Information Matters: an Empirical Study of the Efficiency of On-Demand Services

Hongyan Dai, Ling Ge () and Yali Liu ()
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Hongyan Dai: Central University of Finance and Economics
Ling Ge: University of Texas at Dallas
Yali Liu: Central University of Finance and Economics

Information Systems Frontiers, 2020, vol. 22, issue 4, No 3, 815-827

Abstract: Abstract On-demand services through Internet platforms, e.g. ride-sharing, food take-out services, have emerged as a new business model. In these businesses, customers place orders on Internet platforms and get services fulfilled offline in a timely manner. In this paper, we examine the factors that affect the efficiency of on-demand food take-out services. Besides operational and road factors, we highlight the role of information integration of the ordering platform and the logistics platform. Our results show that information integration of the two platforms significantly increases service efficiency. Through integration, the logistics platform can optimize delivery dispatch based on more comprehensive and accurate historical and real-time demand and delivery information, avoiding suboptimal and short-sighted decisions. We also find that the efficiency of on-demand services depends much more on the information integration and the operational efficiency of the service provider than road conditions. We discuss the theoretical and practical implications for the business model of on-demand services.

Keywords: On-demand services; Information systems; Online platforms; Crowd-sourcing logistic; Delivery efficiency (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10796-018-9883-2

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