Many retailers and manufacturers adopt the practice of accepting product returns from consumers (via money-back guarantee) and retailers (via full-credit returns policy) respectively. While the extant literature focuses on either the manufacturer’s or retailer’s returns policy, this paper

Operations management has the tradition of coming from and going back to real-life applications. It deals with the management of the process of matching supply with demand. The emerging business process in a sharing economy or an innovative marketplace calls for active management from the

Consumers regard product delivery as an important service component that influences their shopping decisions on online retail platforms. Delivering products to customers in a timely and reliable manner enhances customer experience and companies' profitability. In this research, we explore the

This paper investigates the effects of reward redemption hurdles in customer reward programs. Our research context is ``buy X, get one free'' (BXGO) reward programs, which incorporate two common redemption hurdles: a redemption threshold (X purchases are required for a free product) and an expiry

The United States educational policy requires that K-12 students participate in annual standardized tests. As a result, school districts that have traditionally utilized ongoing “formative" assessments of student progress, are increasingly relying on additional, costly “interim"

Telemedicine—remote provision of clinical services through the use of digital technologies—has the potential of significantly improving access to healthcare in rural areas across several low- and middle-income countries. However, evidence regarding the impact of this new channel of healthcare

Interest in cryptocurrencies – one may accurately say, fascination with them – and the decentralized ledger structure supporting them known as the blockchain has accelerated at an astonishing pace in the last year, indeed in just the last six months. Furthermore, the new fundraising mechanism, the

The promised benefits of the Internet of Things (IoT) are predicated on the notion that better decisions will be enabled through a multitude of autonomous sensors (often deployed by different companies) providing real-time knowledge of the state of things. This knowledge will be imperfect, however,

Operational decision making in service systems often depends largely on the characterization of the random fluctuations involved. Exogenous arrivals represent a primary source of uncertainty and their stochastic behavior needs to be modeled carefully. In this talk, we will first argue that the

We derive a generalized likelihood ratio method to estimate any distribution sensitivity in a unified form. Then, the distribution sensitivities are used to in a gradient-based simulated maximum likelihood estimation (GSMLE) to estimate unknown parameters in a stochastic model without assuming that