Donald Ngwe is an assistant professor of business administration in the Marketing Unit. He teaches the Marketing course in the MBA required curriculum.
Professor Ngwe directs his research at identifying successful online and offline retailing strategies, particularly in the fashion and apparel industry. His current work in online retail concerns optimal website design and pricing policies. His work in offline retail focuses on customer segmentation through store location, tracking in-store shopper behavior through video processing techniques, and discounting.
Professor Ngwe earned a PhD in economics at Columbia University, together with an MPhil and MA, also in economics. He holds a bachelor’s degree in economics and a diploma in mathematics from the University of the Philippines.
Donald Ngwe is an assistant professor of business administration in the Marketing Unit. He teaches the Marketing course in the MBA required curriculum.
Professor Ngwe directs his research at identifying successful online and offline retailing strategies, particularly in the fashion and apparel industry. His current work in online retail concerns optimal website design and pricing policies. His work in offline retail focuses on customer segmentation through store location, tracking in-store shopper behavior through video processing techniques, and discounting.
Professor Ngwe earned a PhD in economics at Columbia University, together with an MPhil and MA, also in economics. He holds a bachelor’s degree in economics and a diploma in mathematics from the University of the Philippines.
Outlet stores are a large and growing component of many firms' retailing strategies, particularly in the fashion industry. Outlet stores offer attractive prices in locations far from central shopping districts. The main perspectives on why outlet stores exist can be broadly classified into inventory management, geographic segmentation, and price discrimination through consumer self-selection. I evaluate these perspectives in the context of a major fashion goods firm using newly available and highly granular data. Model-free evidence suggests that inventory management and geographic segmentation are not the main drivers for outlet store use. Consumers who shop at outlet stores also do not differ significantly from those who shop at regular stores in terms of income. I use a structural demand model to show that consumers are segmented according to their sensitivity to travel distance and taste for product newness. I then develop a supply model to predict product development responses to changes in store locations. Through policy simulations, I discover that the firm uses outlet stores to serve lower-value consumers who self-select by traveling to outlet stores from central shopping districts. The firm sells older, less desirable merchandise through outlet stores to prevent cannibalization of regular store revenues by means of exploiting the positive correlation between consumers' travel sensitivity and taste for new products. I find that the rate of new product introduction in regular stores would fall by 16% if outlet stores were closed down, while variable profits would decline by 23%. These results imply that the existence of outlet stores may enable firms to improve quality in their regular channels, thus counteracting brand dilution effects.
Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even increase conversion. We demonstrate using a simple theoretical framework that inducing consumers to inspect higher-priced items first may simultaneously increase the average price of items sold and the overall expected purchase probability by inducing consumers to search more products. We test and confirm these predictions in a series of field experiments conducted with a dominant online fashion and apparel retailer. Furthermore, using information in historical transaction data about each consumer, we demonstrate that price-sensitive shoppers are more likely to incur search costs to locate discounted items. Our results show that increasing search frictions can be used as a self-selecting price discrimination tool to match high discounts with price-sensitive consumers and full-priced offerings with price-insensitive consumers.
Shipping fees are an important aspect of online retail for both consumers and sellers. A common fee structure is contingent free shipping, in which consumers are granted free shipping for basket sizes above a minimum value and are charged a flat fee for orders below this threshold. We seek to characterize how contingent free shipping influences purchase outcomes in a multi-category shopping environment. We build a demand model in which consumers choose how to allocate their spending over different product categories to maximize their direct utility under contingent free shipping. We estimate model parameters using transaction data from a pure online fashion retailer. We find that, relative to offering free shipping, offering contingent free shipping increases basket sizes by encouraging consumers to meet the minimum order threshold. Consumers incur search costs to meet this threshold exactly; sellers may benefit from maintaining high search costs to encourage overshooting. Moreover, we find that contingent free shipping shifts demand to more popular products and that the effects of category-level price changes on profits depends on the active shipping policy. Our findings demonstrate the importance of jointly determining product assortment attributes and shipping fee policies.
Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to more product returns in the online retail industry. Using detailed sales data of more than two million transactions from the Indian online retail market, where price promotions are very common, we document two types of strategic customer behavior that have not been considered in previous research. First, customers who monitor product prices after purchase may initiate opportunistic returns because of price drops. Second, customers who anticipate a future return may strategically choose a payment method that facilitates product returns. Our logistic regression models indicate that (1) realized post-purchase price drops lead to a higher probability of return, and (2) anticipated price drops after purchase lead to a higher probability of using cash on delivery, a payment method with a lower return cost for consumers. Our findings are robust to alternative model specifications and sample selection procedures. We demonstrate that an optimal pricing policy should take into consideration the potential costs of two types of strategic customer behavior: opportunistic returns and strategic choice of payment method.
Prices in a wide variety of contexts are often presented in three parts: an original or suggested list price, a discount off that price, and the final selling price. Limited empirical evidence is available that speaks to the relative impact of each component on purchase behavior, even as theories abound. Measuring these impacts is critically important to sellers, to consumers, and to regulators who are keen on enforcing deceptive advertising guidelines against “fictitious pricing”—the practice of quoting list prices that do not truthfully reflect prior selling prices. This paper uses a large retail transaction data set that features wide variations in these pricing components within a relatively homogeneous product space. The data set has the unique feature of containing sales records from outlet stores wherein a subset of products have verifiably fictitious list prices and discounts, allowing for measurement of their impact on purchase incidence in actual retail settings. By measuring the impact of different pricing components on purchase likelihood, we find that list prices have a strong influence on purchase outcomes, with a $1 increase in the list price having the same positive effect on purchase likelihood on average as a $0.77 decrease in the actual selling price. This effect is larger for fake list prices but smaller in longer-lived stores and stores closer to regular retail channels. In a complementary laboratory experiment, we find that fake list prices have no impact on purchase intent when consumers have full knowledge of the true original price. These results imply that fake prices enhance demand by misleading consumers about true original prices.
Dolan, Robert J., and Donald Ngwe. "Planters Nuts and Planters Nuts (B): The Power of the Peanut." Harvard Business School Teaching Note 516-107, May 2016. (Revised October 2017.)
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In May 2015 Paulo Campos, co-founder and CEO of Zalora Philippines, found himself at a crucial turning point in his young company’s development. In just three years, Zalora had come from entering the Philippine fashion retail industry as an unknown quantity to becoming a household name across the Southeast Asian archipelago. Campos and his team had achieved much in this time: launching one of the first online retailers in the country, building a logistics network from scratch, acquiring customers at an astonishing pace, and signing up major brands to offer on Zalora.com.ph. But now his investors were ready for him to shift gears and focus on turning a profit within the next two years. Zalora Philippines was part of Zalora Group, a Singapore-headquartered online fashion retailer that operated across Southeast Asia. Zalora Group, in turn, was part of a global entity called Global Fashion Group (GFG), which owned online fashion retailers and brands in emerging markets across the world. In addition to Zalora in Southeast Asia, GFG owned Dafiti in South America, Namshi in the Middle East, Jabong in South Asia, Lamoda in Eastern Europe, and The Iconic in Australia. GFG’s principal investors were Kinnevik, a Swedish investment company, and Rocket Internet.
This case picks up from the events in Planters Nuts and describes how the new management team for Planters turned the brand around in 2013 by implementing a new brand positioning accompanied by a multimillion dollar marketing campaign.
In 2012 Planters had about $1 billion in U.S. annual revenues, but had experienced declining unit sales and household penetration over the past six years. The snack nuts category was growing overall, but household spending was shifting away from peanuts, cashews, and mixed nuts—Planters' core business—to almonds and pistachios. A new brand management team for Planters had to develop a plan to reinvigorate the still largest brand in the category, and specifically to decide whether to focus on rebuilding its traditional product categories or on attempting to capitalize on the newer nut categories. Central to this process were questions of segmentation, targeting, and positioning.
