Refine
Year of publication
Document Type
- Article (42)
- Part of Periodical (2)
- Book (1)
- Contribution to a Periodical (1)
Has Fulltext
- yes (46)
Is part of the Bibliography
- no (46)
Keywords
- Corporate Finance (2)
- Tax (2)
- online advertising (2)
- pricing (2)
- Advertising (1)
- App Tracking Transparency Framework (1)
- Apple (1)
- Audience Segments (1)
- Automated Feedback (1)
- Brand focus (1)
- CCPA (1)
- Content analysis (1)
- Cumulative abnormal return (1)
- Customer Acquisition (1)
- Customer Management (1)
- Customer Referral Programs (1)
- Customer Value (1)
- Customer focus (1)
- Datenschutz (1)
- Digitalisierung (1)
- Digitization (1)
- Display advertising (1)
- Dynamic Pricing (1)
- Dynamic pricing (1)
- Earnings call (1)
- Education (1)
- Electronic Commerce (1)
- Event study (1)
- Facebook (1)
- Financial structure (1)
- Firm value (1)
- GDPR (1)
- Generative AI (1)
- Hessen (1)
- Klein- und Mittelbetrieb (1)
- Learning (1)
- Leverage effect (1)
- Loyalty (1)
- Marketing Analytics (1)
- Marketing-finance interface (1)
- Offline advertising (1)
- Online Advertising (1)
- PIPL (1)
- Paid search advertising (1)
- Preisdifferenzierung (1)
- Preisdiskriminierung (1)
- Price differentiation (1)
- Price discrimination (1)
- Privacy (1)
- Privatsphäre (1)
- Prognose (1)
- Prognosemarkt (1)
- Sales (1)
- Shareholder value (1)
- Spotify (1)
- Stock market (1)
- Targeting (1)
- Text analysis (1)
- Third-Party Data (1)
- Virtuelle Börse (1)
- WOM (Word-of-Mouth) (1)
- ad blocker (1)
- argument mining (1)
- consumer behavior (1)
- consumer protection (1)
- cookie (1)
- flat rate (1)
- flat-rate bias (1)
- monetization of content (1)
- news consumption (1)
- nonlinear pricing (1)
- pay-per-use bias (1)
- prediction (1)
- prediction market (1)
- price elasticity (1)
- privacy (1)
- real-time bidding (1)
- service design (1)
- service improvement (1)
- service innovation (1)
- tariff choice (1)
- tariff-specific preferences (1)
- tariffs (1)
- telecommunication (1)
- textual analysis (1)
- three-part tariffs (1)
- value of information (1)
- virtual stock market (1)
Institute
Most event studies rely on cumulative abnormal returns, measured as percentage changes in stock prices, as their dependent variable. Stock price reflects the value of the operating business plus non-operating assets minus debt. Yet, many events, in particular in marketing, only influence the value of the operating business, but not non-operating assets and debt. For these cases, the authors argue that the cumulative abnormal return on the operating business, defined as the ratio between the cumulative abnormal return on stock price and the firm-specific leverage effect, is a more appropriate dependent variable. Ignoring the differences in firm-specific leverage effects inflates the impact of observations pertaining to firms with large debt and deflates those pertaining to firms with large non-operating assets. Observations of firms with high debt receive several times the weight attributed to firms with low debt. A simulation study and the reanalysis of three previously published marketing event studies shows that ignoring the firm-specific leverage effects influences an event study's results in unpredictable ways.
This research examines the impact of online display advertising and paid search advertising relative to offline advertising on firm performance and firm value. Using proprietary data on annualized advertising expenditures for 1651 firms spanning seven years, we document that both display advertising and paid search advertising exhibit positive effects on firm performance (measured by sales) and firm value (measured by Tobin's q). Paid search advertising has a more positive effect on sales than offline advertising, consistent with paid search being closest to the actual purchase decision and having enhanced targeting abilities. Display advertising exhibits a relatively more positive effect on Tobin's q than offline advertising, consistent with its long-term effects. The findings suggest heterogeneous economic benefits across different types of advertising, with direct implications for managers in analyzing advertising effectiveness and external stakeholders in assessing firm performance.
This article uses information from two data sources, Compustat and Nexis Uni, and textual analysis to measure and validate the brand focus and customer focus of 109 U.S. listed retailers. The results from an analysis of their 853 earnings calls in 2010 and 2018 outline that on average, both foci increased over time. Although both foci vary substantially, brand focus varies more widely across retailers than their customer focus. Both foci are independent of each other. Specialty retailers have the highest brand focus, and internet & direct marketing retailers have the highest customer focus. A positive correlation exists between a retailer’s customer focus and its profitability, but not between a retailer’s brand focus and its profitability. The authors use the results to generate a research agenda that can direct future research in further systematically exploring firms’ brand and customer focus.
In recent years, European regulators have debated restricting the time an online tracker can track a user to protect consumer privacy better. Despite the significance of these debates, there has been a noticeable absence of any comprehensive cost-benefit analysis. This article fills this gap on the cost side by suggesting an approach to estimate the economic consequences of lifetime restrictions on cookies for publishers. The empirical study on cookies of 54,127 users who received ∼128 million ad impressions over ∼2.5 years yields an average cookie lifetime of 279 days, with an average value of €2.52 per cookie. Only ∼13 % of all cookies increase their daily value over time, but their average value is about four times larger than the average value of all cookies. Restricting cookies’ lifetime to one year (two years) could potentially decrease their lifetime value by ∼25 % (∼19 %), which represents a potential decrease in the value of all cookies of ∼9 % (∼5%). Most cookies, however, would not be affected by lifetime restrictions of 12 or 24 months as 72 % (85 %) of the users delete their cookies within 12 (24) months. In light of the €10.60 billion cookie-based display ad revenue in Europe, such restrictions would endanger €904 million (€576 million) annually, equivalent to €2.08 (€1.33) per EU internet user. The article discusses these results' marketing strategy challenges and opportunities for advertisers and publishers.
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.
Telecommunications companies traditionally offer several tariffs from which their customers can choose the tariff that best suits their preferences. Yet, customers sometimes make choices that are not optimal for them because they do not minimize their bill for a certain usage amount. We show in this paper that companies should be very concerned about choices in which customers pick tariffs that are too small for them because they lead to a significant increase in customers churn. In contrast, this is not the case if customers choose tariffs that are too big for them. The reason is that in particular flat-rates provide customers with the additional benefit that they guarantee a constant bill amount that consumption can be enjoyed more freely because all costs are already accounted for.
Customer loyalty is a critical measure for success, showing if a firm's product is received well by its customers. To understand its development over time, two fundamental questions must be answered: (I) How will current customers' loyalty develop, and (II) will new customers' loyalty differ from current customers' loyalty? The authors empirically answer these questions based on a data set including ~500 B2B web technologies with jointly ~325 million customers spanning over 24 years. They show that loyalty hardly develops and, if so, it rather decreases than increases. The loyalty of current customers rarely changes and, if so, rather increases than decreases. New customers are most likely less loyal than current customers. These results show that by failing to account for these underlying developments, stakeholders, in most cases, draw the wrong conclusions about product value measured via customer lifetime value.
Digitale Technologien begünstigen den Einsatz einer dynamischen Preisgestaltung, also von Preisen, die für ein prinzipiell gleiches Produkt unangekündigt variieren. Dabei werden in der öffentlichen Diskussion unterschiedliche Ausgestaltungsformen dynamischer Preise oftmals vermischt, was eine sinnvolle Analyse der Vor- und Nachteile der dynamischen Preisgestaltung erschwert. Das Ziel des Beitrags ist die Darstellung der ökonomischen Grundlagen und die Diskussion sowie Klassifikation der Ausgestaltungsmöglichkeiten der dynamischen Preisgestaltung. Darüber hinaus erfolgt eine Bewertung der Vor- und Nachteile der dynamischen Preisgestaltung aus Käufer- und Verkäufersicht. Abschließend werden Implikationen für die betriebswirtschaftliche Forschung diskutiert.