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The Technology: Has the Digital Communication Technology Changed the Way Markets Function? Cooperation or Competition?

Abstract As social beings, humans have traded goods and services for generations. The mechanics of exchange have adapted over time to the changing environment but the underlying incentives remain the same. Differences in preferences and resources are bridged by connecting with individuals in other parts of the economic network using digital communication technology (DCT). DCT has generated new scarcities and new mechanisms for resource allocation, enlarging the scope of exchange along three dimensions. One is the trend toward organizational restructuring (OR) precipitated by granularity and disintermediation. The second trend is the emergence of organizational behemoths (OB), fostered by network effects. And third, competition for scarce resources is channeled into cooperation as individuals adapt to a rapidly changing context for exchange, and this adaptation itself changes the environment.

Keywords Granularity • Organizational restructuring (OR) • Disintermediation • Organizational behemoths (OB) • Competition as information

Economic transactions between individuals have existed since ancient times. They have evolved and adapted to changing circumstances, such as climate change, epidemics, famine, and human nature, periodically creating imbalances in the economic system. Markets, as a mechanism for scarce

© The Author(s) 2017 1

S. Bhatt, How Digital Communication Technology Shapes Markets,

Palgrave Advances in the Economics of Innovation and Technology,

DOI 10.1007/978-3-319-47250-8_1

resource allocation under competing demands, have adapted to these imbalances. Currently, we are in the throes of another shock to the system, a technological shock in the form of digital connectivity, creating a network of economic agents, a network economy. What does this perturbation mean for resources and trade? Are there new scarcities? Is the exchange of goods and services governed by new rules? How can we characterize the network economy?1 If the rules of the trading game have changed, is there more cooperation or competition?

My answer, in brief, is that we are witnessing new scarcities and new mechanisms for resource allocation, as digital communication technology (DCT) shifts boundaries between economic agents. The scope of trade has been redefined along three dimensions. One is the trend toward organizational restructuring (OR) leading to granularity and disintermediation on an economy-wide scale. The second trend is the development of organizational behemoths (OB). And the third trend is a recalibration of competition.

The multiple demands ofinformation and communication have shifted the boundaries between public and private goods and struck against the hard resource constraint of attention. Consequently, a new scarcity has surfaced in the form of cognitive bandwidth, or more simply attention. Attention is a scarce resource and, therefore, a tradable commodity in the world of marketing. Individuals provide personal information, at no cost, in exchange for freebies. This data is sold to marketing firms who create precisely tuned messages and purchase advertising space to acquire consumer attention or eyeballs. Individuals’ attention is effectively traded when this personal data is sold and then sliced and diced so as to best capture “brain space.”

In the restructuring trend (OR), products are becoming more granular and the elimination of intermediaries is making large organizations less dominant in the economic landscape.2 Granularity of products arises from an unbundling of lumpy purchases, such as ridesharing replacing vehicle ownership. Organizational granularity empowers smaller trading units so that control is retained with a concomitant reduction in the size of these trading units, where size is measured by number of employees. Connectivity allows information transfer, which enables restructuring the organization of trading units into smaller entities. These granular person- to-person (P2P) trading units retain authority and autonomy. Consumer demand for functionality has replaced purchases based on brand or product name as buyers use iPads, for example, for purposes beyond their original intention. This fosters innovative product differentiation by projecting user behavior over time such that newer products and services can cross traditional boundaries. More fundamentally, connectivity generates heterogeneity of ideas and cultural diversity, providing fertile ground for startups and entrepreneurial activity.

The number of small firms in the US has been increasing year over year since 2005, where small is defined as firms that have between 3 and 250 employees. But while the number ofsmall firms is increasing, the number of employees at these firms is decreasing. Entities such as Elance ODesk (founded in 2003, but rebranded as Upwork in 2015), Grubhub (2004), Airbnb (2007), TaskRabbit (2008), Uber (2009), Blue Apron (2012), Instacart (2012), and Shyp (2014), were all founded as small firms. While firm age and size are likely to be correlated at inception, the notion of startups is best captured by firm age and not firm size. The data on entrepreneurial activity suggest a resurgence of entrepreneurship: The Kauffman Startup Activity Index, a composite of entrepreneurial activity in the US, increased in 2015, reversing a five-year downward trend that began in 2010. Particularly noteworthy is that this index defines startups as firms younger than one year, with at least one employee other than the owner.3

Most measures of digitization of the economy focus on the implementation of digital technology: investment in digital assets, access to broadband and mobile devices, and the incorporation of this technology into the production process. More difficult to measure is the set of economic possibilities - in terms of new products, new markets, and new ways of doing business and consuming - arising from this technology. Disintermediation and granularity in firm size has fostered a form of market design based on cooperation among trading units. Cooperation and coordination are inherent to market economies where all entities play by the same rules and where prices serve as the hand of coordination, matching demand with supply. But cooperation in the context discussed here is beyond observing the rules of the game - it rests on the sharing of information. This feature is not due to altruism but rather the best response to the unfathomable forces of connectivity.

The second trend, development of OB, arises as connections explode across the global network of individuals and information advantages are overwhelmed by network size effects. OR in some industries, that would favor granularity, is upended in favor of “too big to fail” trading units. The digital economy is a network economy much like the aspen root system. For every aspen grove you see above ground, there is a vast system of underground roots connecting multiple groves. The roots can get entangled and the aspen trees can get denser within a single grove. Similarly, as connections multiply, powerful network effects, information cascades and data-driven algorithms lead to concentration of economic power in OB. These hubs foster homogeneity of ideas, further enhancing benefits of like- minded connections in a reinforcing feedback loop.

We are familiar with Amazon dominating in the retail arena, Facebook in the social dimension, Google in the search area and Netflix in entertainment. If we add Microsoft, Ebay, Priceline, Salesforce, and Starbucks, we have a network economy that is culturally homogenous and short of business dyna- mism.4 The risk of starting new ventures increases in this hyper-connected network. Startups risk obliteration under the glare of “either-you-are-with-us- or-against-us” economic thinking or are acquired by the behemoths, and then torn apart, absorbing only those pieces that add synergy to the acquiring firm. Innovative thinking requires solitude, so hyper-connectivity may play a role in the apparent shortage of business churning or dynamism. Steven Spielberg said in his Harvard commencement speech, “Social media that we’re inundated and swarmed with is about the here and how... this is why it’s so important to listen to your internal whisper” [2]. With cell phone chimes smothering the tender shoots of breakthrough ideas, we might remain in the “too-big-to-fail” grove.

I will be discussing these ideas in the chapters that follow, but for now, let me return to the traditional models. In order to build the connection between technology and disintermediation, we have to start with the most elementary feature of economies - markets.

Trading in markets dates back to the days when farming replaced foraging around 7000 BCE in China and Mesopotamia, what is today Iraq, Jordan, and Syria. Later, around 2200 BCE, we have records suggesting that Egypt’s pharaohs, rich in gold and grain, gave these goods to minor rulers of Lebanese cities, who reciprocated with fragrant cedar. According to Ian Morris [3], “gift exchange was as much rooted in psychology and status anxiety as in economics, but it moved goods, people and ideas around quite effectively. ” Whether the bilateral exchange of goods and services was motivated by considerations ofcommon economic advantage or psychological well-being, barter-trade was recorded somewhere between the seventh- and fifth-century B.C.E when Joseph (of Biblical fame) was sent by his family to Egypt to exchange his coat for food. Prior to that time, the Xia dynasty ruled in Anyang in the Yellow River Valley in China somewhere between 2000 and 1600 BCE, where evidence of trade is depicted in the third-century CE novel of Luo Guanzhong, “The Romance of the Three Kingdoms” [4]. “And the three brothers went forth to welcome the merchants. They went northwards every year to buy horses ... and gave the brothers fifty good steeds, and besides, five hundred ounces of gold and silver.” Importantly, according to Joseph Schumpeter’s analysis, Aristotle was already writing in 300 BCE about the requirement of “money” as a medium of exchange, unit of account and store of value, and that money must itself be one of the commodities exchanged. So the world had moved straight from barter to the use of a medium of exchange in markets by 300 BCE [5].

The design of markets has been stable at least since the time of Aristotle. In ancient Greece, these bazaars were physical congregations of buyers and sellers. But it was not as simple as that. The product quality was uncertain and the exchange rate, or “equivalence” in Aristotle’s terminology, was ambiguous.5 What was the precise composition of tin and copper in the bronze weapon that was for sale? How were you to believe the seller? Were there large inventories of this material so that sellers were eager to dispose of their wares? Did this depress the exchange rate between weapons and horses, for example? Did different sellers have different-sized inventories and if so were buyers aware that some sellers might be willing to bargain for lower values? Did buyers have to search the entire bazaar for these “lower-value” sellers and if so were these search costs manageable? As John McMillan [6] writes, “Two kinds of market frictions arise from the uneven supply of information. There are search costs: the time, effort and money spent learning what is available, where and for how much. And there are evaluation costs, arising from the difficulties buyers have in assessing quality. A successful market has mechanisms that hold down the costs of transacting that come from the dispersion of information.”

In modern times, even with clearly stated prices and observable quality, we have versions of barter where the seller might deliberately obfuscate the exchange rate. For example, many years ago as a teenager visiting my aunt in Baroda, India, I observed her buy vegetables from the local vegetable cart that made morning rounds in the neighborhood. While the central market price for eggplants was around INR 3 per kilo, the vendor, more like a family member who received repeat business and unlikely to deceive, charged slightly more. Instead, he would throw a couple of green chilies and a few pieces of ginger into the bag of eggplants as a “bonus.” The vendor obtained his desired price and my aunt gleefully thought she got a bargain. The exact exchange rate or price remained ambiguous despite numerous neighboring vendors and low search costs.

While the story above may sound apocryphal, repeated interaction between the same two parties plays a powerful role in some markets. The situation, however, is not universal, since in general, price transparency is needed for markets to function efficiently. The actual mechanics of price transparency is via information, not some complicated system. Information is revealed about (i) what is available, (ii) where it is available, and (iii) at what exchange rate it is available, thus fulfilling the matching and price discovery functions of markets. But what are the pre-conditions for prices to provide accurate information?

Competition in the traditional neoclassical economic model is defined as an environment with multiple traders, whose interaction agglomerates disparate bits of relevant information, making prices accurate representations of the underlying technology and tastes. When prices accurately convey information about the exchange value of the good, they provide stabilizing, self-correcting incentives to economic agents, who respond to these price signals by updating their purchase-and-sales decisions. In turn, prices themselves react to fundamental imbalances so the cycle is reinforcing. This dynamic represents competitive activity in markets - traders adapt and learn from interacting with each other and prices adjust along with quantities.

There are three perspectives of competition. First, an environment of multiple traders; second, an interactive process of adaptation and learning; and third, an outcome of informative prices.6 What definition of competition is truly meaningful in a discussion of the network economy? The first aspect of the definition had more support in the pre-Internet days when the only way to have informative prices was the agglomeration ofinforma- tion from multiple traders, in a static model. Therefore, the second and third aspects - the process and outcome - are more relevant today.7 To be clear, in the network economy, the primary mechanism for information sharing is connectivity itself, and not the resultant granularity. Connectivity automatically leads to informative prices. So, in a network economy, a meaningful definition of competition is informative prices, not necessarily multiple traders.

The question posed at the beginning of this chapter - does the Internet move markets toward more competition or more cooperation - is best answered by recognizing this definition of competition. In the network economy, information surges across the network and makes proprietary hoarding of information impossible. This means that the Internet is moving markets toward a new definition of competition since every transaction is based on knowledge sharing made cheap and fast by digital connectivity. Hence, granularity is the result of cooperative information gathering and sharing.

Two basic prerequisites of markets, writes Avinash Dixit, are “security of property and of contract” [7]. Meaningful economic exchange requires confidence in ownership rights over the property or good to be bought or sold and confidence in the successful implementation of the contract. The exchange must be carried out and reneging should be costly; hence legal contract enforcement is vital. In the network economy, where information is the key commodity, the notion of property rights over information becomes awkward to define. How can you restrict the flow of information when it is cheap or costs nothing to share this information between multiple economic units? Information as a product is non-excludable like oxygen in the atmosphere - once it is out there you cannot exclude people from consuming it. It is also non-rival, like viewing a sunset, since my consumption ofinformation doesn’t preclude anyone else from consuming this same information.

In the days of Luo Guanzhong, these informational requirements were addressed by the intervention of friendly and neutral traders, who became the intermediary between the seller and buyer of goods and also the monopoly holder of valuable information. These traders could be the horse dealers who traded horses for gold and steel weapons. Using reputation as collateral, these traders would assure both parties of the veracity of their proposed contract, thus ensuring the trade. Thus was born what became known as an intermediary-trader, who created and monitored the trading links in bazaars, managing trading orders by ensuring the successful matching of buyers and sellers. As John McMillan writes, “Market intermediaries like wholesalers and trading companies reduce search costs for firms” [6].

Moving from ancient bazaars to the Internet bazaar, the release of the iPhone in January 2007 marked the introduction of a technology that has connected or linked markets, so that information is instantly, continuously, and ubiquitously available to all participants. The intermediary- trader was eliminated. The phone was no longer merely a communication device, but a computer and a camera, linking the actual world to the virtual world. The smartphone changed the way people connect to each other and the world. Three key game changers or major drivers of the network economy had been unleashed: mobile connectivity, a vast collection of facts or big data, and a new concept of time.

Connectivity affects the economics of networked markets by eliminating intermediaries, so might the Internet possibly be driving the fourth industrial revolution (following the steam engine; the systematic application of science to technology as in the internal combustion engine, electricity, telephone, telegraph; and the retail productivity revolution as manifested in the assembly line)? Disintermediation in financial markets is evidenced by innovations such as the digital wallet (Apple Pay, Google Pay, Venmo, and Square), shortening the financial supply chain by unbundling the intermediation function of bank deposits and providing a payment mechanism, but not a store of value. Boundaries between products and between industries have become blurred giving rise to a fluid economy where definitions of markets and transactions are ambiguous. For example, the distinction between employee and contract labor is becoming blurry. Facebook is now giving its contract workers more benefits such as paid leave, which makes them more like salaried employees [8]. Connectivity also encompasses organizational change. Industries such as education, healthcare, and the news media were already highly connected, but this new technology has reconfigured the map of these industries. Education must now be redefined to include the virtual classroom or massive, open, online courses (MOOCs); healthcare must include customer review-driven online health newsletters and news media must include social networks such as Twitter, which deliver news in real time. Not only are there new industry definitions, but new uses for old products. The iPhone is a voice communication device and a camera, both of which existed a decade ago, but blending these two capabilities not only defines a new use for old products but redefines the product itself.

Connectivity becomes more potent in its impact because of the mobile dimension - the anytime and anywhere idea. To put mobile connectivity into perspective, consider some numbers. According to a recent Pew Survey, over two-thirds (64 %) of American households own a smartphone and 7 % of American households do not have any Internet connectivity, at home or elsewhere, other than via their smartphones. This smartphone dependency is income related since only 1 % of households earning more than $75,000 are so deeply reliant on the device for Internet connectivity. Of those that own smartphones, 68 % used their phone for breaking news, 62 % used the device for health information, and 57 % for mobile banking. The smartphone has become a necessity for the 46 % of smartphone owners who say they cannot live without it [9].

Painting an extreme scenario, Jeremy Rifkin makes the case that connectivity will undermine the capitalist economy by driving production costs to zero and will be replaced by the Collaborative Commons. The economy he envisions is one where ownership and exchange is replaced by communal sharing. Social capital becomes the bedrock of this economy, where connectivity “brings the human race out of the age of privacy, a defining characteristic of modernity, and into the era of transparency.” Furthermore, he adds, “While privacy has long been considered a fundamental right, it has never been an inherent right.” In fact, the worst punishment meted out to members of society is ostracism. [10]

Currently, we are only witnessing the game-changing role played by mobile connectivity. We have yet to feel the impact of big data. Big data, writes Steve Lohr, is a “catchphrase” which

stands for the modern abundance of digital data from many sources - the web, sensors, smartphones and corporate databases - that can be mined with clever software for discoveries and insights. Its promise is smarter, data- driven decision making in every field. [11]

For example, the growing field of passive telemetrics enables the gathering of unprecedented amounts of longitudinal data that assists in behavioral assessment for monitoring and improved understanding of individuals with autism spectrum disorders (ASD). Matthew Goodwin [12] writes, “ [W]e are developing passive telemetric audio and video technologies for densely sampling behavioral manifestations of ASD in the first two years of life,” which is when most behavioral abnormalities are evident but not diagnosed. Early, prescient diagnosis enables effective, long-term treatment.

Human interaction and engagement generate an intricate web of connections. These connections form coherent patterns that determine how information is transmitted through the network of relationships. Simultaneously, the very exchange of ideas across the network - the transmission of information - determines human behavior and network formation. For example, strong social ties mobilize individuals to act in a social network, whereas economic incentives, which focus on the rational individual, may fail to generate action. Social connections provide value to individuals and these connections can be used to apply pressure for change. In a seminal article, Matthew Jackson writes, “Networks are not only conduits for information or influence, but also adjust in reaction to behaviors” [13].

These ideas are elaborated upon according to the following map. After a brief explanation of the language of networks in the appendix to this chapter, Chap. 2 explains why connectivity, data and a new resource scarcity, attention, are the most significant forces of DCT. In Chap. 3, I explain how these drivers lead to disintermediation, granularity, and cooperation by applying network theory to economic relationships in order to characterize the network economy. The position of an economic unit or node within the network impacts the nature of links between nodes, so the structure of the network has powerful effects on the outcome in terms of prices and welfare.

It has been argued that four industries have powerful effects across the economy. In the language ofnetworks, these industries have a centrality that is not shared by other industries. In this book, I will discuss the education and entertainment industries, leaving the other two industries, energy and environment, for future exploration. Accordingly, I will examine the impact of network structure on education and labor markets in Chap. 4, and the world of entertainment in Chap. 5, captured more broadly in the CIME industries - Communication, Information services, Media (publishing including software, books, newspapers), and Entertainment (motion pictures, sound recording, broadcasting). I broaden the scope, in Chap. 6, to consider macro-level effects in financial markets - information cascades, power laws, and network effects. Chapter 7 considers the intersection of privacy (starting with the law encapsulated in the First and Fourth Amendments to the US Constitution) and technology. The intersection of commerce and regulation that is influenced by, and in turn impacts, the architecture of the Internet is discussed in Chap. 8. Cooperation versus conflict in the network economy is best understood in this framework. Self-determination, liberty, and the freedom of ideas are caught up in the struggle for control over this Internet. Finally, I conclude with some thoughts about why cooperation is driven, not simply by altruism, but by rational calculation.

Let me clarify two important points of nomenclature. First, I use the acronym Internet and DCT to refer to (i) the architecture of mobile, DCT, that is, a network of distributed computing systems and (ii) the entire cyberspace of connectivity that transmits information in digital form. DCT includes artificial intelligence and the Internet of Things, which is connectivity across inanimate objects. Second, I use the term network economy to capture connections between economic agents and the term digital economy to signify that these connections are digitally powered. The two are inextricably related and I use them interchangeably, depending upon context.

My Take

DCT has shifted the boundaries between economic agents and between public and private goods. Boundaries between firms are reorganized, as firms are restructured into granular entities as well as behemoths. Information transparency has moved the needle on privacy and encroached upon individual autonomy, so we fight for control over personal data - our attention, our work, and our access to information. But in order to adapt to the changing and unfathomable environment, our best response is to cooperate when we cannot control.


  • 1. I use the acronym Internet to refer to the architecture of mobile, digital communication technology as well as the entire cyberspace of connectivity. In 1995, Tim Berners-Lee called this the World Wide Web (WWW) or a multi-purpose network of packet switched data.
  • 2. By granular, I mean “small,” comparable to grains of sand. In other words, no economic participant is distinguishable in size from another. However, the character of each grain will differ.
  • 3. For more on the Kauffmann Index [1], see Chap. 3.
  • 4. I discuss the term business dynamism in Chap. 3.
  • 5. Joseph Schumpeter writes, “Aristotle no doubt sought for a canon of justice in pricing, and he found it in the ‘equivalence’ of what a man gives and receives. Since both parties to an act of barter or sale must necessarily gain by it in the sense that they must prefer their economic situations after the act to the economic situations in which they found themselves before the act - or else they would not have any motive to perform it - there can be no equivalence between the ‘subjective’ or utility values of the goods exchanged.... [However] the just value of a commodity is indeed ‘ objective’ but only in the sense that no individual can alter it by his own action” [5].
  • 6. Economic models contextualize trade by positing environmental coordinates or exogenous parameters such as number of firms, consumer tastes, production technology, social and political institutions, and organizational structure of trading units. Business strategy is essentially about endogeniz- ing these parameters, as, for example, in changing the organizational architecture of firms from a hierarchical to a flatter layout.
  • 7. While granularity of economic units in the network economy means a decrease in the size of the trading unit, there is concomitantly an increase in the number of buyers and sellers when the overall population is fixed.
  • 8. This fairly common phrase is the tag line used by Fareed Zakaria in his weekly CNN broadcast, Global Public Square (GPS). I use it here to provide a perspective on the central issues raised in each chapter.
  • 9. A detailed exposition of graph theory and its application to networks is in the excellent textbook by David Easley and Jon Kleinberg [14].


[1] Kauffman Index of Startup Activity. Accessed July 3, 2016 from http:// 20and%20covers/2015/05/kauffman_index_startup_activity_national_ trends_2015.pdf

[2] Steven Spielberg Commencement Speech, Harvard University, May 2016 (transcript). Accessed July 21, 2016 from article/276561

[3] Morris, Ian. Why the West is Winning - For Now, pp. 190. McMillan, 2014.

[4] Guanzhong, Luo. The Romance of Three Kingdoms. Translated by C.H. Brevitt Taylor. E-book distributed by XinXii at

[5] Schumpeter, Joseph. History of Economic Analysis, pp. 61. Oxford: Oxford University Press, 1954.

[6] McMillan, John. Reinventing the Bazaar: A Natural History of Markets. New York: W.W. Norton, 2002.

[7] Dixit, Avinash. Microeconomics: A Very Short Introduction. Oxford: Oxford University Press, 2014.

[8] Economist. “The Truly Personal Computer.” February 28, 2015.

[9] Smith, Aaron. “U.S. Smartphone Use in 2015.” Pew Research Center. Accessed April 1, 2015 phone-use-in-2015/

[10] Rifkin, Jeremy. The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism. New York: Palgrave Macmillan, 2014.

[11] Lohr, Steve. “Sizing Up Big Data, Broadening Beyond the Internet”, The New York Times, August 17, 2014.

[12] Goodwin, Matthew. “Passive Telemetric Monitoring: Novel Methods for Real-World Behavioral Assessment.” Chapter 14. In Handbook of Research Methods for Studying Daily Life, edited by Matthias Mehl and Tamlin Conner. New York: The Guilford Press, 2012.

[13] Jackson, Matthew. “Networks in the Understanding of Economic Behaviors.” Journal of Economic Perspectives, vol 28, no 4, Fall (2014).

[14] Easley, David, and Jon Kleinberg. Networks, Crowds and Markets: Reasoning about a Highly Connected World. New York: Cambridge University Press, 2010

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