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\"How do you develop an effective strategy for launching a fashion brand? What marketing activities do you need to undertake to identify and engage with your customers? How are new technologies shaping business models? This definitive guide explains the realities of the fashion industry. Fashion Brand Management is an introduction to how to operate a fashion business in a multi-trillion revenue industry. Written by a leading innovator in the fashion industries, it's a guide to conceptualizing, developing and building a successful brand. It explains key need-to-know marketing and branding models and shows you how to apply them successfully to your business, such as Porter's Five Forces and Generic Strategy, Kapeferer's Brand Identity Prism, the 10 Ps of marketing, how to differentiate your value proposition using Sinek's Golden Circle and Greiner's Growth Strategy. Fashion Brand Management looks at the key challenges facing today's fashion industry and explores the ways in which both micro-brands and international businesses need to adapt. It explore issues such as an uneven recovery, logistics gridlock, the impact of the metaverse, the circular economy, digital only collections, social selling and see-now-buy-now. Using case studies from a range of brands and covering luxury, mainstream and discount, this textbook is supported by online resources which include questions, extra resources and lecture notes\"-- Provided by publisher.

When a product of uncertain quality is first introduced, consumers may choose to strategically delay their purchasing decisions in anticipation of the product reviews of their peers. This paper investigates how the presence of social learning affects the strategic interaction between a dynamic-pricing monopolist and a forward-looking consumer population, within a simple two-period model. Our analysis yields three main insights. First, we find that the presence of social learning has significant structural implications for optimal pricing policies: In the absence of social learning, decreasing price plans are always preferred by the firm; by contrast, in the presence of social learning we find that (i) if the firm commits to a price path ex ante (preannounced pricing), an increasing price plan is typically announced, whereas (ii) if the firm adjusts price dynamically (responsive pricing), prices are initially low and may either rise or decline over time. Second, we establish that under both preannounced and responsive pricing, even though the social learning process exacerbates strategic consumer behavior (i.e., increases strategic purchasing delays), its presence results in an increase in expected firm profit. Third, we illustrate that, contrary to results reported in existing literature on strategic consumer behavior, in settings where social learning is significantly influential, preannounced pricing policies are generally not beneficial for the firm. This paper was accepted by Yossi Aviv, operations management .

A fast fashion system combines quick response production capabilities with enhanced product design capabilities to both design \"hot\" products that capture the latest consumer trends and exploit minimal production lead times to match supply with uncertain demand. We develop a model of such a system and compare its performance to three alternative systems: quick-response-only systems, enhanced-design-only systems, and traditional systems (which lack both enhanced design and quick response capabilities). In particular, we focus on the impact of each of the four systems on \"strategic\" or forward-looking consumer purchasing behavior, i.e., the intentional delay in purchasing an item at the full price to obtain it during an end-of-season clearance. We find that enhanced design helps to mitigate strategic behavior by offering consumers a product they value more, making them less willing to risk waiting for a clearance sale and possibly experiencing a stockout. Quick response mitigates strategic behavior through a different mechanism: by better matching supply to demand, it reduces the chance of a clearance sale. Most importantly, we find that although it is possible for quick response and enhanced design to be either complements or substitutes, the complementarity effect tends to dominate. Hence, when both quick response and enhanced design are combined in a fast fashion system, the firm typically enjoys a greater incremental increase in profit than the sum of the increases resulting from employing either system in isolation. Furthermore, complementarity is strongest when customers are very strategic. We conclude that fast fashion systems can be of significant value, particularly when consumers exhibit strategic behavior. This paper was accepted by Yossi Aviv, operations management.

\"Corporate Brand Personality addresses the increasing need for organizations to refocus and realign their corporate culture in order to compete in a business world that demands trust, respect, and strong values. Moving beyond simply how products are marketed and perceived, it explains how to lead and engage people at every level within the organization to ensure consistent engagement with brand values. Including practical models to show how corporate culture and values can be managed and improved, author Lesley Everett provides real examples and case studies from sectors including hospitality, engineering, retail, and finance that show how employees' behaviors can deeply affect brand reputation through all areas of the organization. Incorporating a complete strategy from start to finish, this book will help managers and HR directors build visible leadership, project an authentic brand image, and reinforce the company's values\"-- Provided by publisher.

This paper studies the potential benefits of responsive pricing and demand learning to sellers of seasonal fashion goods. As typical in such markets, demand uncertainty is high at the beginning of a season, but there is a potential opportunity to learn about demand via early sales observations. Additionally, although the consumers have general preference for purchasing a fashion product earlier rather than later in the season, they may exhibit strategic behavior—contemplating the benefits of postponing their purchase in anticipation of end-of-season discounts. Our results demonstrate that the benefits of responsive pricing, in comparison with a benchmark case of a fixed-price policy, depend sharply on the nature of the consumers’ behavior. Interestingly, in stark contrast to markets of myopic consumers, when the consumers are all strategic, the benefits of responsive pricing tend to worsen when there is a higher potential for learning. We explain this counterintuitive outcome by pointing to two phenomena: the spread effect and information shaping. For example, sellers of fashion products that consider upgrading their pricing systems to incorporate “ accurate response ” strategies (i.e., integrating learning and responsive pricing) should be aware of the possibility that such action might lead them to a new and potentially worse equilibrium, particularly when there is a higher opportunity to learn. Despite the fact that price commitment completely eliminates the seller’s ability to learn, it appears to increasingly dominate responsive pricing as the portion of strategic consumers in the market increases. But, although performing better than responsive pricing, a price-commitment policy is typically limited in performing effective discrimination. Finally, we studied the potential benefits of quick response strategies—ones that embed both dynamic pricing and quick inventory replenishment during the sales season—and found that they are particularly significant under strategic consumer behavior. We explain this result by arguing that quick response provides the seller with a real option that serves as an effective implicit threat to the consumers: encouraging them to buy earlier at premium prices rather than wait for discounts at the end of the season. The online appendix is available at https://doi.org/10.1287/mnsc.2018.3114 . This paper was accepted by Martin Lariviere, operations management.

Demand information and consumer valuation uncertainty of new products have significant impacts on both consumers’ purchasing behavior and retail operations. To address the information transparency for new products launching, this study examines the profitability of omni-channel pre-ordering (i.e., compared to traditional online pre-ordering), a new advance selling strategy for retailers whereby consumers can solve product value uncertainty first and then decide whether to purchase in advance. Our analysis finds that advance selling is not always an appropriate choice for the retailer, but is contingent on related costs (e.g., losses from the costs of returns for retailers and consumers and the hassle cost of solving uncertain value for consumers). Specifically, only when the retailer’s return cost is relatively low and the hassle cost of solving uncertain value is relatively high should the retailer adopt the traditional online pre-ordering strategy. However, when the hassle cost of solving uncertain value is relatively low, the omni-channel pre-ordering strategy is more profitable for the retailer. By contrast, advance selling should not be offered when the retailer’s return cost and the hassle cost of solving uncertain value are both high. Next, we derive the optimal advance selling price and ordering quantity for the regular season for different strategies. Our results reveal that the optimal price varies along with the costs involved in the consumer’s purchasing choice. Finally, we find that the retailer is more likely to order a smaller quantity when the traditional online pre-ordering option is used.

Consumers often consult the reviews of their peers before deciding whether to purchase a new experience good; however, their initial quality expectations are typically set by the product’s observable attributes. This paper focuses on the implications of social learning for a monopolist firm’s choice of product design. In our model, the firm’s design choice determines the product’s ex ante expected quality, and designs associated with (stochastically) higher quality incur higher costs of production. Consumers are forward-looking social learners, and may choose to strategically delay their purchase in anticipation of product reviews. In this setting, we find that the firm’s optimal policy differs significantly depending on the level of the ex ante quality uncertainty surrounding the product. In comparison to the case where there is no social learning, we show that (i) when the uncertainty is relatively low, the firm opts for a product of inferior design accompanied by a lower price, while (ii) when the uncertainty is high, the firm chooses a product of superior design accompanied by a higher price; interestingly, we find that the product’s expected quality decreases either in the absolute sense (in the former case), or relative to the product’s price (in the latter case). We further establish that, contrary to conventional knowledge, social learning can have an ex ante negative impact on the firm’s profit, in particular when the consumers are sufficiently forward-looking. Conversely, we find that the presence of social learning tends to be beneficial for the consumers only provided they are sufficiently forward-looking. This paper was accepted by Serguei Netessine, operations management.

A technology firm launches newer generations of a given product over time. At any moment, the firm decides whether to release a new version of the product that captures the current technology level at the expense of a fixed launch cost. Consumers are forward-looking and purchase newer models only when it maximizes their own future discounted surpluses. We start by assuming that consumers have a common valuation for the product and consider two product launch settings. In the first setting, the firm does not announce future release technologies and the equilibrium of the game is to release new versions cyclically with a constant level of technology improvement that is optimal for the firm. In the second setting, the firm is able to precommit to a schedule of technology releases and the optimal policy generally consists of alternating minor and major technology launch cycles. We verify that the difference in profits between the commitment and no-commitment scenarios can be significant, varying from 4% to 12%. Finally, we generalize our model to allow for multiple customer classes with different valuations for the product, demonstrating how to compute equilibria in this case and numerically deriving insights for different market compositions. This paper was accepted by Yossi Aviv, operations management.

In this paper, we study the impact of consumer-generated quality information (e.g., consumer reviews) on a firm’s dynamic pricing strategy in the presence of strategic consumers. Such information is useful, not only to the consumers that have not yet purchased the product but also to the firm. The informativeness of the consumer-generated quality information depends, however, on the volume of consumers who share their opinions and, thus, depends on the initial sales volume. Hence, via its initial price, the firm not only influences its revenue but also controls the quality information flow over time. The firm may either enhance or dampen the quality information flow via increasing or decreasing initial sales. The corresponding pricing strategy to steer the quality information flow is not always intuitive. Compared to the case without consumer-generated quality information, the firm may reduce the initial sales and lower the initial price. Interestingly, the firm may get strictly worse off due to the consumer-generated quality information. Even when the firm benefits from consumer-generated quality information, it may prefer less accurate information. Consumer surplus can also decrease due to the consumer-generated quality information, contrary to the conventional wisdom that word of mouth should help consumers. We examine extensions of our model that incorporate capacity investment, firm’s private information about quality, alternative updating mechanisms, as well as multiple sales periods, and show that our insights are robust. This paper was accepted by Yossi Aviv, operations management.