This paper reviews the state of the art in Productions and Operations Management (POM) academic research regarding outsourcing in supply chain contexts. We first acknowledge the “Theory of the Firm” (ToF), the venerable and vast body of thought regarding where the firm draws the boundary between what it performs in‐house and what it outsources. Despite the clear linkage between outsourcing and POM, the ToF literature is most closely associated with the fields of strategy and economics. This disconnect might in part be due to a difference in theoretical lenses and terminology, which we address for the POM audience by providing a ToF tutorial. Our review of publications by the POM community from 2000 to 2016 includes a framework that organizes the in‐scope papers and a structured summary of each work. We partition the research into empirical/conceptual and analytical sub‐literatures, each of which gets its own critical assessment and discussion of open opportunities. Along the way, we articulate the features of the POM lens that distinctively position POM researchers to contribute further to the ToF, a convergence which we hope to encourage through this study. A deeper conversation among strategy, economics, and POM would enrichen the rigor and the relevance of each field.

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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