Designing crowdsourced delivery systems: The effect of driver disclosure and ethnic similarity

Published date01 May 2018
Date01 May 2018
DOIhttp://doi.org/10.1016/j.jom.2018.06.001
Contents lists available at ScienceDirect
Journal of Operations Management
journal homepage: www.elsevier.com/locate/jom
Designing crowdsourced delivery systems: The eect of driver disclosure
and ethnic similarity
Ha Ta
a,
, Terry L. Esper
b
, Adriana Rossiter Hofer
c
a
David D. Reh School of Business, Clarkson University, Potsdam, NY, 13699, USA
b
Department of Supply Chain Management, Fisher College of Business, The Ohio State University, Columbus, OH, 43210, USA
c
Department of Supply Chain Management, Sam M. Walton College of Business, University of Arkansas, Fayetteville, AR, 72701, USA
ARTICLE INFO
Handling Editor: S. de Treville.
Keywords:
Crowsourced delivery
Sharing economy
Service design
Technology management
Ethnicity
ABSTRACT
Crowdsourced delivery is a service operations model that has proliferated in recent years, bringing unique
opportunities and challenges to online retail operations. In particular, new technology enabled features, such as
the disclosure of delivery drivers' identities, introduce a social dimension prior to delivery service encounters
that might inuence customers' service quality expectations and ultimately impact their attitudes towards the
retailers. Building on premises of social identity theory, this research investigates eects of various crowd-
sourced delivery system designs related to driver disclosure and ethnicity on customers' attitudes towards the
drivers and retailers. Using data from a scenario-based experiment with 761 participants across two studies, we
nd that crowdsourced delivery designs that disclose drivers' identity increase customers' trust, satisfaction, and
repurchase intentions only when customers perceive the drivers to be similar to them, particularly with regard to
ethnicity. The designs that oer driver choice options are also found to be highly regarded by customers. In
addition, the similarity eects of crowdsourced delivery designs dier depending on certain customer char-
acteristics. Overall, our research shows crowdsourced delivery - as a technology-driven phenomenon - may
portend unexpected and challenging social dilemmas for operations managers. Our ndings contribute to
emerging research on the intersection of service design, technology management, and the sharing economy.
1. Introduction
A signicant trend impacting contemporary business is the growth
of the sharing economy (Zervas et al., 2017). Dened as peer to peer
activity of obtaining, giving, or sharing access to goods and services via
online technology platforms(Hamari et al., 2015, p.1), the sharing
economy has been characterized as one of today's fastest growing and
most innovative business segments. Business ventures rooted in the
sharing economy are projected to reach $335B in revenue by 2025
(PricewaterhouseCoopers, 2015) with a sizable portion of such growth
involving crowdsourced delivery and physical distribution services
(PDS).
Often referred to as the uberizationof PDS, due to an operational
similarity to the ride-sharing service company Uber, crowdsourced
delivery (illustrated in Fig. 1) involves the outsourcing of last mile PDS
to a mass of marketplace actors through technology-based coordination
infrastructures (Mehmann et al., 2015). While crowdsourced delivery
still reaches only a small percentage of the U.S. market - 10% among
millennials and 3% among non-millennials (Ivory and Barker, 2016)-
the potential growth opportunities have attracted many new
marketplace entrants. Crowdsourcing-based service providers such as
UberEats, Amazon Flex, Deliv, Deliveroo, Instacart, JoyRun, Dada,
Zipments, DoorDash, and Postmates have emerged in recent years,
making crowdsourced delivery a viable tactic for designing and
managing last mile PDS operations. This idea is notably represented by
retailers such as Amazon, which estimates a 30% reduction in costs
using crowdsourced delivery (Kitroe, 2016), and China's JD Daoja,
which reported higher repeat customer purchasing rates due to service
enhancements associated with crowdsourced delivery (Perez, 2016).
Though crowdsourced delivery is growing in use, operations man-
agers must acknowledge a number of dierences from traditional de-
livery services. If not designed and managed eectively, these dier-
ences could have a negative impact on customers' performance and
quality evaluations (Heim and Field, 2007;Heim and Sinha, 2001b). In
particular, several unique service-oriented features oered by crowd-
sourcing technologies, such as real time GPS-based package/driver
tracking, direct communication with drivers via phones/texts, and
disclosure of driver identication specics such as name and photo,
provide a dierent customer experience before, during, and after ser-
vice encounters. Moreover, because crowdsourcing technology allows
https://doi.org/10.1016/j.jom.2018.06.001
Received 8 September 2016; Received in revised form 31 May 2018; Accepted 5 June 2018
Corresponding author.
E-mail addresses: hta@clarkson.edu (H. Ta), Esper.9@osu.edu (T.L. Esper), ahofer@walton.uark.edu (A.R. Hofer).
Journal of Operations Management 60 (2018) 19–33
Available online 22 June 2018
0272-6963/ © 2018 Elsevier B.V. All rights reserved.
T

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