團隊

人工智能正在經歷從「副駕駛」向「智慧體」的進化，這一躍遷對市場營銷行業的影響將是史無前例的。在過去幾年，我們見證了 AI 如何作為一種效率工具優化營銷鏈條：客服機器人削減了運營成本，生成式 AI（AIGC）實現了內容的規模化生產，而機器學習讓消費者洞察變得更加精準。

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.

2023年，比利時報紙Dernière Heure 爆料指出，網約車平臺Uber會根據用戶手機電量的不同向不同的使用者收取不同的價格。 [1] 具體而言，對於相同的一段旅程，如果你的手機剩餘電量有84%，Uber的收取的價格是16.6歐元;而如果你的剩餘電量只有12%，你的價格將是17.56歐元。 定價背後的邏輯顯而易見：如果你的手機快沒電了，你大概率是「等不起」的，只能無奈接受Uber的高價。

網購時代，「舊用戶與狗不得享受」的優惠，往往讓忠實的消費者感到無奈。許多電商平台實施「一人一價」策略，甚至基於用戶的購買習慣和瀏覽記錄「看人下菜碟」，讓不同的消費者為同樣的商品支付不同的價格。此外，機票價格也不斷波動，越搜越貴已成常態。許多消費者發現，同一班機在不同時段價格差異龐大，甚至剛查看的票價，片刻後便上漲了。沒錯，你被演算法操控了──身為消費者，我們對商家的這些套路早已見怪不怪。

近期內地電商巨頭淘寶、京東、拼多多紛紛發力，將香港市場納入包郵區。過去港人需先通過中轉集運才能接收所訂貨品，相比之下，最新推出的一站式購物服務，自然大受歡迎。 無庸置疑，內地電商龍頭的搶灘行為必會影響本地零售業，讓早已低迷的銷情雪上加霜。這種趨勢下，本土零售業有什麼應對之道？筆者從以下3個角度建議業界如何破解困局。

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.