4.6 Article

Understanding the Choice of Online Resale Channel for Used Electronics

期刊

PRODUCTION AND OPERATIONS MANAGEMENT
卷 29, 期 5, 页码 1188-1211

出版社

WILEY
DOI: 10.1111/poms.13149

关键词

product acquisition; used electronics; online markets; choice models; lab experiment; MTurk

资金

  1. Blake Family Fund for Ethics, Governance and Leadership

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Each year, global consumers dispose of 20 million-50 million tons of electronic products, including laptops, tablets, and, most commonly, cell phones. Realizing the residual value in used electronics, consumers frequently look for ways to sell their devices, whereas independent parties (IPs) such as Gazelle and NextWorth and original equipment manufacturers (OEMs) such as Apple compete in acquiring them. These firms also compete with online marketplaces such as eBay, which offer a channel for individuals to sell used devices to others. To succeed in this highly competitive market, buying firms (i.e., OEMs and IPs) must understand factors that influence sellers' estimated utility and their decisions in a resale process. We conduct laboratory experiments with a two-stage resale process, where subjects in the first stage choose a resale channel to sell their used cell phone. In the second stage, subjects evaluate a potential counteroffer decision, that is, post-choice decision. Our results from the resale-channel choice stage show that individuals have a higher sensitivity to price, time until payment, and online ratings when selling to an IP than when selling to an OEM or through an OM. No significant difference exists, however, in their sensitivity to IP or OEM data security policies. Our results from the post-choice decision stage show that a seller's share in the counteroffer increases the likelihood of acceptance in all resale channels, whereas higher online ratings might increase or decrease the likelihood of accepting a counteroffer depending on the resale channel. Our laboratory experiment results generally are consistent, with some differences, when replicated on Amazon's Mechanical Turk (MTurk).

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