People

Artificial intelligence is evolving from a “copilot” into an “intelligent agent,” and this leap will have an unprecedented impact on the marketing industry.In the past few years, we’ve witnessed how AI, as an efficiency tool, has optimized the marketing value chain: customer service bots have reduced operating costs, generative AI (AIGC) has enabled large‑scale content production, and machine learning has made consumer insights more precise.

Manufacturers often preannounce reference prices for products that have not yet been produced or even developed. These prices are rarely binding, meaning that the manufacturers can make price adjustments in the future, possibly at a cost. In this paper, we argue that price preannouncements can serve as a weak price commitment that, we find, helps the manufacturers secure better deals from their suppliers, thereby lowering their procurement costs and improving their profit. Surprisingly, even an extremely weak price commitment can substantially improve a manufacturer’s profit. On the other hand, when the price commitment is credible enough, the manufacturer forgoes the price preannouncement. Collectively, these results underscore the strategic effects that price preannouncements can have on firms’ marketing decisions.

In 2023, the Belgian newspaper Dernière Heure revealed that the ride-hailing platform Uber charges different prices to users based on their phone’s battery level.[1] Specifically, for the same trip, if your phone has 84% battery remaining, Uber charges 16.6 euros; but if you only have 12% battery left, the price rises to 17.56 euros. The logic behind this pricing is obvious: if your phone is about to run out of battery, you’re probably in no position to wait, and have no choice but to accept Uber’s higher price

In the era of online shopping, the so-called "no discounts for old customers or dogs" policy often leaves loyal consumers feeling helpless. Many e-commerce platforms implement a "one person, one price" strategy, and even tailor prices based on users' purchasing habits and browsing histories, causing different consumers to pay different prices for the same product. In addition, airline ticket prices fluctuate constantly, with the phenomenon of "the more you search, the more expensive it gets" becoming the norm.

Recently, Chinese Mainland e-commerce giants Taobao, JD.com, and Pinduoduo have upped their game by incorporating Hong Kong into their free shipping zones. In the past, Hongkongers relied on transshipment consolidation to facilitate the receipt of their ordered goods. Little wonder that customers have warmly welcomed the new one-stop shopping services.

Ensuring equal access to entrepreneurship and startup funding for both female and male entrepreneurs is crucial for societal perceptions of justice and long-term prosperity. Previous research presents contrasting findings, with some studies indicating a male advantage and others suggesting a female advantage. This research reconciles these inconsistencies by identifying the decision frame as a moderator. Specifically, in crowdfunding contexts, a consumer decision frame leads to stronger reliance on communal evaluation norms, resulting in favoring female entrepreneurs who are perceived as more disadvantaged. Conversely, an investor decision frame leads to stronger reliance on exchange evaluation norms, resulting in favoring male entrepreneurs who are perceived as more determined/passionate. Based on this, the authors propose that the strategic use of an entrepreneur's profile, activating a specific evaluation norm, and showing crowdfunding dependence attenuate the differential support for female versus male entrepreneurs, resulting in equal support for both. Results from six studies using a multimethod design provide converging support for this framework. This research is the first to differentiate between and directly compare consumer and investor decision frames, advancing the related literature and offering valuable guidelines for entrepreneurs, funding platforms, and public policy makers.

Firms must often decide whether to disclose private information regarding their costs to other market participants. Although extant literature has explored firms’ incentives to disclose exogenous and uncertain costs, little is known about when their endogenous costs should be disclosed. This paper studies the cost-disclosure strategies of competing firms whose inputs are sourced from and endogenously priced by upstream suppliers. We find, first, that cost disclosure affects not only market competition but also the motivations of suppliers in setting their input prices. As such, firms can strategize their disclosure decisions to optimize their procurement costs. Second, we find that firms’ disclosure decisions vary depending on both the nature of the competition and the market structure at hand. That is, when competing firms source from the same supplier or compete on price, they never disclose their costs; in such a case, nondisclosure is strictly better for consumers and welfare compared with disclosure. When competing firms source from different suppliers and compete on quantity, they always disclose; in such a case, disclosure is strictly better for consumers and welfare compared with nondisclosure. We also find that whereas manufacturers’ disclosure incentives are misaligned with those of suppliers, they are largely aligned with the goal of maximizing channel profits. Together, our results underscore the distinct role that endogenous costs play in firms’ disclosure decisions.

To balance the need for privacy and the benefits of big-data analytics, regulators around the world are giving consumers control over their data, allowing them to choose whether or not to voluntarily share their purchase history data with firms. Intuition suggests that voluntary data sharing only benefits consumers who can now choose to share their data only when it is profitable to do so. To investigate this argument, we build a model in which a monopolistic firm sells a repeatedly purchased product to consumers over two periods, and consumers decide whether or not to share their purchase history data with the firm, who can use it in the future to price discriminate against them. We find that, compared to when data collection is completely outlawed, voluntary data sharing can benefit the firm but at its consumers’ expense. Moreover, regulations that mandate firms to better protect consumer data against data breaches can backfire on consumers. Finally, we show that under voluntary data sharing, a firm’s ability to offer consumers a monetary incentive to share their data can improve profits without hurting consumers. Taken together, these findings underscore the surprising effects of voluntary data sharing and caution public policymakers of how certain data policies that, on the surface, seem purely beneficial can lead to unintended consequences.