Sharing Economy, Platforms and Crowds

Track Description
Topics around sharing economy, platforms, and crowds have become focal areas of research in information systems. This track continues a series of prior tracks at the International Conference on Information Systems (ICIS) and invites cutting-edge research on these topics. The papers may address one or more of these topics.

Information technology (IT) has enabled the creation of multi-sided platforms, which connect varied actors throughout the world for little marginal cost. These platforms facilitate transactions and interactions in a variety of contexts: transportation, housing and hospitality, crowdfunding, fintech, classified ads, education and massive open online courses (MOOCs), dating, e-commerce, and product review sites. These platforms have disrupted and revolutionized industries, for better and for worse, with both promising and discouraging economic and societal impacts.

The sharing economy in particular leverages platforms and other infrastructures to allow individuals to offer and share their assets with others and have had significant social, legal and economic impacts. Typical user-owned asset platforms include Airbnb, Uber, Didi, Grab, NetJets, and Ouibring. However, the sharing economy also includes platforms that facilitates sharing and renting of company-owned assets such as CitiBike, Ofo, Bird, and Lime, and this track will be open to this broad definition of sharing economy platforms.

Crowd-based models of content production, innovation, funding among others leverage the capability of digital platforms and infrastructures to connect distributed and heterogeneous individuals and organizations for a variety of economic, social, and societal purposes. Here again, the track will entertain crowd-based models within the organization as well as beyond the organizational boundaries.

Track Chairs
Sirkka Jarvenpaa, University of Texas at Austin,
Tuan Phan, University of Hong Kong,
Jui Ramaprasad, McGill University,
Jing Wang, Hong Kong University of Science and Technology,

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Monday, December 14th

A Machine Learning Method for Measuring Information Disclosure in Sharing Economy Platforms

Xin Wei, Tianjin University, College of Management and Economics
Wei He, Texas Tech University
Xi Zhang, Tianjin University
Chuang Zhao, Tianjin University
Hongke Zhao, Tianjin University

Can Digital Platforms help SMEs Develop Organizational Capabilities? A Qualitative Field Study

Ahmad Asadullah, National University of Singapore
Isam Faik, National University of Singapore
Atreyi Kankanhalli, National University of Singapore

Destructive Domination in Crowdsourcing

Reihaneh Bidar, Queensland University of Technology
Arthur ter Hofstede, Queensland University of Technology
Renuka Sindhgatta, Queensland University of Technology

Do Featured Consumer Reviews Matter?

Alexander Kupfer, University of Innsbruck
Ronald Maier, University of Innsbruck
Steffen Zimmermann, Ulm University
Janna Josefina Thiele, University of Innsbruck

Driving Future Mobility by Shared Mobility: A Taxonomy of Ridesharing Business Models

Tim-Benjamin Lembcke, University of Goettingen
Bernd Herrenkind, University of Goettingen
Mathias Willnat, University of Goettingen
Johannes Bührke, University of Goettingen
Ilja Nastjuk, University of Goettingen

Gazing at the Stars: How Signal Discrepancy Affects Purchase Intentions and Cognition

Maik Hesse, TU Berlin
Otto Hans-Martin Lutz, Fraunhofer FOKUS
Marc Adam, University of Newcastle
Timm Teubner, TU Berlin

Haters Gonna Hate? How Removing Downvote Option Impacts Discussion Culture in Online Forum

Warut Khern-am-nuai, McGill University
Changseung Yoo, McGill University
Jitsama Tanlamai, McGill University
Yossiri Adulyasak, HEC Montreal

How Algorithmic Regulation Affects Sharing Markets: Analysis Using a Quasi-Natural Experiment

Shagun Tripathi, IESE Business School
Harris Kyriakou, IESE Business School

How Users Drive Platform Value

Zhou Zhou, Boston University
Lingling Zhang, University of Maryland
Marshall Van Alstyne, Boston University

Identifying Successful Ideas in Crowdsourcing Contest: Effects of Idea Content and Competition Intensity

Tingru Cui, University of Melbourne
Libo Liu, University of Melbourne

Modeling Consumers’ Sequential Browsing Behavior Considering the Path Dependence

Meihua Zuo, Huizhou University
Carol Ou, Tilburg University
Hongwei Liu, Guangdong University of Technology
Zhouyang Liang, Guangdong University of Technology

On Platform’s Incentive to Filter Fake Reviews: A Game-Theoretic Model

Zhe Wang, Tsinghua University
Subodha Kumar, Temple University
Dengpan Liu, Tsinghua

People Don't Change, Their Priorities Do: Evidence of Value Homophily for Disaster Relief

Amin Sabzehzar, Arizona State University
Yili Hong, Arizona State University
Raghu Santanam, Arizona State University

Tackling Android Fragmentation: Mobile Apps’ Dilemma and the Platform’s Strategies

Xi Wu, Temple University
Subodha Kumar, Temple University
Min-Seok Pang, Temple University

The Impact of Government Regulation on Sharing Platform Growth: A Channel of Supplier Behavior Change

Miaozhe Han, The Chinese University of Hong Kong
Xiaoquan (Michael) Zhang, The Chinese University of Hong Kong

The More, the Better? The Impact of Data Analytics and Data Provisioning on Publisher Competition

Xin Zhang, City university of Hong Kong
Ran Zhang, City University of Hong Kong
Wei Thoo Yue, City University of Hong Kong
Yugang Yu, University of Science and Technology of China

To Train or Not to Train? How Training Affects the Diversity of Crowdsourced Data

Shawn Ogunseye, Bentley University
Jeffrey Parsons, Memorial University of Newfoundland
Roman Lukyanenko, HEC Montreal

Toss a Coin to your Host - How Guests End up Paying for the Cost of Regulatory Policies

Michelle Müller, Paderborn University
Jürgen Neumann, Paderborn University
Dominik Gutt, Erasmus University Rotterdam
Dennis Kundisch, Paderborn University

Transforming Work Organization with Internal Crowds: a Process Theory

Michael Greineder, Universität St. Gallen
Ivo Blohm, University of St. Gallen

Wolf in a Sheep’s Clothing: When Do Complementors Face Competition With Platform Owners?

André Halckenhaeusser, University of Mannheim
Jens Foerderer, Technical University of Munich
Armin Heinzl, University of Mannheim