Channel Strategies and Marketing Mix in a Connected World

The inventory and revenue management models most commonly taught in the operations management and industrial engineering disciplines typically assume that the demand for a product is easily estimated and is independent of competing products offered through the same channel. In this chapter, we show why this is rarely a good assumption and provide a review of the statistical techniques that have been developed to correct product demand distribution estimates that are biased due to truncated demand or product substitution effects. Failure to correct product demand estimates for these biases has been shown to result in significantly missed opportunities in meeting customers’ true demand due to incorrectly calculated optimal product stocking levels.

This chapter reviews research on buyer valuation uncertainty originated from information asymmetry between the firm and consumers, and the firm’s information provision strategy. Before purchase, consumers could be uncertain about the product’s vertical attributes, i.e., quality uncertainty, and/or the product’s horizontal attributes, i.e., fit uncertainty. For each type of uncertainty, we discuss the firm’s inventive and instruments to disclose information, as well as other mechanisms to reveal information that help consumers resolve such valuation uncertainty. We then review recent literature on advance selling and opaque selling strategies, where the firm benefits from creating consumer valuation uncertainty. We conclude the chapter with discussions on future research directions.

Promotion planning is an important problem for supermarket retailers who need to decide the price promotions for thousands of items. One of the key reasons retailers use promotions is to increase sales and profits by exploiting relations among the different items. We formulate the promotion optimization problem for multiple items as a nonlinear Integer Program (IP). Our formulation captures several business requirements, as well as important economic factors such as the post-promotion dip effect (due to the stockpiling behavior of consumers) and cross-item effects (substitution and complementarity). Our demand models are estimated from data and are typically nonlinear, hence rendering the exact formulation intractable. In this chapter, we discuss a class of IP approximations that can be applied to any demand function. We then show that for demand models with additive cross-item effects, it is enough to account for unilateral and pairwise deviations, leading to an efficient method. In addition, when the products are substitutable and the price ladder is of size two, we show that the unconstrained problem can be solved efficiently by a linear program. This result is unexpected as the feasible region of the formulation is not totally unimodular. Next, we derive a parametric worst-case guarantee on the accuracy of the approximation relative to the optimal solution. Finally, we test our model on realistic real-world instances and show its performance and practicality. The model and tool presented in this chapter allow retailers to solve large realistic instances and to improve their promotion decisions.

The digital advertising industry has witnessed an impressive explosion since its inception. With Internet advertising revenues already at over $200 billion, the projections are for continued growth. The format and technological underpinnings of digital advertising make it a fascinating subject of study for practitioners and academics alike, and distinguish it from traditional advertising in many ways. In contrast to traditional advertising, online advertising offers significantly more channels, a lower cost alternative, greater targeting and personalization capabilities, and dynamic pricing capabilities. While these digital technologies offer unprecedented opportunities to marketers to maximize the ROI on their marketing budgets, the data-rich environment also presents a unique set of managerial, operational, and intellectual challenges. In this chapter, we introduce the reader to some of these challenges. Our goal is to identify some of the salient operational challenges facing advertisers and publishers in this digital advertising environment, and summarize the state of the art of the published research that attempts to address these challenges. Our hope is that practitioners, academics, and graduate students will find this to be a valuable resource in their various endeavors.

In the omnichannel era, consumers optimize their shopping experience by exhaustively considering all possible alternatives across both online and offline channels. In this chapter, we present new approaches to model consumer behavior in the omnichannel environment. We start by reviewing traditional models of strategic consumer behavior and then apply them to omnichannel initiatives in the retail industry. These omnichannel strategies help mitigate two key problems in retail: stockouts and product misfit. We hope that our models can inspire future research in the emerging area of omnichannel retailing.

In this chapter, we study the impact of two major technological advances in demand fulfillment—the emergence of dual channels in retail (i.e., online and in-store) and the adoption of on-demand customization technology (such as additive manufacturing or 3D printing). Our analysis shows that such technology adoption can have differential impacts to the two channels. The technology leads to increased product variety offered online, as well as allows the firm to charge a price premium for online customers. Yet it also induces the firm to offer a smaller product variety and a reduced price in-store. Moreover, the online demand increases (decreases) if the customer online wait cost is low (high). The firm’s profitability with the new technology is driven by the production setup cost of the traditional production technology it replaces and also by how much customers care about the product’s custom fit.

Price-matching has become a ubiquitous strategy for retailers both in product and service industries, especially with the growing ease of checking prices online. With this strategy, retailers promise not to be undersold and match competitor’s lower price (if any). Price-sensitive consumers tend to be happy with this since they potentially can get the lowest price at their “favourite” retailer. A relatively under-researched topic in this context is the fact that this price convenience normally comes with a number of conditions. We analyze two of the most common ones—the product must be available at the lower priced retailer (availability condition) and the price-match extends only to a competing retailer and not to a direct-to-consumer manufacturer (channel condition)—and investigate their implications for the channel and consumers.

We show that if consumers consider the fact that they might be denied the price-matching benefit based on verification of availability at the competitor’s location while making a purchase decision, then they will benefit from a lower price by increasing the competition between the retailers; on the other hand, not considering this fact would allow the retailers to price discriminate and might harm consumers.

As regards channel structure, we prove that if the upstream partner has the power to set the wholesale price, then it does not make sense for a retail channel to price match with a manufacturer selling directly to consumers. But, in sectors where there are dominant retailers who have a say in determination of the wholesale price, price-matching can be an equilibrium strategy for the retail channel, even when manufacturers are directly selling to consumers. Furthermore, price-matching is also the equilibrium strategy for upstream manufacturers as it redirects demand from the retail to their direct channel.

In many developing countries, micro-retailers in remote rural places struggle to survive due to high inventory replenishment costs caused by lack of efficient infrastructure and distribution networks. Consumers, in turn, suffer from higher prices and limited accessibility of products provided by these micro-retailers. Some of these products are necessities, including food or medical items. In some cases, micro-retailers are the only sources for consumers to obtain these products. In order to help micro-retailers and the communities they serve, NGOs have been exploring different approaches aiming to coordinate the retailers’ inventory replenishment strategy. This chapter explores two major types of collaborative strategies observed in practice, and studies their welfare implications for micro-retailers and local consumers. One strategy is based on an “open” cooperative where participating retailers jointly replenish inventories and share the travel cost incurred. The other strategy introduces an intermediary “non-profit” wholesaler who will consolidate retailers’ orders and replenish on their behalf under a low service charge. The study unveils several key trade-offs associated with these collaborative strategies. In particular, when retailers’ market entry is controlled and regulated, the cooperative strategy always leads to Pareto improvement. That is, retailers’ profit improves and consumers are also better off. However, establishing a non-profit wholesaler improves retailers’ profit at the expense of consumer welfare. This trade-off can be mitigated when retailers can freely enter the retail market. That is, the wholesaler strategy also leads to Pareto improvement under some general conditions. We further show that the cooperative strategy benefits the consumers more, while the non-profit wholesaler strategy is more effective in improving retailers’ profit and encouraging their market participation. We discuss the policy implications of these trade-offs for the deployment of collaborative replenishment for micro-retailers in practice.

The retail industry’s economic and environmental impact encompasses global supply chains and many thousands of facilities; it therefore has a significant impact on human health and the environment, and a responsibility for reducing this impact. This chapter begins with an overview of retail’s most common and significant environmental impacts and examines the origin of sustainable planning and operations, the business case for sustainability programs, and the maturation of retail sustainability programs.

Companies start sustainability programs for different reasons—some internal to the company and some as a result of external pressures. These pressures continue to drive further action, advancing and maturing sustainability programs across the industry. Those programs tend to grow and mature around common dimensions, beginning with a focus on the basics, primarily complying with regulatory requirements, then growing to cover operational efficiencies that save costs, reducing reputational risks, and eventually innovating on the very core of their businesses. The chapter includes business-actionable steps for retail sustainability practitioners and ends by describing the critical programmatic components for a strong retail sustainability program.