3730 Walnut Street
559 Jon M. Huntsman Hall
Philadelphia, PA 19104
Research Interests: Business operations and innovation in supply chains, online markets, and healthcare; Data analytics; Empirical studies
Ken Moon is an Assistant Professor of Operations, Information and Decisions at the Wharton School. He studies business operations and innovations in supply chains, online markets, and healthcare. His research is carried out using large datasets from industry partners — including online platforms and marketplaces, multi-channel retailers, consumer technology manufacturers, and hospital wards treating high acuity patients.
Ken completed his undergraduate studies in mathematics and economics (two majors) at Stanford University, his JD at the Harvard Law School, and his PhD at the Stanford Graduate School of Business.
Abstract: Product reliability is a long-standing concern among product manufacturers, and researchers have identified a number of factors that significantly affect product reliability. In this paper, we examine a previously under-recognized yet impactful determinant of product reliability: a high rate of turnover on the manufacturing line when the product was assembled. Even when assembly lines are designed to minimize product defect rates through simplified tasks and stringent quality control tests, quality variations may exist in the manufactured units that are only revealed after they have been used repeatedly. If this is the case, then the disruptiveness of high turnover may directly lead to product reliability issues. To evaluate this possibility, we link four post-production years of field failures for tens of millions of consumer mobile devices back to their production lines. After controlling for known factors affecting reliability (workloads, learning, and component quality), we find that the likelihood of field failure increases by 7-8% when a device is produced in the monthly high-turnover weeks following paydays; and that even in other weeks, product reliability responds significantly (2-3%) to the individual assembly lines' weekly turnover rates. Together, we demonstrate that staffing and retaining a stable factory workforce critically underlies product reliability, and we show the value of connected field data in informing manufacturing operations. Ultimately, products are more reliable when workers are more reliable.
Gad Allon, Georgios Askalidis, Randall Berry, Nicole Immorlica, Ken Moon, Amandeep Singh (Under Revision), When to Be Agile: Ratings and Version Updates in Mobile Apps.
Abstract: Lean and agile models of product development organize flexible capacity to rapidly update individual products in response to customer feedback. While agile operations have been adopted across numerous industries, neither the benefits nor the factors explaining when firms choose to become agile are validated and understood. We study these questions using data on the development of mobile apps, which occurs through the dynamic release of new versions into the mobile app marketplace, in conjunction with customer ratings. We develop a structural model estimating the dependence of product versioning on (A) market feedback in the form of customer ratings, against (B) project and work-based considerations, such as development timelines, scale economies, and operational constraints. In contrast to when they actually benefit from operational agility, firms become agile when launching riskier products (in terms of uncertainty in initial customer reception) and less agile when able to exploit scale economies from coordinating development over a portfolio of apps. Agile operations increase firm payoffs by margins of 20-80%, and interestingly partial agility is often sufficient to capture the bulk of these returns. Finally turning to a question of marketplace design, we study how the mobile app marketplace should design the display of ratings to incentivize quality (increasing app categories’ average user satisfaction rates by as much as 26%).
Haim Mendelson, Ken Moon, Yuanyuan Shen (Working), Behavioral and Social Motivations in a Crowdfunding Marketplace.
Haim Mendelson and Ken Moon (2018), Modeling Success and Engagement for the App Economy, ACM The Web Conference (WWW'18).
Elena Belavina, Karan Girotra, Ken Moon, Jiding Zhang (Working), Matching in Labor Marketplaces: The Role of Experiential Information.
Abstract: Online labor marketplaces assign workers to short-term jobs. For some jobs, the choice of the best worker is based on ex-ante observable information (e.g., driver assignment based on location in ride-hailing). In others, the assignment is driven by experiential information, that is information obtained privately only through the worker performing the job (e.g., the fit of a childcare provider with a family). This study develops an empirical framework to impute the relative importance of each kind of information from participants' past hiring choices. Our moment inequality approach accommodates high worker turnover, varying choice sets, and limited observations of a very large number of market participants -- all key characteristics of online labor markets. We apply our framework to two markets, exploiting a natural experiment that changed marketplace commissions. Based on over 1.2M hiring decisions, we estimate that experiential information is a key driver of hiring choices, while ex-ante observable fit is relevant only for the simplest jobs. Using our estimates, we propose and evaluate alternate assignment policies. The best-performing policies prioritize repeat work and, surprisingly, ignore ex-ante observable information to instead experiment with new workers and generate experiential information. Such policies can increase buyer welfare by as much as 45.3% (47.1%) of gross revenue in the Data Entry (Web Development) market compared to the current practice of skills-based matching. Policies exploiting buyers' past revealed preferences (in repeat work) without incorporating exploration still under-perform by 18.9% in Data Entry and 8.7% in Web Development.
OIDD 101 explores a variety of common quantitative modeling problems that arise frequently in business settings, and discusses how they can be formally modeled and solved with a combination of business insight and computer-based tools. The key topics covered include capacity management, service operations, inventory control, structured decision making, constrained optimization and simulation. This course teaches how to model complex business situations and how to master tools to improve business performance. The goal is to provide a set of foundational skills useful for future coursework atWharton as well as providing an overview of problems and techniques that characterize disciplines that comprise Operations and Information Management.
Matching supply with demand is an enormous challenge for firms: excess supply is too costly, inadequate supply irritates customers. In the course, we will explore how firms can better organize their operations so that they more effectively align their supply with the demand for their products and services. Throughout the course, we illustrate mathematical analysis applied to real operational challenges--we seek rigor and relevance. Our aim is to provide both tactical knowledge and high-level insights needed by general managers and management consultants. We will demonstrate that companies can use (and have used) the principles from this course to significantly enhance their competitiveness.
Operations strategy is about organizing people and resources to gain a competitive advantage in the delivery of products (both goods and services) to customers. This course approaches this challenge primarily from two perspectives: 1) how should a firm design their products so that they can be profitably offered; 2) how can a firm best organize and acquire resources to deliver its portfolio of products to customers. To be able to make intelligent decisions regarding these high-level choices, this course also provides a foundation of analytical methods. These methods give students a conceptual framework for understanding the linkage between how a firm manages its supply and how well that supply matches the firm's resulting demand. Specific course topics include designing service systems, managing inventory and product variety, capacity planning, approaches to sourcing and supplier management, constructing global supply chains, managing sustainability initiatives, and revenue management. This course emphasizes both quantitative tools and qualitative frameworks. Neither is more important than the other.
High worker turnover rates in manufacturing can cost companies hundreds of millions of dollars. A new paper co-authored by Wharton’s Ken Moon looks at how firms can keep employees on the job longer.Knowledge @ Wharton - 2018/12/4