed effects model with unbalanced panel data. The results show that previous sales have strong momentum effects. Total views, number of live commercial products and live streaming duration all have a positive impact on sales volumes. Heterogeneity analysis reveals significant differences across identity types, industry types, and authentication statuses, with celebrities, streamers from entertainment and leisure sectors, and unverified streamers showing notably stronger gains. These findings provide empirical evidence to guide streamers and platforms in optimizing marketing strategies in the competitive live streaming commerce.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"72 ","pages":"Article 101510"},"PeriodicalIF":5.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.elerap.2025.101505
Xin Yan , Wenxin Wang , Yuanyuan Jiao
The information cocoon, a phenomenon prevalent on digital platforms, significantly influences customer experiences. However, its impact remains debated, and it is still unclear whether it facilitates or hinders customer engagement. This study develops and empirically tests a conditional process model to examine how the information cocoon influences customer stickiness within the context of e-commerce platforms. The findings indicate that the effect of the information cocoon on customer stickiness is dual-edged and contingent upon customers’ decision-making styles. In addition, the underlying mechanisms through which the information cocoon affects different dimensions of customer stickiness, namely purchase stickiness and visit stickiness, are not the same. This study expands the application scope and theoretical boundaries of the information cocoon concept, highlights its dual impact on customer stickiness, and deepens the theoretical understanding of how customer stickiness develops.
{"title":"Promoting or inhibiting? The impact of the information cocoon on customer stickiness in e-commerce platforms: The moderating role of decision-making style","authors":"Xin Yan , Wenxin Wang , Yuanyuan Jiao","doi":"10.1016/j.elerap.2025.101505","DOIUrl":"10.1016/j.elerap.2025.101505","url":null,"abstract":"<div><div>The information cocoon, a phenomenon prevalent on digital platforms, significantly influences customer experiences. However, its impact remains debated, and it is still unclear whether it facilitates or hinders customer engagement. This study develops and empirically tests a conditional process model to examine how the information cocoon influences customer stickiness within the context of e-commerce platforms. The findings indicate that the effect of the information cocoon on customer stickiness is dual-edged and contingent upon customers’ decision-making styles. In addition, the underlying mechanisms through which the information cocoon affects different dimensions of customer stickiness, namely purchase stickiness and visit stickiness, are not the same. This study expands the application scope and theoretical boundaries of the information cocoon concept, highlights its dual impact on customer stickiness, and deepens the theoretical understanding of how customer stickiness develops.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"71 ","pages":"Article 101505"},"PeriodicalIF":5.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.elerap.2025.101506
Ankai Li , Li Wang , Haijun Yang , Harris Wu
The growth of content-sharing platforms facilitates the transfer of users to e-commerce sites. However, content-sharing platforms face copyright infringement issues related to content theft and platform invasion, dampening the flow of traffic to e-commerce. Traditional copyright protection methods lack effectiveness and efficiency, which can be solved by Non-Fungible Tokens (NFTs) stored on a blockchain. This study examines how a content-sharing platform adopts three NFT-based copyright protection strategies: the NFT-based copyright certification strategy to combat content theft, the NFT-based content moderation, and copyrighted material provision strategies to combat platform invasion. Our paper models a two-sided platform with content consumers and suppliers. Platform invasion occurs when suppliers bring copyright-infringing content to the platform, while content theft refers to content suppliers being pirated outside the platform. We identify the optimal combination of platform copyright protection strategies. The platform may adopt the copyright certification strategy to combat content theft. However, we show that the platform cannot benefit from adopting both content moderation and material provision strategies to counter platform invasion if the quantity of infringing materials used by infringers is small and the material provisioning costs of the platform are low. Moreover, there are mutually enhancing effects between content moderation and material provision strategies. Our study emphasizes the importance of NFT-based copyright protection strategies to content-sharing platforms and provides a comprehensive framework for understanding the implications of copyright certification, content moderation, and copyrighted material provision.
{"title":"Content-sharing platforms’ copyright protection strategies with non-fungible tokens","authors":"Ankai Li , Li Wang , Haijun Yang , Harris Wu","doi":"10.1016/j.elerap.2025.101506","DOIUrl":"10.1016/j.elerap.2025.101506","url":null,"abstract":"<div><div>The growth of content-sharing platforms facilitates the transfer of users to e-commerce sites. However, content-sharing platforms face copyright infringement issues related to content theft and platform invasion, dampening the flow of traffic to e-commerce. Traditional copyright protection methods lack effectiveness and efficiency, which can be solved by Non-Fungible Tokens (NFTs) stored on a blockchain. This study examines how a content-sharing platform adopts three NFT-based copyright protection strategies: the NFT-based copyright certification strategy to combat content theft, the NFT-based content moderation, and copyrighted material provision strategies to combat platform invasion. Our paper models a two-sided platform with content consumers and suppliers. Platform invasion occurs when suppliers bring copyright-infringing content to the platform, while content theft refers to content suppliers being pirated outside the platform. We identify the optimal combination of platform copyright protection strategies. The platform may adopt the copyright certification strategy to combat content theft. However, we show that the platform cannot benefit from adopting both content moderation and material provision strategies to counter platform invasion if the quantity of infringing materials used by infringers is small and the material provisioning costs of the platform are low. Moreover, there are mutually enhancing effects between content moderation and material provision strategies. Our study emphasizes the importance of NFT-based copyright protection strategies to content-sharing platforms and provides a comprehensive framework for understanding the implications of copyright certification, content moderation, and copyrighted material provision.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"71 ","pages":"Article 101506"},"PeriodicalIF":5.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.elerap.2025.101503
Lu Wang , Min Zhang , Yiwei Li
In order to improve the information exchange between customers, the social development of online review systems enables customers to interact with focal customers by responding to initial reviews. Our purpose is to investigate the effect of customer responses (CRs) on subsequent customer rating behavior. Based on cue utilization theory, we hypothesize that CRs minimize fit uncertainty, resulting in better customer and product fits, and eventually high ratings. We examine whether and how CRs affect subsequent ratings through cross-platform difference-in-differences and within-platform identification strategies. The results show that CRs have significant positive effects on subsequent ratings. The features of CR, including CR content, CR sentiment, and CR timeliness have an impact on the subsequent review rating. Additionally, rating variance positively moderates CRs’ effect. This study contributes to the customer-to-customer interactions literature and provides practical guidance for customers, platforms, and businesses to manage and leverage online reviews.
{"title":"The power of C2C interactions: Effect of customer responses to online reviews on subsequent ratings","authors":"Lu Wang , Min Zhang , Yiwei Li","doi":"10.1016/j.elerap.2025.101503","DOIUrl":"10.1016/j.elerap.2025.101503","url":null,"abstract":"<div><div>In order to improve the information exchange between customers, the social development of online review systems enables customers to interact with focal customers by responding to initial reviews. Our purpose is to investigate the effect of customer responses (CRs) on subsequent customer rating behavior. Based on cue utilization theory, we hypothesize that CRs minimize fit uncertainty, resulting in better customer and product fits, and eventually high ratings. We examine whether and how CRs affect subsequent ratings through cross-platform difference-in-differences and within-platform identification strategies. The results show that CRs have significant positive effects on subsequent ratings. The features of CR, including CR content, CR sentiment, and CR timeliness have an impact on the subsequent review rating. Additionally, rating variance positively moderates CRs’ effect. This study contributes to the customer-to-customer interactions literature and provides practical guidance for customers, platforms, and businesses to manage and leverage online reviews.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"71 ","pages":"Article 101503"},"PeriodicalIF":5.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.elerap.2025.101500
Yushuo Cao , Wei Zhong Wang , Yajing Zhang , Muhammet Deveci , Seifedine Kadry , Limin Wang
The exchange of goods on e-commerce platforms has become an essential channel in contemporary digital landscapes. Utilizing data-driven nudging as a strategic approach to shaping consumer behavior should consider numerous influential factors. Nevertheless, there remains a deficiency in analyzing the factors that facilitate the implementation of data-driven nudging on e-commerce platforms. This work explores the influencing factors of data-driven nudging adoption in e-commerce platforms using a probabilistic linguistic decision framework that incorporates the DEMATEL (decision-making trail and evaluation laboratory)-ISM (interpretive structural modeling) method. To uncover the challenges and opportunities of using data-driven nudging for e-commerce platforms, we identify sixteen influencing factors based on SWOT (strengths, weaknesses, opportunities, and threats) and a literature review. Then, the probabilistic linguistic DEMATEL method is introduced to depict the interaction relationships among these factors. Subsequently, the ISM method is used to build these factors’ contextual linkages and hierarchical structures. Finally, we conducted a questionnaire survey to obtain the data for the analysis framework. The results show that the main strength is “the desirability of handling and utilizing a product ()”, the main weakness is “misdirection ()”, the primary opportunity is “Making appropriate policies ()”, and the main threat is “affecting freedom and autonomy ()”. Our research provides a new analytical tool for identifying the factors that utilize data-driven nudging in e-commerce platforms, offering practical implications for both e-commerce platforms and merchants.
{"title":"Analyzing adoption factors of data-driven nudging for e-commerce platforms using an integrated decision model","authors":"Yushuo Cao , Wei Zhong Wang , Yajing Zhang , Muhammet Deveci , Seifedine Kadry , Limin Wang","doi":"10.1016/j.elerap.2025.101500","DOIUrl":"10.1016/j.elerap.2025.101500","url":null,"abstract":"<div><div>The exchange of goods on e-commerce platforms has become an essential channel in contemporary digital landscapes. Utilizing data-driven nudging as a strategic approach to shaping consumer behavior should consider numerous influential factors. Nevertheless, there remains a deficiency in analyzing the factors that facilitate the implementation of data-driven nudging on e-commerce platforms. This work explores the influencing factors of data-driven nudging adoption in e-commerce platforms using a probabilistic linguistic decision framework that incorporates the DEMATEL (decision-making trail and evaluation laboratory)-ISM (interpretive structural modeling) method. To uncover the challenges and opportunities of using data-driven nudging for e-commerce platforms, we identify sixteen influencing factors based on SWOT (strengths, weaknesses, opportunities, and threats) and a literature review. Then, the probabilistic linguistic DEMATEL method is introduced to depict the interaction relationships among these factors. Subsequently, the ISM method is used to build these factors’ contextual linkages and hierarchical structures. Finally, we conducted a questionnaire survey to obtain the data for the analysis framework. The results show that the main strength is “the desirability of handling and utilizing a product (<span><math><msub><mi>θ</mi><mn>4</mn></msub></math></span>)”, the main weakness is “misdirection (<span><math><msub><mi>θ</mi><mn>5</mn></msub></math></span>)”, the primary opportunity is “Making appropriate policies (<span><math><msub><mi>θ</mi><mn>12</mn></msub></math></span>)”, and the main threat is “affecting freedom and autonomy (<span><math><msub><mi>θ</mi><mn>13</mn></msub></math></span>)”. Our research provides a new analytical tool for identifying the factors that utilize data-driven nudging in e-commerce platforms, offering practical implications for both e-commerce platforms and merchants.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"71 ","pages":"Article 101500"},"PeriodicalIF":5.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-11DOI: 10.1016/j.elerap.2025.101502
Huiran Li , Qiucheng Li , Baozhu Feng
In search engine advertising (SEA) market, where competition among retailers is intense and multifaceted, channel coordination between retailers and manufacturers emerges as a critical factor, which significantly influences the effectiveness of advertising strategies. This research attempts to provide managerial guidelines for cooperative advertising in the SEA context by modeling two cooperative advertising decision scenarios. Scenario I defines a simple cooperative channel consisting of one manufacturer and one retailer. In Scenario II, we consider a more general setting where there is an independent retailer who competes with the Manufacturer-Retailer alliance in Scenario I. We propose a novel cooperative advertising optimization model, wherein a manufacturer can advertise product directly through SEA campaigns and indirectly by subsidizing its retailer. To highlight the distinctive features of SEA, our model incorporates dynamic quality scores and focuses on a finite time horizon. In each scenario, we provide a feasible equilibrium solution of optimal policies for all members. Subsequently, we conduct numerical experiments to perform sensitivity analysis for both the quality score and gross margin. Additionally, we explore the impact of the initial market share of the competing retailer in Scenario II. Finally, we investigate how retail competition affects the cooperative alliance’s optimal strategy and channel performance. Our identified properties derived from the equilibrium and numerical analyses offer crucial insights for participants engaged in cooperative advertising within the SEA market.
{"title":"Dynamic cooperative strategies in search engine advertising market: With and without retail competition","authors":"Huiran Li , Qiucheng Li , Baozhu Feng","doi":"10.1016/j.elerap.2025.101502","DOIUrl":"10.1016/j.elerap.2025.101502","url":null,"abstract":"<div><div>In search engine advertising (SEA) market, where competition among retailers is intense and multifaceted, channel coordination between retailers and manufacturers emerges as a critical factor, which significantly influences the effectiveness of advertising strategies. This research attempts to provide managerial guidelines for cooperative advertising in the SEA context by modeling two cooperative advertising decision scenarios. Scenario I defines a simple cooperative channel consisting of one manufacturer and one retailer. In Scenario II, we consider a more general setting where there is an independent retailer who competes with the Manufacturer-Retailer alliance in Scenario I. We propose a novel cooperative advertising optimization model, wherein a manufacturer can advertise product directly through SEA campaigns and indirectly by subsidizing its retailer. To highlight the distinctive features of SEA, our model incorporates dynamic quality scores and focuses on a finite time horizon. In each scenario, we provide a feasible equilibrium solution of optimal policies for all members. Subsequently, we conduct numerical experiments to perform sensitivity analysis for both the quality score and gross margin. Additionally, we explore the impact of the initial market share of the competing retailer in Scenario II. Finally, we investigate how retail competition affects the cooperative alliance’s optimal strategy and channel performance. Our identified properties derived from the equilibrium and numerical analyses offer crucial insights for participants engaged in cooperative advertising within the SEA market.</div></div>","PeriodicalId":50541,"journal":{"name":"Electronic Commerce Research and Applications","volume":"71 ","pages":"Article 101502"},"PeriodicalIF":5.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143847318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.elerap.2025.101499
Wang Zhao , Dongxiao Gu , Rui Mao , Xiaoyu Wang , Xuejie Yang , Kaixuan Zhu , Hao Hu , Haimiao Mo , Erik Cambria
The COVID-19 pandemic has markedly exacerbated the complexities surrounding the diagnosis and prognosis of diverse severe pneumonia types, posing extraordinary challenges to healthcare systems worldwide. While previous AI-based approaches primarily targeted COVID-19 severe pneumonia and sought to enhance machine learning accuracy, they often neglected critical aspects such as distinguishing diagnostic and prognostic features among COVID-19 infectious, non-COVID infectious, and non-infectious severe pneumonia, as well as the explainability and fairness of user-centric AI assist decisions. This study es the need for robust, fair, and reliable diagnosis and prognosis of severe pneumonia within the context of the COVID-19 pandemic. This paper introduces a user-centric framework that first employs a GaussianCopula-based data augmentation method to enhance fairness by addressing small imbalanced sample sets. Following this, the framework introduces an explainable AI system designed to classify three types of severe pneumonia using demographic and physiological indicators, offering transparent decision-making processes and an understandable analysis of prognosis risk factors. Our fair system utilizes transparent models exclusively, which enables healthcare practitioners to access intelligent and reliable medical services such as pre-diagnosis and prognosis analysis (the likelihood of death) of severe pneumonia. The results show the data augmentation method efficiently reduces data bias and enhances fairness, reaching 70.70% distribution similarity. Our transparent model-based severe pneumonia classification module achieves 98.88% F1-scores on a real-world dataset. The transparent mechanism reveals that the four most significant features for classifying severe pneumonia types are ‘Interleukin_6’, ‘Albumin’, ‘D_Dimer’, and ‘CD4_absolute_count’. Meanwhile, the explainable statistical analysis identifies critical mortality risk factors for each pneumonia category: ‘Blood platelet’ and ‘Creatinine’ for COVID-19 severe pneumonia, ‘Hemameba’, ‘Interleukin-6’, and ‘Uric Acid’ for non-COVID-19 infectious severe pneumonia, and ‘Hemameba’, ‘BNP’, ‘Cholesterol’, and ‘PT’ for non-infectious severe pneumonia. Our study highlights the potential of transparent machine learning algorithms for accurate diagnosis and Cox proportional regression for transparent risk trend prediction. These analytical tools and medical results can facilitate early and appropriate management of pneumonia patients for doctors, potentially revolutionizing diagnostic processes and patient care strategies to improve clinical outcomes.
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