邱平简历
教育背景
研究情况
已发表的研究
正在被审稿中的研究
正在进行中的研究
课题参与情况
博士导师
学术会议参会情况
教学经历
领导力 & 社区服务
荣誉 & 奖项
外语 & 技能
外语能力
软件技能
专业技能证书
个人照片
研究成果
Disentangling the impact of bidding price on advertising performance in E-commerce search advertising: The moderating role of product competitiveness
📝 摘要
Though E-commerce search advertising has become an increasingly prevalent approach for online retailers to promote their products, it is nontrivial for online retailers to use search advertising effectively, particularly without a comprehensive understanding of the effect of bidding price. This research investigates the effect of bidding price on product click-through rate and conversion rate, with a focus on the moderating role of product competitiveness. We collected data consisting of 10,734 search advertising records of 421 advertised stock keeping units and 206 keywords from a retailer operating on a leading e-commerce platform. This dataset was matched with data of 39,066 rival products to construct the indexes of product competitiveness in terms of mouth and product competitiveness in terms of sale price. Contradictory to the wisdom that there is a monotone relationship between bidding price and click-through/conversion rate, our result reveals an inverted U-shaped relationship between bidding price and click-through/conversion rate. Moreover, product competitiveness in terms of word-of-mouth weakens the inverted U-shaped relationship between bidding price and click-through/conversion rate, while product competitiveness in terms of sale price only weakens the inverted U-shaped relationship between bidding price and click-through rate, but not conversion rate. This research enriches the literature on search advertising by untangling the impact of bidding price and the moderating role of product competitiveness.
Designing tax plans in international environmental agreements with heterogeneous benefits
📝 摘要
We present an analysis of carbon abatement regulation through a self-enforcing international environmental agreement (IEA) model featuring two types of countries with dissimilar abatement benefits. The IEA involves a tax plan function that allocates an emission tax rate to each type of country under every coalition of voluntary signatories. An efficient tax plan is one that maximizes social welfare under a stable coalition, while an optimal tax plan maximizes the average payoff of a stable coalition. We demonstrate that an efficient or optimal tax plan always exists, and that the corresponding value of social welfare or average coalition payoff is greater than that under certain traditional tax systems. If the benefit heterogeneity between the two types of countries is sufficiently small, full cooperation and social optimum can be achieved or approximated through an efficient or optimal plan. Conversely, a high degree of heterogeneity will result in a relatively small coalition and an inefficient outcome, regardless of the tax plan employed.
How to Kickstart New Product Variant in E-Commerce: Roles of Variant Similarity and Word-of-Mouth
📝 摘要
In e-commerce platforms, a product category typically encompasses multiple variants in different colors and styles. Effectively managing these product variants, particularly the strategy of introducing new variants, is crucial for online retailers' success. However, there is limited theoretical understanding on the effectiveness of adding new variants especially in Ecommerce retailing. This study examines how retailers should introduce new product variants by investigating the impact of variant similarity on sales performance, as well as the moderating role of word-of-mouth (WoM) in the online retail context. Analyzing data from an online retailer operating in a leading e-commerce platform, we find that variant similarity between new and existing variants has inverted U-shaped relationships with both the new variant's sales and the existing variant's sales. Furthermore, WoM moderates both curvilinear relationships by strengthening these inverted U-shaped curves. Our findings provide valuable insights for online retailers' variant introduction strategies and contribute to the literature on e-commerce product category management, new product variant launch, and WoM.
Keyword Advertising for Multiple Products: A Joint Optimization Strategy for Bidding and Budget Allocation Based on Hierarchical Architecture
📝 摘要
This research proposes a hierarchical optimization framework to address the complex decision making challenges faced by ecommerce retailers in multiproduct keyword advertising. In search advertising, retailers must simultaneously manage two interdependent key decisions: bid setting and budget allocation. The optimal bidding strategy depends on the available budget level, while effective budget allocation depends on advertising performance under different bids. Existing research is often limited to single dimension or single-campaign scenarios. This study decomposes the decision process into two levels: the upper strategic level manages budget allocation through a Markov Decision Process for dynamic allocation across multiple periods, and applies differentiated KKT optimality conditions for efficient allocation among different types of campaigns (mature products, promotional products, new products) within a single period; the lower execution level integrates operations research-based bidding models to determine the optimal bid for each campaign under given budget constraints. This dual layer architecture effectively mitigates the curse of dimensionality while enabling precise modeling and quantitative analysis of market mechanisms, dynamically adapting to market environment changes and seasonal fluctuations. Extensive simulation experiments demonstrate that the proposed framework achieves superior performance compared to benchmark strategies.
Disentangling the Impact of AI Anthropomorphism on Planning Satisfaction: An Experimental Investigation
📝 摘要
As artificial intelligence systems become increasingly integrated into planning tasks, the degree of anthropomorphism—attributing human-like characteristics to AI—has emerged as a critical design consideration. This study investigates whether excessive anthropomorphism reduces user satisfaction with AI-assisted planning compared to normal anthropomorphism levels. We conducted a between-subjects experiment with participants randomly assigned to normal or excessive anthropomorphism conditions. Planning satisfaction was measured using a validated multi-item scale with high reliability. Analysis of covariance (ANCOVA) controlled for three theoretically relevant covariates: perceived threat from AI, technology familiarity, and AI literacy. All scales demonstrated excellent internal consistency. Importantly, all covariates significantly correlated with the dependent variable but showed no significant correlation with the experimental condition, confirming proper covariate selection and successful experimental control—a critical requirement for valid ANCOVA inference. Results revealed a significant main effect of anthropomorphism on planning satisfaction. Participants in the normal anthropomorphism condition reported significantly higher satisfaction than those in the excessive anthropomorphism condition. This effect remained robust after controlling for all covariates, indicating that the impact of anthropomorphism level on planning satisfaction is consistent across diverse user characteristics and independent of individual differences in AI perceptions and technological proficiency. These findings provide experimental evidence that excessive anthropomorphism significantly reduces planning satisfaction. Designers of AI planning systems should carefully calibrate anthropomorphic features to avoid crossing the threshold from engagement-enhancing to satisfaction-reducing. The results have important implications for human-AI interaction design, particularly in contexts where user satisfaction and trust are paramount.
Unveiling the nonlinear effect of ESG greenwashing on trade credit provision: A signaling theory perspective
📝 摘要
The escalating environmental, social, and governance (ESG) pressure from stakeholders has precipitated a surge in corporate greenwashing practices. While trade credit represents a critical financing resource, the relationship between ESG greenwashing and trade credit provision remains inadequately explored. To narrow this gap, this study draws upon the signaling theory to explore the relationship between ESG greenwashing and trade credit provision. Furthermore, recognizing that signal effectiveness is contingent upon signal cost and signal observability, this study examines the moderating effects of female representation and industry competition. Analyzing panel data from 1,394 Chinese listed companies spanning 2009-2023, we reveal an inverted U-shaped relationship between ESG greenwashing and trade credit provision. Notably, both female representation and industry competition intensify this curvilinear association, resulting in a steeper inverted U-shaped curve. These findings offer valuable insights for deterring corporate ESG greenwashing and promoting authentic sustainable initiatives in the business landscape.
期刊介绍
Information & Management 是信息系统领域的顶级期刊，中科院SSCI Q1 Top期刊，影响因子8.2。该期刊专注于发表信息技术管理、数字经济、电子商务、数字化转型等领域的高质量研究成果。
期刊介绍
Energy Economics 是经济学领域的顶级期刊，中科院SSCI Q1 Top期刊，影响因子14.2。该期刊是影响因子最高的经济学类专业期刊。
会议介绍
AOM Annual Meeting是美国管理学会（Academy of Management）的年度学术会议，是全球管理学领域最重要的学术盛会之一。该研究已被AOM Annual Meeting Proceedings 2025收录，并正在被Journal of Business Research期刊审稿中。
荣誉&奖项
🎓 学业奖项
🏫 校内荣誉
🏅 学科竞赛奖项
编程能力
Python
Mathematica
Stata
LaTeX
HTML
导师介绍
蔡昭博士是宁波诺丁汉大学商学院(NUBS China)信息系统学教授。在2018年9月加入NUBS China之前，他曾在中国科学技术大学(USTC)担任博士后研究员，并在哥本哈根商学院(CBS)担任访问学者。
蔡教授的研究兴趣专注于数字化运营管理、平台竞争和数字健康的交叉领域。他的研究成果发表在多个顶级期刊上，包括MIS Quarterly (MISQ)、Journal of Operations Management (JOM)、Journal of the Academy of Marketing Science (JAMS)和Journal of the Association for Information Systems (JAIS)等。
蔡教授还是国家自然科学基金委员会(NSFC)面上和青年项目的主持人。在学术服务方面，他担任Industrial Management & Data Systems (IMDS)的执行主编和Internet Research (IR)的副主编。
🎓 主要学术职务
期刊编辑职务：Industrial Management & Data Systems (管理主编)、Internet Research (副主编)
会议职务：Pacific Asia Conference on Information Systems (PACIS) Track Chair、Americas' Conference on Information Systems (AMCIS) Mini-track Chair
会议编辑：International Conference on Information Systems (ICIS)、European Conference of Information Systems (ECIS) 副主编
基金项目：国家自然科学基金委员会(NSFC)青年基金项目主要负责人
陈庆佳教授已发表超过250篇学术文章和9部专著。他的研究成果发表在诸多顶级期刊上，包括Production and Operations Management、European Journal of Operational Research、International Journal of Operations and Production Management、International Journal of Production Economics、Decision Support Systems以及IEEE Transactions等权威期刊。
陈教授目前担任Industrial Management & Data Systems的联合主编(Co-Editor)，以及Transportation Research Part E: Logistics and Transportation Review的副主编(Associate Editor)。此外，他还是多个知名期刊的编委会成员，包括International Journal of Operations and Production Management、International Journal of Production Economics等。
多年来，陈教授为多个备受推崇的国际期刊(联合)编辑了超过20个特刊。在加入学术界之前，陈教授在电子制造业积累了丰富的实践经验，这为他的学术研究提供了深厚的产业背景。
🎓 主要学术职务
期刊编辑职务：Industrial Management & Data Systems (联合主编)、Transportation Research Part E (副主编)
编委会成员：International Journal of Operations and Production Management、International Journal of Production Economics 等
特刊编辑：为20多个国际知名期刊编辑特刊
孔祥天瑞现任深圳大学经济学院供应链管理系长聘副教授，特聘研究员，博士生导师，深圳大学经济学院院长助理。研究领域为智能拍卖、实物互联网（Physical Internet）、决策优化，研究成果已发表在40多个国内外知名期刊，包括《中国管理科学》，Transportation Research Part B, Transportation Research Part E, International Journal of Production Economics, IEEE Transaction on Automation Science and Engineering等。出版《数智化生鲜农产品拍卖机制与运营优化》专著1部。获得中央领导正面批示的国家级资政报告2项。
目前主持多项纵向和国央企横向课题，包括国家自然科学基金委面上和青年项目、教育部人文社科青年项目、广东省自然科学基金面上项目、广东省哲学社科青年项目、香港研究资助局重大项目子课题、深圳科创委重大科技攻关项目子课题等。他为多家知名制造、物流行业的龙头企业提供咨询服务，包括昆明国际鲜花拍卖中心、香港飞机工程有限公司、联想集团、中国烟草、南山集团、美的集团、国药集团等，在智能拍卖领域已授权多个发明专利和实用新型。
🎓 主要学术职务
期刊编辑职务：Industrial Management & Data Systems 编委
学术组织：中国管理现代化研究会管理与决策科学专业委员会理事、中国优选法统筹法与经济数学研究会高等教育管理分会理事、广东经济学会理事
专家委员会：深圳市物流与供应链专家委员会委员
人才项目：深圳市"孔雀计划"海外高层次人才、深圳市南山区领航人才、深圳大学荔园优青
AOM会议pre视频
How to kickstart new product variant in E-commerce: Roles of variant similarity and word-of-mouth
会议名称：AOM Annual Meeting
会议地点：Copenhagen, Denmark
会议时间：2025年7月
留言板