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Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond

Published: 14 August 2022 Publication History

Abstract

Online marketplace is a digital platform that connects buyers (demand) and sellers (supply) and provides exposure opportunities that individual participants would not otherwise have access to. Online marketplaces exist in a diverse set of domains and industries, for example, rideshare (Lyft, DiDi, Uber), house rental (Airbnb), real estate (Beke), online retail (Amazon, Ebay), job search (LinkedIn, Indeed.com, CareerBuilder), and food ordering and delivery (Doordash, Meituan). Besides academia, many companies and institutions are researching on topics specific to their particular domains. The fundamental mechanism of an online marketplace is to match supply and demand to generate transactions, with objectives considering service quality, participants experience, financial and operational efficiency. It is valuable to bring together researchers and practitioners from different application domains to discuss their experiences, challenges, and opportunities to leverage cross-domain knowledge. The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains. This workshop will follow a dual-track format. Track 1 covers the issues and algorithms pertinent to general online marketplaces as well as specific problems and applications arising from those diverse domains, such as ridesharing, online retail, food delivery, house rental, real estate, and more. Track 2 focuses on the state of the art advances in the computational jobs marketplace. Interesting challenges in this domain include the drastic increase of work from home or remote work, the imbalance between the demand and supply of the job market, the popularity of independent workers, the capability of helping job seekers on their whole job seeking journey and career development, the different objectives and behaviors of all major stakeholders in the ecosystem, e.g. job seekers, employers, recruiters and job agents.

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  • (2024)Towards Supply-Demand Equilibrium With Ridesharing: An Elastic Order Dispatching Algorithm in MoD SystemIEEE Transactions on Mobile Computing10.1109/TMC.2023.330309023:5(5229-5244)Online publication date: May-2024

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  1. Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond

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      cover image ACM Conferences
      KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
      August 2022
      5033 pages
      ISBN:9781450393850
      DOI:10.1145/3534678
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

      Publication History

      Published: 14 August 2022

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      Author Tags

      1. data science
      2. decision intelligence
      3. machine learning
      4. marketplace
      5. on-demand platform
      6. online experiments
      7. online job marketplace
      8. optimization

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      • (2024)Towards Supply-Demand Equilibrium With Ridesharing: An Elastic Order Dispatching Algorithm in MoD SystemIEEE Transactions on Mobile Computing10.1109/TMC.2023.330309023:5(5229-5244)Online publication date: May-2024

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