The Digital Future

By Varda Saxena

Instagram and Facebook are tech giants who’ve created an extraordinary demand and supply of products. The services offered by them are not paid. However, such giants have revolutionised the modern-day economy. The way most markets are organised, like a market for agricultural products, these social media platforms are used by large, medium and small-sized enterprises to understand, target and influence the buyers who in turn get commercialised in the process. This paper analyses the business model of platforms like Instagram via economic theories and the implications of their revenue system on the market.

Introduction

The market offered by tech giants is a closely connected system, similar to the market of any other global commodity. For example, in the market of flavoured yoghurt or chocolate, each seller has a different price of the commodity from which the buyer is free to choose. Even though this market does not look as connected as it is, the market created by Instagram and Facebook is highly organised and sophisticated. It is challenging for Small and medium-sized enterprises (“SMEs”) to reach out the number of buyers which they are now influencing by paying to advertise on these platforms (Gatautis, 170). Therefore, the target audience of these tech giants are SMEs and big enterprises so that they can sell their users (174).

While scrolling through Instagram or Facebook, one notices the umpteenth number of advertisements, videos, photos and other media. These tech giants analyse our preferences according to how much time we are spending in watching these videos (Joseff, 3). Therefore, if a user scrolls through these platforms for ten minutes, and stops for longer durations at videos of confectionaries, Instagram analyses the data and monitors the time spent while watching the categories of content and presents similar content to the user repeatedly. Therefore, a user feels that by getting the content which is preferred by them, tech giants are providing them with an optimum experience. However, those preferences are being provided because we are the product, and SMEs are paying for this broadcast (Gatautis, 175). Through the analysis presented in this paper, the ethical implications of Instagram’s business model are highlighted, the effect on the market, the competition regime and commodification of individuals, is explored using the discourses of rationality, consumer behaviour and egalitarianism.

Weaponizing Behaviour Mapping

The demands of individuals are analysed by monitoring their activity. These platforms show a particular product at multiple instances and repeatedly to influence users, trying to tilt the market demand in their favour (Joseff, 5). The users are affected by the assemblage of their psychological trait logs via supercomputers, which can allocate preferred content with more accuracy as time passes (Krombholz, 185). These preferences help determine the demand of users and are seldom used in election campaigns too (Joseff, 4). The algorithm based on shared and searched content can analyse the socio-economic status of an individual, their needs and cravings. On this analysis, individuals are presented with substitutes, necessities and luxuries. With the growing user base, the supercomputers which are analysing user data 24/7 can predict more accurately, increasing the willingness of enterprises or election candidates to pay these tech giants for advertising and user influence (CNBC). These processes are brought about technologically, hence causing shifts in supply and demand curves. Change in weather, political differences, income changes cause fluctuations in the demand of users. These fluctuations are monitored, and they are presented with plausible solutions in the form of media. For example, during a recession, an election candidate pays Facebook to pinpoint the needs of various economic groups. These targeted people are then shown memes, posters and videos where the election candidate is addressing their problem. This process is repeated to lobby in favour of/against candidates to influence the masses.

Commodification of User Data

Such targeted campaigns influence the market equilibrium. When the enterprises or election candidates desire to sway a more significant set of audience, the supply of media content rises. Similarly, the demand amongst users also rises due to election season or repeated access to a particular amount of targeted media. For example, in March of 2020, a lady began posting politically charged content on her stories, and Instagram TV (“IGTV”) feed regarding masks. In a controversial video posted May 24, she alluded to a conspiracy behind the mask mandates and encourages audience members to “do their own research”. The video got more than 24,700 views (Joseff, 2); such incidents flair curiosity within the users, leading to more similar searches. This results in a larger audience which can be exploited by tech giants. Political incidents provide an incentive for SMEs and large enterprises to invest more, getting more user data in return. This causes a forward shift in the demand curve and the market equilibrium shifts (Mankiw, 80).

The algorithm used by Instagram can also be used to monitor the responsiveness of individuals to socio-economic changes (Ferwerda, 853). The demand for various commodities and political inclinations of individuals changes as the income levels vary. The more an individual is responsive to such changes, the more elastic is their demand (Mankiw, 97) and the more it can be manipulated. The consumer surplus is a good measure of economic well-being and is based on factors like income, tastes and preferences (Mankiw, 130). The taste and preferences are influenced by the attractive interface of such tech giants, which expose users to global products. The constant notifications and updates increase the willingness of users to buy and to scroll further. This scrolling is monetised and is sold to election candidates and SMEs (Ferwerda, 852). A benevolent social planner might concentrate on both efficiencies of the market and equality amongst the actors. However, the algorithm adopted by these tech giants acts as a parasite where the buyers and sellers in the market don’t have a similar level of economic well-being. In essence, the gains from trade are not equally shared among the market participants (Mankiw, 145).

Utility Maximisation via Preference Mapping

The content suggested to individuals is customised and indicative of preferences. These preferences are monitored and supplied after value propositions and customisations (Gatautis, 170). The activities of customers are also monitored adequately due to in-app permissions. These permissions allow access to an individual’s calls, messages and photos. This data helps the algorithm evaluate the valuation of goods and services done by an individual. They pitch the relative price of a good against the marginal rate of substitution and present optimum solutions on the user’s feed, which results in the matching of optimum consumer content (Mankiw, 443). This is one of the reasons Instagram users feel that they are the buyers/consumers because the Instagram business model makes users think that their utility is being maximised by the customised content (Ferwerda, 854).

Economists regard choices not as mental determinations but rather as actions that arise from constraints, preferences, and beliefs (Somers, 46). The revealed preference theory helps in separating preference and choice to explain how they depend on beliefs. These preferences are then ranked, and the highest-ranked content shows up on their feeds. However, these preferences are not a depiction of the highest degree of happiness or pleasure of a user (Somers, 48). The preferences rankings are generated over time, and they keep getting accurate with development in user base and longevity. Therefore, SMEs pay to target several individuals. This content is displayed to the users whose inclinations are towards the commodity produced by the enterprise. While this model may not be ethically correct, it provides a Pareto efficient system. A Pareto optimum is also known as a Pareto efficient allocation and is a state wherein it is impossible to make anyone better off without making someone worse-off. (Somers, 65). Additionally, the finger movements, notification sounds and interactive mechanisms employed by these tech giants are designed by exceptional professionals to influence user behaviour and induce addiction (Kircaburun, 159). There are multiple arguments against the morality of a Pareto efficiency as distributional injustice is morally undesirable. However, one needs to realise that Pareto optima will have to be given up to satisfy the other moral constraint, leading to another undesirable result. (Somers, 66)

This Pareto efficient model where Instagram and SMEs are benefiting more runs on the revenue generated by Ad impressions. Ad impressions are the clicks on various media and links, done by users of Instagram and Facebook. In 2019, Instagram generated 20 Billion Dollars as advertising revenue (Business Today). The cost of advertising on social platforms depends on the number of users which the enterprise is willing to target. This cost is fixed in the short run but varies in the long run. However, the specialisation of Instagram’s algorithm increases and can collect more accurate data and causes the economics of scale (Mankiw, 273). There are fewer chances of diseconomies of scale because coordination mechanisms are usually algorithm-specific and therefore are less prone to human errors.

Creation of Competition

There are multiple such tech giants which provide similar advertising services, for example, Pinterest, Google, Twitter. They create competition in a market where the customer chooses the corporation with the maximum user base and cost-effective advertisement packages. Due to a smaller number of existing firms which provide such services, one can quickly assess why the cost of large-scale advertising is high. For example, the anti- Trump super PAC (also known as “independent expenditure-only political action committees” and engage in political campaigning) incurred a cost of 800,000 dollars only due to online advertising. (Joseff, 5). Profit maximisation is the crucial need of these platforms and therefore, to maintain themselves in the long-run equilibrium of a competitive market with free entry and exit, firms should operate at an efficient scale (Mankiw, 298).

Obtaining such efficiency has become slightly more manageable with the emergence of platforms like Instagram. The input costs of advertising include capital investments in wages, monetised accounts, influencer payments, and maintenance of technology. With the increase in the user base of these platforms, it has become sufficiently easier to finance these input costs and provide services. Therefore, the Platform phenomenon has become popular nowadays and has paved the way for a platform economy. This economy is “one in which tools and frameworks based upon the power of the internet will frame and channel our economic and social lives” (Kenney, 156). There are four factors that ensure the functioning of such an economy. These are infrastructure, training and skills, social protection, and regulatory transition. Platform economies have caused significant changes in market competition, as addressed during World Economic Forum 2016, by outlining the importance of platforms for organisations, lowering market entrance barriers, and causing changes to the logic of value creation, capture, and transfer to market (World Economic Forum).

However, the statistics which reflect the cost of such advertising, such as the Anti-Trump campaign, indicate how the platform with the highest user base could monopolise the online campaign market. Instagram reached one billion monthly active users in 2018 and has been growing consistently (Statista). It is evident how these platform economies are monopolised as the price exceeds marginal cost. Such monopolies don’t have a supply curve; therefore, they are free to charge different prices, customised based on the need of enterprises and election campaigners (Mankiw, 308). This price discrimination is not well highlighted due to the ambiguity of the product offered by such platforms and the consensual commercialisation of users. However, each society has anti-competition laws which regulate certain malpractices. One reason why such laws are needed is hidden in the principles of welfare economics. The invisible hand of the market allocates resources which leads to maximisation of total surplus. Because a monopoly leads to a different allocation of resources than in a competitive market, the outcome fails to maximise total economic well-being (Mankiw, 311).

Taxation to Curb Externalities

When one talks about welfare economics, not only the buyers and sellers but the holistic development of the society is factored in by economists. The negative and positive externalities are also indications of factors that influence a country’s economy. The negative externalities reflect certain damages or losses which result during the production of a commodity, and they should be factored in while calculating marginal costs (Goodwin, 293). However, most people don’t factor in such externalities, and therefore the government introduced Pigovian taxes to decrease economic inefficiencies. Pigovian taxes are generally introduced to reduce the economic loss caused due to the unintended consequences caused by a product’s production (294). One can also infer that a far-fetched reason for the high costs of Instagram advertisings and Platform economy services could be the high amounts of electricity which are needed by computers to analyse the data. This is also inherent in the fact that most countries have an environmental tax, like an upstream tax, levied on almost all goods (Goodwin, 297).

Welfare Economics

Another discourse of welfare economics could stem from a radically egalitarian distribution of material conditions of life (Wright, 2). Commodity allocation always favours one side of the scale; this has also been one of the criticisms of Pareto efficient systems (Somers, 66). However, in today’s complex economy, equitable distribution of resources has become materially impossible. Further, the capitalist ideals of enterprises actively block socialist ideals by upholding personal economic interests while alienating the masses from their means of sustenance, or exploiting their capital and commodifying them, just like today’s social media platforms. The way a person scrolls through Instagram, the manner and time at which notifications are delivered is strategically planned to feed us sponsored content and generate revenue that is not even shared with us.

Conclusion

Through an economic analysis of the models of tech giants like Instagram, we were able to highlight various tenets of welfare economics and their application to the new-age Platform economies. Further, the way small, medium and large-scale enterprises have increased their hold onto the advertising market of such giants has increased the need for such giants to monitor, influence, and manipulate user behaviour and presence. Such manipulation has led to the commodification of social media users and has created an unregulated business where it is easy to generate revenue by coercing individuals by way of technologies they consensually buy.

REFERENCES

Block, Fred and Margaret R. Somers. The Power of Market Fundamentalism. Harvard University Press, 2014.

“Davos 2016-A New Platform for the Digital Economy.” YouTube, uploaded by World Economic Forum. 12 May 2017, https://www.youtube.com/watch?v=-pFRIlgEdl0.

Ferwerda, Bruce, Markus Schedl, and Marko Tkalcic. “Using instagram picture features to predict users’ personality.” International Conference on Multimedia Modeling. Springer, Cham, 2016, pp. 850-861.

Goodwin, Neva, et al. Principles of Economics in Context. Routledge, 2014.

“Instagram generated more ad revenue than YouTube in 2019.” Business Today, 5 Feb. 2020, https://www.businesstoday.in/technology/news/instagram-generated-more-ad-revenue-than-youtube-in-2019/story/395513.html#:~:text=Instagram%20earned%20%2420%20billion%20in,from%20advertising%20during%20the%20year. Accessed 7 December 2020.

Joseff, Katie, et all. “Social Media Influencers and the 2020 U.S. Election: Paying ‘Regular People’ for Digital Campaign Communication.” Centre for Media Engagement: Moody College of Communication, 2020, https://mediaengagement.org/wp-content/uploads/2020/10/Social-Media-Influencers-and-the-2020-U.S.-Election-1.pdf. Accessed 7December 2020.

Kenney, Martin, & John Zysman. “Choosing a future in the platform economy: the implications and consequences of digital platforms”. Kauffman Foundation New Entrepreneurial Growth Conference, 2015, pp. 156-160.

Kircaburun, Kagan, and Mark D. Griffiths. “Instagram addiction and the Big Five of personality: The mediating role of self-liking”. Journal of Behavioral Addictions J Behav Addict, vol. 7, no.1, 2018, pp. 158-170.

Krombholz, Katharina, et al. “Fake Identities in Social Media: A Case Study on the Sustainability of the Facebook Business Model.” Journal of Service Science Research, vol. 4, 2012, pp. 175-212.

Levy, Ari, et al. “Why political campaigns are flooding Facebook with ad dollars.” CNBC, 8 Oct. 2020, https://www.cnbc.com/2020/10/08/trump-biden-pacs-spend-big-on-facebook-as-election-nears.html. Accessed 7 December 2020.

Mankiw, N. Gregory. Principles of Microeconomics. 7^th ed.,Cengage Learning, 2015.

Statista. 24 Nov. 2020, https://www.statista.com/statistics/253577/number-of-monthly-active-instagram-users/. Accessed 7 December 2020.

Wright, Erick O. Approaches to Class Analysis. Cambridge University Press, 2005.