Learning Adaptive Display Exposure for Real-Time Advertising

In E-commerce advertising, where product recommendations and product ads are presented to users simultaneously, the traditional setting is to display ads at fixed positions. However, under such a setting, the advertising system loses the flexibility to control the number and positions of ads, resulting in sub-optimal platform revenue and user experience. Consequently, major e-commerce platforms (e.g., Taobao.com) have begun to consider more flexible ways to display ads. In this paper, we investigate the problem of advertising with adaptive exposure: can we dynamically determine the number and positions of ads for each user visit under certain business constraints so that the platform revenue can be increased? More specifically, we consider two types of constraints: request-level constraint ensures user experience for each user visit, and platform-level constraint controls the overall platform monetization rate. We model this problem as a Constrained Markov Decision Process with per-state constraint (psCMDP) and propose a constrained two-level reinforcement learning approach to decompose the original problem into two relatively independent sub-problems. To accelerate policy learning, we also devise a constrained hindsight experience replay mechanism. Experimental evaluations on industry-scale real-world datasets demonstrate the merits of our approach in both obtaining higher revenue under the constraints and the effectiveness of the constrained hindsight experience replay mechanism.Comment: accepted by CIKM201

Alibaba's strategic drift

It is fundamental in both a theoretical and practical sense, to analyse the strategies of successful e-businesses who were formulated and operated alongside incumbent competitors. Thus, there have been an array of strategic arguments concerning the rapidly-burgeoning virtual powerhouse Alibaba, who amidst a sea of fortified competitors, found their ground to become one of the most prominent e-businesses of the decade. At the commencing stages, Alibaba lacked a specific strategic goal, aside from the ethnic-originated ecology scheme. Further mishaps arose even after the take-off stage, when Alibaba opted to adhere to the diversification strategy, an evidently unusual phase for a virtual firm. Hence, it is the subject of common debate as to whether Alibaba cited a definitive strategic goal which guided their progress, or whether they were merely the product of a breakneck growth in the Chinese economy. This research will show how a leading e-Commerce company Alibaba has built B2B/C2C business portal Taobao/TMall and has transformed its transaction system from zhifubao into yuerbao and how it propelled Alipay to become a leading financial institution in the thriving digital market. In addition, strategic diversification on Chinese digital business will be examined through Alibaba case

Ecosystem synergies, change and orchestration

This thesis investigates ecosystem synergies, change, and orchestration. The research topics are motivated by my curiosity, a fragmented research landscape, theoretical gaps, and new phenomena that challenge extant theories. To address these motivators, I conduct literature reviews to organise existing studies and identify their limited assumptions in light of new phenomena. Empirically, I adopt a case study method with abductive reasoning for a longitudinal analysis of the Alibaba ecosystem from 1999 to 2020. My findings provide an integrated and updated conceptualisation of ecosystem synergies that comprises three distinctive but interrelated components: 1) stack and integrate generic resources for efficiency and optimisation, 2) empower generative changes for variety and evolvability, and 3) govern tensions for sustainable growth. Theoretically grounded and empirically refined, this new conceptualisation helps us better understand the unique synergies of ecosystems that differ from those of alternative collective organisations and explain the forces that drive voluntary participation for value co-creation. Regarding ecosystem change, I find a duality relationship between intentionality and emergence and develop a phasic model of ecosystem sustainable growth with internal and external drivers. This new understanding challenges and extends prior discussions on their dominant dualism view, focus on partial drivers, and taken-for-granted lifecycle model. I propose that ecosystem orchestration involves systematic coordination of technological, adoption, internal, and institutional activities and is driven by long-term visions and adjusted by re-visioning. My analysis reveals internal orchestration's important role (re-envisioning, piloting, and organisation architectural reconfiguring), the synergy and system principles in designing adoption activities, and the expanding arena of institutional activities. Finally, building on the above findings, I reconceptualise ecosystems and ecosystem sustainable growth to highlight multi-stakeholder value creation, inclusivity, long-term orientation and interpretative approach. The thesis ends with discussing the implications for practice, policy, and future research.Open Acces

Developing a Leading Digital Multi-sided Platform: Examining IT Affordances and Competitive Actions in Alibaba.com

In recent times, digital multi-sided platforms (DMSPs) have revolutionized electronic commerce by enabling new forms of competition and collaboration. Existing studies provide useful insights yet do not recognize the role of information technologies (IT) in examining the development of DMSPs. To address this knowledge gap, we conducted a case study of Alibaba.com (henceforth simply Alibaba), the largest online B2B marketplace in the world with over 80 million members. We applied the theoretical notion of IT affordances to examine the possibilities for competitive action at a platform level based on organizational variables and IT features in the context of the environment in which they function. Our findings show that, toward market leadership, Alibaba has developed competitive actions from actualizing IT affordances. At Alibaba, actualizing IT affordances links closely with its defined organizational goals of developing: (1) a collectivist structure, (2) a coopetitive structure, and (3) an autonomous community among platform constituents. Our stage-wise model captures the relational aspects of IT affordances and proposes actionable prescriptions for a DMSP to achieve market leadership

What Should Streamers Communicate in Livestream E-Commerce? The Effects of Social Interactions on Live Streaming Performance

Compared with traditional e-commerce, livestreaming e-commerce is characterized by direct and intimate communication between streamers and consumers that stimulates instant social interactions. This study focuses on streamers’ three types of information exchange (i.e., product information, social conversation, and social solicitation) and examines their roles in driving both short-term and long-term livestreaming performance (i.e., sales and customer base growth). We find that the informational role of product information (nonpromotional and promotional) is beneficial not only to sales performance, but also to the growth of the customer base. We also find that social conversation has a relationship-building effect that positively impacts both sales and customer base growth, whereas social solicitation has both a relationship-building and a relationship-straining effect that positively affects customer base growth but can hurt sales. Furthermore, our results show that streamers’ social interactions with consumers can stimulate consumer engagement in different ways, leading to different effects on livestreaming performance

Short-Video Marketing in E-commerce: Analyzing and Predicting Consumer Response

This study analyzes and predicts consumer viewing response to e-commerce short-videos (ESVs). We first construct a large-scale ESV dataset that contains 23,001 ESVs across 40 product categories. The dataset consists of the consumer response label in terms of average viewing durations and human-annotated ESV content attributes. Using the constructed dataset and mixed-effects model, we find that product description, product demonstration, pleasure, and aesthetics are four key determinants of ESV viewing duration. Furthermore, we design a content-based multimodal-multitask framework to predict consumer viewing response to ESVs. We propose the information distillation module to extract the shared, special, and conflicted information from ESV multimodal features. Additionally, we employ a hierarchical multitask classification module to capture feature-level and label-level dependencies. We conduct extensive experiments to evaluate the prediction performance of our proposed framework. Taken together, our paper provides theoretical and methodological contributions to the IS and relevant literature

A New Approach for Product Quality Check Based on Social Networks Opinions Analysis

In this paper, we aim to enhance the relevance of e-commerce web sites by a prior quality checking of proposed products. This checking is done by analyzing social networks and YouTube videos comments. To achieve this objective, we have broken down the work into a few steps. The first one consists in scraping text from social networks groups and storing it in a NoSQL graph database. Each scraped word is linked to one or many reactions that are coming from the social network. Therefore, we can utilize the database as a knowledge source that associates each set of terms with a specific type of reaction: positive, negative or neutral. Afterwards, we use a TF-IDF based filtering method to keep only relevant words and eliminate those which are a connected to all reactions. The advantage of this stage is the presence of a knowledge source that can be used for product quality checking. In the e-commerce web site, data are coming from multiple e-commerce websites. The latter, offer products without quality checking. Concretely, we aim to allow users to check quality by a simple check button which call an implemented web service using human reactions and comments. After evaluating our approach, we have obtained an accuracy of 0,75. This result means that our method gives a three quarter of chance to have a good product

Bigtechs and the financial system

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