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Understanding the Choice of Online Resale Channel for Used Electronics
Author(s) -
Esenduran Gökçe,
Hill James A.,
Noh In Joon
Publication year - 2020
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.13149
Subject(s) - original equipment manufacturer , business , channel (broadcasting) , payment , marketing , dispose pattern , order (exchange) , commerce , industrial organization , telecommunications , computer science , finance , programming language , operating system
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 ( IP s) such as Gazelle and NextWorth and original equipment manufacturers ( OEM s) such as Apple compete in acquiring them. These firms also compete with online marketplaces such as eB ay, which offer a channel for individuals to sell used devices to others. To succeed in this highly competitive market, buying firms (i.e., OEM s and IP s) 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 ( MT urk).