The idea of monetization is based on the repetitive utilization of the gained information about the consumers’ interests, wishes, wants, and pains. Baecker et al. (2020) refer to data monetization as “using data for quantifiable benefits”, and those benefits include both a monetary value and any other type of economic profit. According to Ye et al. (2021), the digitalization of content has ubiquitously provided business organizations with new optimization models and business strategies, including subscription or the pay-per-item model. Hence, data monetization can be considered one of the core factors of progress in the company’s increase in income and popularity.
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The well-known company Google utilized data monetization mechanisms in the vast majority of its services. Therefore, it can be concluded that the company implements indirect monetization in its functioning. For example, some of the most popular products of the Google company are Google Advertisement, Google Maps, Google Music, and Google Movies, as well as Google Search. Additionally, Kopf (2020) explains that, for example, YouTube, a social platform that is a subsidiary of Google, is provided by this company to generate higher profits and utilize the opportunities of data monetization to the full. All of the mentioned above examples use the monetization of data to increase the number of services provided to their users. For instance, Google Movies, Google Music suggest to their users new pieces of music in the section of recommendations, that are based on their personal preferences. These preferences are generally based on the music or movie collections created by the customer, previously watched movies or played songs, and search history. Google Maps can show cafes, restaurants, or cinemas based on the location of the phone, while Google Search automatically modifies the suggested search options based on the location, region, chosen language, and search history.
Google Advertisement is a broad-based service that helps to generate advertisements and increase the popularity of certain products or services. This function utilizes both direct and indirect monetization. The direct one is utilized to provide other online apps, shops, or manufacturers with an opportunity of advertising their goods and services. This creates additional income for Google as outside companies pay it for the data monetization. Indirect data implementation is used for increasing the popularity of Google and concerning apps. Therefore, Google Advertisement is the service that allows the company and its partner companies to gain larger profit and enhance their image and popularity. The monetization of data in social media is quite relevant and beneficial for companies utilizing this method.
Ethical, Privacy, and Legal Issues
Although the implementation of data monetization schemes in diverse business processes helps companies raise this efficiency and benefits, this technique is associated with several challenges and risks that mostly concern ethical issues and customer privacy. Napoli (2019) states that social media platforms and data monetization processes on such platforms need to be controlled as diverse disclosures of information often occur. The author underlines that the problems of inappropriate data utilization range from Russian interference in the U.S. election, to the security of users’ private information and the breakdown of search engines and social media platforms (Napoli 2019). Therefore, the privacy of information can be taken as one of the integral elements that needs to be taken into consideration.
As mentioned earlier, the disclosure of customers’ private information is one of the most significant threats to the utilization of data monetization. It can occur in many ways, such as sharing personal data via unreliable messengers or social platforms, breakdowns in data security systems along with hacker attacks that are quite popular in the 21st century. Additionally, even without the public disclosure of the users’ private information, sharing data among collaborating companies can be viewed as unethical because the users are generally not aware of their data being disclosed. Moreover, business ethics should be taken as a significant factor that influences the decision-making process, as well as the decision to monetize data or not. In addition, if any of the companies utilizing data for monetization happens to make a mistake that leads to data disclosure, diverse legal issues can occur as well.
Therefore, different organizations that aim to provide businesses with legal or ethical advice were established during the last decade. However, governmental regulation regarding private information security is generally based on the ‘informed consent’ approach; therefore, it is not enough for overall data protection (Choi et al. 2019). The main agencies related to cybersecurity, the maintaining of information privacy, and regulating the norms of information disclosure mostly issue various norms, plans, certificates, and regulations that aim to envelop data monetization. For example, the International Organization for Standardization (ISO) is well-known for its data monetization and private data security standards. Hence, such agencies provide businesses with broad-based legal regulations that need to be followed if the enterprise does not want to have trouble with the law.
GVV and Code of Conduct
If I was employed by Google and saw my colleague trying to use monetized data for their own sake, I would definitely report it to my supervisor or the headquarters. In my opinion, personal utilization of someone’s private information is fully inappropriate and needs to be punished. In this situation, such an innovative approach as giving voice to values could bring additional benefits for me as an average employee. The main idea of GVV is that ethical awareness and analysis should be supported by an action-oriented approach that involves active partaking in finding the right solutions and making appropriate decisions. In this case, an ethical dilemma of reporting your co-worker or hiding his illegal actions arises. I would definitely report the inappropriate utilization of data because if the company allows it once, this situation will happen repeatedly fulfilled by different workers. If such a problem becomes broad-based in a company, sooner or later such an organization will lose customers’ support, public image, popularity, and status. Therefore, the giving voice to values approach supports the decision of reporting in the case of this inside data disclosure.
A code of conduct is one more set of regulations that could help in the establishment of an appropriate organizational environment regarding private information security and data monetization. If such a code of conduct existed, it would be easier for employees to make decisions in stressful and ethically pressurizing situations, for example, reporting their colleague’s fraud regarding data. It would define what needs to be done in certain situations of urgency, and hence the corporative environment would become more structured and organized. In my opinion, every organization needs a code of conduct to reduce the number of possibilities for information disclosure and the company’s employees’ involvement in illegal actions.
Baecker, J, Engert, M, Pfaff, M & Krcmar, H 2020, ‘Business strategies for data monetization: deriving insights from practice’, in Wirtschaftsinformatik (Zentrale Tracks), Technical University of Munich, Munich, pp. 972-987.
Choi, J, Jeon, D & Kim, B 2019, ‘Privacy and personal data collection with information externalities’, Journal of Public Economics, vol. 173, pp. 113-124. Web.
Kopf, S 2020, ‘“Rewarding good creators”: corporate social media disclosure on monetization schemes for content creators’, Social Media + Society, vol. 6, no. 4, pp. 1-12. Web.
Napoli, P 2019, ‘User data as public resource: implications for social media regulation’, Policy and Internet, vol. 11, no. 4, pp. 439-459. Web.
Ye, H, Yang, X, Wang, X, & Stratopoulos, T 2021, ‘Monetization of digital content: drivers of revenue on Q&A platforms’, Journal of Management Information Systems, vol. 38, no. 2, pp. 457-483. Web.