Trade-off Between Two Advertising Strategies: Coverage or Penetration

Advertising has always been an important way for companies to promote their products and carry out product publicity. With the advent of the information age and the convenience of the Internet, the spread and dissemination of advertising are becoming widespread. There are two different basic advertising strategies, namely expanding market coverage and increasing market penetration. Expanding market coverage is a common advertising strategy for company managers. Through this strategy, they focus on the size of the market. Increasing market penetration is another way to increase demand. Company managers focus on the current market, but gain and maintain greater penetration by improving the quality of products or services. The first (coverage) strategy can be seen as distributing flyers, advertising boards and mass acquisitions. The efforts of the second (penetration) strategy can be seen as improving product quality, service environment and positive reputation. Which one is more effective, coverage or penetration? Under what conditions is it better for the company manager? These problems have not been found in the literature. By establishing a two-stage model, this article discusses the optimal advertising levels of these two strategies. Specifically, this article compares the optimal profits of the two strategies in various market environments and finds more effective advertising strategies. Management insights are generated for decision-making of firm managers

On Point Predictions and Reference Dependence in Behavior-Based Pricing Experiments

It has been shown that the comparative static results of two-period behavior-based pricing models hold in laboratory experiments, while point predictions do not. This study aims to check whether these findings replicate and to evaluate why observed prices deviate from point predictions. We report observed prices in conformity with point predictions through: (1.) a uniform pricing benchmark, (2.) a replication of a behavior-based pricing experiment, and (3.) a follow-up experiment in which we consider the second period disjointed from the first period. By disjoining the two periods, we show that reference dependence toward first-period prices shifts the second-period pricing behavior of participants upwards. In a post hoc analysis, we show that considering consumers' myopic instead of strategic explains a downward shift in first-period prices and rationalizes prior experimental findings. Volatile price levels affect price-based welfare measures – such as seller profits and total customer costs. We show that transport costs are a robust welfare measure that alleviates the impact of distorted prices. Ultimately, our findings are relevant for the design and assessment of multi-period pricing experiments

The Ethics of BI with Private and Public Entities

The Internet plays a vital role in data collection, information creation, and business intelligence (BI). The nature of information collected on the Internet, and the degree to which such information is collected, both have ethical ramifications. What data can be collected is very different from what data should be collected. Disregarding the latter question can be more profitable, but doing so can often involve unethical practices and more importantly, compromise the privacy of individuals. It has become widely known that private enterprises collect all manner of (BI) data about individuals, causing ethical concerns. The ethics of privacy do not affect private enterprises alone. In recent times the development and implementation of public information systems by public agencies have also resulted privacy breaches, both overt and inadvertent. This is despite the fact that governments have a responsibility to protect private data from external parties. While some privacy laws have been enacted, paradoxically, other governmental legislation such as the Freedom of Information Act (FOIA) has actually eased restrictions on the very information that the privacy laws have sought to protect. In this context, it is useful to compare US privacy regulations other countries, e.g. Canada. It is also useful to contrast federal regulations with those in States, e.g. Connecticut. Ethical concerns regarding private information have also spawned various “solutions” whose motives and success can be widely interpreted. It can be argued that the protection of privacy and private information are the responsibility of both private and public entities, who should take concrete steps to classify and protect private informatio

The Effect of Product Recommendations on Online Investor Behaviors

Despite the popularity of product recommendations on online investment platforms, few studies have explored their impact on investor behaviors. Using data from a global e-commerce platform, we apply regression discontinuity design to causally examine the effects of product recommendations on online investors' mutual fund investments. Our findings indicate that recommended funds experience a significant rise in purchases, especially among low socioeconomic status investors who are most influenced by these recommendations. However, investors tend to suffer significantly worse investment returns after purchasing recommended funds, and this negative impact is also most significant for investors with low socioeconomic status. To explain this disparity, we find investors tend to gather less information and expend reduced effort in fund research when buying recommended funds. Furthermore, investors' redemption timing of recommended funds is less optimal than non-recommended funds. We also find that recommended funds experience a larger return reversal than non-recommended funds. In conclusion, product recommendations make investors behave more irrationally and these negative consequences are most significant for investors with low socioeconomic status, which can amplify wealth inequality among investors in financial markets

Who Benefits from Online Privacy?

When firms can identify their past customers, they may use information about purchase histories in order to price discriminate. We present a model with a monopolist and a continuum of heterogeneous consumers, where consumers can opt out from being identified, possibly at a cost. We find that when consumers can costlessly opt out, they all individually choose privacy, which results in the highest profit for the monopolist. In fact, all consumers are better off when opting out is costly. When valuations are uniformly distributed, social surplus is non-monotonic in the cost of opting out and is highest when opting out is prohibitively costly. We introduce the notion of a privacy gatekeeper — a third party that is able to act as a privacy conduit and set the cost of opting out. We prove that the privacy gatekeeper only charges the firm in equilibrium, making privacy costless to consumers

Privacy and Liberty in an Always-On, Always-Listening World

The home is often considered the last bastion of privacy and the Fourth Amendment guarantees people the right to be secure in their houses against unreasonable searches and seizures. But today, the government is not the only entity seeking to invade homes to obtain information—technology companies like Amazon and Google are making an aggressive push into homes with devices like Amazon Echo, Google Home, and Apple HomePod. We are entering an always-on, always-connected world. A generation of always-on devices, capable of watching and listening to everything we do, is entering the consumer electronics market. These devices promise to make daily lives easier, safer, and more enjoyable, but they also bring powerful surveillance tools into our most private spaces. Privacy and security issues associated with always-on, alwayslistening, and always-watching devices are demanding increased attention. After examining the current state of government regulation and the rapid technological development of always-on devices, this Article argues that existing legal regimes are not sufficient to protect consumers. The Federal Trade Commission (FTC), for example, can only protect consumer privacy through sector-specific privacy laws that give the FTC oversight authority or by invoking its Section 5 “unfairness and deception” authority. Moreover, existing laws like the federal Wiretap Act or state one- and two-party consent laws do little to protect consumers from always-on device privacy intrusions. While sector-specific legislation like the Health Insurance Portability and Accountability Act (HIPAA) and the Children’s Online Privacy Protection Act (COPPA) offer stronger protection in certain situations, these laws are not comprehensive solutions to the challenges posed by always-on devices. This Article, developed as part of a collaborative effort between lawyers and data scientists, identifies three major gaps in the current law. First, when and how law enforcement agencies may access sensitive always-on device data is not clearly defined, giving always-on technology the potential to erode Fourth Amendment privacy rights. Second, consumers often lack control over what data always-on devices may collect and what happens to that data once it is collected. Finally, there is insufficient recourse for holding always-on service providers legally accountable for refusing to take data security seriously. This Article proposes model legislation to address these gaps. This proposal enhances consumer control and transparency, regulates law enforcement access to information captured by always-on devices, and requires service providers to adhere to industry security standards or higher security standards set by the FTC. The Article provides a new analytical context to view policies that will increase consumer confidence, protect privacy, and prevent disastrous, costly data breaches as we move towards an always-on, always-connected world

The effects of mobile advertising alerts and perceived value on continuance intention for branded mobile apps

This paper examines consumers’ behaviours towards mobile advertising alerts offered by branded mobile apps in the fashion industry. While consumer-driven factors have attracted much attention, little research has examined the impact of data-driven mobile advertising alerts on consumer continuance intention for branded mobile apps. This paper analyses the combined influence of consumer beliefs, data-driven mobile advertising alerts, and perceived value on mobile advertising acceptance, intention to repurchase, and recommendation behaviour towards branded mobile apps on social media. In total, 340 valid responses from Spanish customers of an online fashion outlet, all social media users, who make their purchases from the company exclusively through its branded mobile application, were analysed to test the hypotheses, using structural equation modelling. The results showed that mobile advertising acceptance, intention to repurchase, and recommendation behaviour are driven by the perceived value of the branded mobile app. Perceived value is determined by the usefulness of the branded mobile app, attitudes towards mobile advertising alerts, and irritation. Mobile advertising content (informativeness and credibility) improves attitudes towards mobile advertising alerts. Ease of use increases perceived usefulness, while perceived control decreases irritation. Managerial implications are provided