Managerial Economics/Information Economy
The information economy is a contemporary way of looking at how economic activity is drawn from information being acquired, shared and used as a good, or non-physical capital. That is, agents can increase productivity and wealth can be through using knowledge to produce more information . Value is derived from utilising data to inform and predict outcomes. An example of this is the reflection of information releases on stock price data - data releases with negative sentiment can drive stock prices down, and vice versa.
Information Good[edit | edit source]
Products, services or experiences that are valuable to individuals because of the information they hold are called information goods. Information goods come in many forms and can be either tangible or intangible, or digital or non-digital. Some examples include; books, ebooks, newspapers, websites or even telephone conversations. Information goods generally need a form of payment before an individual can have access to it, for example - a movie, journal articles or a podcast. Information goods such as movies are subjected to copies leading to free-rider problems (Knowledge spillover). To fully gauge what the movie is like and if you, yourself like it, you would need to enter into a transaction (i.e. purchasing a ticket) to gain access to the movie. However,
true value is very subjective in this specific scenario, every perspective of a similar information brings different value to everyone. It might be information you already know or information that is not as exclusive. To avoid overpaying for information, people can go online and find easily available reviews or abstracts that has the ability to give a vague representation of the utility gain from said information.
There are three main properties of the information that make it difficult for market transactions:
Experience Good[edit | edit source]
- Unable to evaluate product or service prior to purchase as the characteristics are unknown therefore their characteristics become evident after consumption. Purchasers rely on customer loyalty, reputation and word of mouth when purchasing an experience good.
- For example, you can only assess if the movie was worth watching and paying for after you have watched it. You can only assess whether a meal was worth the price after eating it.
Returns to Scale[edit | edit source]
- Information has a high fixed (and typically sunk) cost of production but a low marginal cost of reproduction. This could lead to a free-rider problem. With returns not on par with the high cost in production (time, energy and knowledge), the utility gained is not enough to push for further contributions into technological advancements to allow creations.
- Initial cost of production of an information good is expensive but producing subsequent units or copies has low to no cost. (almost zero marginal cost)
- For example producing a movie has high initial costs (hiring actors, crew, studio etc.) but producing copies of the movie has minimal costs in comparison.
Public Goods[edit | edit source]
Information goods are non-rival and sometimes non-excludable
- Non-rival: consuming information does not affect another individuals consumption. Subsequent and simultaneous consumption of the good is feasible.
- An example would be a book or lecture slides, they can be viewed multiple times at the same instant
- Non-excludable: Information has the nature that, if it is known, is it almost impossible to exclude usage of another individual. be it a transaction has been made or not. But there are possibilities of having exclusive rights to informations. Legal rights such as patents, trade secret or trademarks.
- The properties of non-rivalry and non-excludability makes information goods have similar properties to public goods. The free-rider problem may be relevant.
- Free-rider problem can be characterised as an action that an individual take when they have the incentive to use without paying. This creates social inefficiencies. Without a solution or intervention the information good could be subjected to under-produced and over-consumed.
- An example would be publicly funded studies or statistics gathering. In some countries with incomplete copyright laws, one person may pay and download a digital file then share it with friends, their friends might share it with more people, and eventually the consumer might be unwilling to purchase the information goods.
- Not all goods fit perfectly into the sub categories of private and public. Goods that are non-rivalrous but excludable are known as collective goods. An example of this is paid television, you have to pay to view it, but viewing does not affect the amount of enjoyment someone else get from viewing it. Whereas, Rivalrous but non-excludable are common goods. Common goods are free to use, this leads to people over using them sometimes to exhaustion. This is called the "tragedy of the commons", examples include: overfishing, Earth's atmosphere and traffic congestions on main roads.
Network effects: Demand side economies of scale[edit | edit source]
Network effects may occur when decisions are aligned with the behaviour of others. Existing users benefit from each new user that joins the network. Specifically, network effects are characterised by the effects if one agent's adoption of a good:
- (a) benefits other adopters of the good (a "total effect"), such that if most people are using Facebook Messenger, it would benefit other users as information can travel faster through the same platform without the need for switching.
- (b) increases others' incentives to adopt it (a "marginal effect"), such that if a certain number of people you know are using a particular messaging application, you would have the incentive to adopt it as you could be included in messages shared on that particular platform.
- For example, owning a game console is better when many others have the same one because developers will produce more games for it (higher incentive for developers, allowing higher gain of utility on both consumer and developer ends). A credit card is more useful when many people own the same card as more shops will accept is as payment. An example would be EFTPOS (Electronic funds transfer at point of sale) becoming a common sight in most physical stores in Australia.
- Social media platforms are another common example of network effects. Facebook and Twitter would provide the same value as a personal diary without the interaction of other users. Utility and worth of social media increases due to having high amount of users.
- However, these effects could be localised, in which adopters of a good might only gain more benefit if people they know adopt the good instead of strangers. There may be minimal incentive to adopt a good if the good is not adopted by a majority of people you know. An example would be WhatsApp or Telegram, they are messaging app which are commonly used to contact friends and family.
Technology has given rise to a number of network effects where value is gained from interactions and compatibility. An example of a technology that's value depended on other adopters is the fax machine. That is the value of sending fax depended on others' willingness to adopt the technology.
Network Effects: Adoption[edit | edit source]
When customers are faced with a segmented market, adoption can become a complicated concept to understand. Choices amongst customers can differ in terms of an individual’s expectations and how they coordinate amongst one another. If coordination considered smooth amongst adopters, firms have a clear incentive to offer the best value/ deals in the market.
Adoption doesn’t occur often and is difficult to achieve. Adoption happens in two main ways: 1. Simultaneous adoption (Static) - There are multiple equilibria as each customer makes a single decision. Customers do not know the decision made by others. Expectations are essential to identify here and are self-fulfilling (to be discussed).
2. Sequential Adoption (Dynamic) - Customers have at least some information about the strategies chosen by other players (customers).
However, with simultaneous adoption, customers may fail to coordinate or consequently coordinate on a different equilibrium which may not be preferred. A common example of this exists when customers settle for low-quality products based on the past success experienced by the producer/ firm. For example, early choices, such as the QWERTY typewriter keyboard, lock in the market; new entry, especially against established networks with proprietary technology, is often nearly impossible.
When sequential adoption is present, it is common to see an early sign of indecisiveness and instability involving coordination. Corresponding to multiple equilibria, early adoptions have a significant influence over all future adoptions. In short, full sequential adoption will achieve efficient coordination if it is best for all customers.
As more people adopt a good, it increases one’s incentive to adopt it too. This payoff from an individual’s adoption of goodwill result in direct network effects, but only if the adoption by individual users is complementary. For instance, popular telecommunication networks can attract more non-users who are considering adoption.
Adoption also leads to indirect network effects if it is complementary because of its impact on a market. For example, hardware users can benefit if more users are using it with them. Even though these users do not receive any direct benefits, it promotes the provision of more improved software(Klemperer 2018)
Network effects are externalities[edit | edit source]
Network effects occur when the user of a good or service that impacts others who have adopted a compatible good or services. Externalities often occur from network effects that are unable to represent the value that is brought by adopters to the network.
There are three types of indirect network externalities (Evans and Schmalensee, 2018):
- Usage externality: The system is more useful to both sides of the platform when each side (or agent) uses the platform. For example, getting a vaccine that prevents the spreading of disease.
- Membership externality: The system is more valuable to users when more agents use the platform or become members. For example, credit cards - when many people use the same type of credit card, more shops will accept that type of credit card.
- Behavioural externality: The system may create rules to offset negative behavioural externalities. For example, a restaurant booking app may ban diners who fail to show up for four reservations in a row, as this is reducing utility for restaurant owners and other diners.
The impact of externalities on a network effect good or service occurs when: A person buys a good or service, they become part of a network
- Thus, the network increases in size
The utility that people derive depends on the size of the network
- "By joining the network, I make everyone else in the network better off"
Externalities might lead to market failure
- "I am not compensated for the benefit that I create for others, so I will not join the network"
- Therefore, in order to mitigate the market failure, public policymakers should have a cautious presumption in favour of compatibility and should look particularly carefully at markets where the incompatibility is strategically chosen rather than inevitable.
In summary, the effort of the adopters is not accurately represented by joining the network.
Consumer Expectations[edit | edit source]
In markets with network effects the utility of each consumer depends on how many consumers will purchase the product. The expected size of the network will influence consumer decision making.
Consumer expectations of a network depend on the following factors:
- Price and quality of a product by joining the network (e.g. a consumer may compare the product with substitutes and access whether or not the quality and price are competitive)
- Firm reputation (e.g. Is the company well regarded? Do multiple people hold the opinion that the firm provides quality service?)
- Growth path of the network
Self-fulfilling Expectations[edit | edit source]
Consumer expectations can alter outcomes through self-fulfilling expectations/prophecies. Firstly, the agent hypothesises a conclusion on future market expectations. Secondly, based on the agent's hypothesis the agent responds by changing their actions to meet expectations. Thirdly, changes to consumer actions support the agent's hypothesised conclusion forming a self-fulfilling expectation.
Key characteristics and examples of self-fulfilling expectations include:
- If for any reason each consumer expects no other consumer will join the market, then indeed no one will join as there will be no network benefits. e.g. Google+, Pixel
- If each consumer expects other consumers to join the market then everyone will join the market as there will be perceived benefits. e.g. Facebook, Spotify, Instagram
- Network effects may imply multiple equilibria, even if all consumers have rational expectations. Network effects create incentives to ‘herd’ with others. Therefore, beliefs based on the rational actions and behaviours of consumers implies equilibria for both outcomes. Both beliefs will then decide the size of the market that the firm is operating in. A definite equilibrium only arises when it is possible to manipulate the population's beliefs.
- More thoughts about how consumers making rational decisions: Consumers consider all the options available to them. Then consumers think the outcome of all these choices and how advantageous each outcome would be. They consider the probabilities associated with each of these options. And then they make a decision.
Critical Mass[edit | edit source]
All new businesses need to attract enough customers to become profitable before their money runs out. New companies face a chicken-and-egg problem. The major challenge for most aspiring platforms is to get enough agents on each side to secure the critical mass necessary to ignite indirect network effects and drive growth. Expectations depend on many factors such as quality of the product, price (stand alone and in comparison to competitions), reputation (stand alone or umbrella e.g. Apple launches new products under the umbrella), advertising and growth path of potential networks. However, the launch of Apple Pay shows how hard it can be for even sophisticated firms to attain critical mass. This is because most consumers didn’t have the new iPhone at first, leading to limited demand to use Apple Pay. This gives merchants little reason to acquire the new terminals and promote the use of Apple Pay. Since consumers thus couldn’t use Apple Pay at many merchants, even early adopters had little incentive to use it. 
- In the early phases of a new network technology incentives to adopt the technology is low, therefore, adoption is a dominated strategy.
- However, some consumers might adopt the technology anyway with an optimistic outlook.
- Once the technology gains traction and has a sufficient user base then adoption becomes a dominant strategy.
- After this tipping point or threshold, more consumers adopt. The benefit of adoption increases and thereby a very quick conversion to a high adoption equilibrium.
- The threshold or tipping point where adoption of new technology becomes a dominant strategy is called the critical mass.
Advertisement is one way to reach the "chain reaction" of people, which can quickly spread from person to person and then form people's perception of product. For example, DiDi launches its app into the Australian market which distributes vouchers weekly and rewards users who invite friends to download the app. This strategy can spread influence and attract more new users to join. Another way is to create an image of advertising that many people are using it, so this can increase potential users perceived "total effect" utility of joining that network and therefore increase the likelihood to join it.
Existing market size plays an important role here. If you are powerful network and have more users, it makes easier for the users of the other network to connect your network. The question is which different tool technologies you use that allowing or accommodating people to convert their files and contents. It depends on the market size. e.g If you want to build a bridge between large firms with 900 million people and small size networks have 100 million users, large firm would have lower incentive to build this bridge as it only can assess additional 100 million users. Small firm would get frustrated because of lack of connectivity.
How can firms reach a critical mass of consumers quickly?
Firms can try a range of strategies. Some of these strategies are risky as the critical mass may never be reached.
- Charge low initial prices. (Didi and Ola rideshare). Lower prices will entice users to switch from their existing platforms to the new platform. Consumers are particularly sensitive to prices and if their switching costs are low (e.g. for rideshare) the likelihood is that offering a lower price for the same service will encourage people to switch. An example would be when Spotify first started, where prices were below $10/month, which has been steadily increasing
- Give discounts to early adopters. (Didi and Ola rideshare). Price-sensitive users more likely to switch as a result of the discount as well as encouraging early adoption of the platform by rewarding them. Thus allowing the platform to gain more members at an early stage and reach critical mass. Example of ride-sharing firms such as OLA, gives early adopters discount codes and individual drivers additional monetary benefits.
- Conduct large marketing campaigns (e.g. AirBnB). Through the use of referral marketing an organisation may be able to conduct a large marketing campaign, reaching the maximum amount of individuals in their target market. This process is simple and can be incentivised through discounts as shown through AirBnB. The degree of separation is needed to explain the number of steps needed for referral marketing. It refers to the number of social connections required to connect one person with another. In 1929, it was postulated by F. Karinthy that every person is connected by six degrees of separation or less.
- Provide a single user value. User benefits from adopting the product even if there are little to no adopters such as having content for that single user. An example would be Twitter, even when no one is "online", there are news updates providing single user value.
However, it is important to note that some of these strategies are risky as there is no guarantee that critical mass can be reached and the cost of those strategies will be lost. Even when critical mass is reached, there is the possibility you will be unable to exert market power due to competitors or regulations, in which case the venture still results in a loss. 
In most standard economic models, any historical background is typically ignored since, in many cases, forces of supply and demand outweigh the effect of historical events and render idiosyncratic events to be transitory. In other words, history is neglected because it is often overshadowed by supply and demand variables. In reality, path dependence is a phenomenon where network externalities have a significant impact on the outcome. For example, consider whether the English language is the lingua franca (common language) of the modern world because it is the “best” (easiest to learn/speak, most beautiful, etc.) language. It could be argued that rather than English being the “best” in any way, instead, path dependence had a hand in elevating the popularity of English as early adopters influenced subsequent speakers to choose English due to convenience.
Path dependence can be illustrated with an example which considers competing technologies A and B, with consumers arriving at the market sequentially to choose one technology to adopt. Each consumer may prefer one over the other; however, all consumers would prefer the technology that has attracted the most user base thus far. This means that if both technologies have an equal number of adopters, then the consumer would choose according to their personal preference, but when one technology as amassed a larger user base over the other, then consumers would start to deviate towards that technology. As consumers are deciding sequentially, each subsequent consumer’s choice would be affected by the choices of all previous consumers’ choices before them. As such, the resulting user bases of each technology are path dependent. Each subsequent consumer reinforces the choice of consumers before them, and eventually, the industry is locked-in on one technology. Whichever technology the majority chooses may not necessarily be the better choice – if consumers that prefer the inferior technology are over-represented in the early adopters, then path dependence results in the industry being locked-in to the inferior technology.
Connectivity and Compatibility[edit | edit source]
Network externalities is used to describe how the effect of more or fewer people using a product or service, effects those that are already using the product. Positive externalities inferess that there is a positive relationship between marginal utility and amount of people using the network. While negative externalities represent a negative relationship between amount of users and marginal utility. It is often found that the magnitude of the network externalities is dependant on how alternative or competing networks are connected.
When externalities are strong, it is beneficial for the product or service to be more compatible and be able to connect easily to increase the utility provided by the product. This intuitively then increases consumer value. However, it is possible for consumer value to be reduced in the case when one a large network with substantial power eliminates the ability to connect or be compatible. This is beneficial for the company, increasing market power and dependence in their product while forcing the hand of consumers to purchase with the largest network. Only with complete connectivity is it difficult for anyone provider to dominate the market.
This relates to the ideology that smaller networks benefit much more in connecting with other networks than those that are substantially larger. The larger networks witness diminishing incentives to connect with smaller networks.
Compatibility[edit | edit source]
Often, compatibility decisions will be made during the early stages of an industry. However, in these early stages firms are not established in the market and do not have concrete information on their current or future market share. Subsequently, firms need to make decisions on the compatibility of their products on the basis of expected market share.
Here they must make a trade-off:
- Incompatibility: If the firm expects to dominate the market, they decrease the compatibility of their products as compared to their competitors' products and expected profits are defined by 1/2 x πm + 1/2 x 0. The equation describes that there is 50% probability of earning monopoly profits and gaining all the market share and a 50% probability of losing all market share and earning 0 profits if consumers prefer competitors' products.
- Compatibility: If the firm expects to share the market, they ensure their product is compatible with its competitors products and each gets duopoly profits: πD. Where they share the market share equally and earn equal profits if cost functions are the same. But compatibility often intensifies competition and nullifies the competitive advantage of a large installed base, whereas proprietary networks tend to make competition all-or-nothing, with the advantage going to large firms, and may completely shut out weaker firms. So large firms and those who are good at steering adopters’ expectations may prefer their products to be incompatible with rivals and may be able to use their intellectual property to enforce this.
Compatibility vs Incompatibility[edit | edit source]
There is no need for consumers to buy from the same firm if the firm offers compatible products. This means that consumers are still able to experience the full network benefits when they purchase the compatible product from a different firm.
Consumers, willingness to pay increases substantially when these benefits are available and can be a determining factor in why firms choose compatibility. However, there are disadvantages of firms using compatibility as competition increases and the competitive advantage of firms is removed.
Proprietary networks entirely exclude weaker firms and the advantage is given to the large firms. Therefore, firms of a larger scale who are able to adjust and influence consumers' expectations benefit from selling products that are incompatible with rivals. Incompatible networks are affected by different forms of competition including;
Incompatible networks are reliant almost solely on how consumers form their expectations along with how they coordinate their choices. This means that competition under these circumstances is unusually fierce due to all-or-nothing competition counterbalancing horizontal differentiation. Additionally, incompatibility suggests consumers are exposed to a segmented market that has low network benefits.
Multi-sided Platforms[edit | edit source]
Multi-sided platforms (MSP’s), also known as matchmakers, are technologies, products or services which create value by coordinating agents and allowing them to interact directly with each other. MSP’s reduce the transaction costs/economic friction which would otherwise make productive and efficient interaction impossible.
Broadly speaking, a Multi-sided Platform is one in which:
- Two (or more) sets of agents interact through an intermediary or platform, and
- The decisions of each set of agents affect the outcomes of the other set of agents, typically through an externality.
Consumers participate in Multi-sided Platforms every day, such as:
|Activity||One Side||Second Side||Platform|
|Using a credit card to make a purchase||Store (Coles/Woolworths)||Consumer||Visa/MasterCard/American Express|
|Making a search on the internet||Advertiser||Consumer||Internet search engine (Google/Bing)|
|Using social networking sites||Advertiser||Consumer||Networking site (Facebook/Twitter)|
|Using dating sites||Potential partners||Consumer||dating sites (match.com.au/rsvp.com.au)|
|Using discount sites||Merchant||Consumer||Discount site (Groupon/LivingSocial)|
|Using a smartphone||App Developer (Angry Birds/Lonely Planet Guide) Also the smartphone producer (Samsung/Apple)||Consumer||Operating System (iOS/Android/Windows)|
Most of these platforms are created and operated for profit by private firms. For example, in exchange for hosting web searches, Google receives ad revenue and Apple receives a cut of app sales in exchange for providing the app store and iPhone operating system.
There are instances where the removal of economic frictions and transaction costs due to MSP’s have created opportunities for new economic agents. For example, before Android and iOS there was no market for smartphone app developers as they had no financially viable option to advertise, sell or distribute their apps from. The widespread adoption of these operating systems has since removed these transaction costs and has enabled the emergence of app developers as economic agents. Further examples of this can be seen in the gig-economy (described below) which has recently grown exponentially due to smartphone and communications advances opening numerous new possibilities. 
Multi-Sided Platforms are similar to markets with network effects, often one or both side of the market exhibit direct network effects. Direct network effects arise if each user’s payoff from the adoption of a good, and his incentive to adopt it, increase as more others adopt it; that is if adoption by different users is complementary. For example, telecommunications users gain directly from more widespread adoption, and telecommunications networks with more users are also more attractive to non-users contemplating adoption.
There are two major distinctions:
- In Multi-sided Platforms, the role of the intermediary/platform is crucial
- Two sided markets are characterised by indirect network effects
A good exhibits an indirect network effect if demand for the good depends on the provision of a complementary good, which in turn depends on demand for the original good. Indirect network effects arise if adoption is complementary because of its effect on a related market. For example, users of hardware may gain when other users join them, not because of any direct benefit, but because it encourages the provision of more and better software.
Consumer Welfare[edit | edit source]
Multi-sided Platforms are faced with catering for the interests of all interdependent parties that the service hosts. The platform must find the balance of these interests to not only ensure consumer welfare but to maximise their own profits. A search engine such as Google, for example, will typically host and manage the interactions between three parties:
- Publicly available websites that have been indexed and are available through the engine;
- Individuals using the search engine to find the websites; and
- Firms looking to advertise on the platform. Google’s primary source of income comes from the third party, search related advertisements. Search engines will generally charge on the pay-per-click model, forcing the search engine to provide the best possible exposure for their customers.
Put simply, the more accurate a search engine can pinpoint the target market, the greater the value for advertisers. However, the issue of consumer welfare arises when the balance of the interests of interdependent parties is skewed. If Google were to give advertisers too much exposure on their platform in an attempt to increase profits over the short-term, it is likely that the other two parties would be negatively affected. Individuals using the search engine would become frustrated at the increase in advertising inhibiting their experience with the service and would potentially switch to a competing search engine. As a result, the exposure received by the indexed websites would decrease. This example provides an insight into the importance of balance of interests that MSPs must consider between the parties the platform serves. The coordination between agents that a platform offers also creates a delicate relationship that must be addressed accordingly if a MSP is to ensure profit-maximisation.
Evans, D. & Schmalensee, R. (2018) Multi-sided Platforms, The New Palgrave Dictionary of Economics, Macmillan Publishers Ltd, pp. 7.
Instructive Example[edit | edit source]
An instructive example of a multi-sided platform in the US based company OpenTable. OpenTable serves restaurants and consumers across the U.S. and in other countries. It allows consumers to make and restaurants to accept reservation over the Internet. The purpose of this company is to solve a transaction problem between consumers and restaurants. In the U.S. this transaction problem is present because telephone calls is the most common and widespread method of setting reservations.
OpenTable has several features that are prevalent among multi-sided platforms. Firstly, OpenTable provides a platform for interactions between two unique groups of agents: consumers and restaurants. Members of each group gain utility from interacting with members of the other group underlies the indirect network externalities present. This also highlights the opportunity for an entrepreneur to create a platform and generate profit by reducing transaction costs.
Secondly, OpenTable has three varieties of indirect network externalities:
- Usage Externality: Both consumers and restaurants benefit when each other uses the platform to make a reservation.
- Membership Externality: The platform is more valuable to consumers the more restaurants access it and vice versa.
- Behavioral Externality: Unlike most single-sided businesses, OpenTable punishes conduct violations of their platform if it impacts other users. Eg. a 12 month ban from the platform is imposed if consumers fail to show up for four reservations.
Thirdly, as common with match making services OpenTable’s price structure involves a ‘money side’ (which pays more than marginal cost) and a ‘subsidy side’ (which pays less than marginal cost). OpenTable offers the platform to be used by consumers for free. Whereas restaurants are the money side and must license OpenTable’s management software and pay a fee for every patron they seat through OpenTable. That is, they pay a fixed access fee and usage fee.
When a single sided firm sets a price below marginal cost it is usually indicative of a possibility of predatory pricing. OpenTable’s multi-sided platform allow a below marginal cost price to be set for one side as the other side can accommodate for the loss. Therefore, correct pricing must consider both sides of the platform. This has considerable consequence for competition policy authorities. Multi sided platform mergers are considerably more dynamic than single sided mergers due to the complexities of establishing Pareto equilibrium.
Pricing[edit | edit source]
Pricing in two sided platforms is more complex than in single sided businesses. Single sided firms demand functions depend on the prices of its products and the prices of complements and substitutes. For multi sided platforms, the demand for one side is dependent on the number of members of the other side of the platform. Consequently, the sides are complements in demand.
Pricing for multi-sided platforms is more elastic compared with a single sided business. This is demonstrated in the following scenario. A platform has sides A and B. An increase in price to A-type customers will reduce the number of A’s on the platform. Since B-type customers derive utility from accessing A-type customers, the number of B-type customers will fall. This begins a virtuous cycle as now the demand of A’s will fall again due to there been fewer B firms. Therefore, the ability to change prices of multi-sided platforms is difficult and complex due to the feedback loops.
Gig-Economy[edit | edit source]
The gig-economy can be described as the increasing preference towards individual work operating from task-to-task, and the overall increase in contribution into the collaborative consumption/sharing economy where individuals abandon the usual 9 to 5 workweek, in favour of flexible and autonomous work for a variety of employers .
|Package delivery||Amazon Flex|
|Ride-sharing||Lyft, Uber, Didi|
|Peer-to-Peer accommodation||Airbnb, One Fine Stay|
|Car-sharing||Turo, Car Next Door|
|Food delivery||UberEats, Menulog, Deliveroo|
|Peer-to-Peer task assignments||TaskRabbit, AirTasker|
The Gig Economy is also known as the Freelancer economy, Sharing economy, or Independent workforce. In the general labour force environment, tempory engagements, short-term contracts and individual contracting are also widespread.
Multi-Sided Platforms e.g. DiDi, Uber, AirBnB and AirTasker are examples of application developers harnessing the popularity of the online gig-economy and allowing autonomous agents to use their platforms to seek a service or to create an income. Taking the US for example, 36% of the U.S. workforce or 57 million people freelanced in 2016. Furthermore, by 2020, it is estimated that 7.6 million Americans will be working in the gig economy. The main difference between gigging and freelance is that a freelancer is an independent worker who essentially runs their own business, whereas gig workers are classified the same way as freelancers, but they don’t run their own business, it is usually mediated through a specialised app or platform. This raised concerns as these firms tend to view workers as 'independent-contractors' rather than 'employees'. This encourages firms to neglect the rights of these individuals in the context of their relationship with the business.
On a global scale, by 2025, some supply-side estimates propose the online gig-economy could raise global GDP by $2.7 trillion and increase global employment by 72 million, highlighting the expected continued expansion and increased importance of the industry .
The gig economy can be risky to markets and the economy structure in general. In short there is a level of skill loss, high rates of underpaying of wages and superannuation and loss of bargaining power especially in the wages sector.
Transaction Costs[edit | edit source]
Transaction costs are the expenses in the market when buying and selling goods and services. Transaction costs are the necessary labour required by goods and services in the market. In other words, a transaction cost is the additional cost on top of what someone is paying for a good or service, for example the commission that a real estate agent receives when they sell a house. The presence of transaction costs has created entire industries that facilitate for the transaction cost elements in exchanges.
A multi-sided platform reduces transaction costs by enabling direct interactions between participating parties. Multi-sided platforms lower information and search costs and reducing other transaction costs associated with market interaction. By eliminating such costs, these platforms can create opportunities for the entry of new economic agents, such as the aforementioned app developers for smartphones .
Reducing Transaction Costs [edit | edit source]
So how does a platform reduce transaction costs? By playing the role of matchmaker, platforms attempt to match buyers with sellers. This can be done through advertising media which matches potential sellers with potential buyers. Further, platforms can work to create economies of scale and reduce duplication costs. We see this in shopping centres (malls) , where the centre provides common amenities such as, toilets, public transport hubs, parenting rooms, kids play areas and carparks, along with the overarching synergies of co-locating multiple shops for the convenience of the consumer. The cumulative effect of this structure is to provide the shopper with a more convenient experience which keeps them in the centre for longer and improve the chances of spending with a given shop, which might otherwise not have occurred. Further, by providing other services such as a food court, entertainment hubs such as the cinema and supermarkets all under one roof, it encourages consumers to spend more time and money at the mall.
An example of platform playing the role of match-maker is when eBay matches potential consumers with related products that the consumer might be interested in.
Strategies for the Platform: Starting Up[edit | edit source]
Knowing where to begin when creating a new platform is a complex and critical issue. Platform creators are tasked with harmonizing both sides of the market within their platform. We can categorise potential strategies into design decisions, rules and regulations and pricing.
The Chicken and the Egg[edit | edit source]
Similar to the network effect, the chicken and the egg dilemma gives an insight into how consumer behaviour can affect patron attraction strategies for creators. The chicken and the egg problem posits that if one individual joins, then the other individual will also. Meaning that the platform will need to coordinate so that both join at the same time if the platform is to be successful. The window for both parties to join can be quite small depending on the industry. In particular, technology becomes outdated within a few years, so adoption much occurs rapidly. This is akin to what we observe with network effects and the value created when others join the network. When platforms are successful, we see that these network effects create great profits.
The chicken and the egg dilemma gets its name from the age old philosophical question, “Which came first? The Chicken? Or the Egg?” First documentation of this dilemma can be traced back to 1st century CE, when Greek philosopher Plutarch introduced the question in his essay “The Symposiacs.” As the name suggests, the question arises from the puzzling issue that only chickens can lay chicken eggs, and every chicken must hatch from a chicken egg, so where did the first egg come from? Chicken and egg has now become a common metaphorical adjective for any situation in which a sequence of cause and effect is not obvious. 
Example:[edit | edit source]
Of course, the chicken and egg problem is common in that of start-up companies and an anchoring source is needed to kick start most platforms so they are able to reach the critical surviving mass. This problem is faced by start-up company “Stitch”. Stitch is an online platform for people over 50 years of age to meet lifelong friends and companions. The company’s business model relies on the network effects of adults attending local community events, groups and activities set up by Stitch to meet friends with similar interests. Of course however, people will not go to community events that aren’t well established and no one attends. Stitch addresses this problem by hiring temporary community ambassadors to attend events, hatching the eggs to increase the network of chickens, so Stitch has popular events for people to attend with no time lag in the reputation and success of events. 
Other Possible Strategies:[edit | edit source]
· Targeting segments of the market including single independent users or small niche areas.
· Discounting, sign-up bonuses/registration perks and money-back guarantees/warranties.
· Increased marketing presence to shift consumer expectations.
· Beginning in a small local market and gradually scaling up production.
These strategies all aim to generate conversation and interaction with the platform to create a consumer base and involve both sides of the platform.
Although there are many failures, platforms that succeed become very profitable due to network effects.
Strategies for the Platform[edit | edit source]
|Design Decisions||Rules & Regulations||Pricing|
|Facilitating interactions||Regulating interactions||Determine relative prices|
|Get customers on board||Prevent negative externalities||Access prices and variable fees|
|Escalators on opposite sides||Rules on eBay||Credit Card Fees|
Pricing[edit | edit source]
Pricing in two-sided platforms is more complex than in ordinary multi-product businesses. For single-sided firms, demand depends on the prices of its products as well as the prices of complements and substitutes. For multi-sided platforms, the demand by one group of economic agents also depends on the number of (or, more precisely, measures of the expected value of potential matches with) members of each of the other groups that the platform serves. Loosely speaking, the sides are complements in demand. (Ad-supported media typically require a different analysis because advertisers value more users, but users don’t necessarily value more advertising.)
In a multi-sided platform, demand is interdependent.
For multiple-sided platforms, the demand for one group of economic agents depends on the number of members of each of the other groups that the platform serves.
Mathematically this requires solving two equations with two prices (, ) simultaneously. The price on each side/product is dependent on the price and marginal cost of each side and the indirect network effects on each side.
The price for each side depends on:[edit | edit source]
- The optimal prices depend in a complex way on:
- The prices elasticities of demand on each side
- Marginal costs that result from changing output of each side
- Indirect network effects between each side
- The profit-maximizing prices for one side can be lower than the marginal cost, or even negative
Low price on one side leads to more customers on the other side who pay enough to offset the loss.
- One side subsidies the other side
- Such as free newspapers, credit card markets or even social networks
- This behaviour is the consequences of "the Seesaw principle" - A factor that is conducive to a high price on one side, to the extent that it raises the platform's margin on that side, also tends to call for a low price on the other side as attracting members on that other side becomes more profitable.
Feedback effects (with positive externalities)[edit | edit source]
Assume a platform with side A and side B. And it has already established prices to both groups and is considering changing them.
- A price increase in side A will decrease the number of customers for A
- Decrease in side A customers leads to reduction in demand from side B
- Reduction in demand from side B leads to a lower demand from side A
- Which in turn leads to an even more decrease in demand from side B, and so on
There is a feedback loop between side A and side B. Once this is taken into account the effect of an increase in price on side A(or B) is a decrease in demand on the side A(or B) because of the direct effect of the price elasticity of demand and on both sides as result of the indirect effect from the externalities.
This multiplier effect makes the demand more elastic on each side of the platform, and the profitability of a price increase is lower
Pricing Strategy[edit | edit source]
A pricing strategy is a method or model used to determine the best price for a product or service. Different pricing strategies help business owners select prices at which profit and shareholder value are maximized while looking at the consumer and market demand. Price Elasticity of Demand, the degree to which a change in price affects consumer demand, is an important pricing concept that will apply in various pricing strategies:
- Elastic - If the customer will switch to alternatives when there is an increase in the price of product or service and vice-versa. Occurs where there are low levels of differentiation and a variety of substitutes (e.g. confectionery/chocolates, industrial goods). Consequently, elastic goods are materially affected by pricing fluctuations;
- Inelastic - If the customer's demand for a good is largely unaffected by price increases, their demand for the good is considered to be inelastic. This often arises in the context of goods which are considered essential or for which there are few/no substitutes (e.g. petrol and tap water);
The price elasticity of demand formula: percentage change in Quality/percentage change in Price
In many markets platforms charge only one-side of the market:
- e.g. eBay only charge a fee to seller, Google(search)and Facebook only charge advertisers
How do platforms decide on which side to charge?
- Price low to the side that is "needed the most" or is "hardest to attract" (with more elastic demand)
- One side subsidising the other side.
Which side? It is easy to say ex-post but not so clear ex-ante.
Two-part tariffs play an important role: membership(access) charge and usage charge (based on interactions) The video games industry provides a clear example of this, as platforms charge fees for development kits sold to video game development and royalties for each game sold. Additionally, platforms also charge users for each console sold.
-negative usage fee (miles, bonuses)
- Affect future usage, hence the positive externalities between the two sides.
- Might be desirable if interactions between the two sides are not observable by the platform (dating sites)
Dynamic pricing issues:
- Penetration pricing, such as when an intermediary lowers price early in the product life cycle and raises it after having established a base, is a natural outcome in Multi-sided Platforms.
- Leakage occurs when users who meet in the platform start to transact outside it
- This is usually done by building a relationship between the two parties and avoiding charges they experience by transacting on the platform versus transacting personally
- The two parties may initially meet on the platform but subsequent transactions take place outside the platfor. For example: A platform for finding babysitters may connect a babysitter and a parent allowing them to conduct an exchange. However, after the initial service, the babysitter may provide their personal contact information to the parent for future transactions. Assuming the parent is satisfied with the service provided by the babysitter, they would then contact the babysitter using the babysitter's personal contact information rather than using the platform which initially connected them. In this way, the platform becomes obsolete and the babysitter avoids any charges the platform would have otherwise imposed.
- Due to leakage, there is limited repeat use of the platform and there is a constant need to attract a constant stream of new users (both parents and babysitters) in order for the platform to remain useful
- Platforms can prevent leakage by taking advantage of economies of scale that individuals transacting outside the platform do not enjoy. For example, the platform may provide a basic insurance cover to all babysitters when working at a job conducted via the platform. Thus encouraging users to continue using the platform and reducing leakage. Switching costs can have a significant effect in stopping leakage. If someone has built a substantial reputation on a platform including a network of contacts, it may be difficult to leave. The time and effort investment of building the reputation cannot be recouped.
Single/Multi Homing[edit | edit source]
One of the key competitive aspects of multi-sided platforms is the extent to which economic agents engage in what they called single-homing or multi-homing. An economic agent single-homes if she uses only one platform in a particular industry and multi-homes if she uses several. In the case of payments, consumers and merchants both generally use several payment platforms and therefore multi-home. Definition: The use of multiple platforms to overcome incompatibility strategies by platforms. Examples:
- Many retailers accept both Visa and Master Card.
- Video game users purchase more than one console or developers make games for all platforms.
This ensures that customers ‘meet’ in the platform and do not transact outside the platform.
On the other hand, platforms can try to prevent multi-homing by: 1. Limit transfers: Facebook trying to prevent users from “exporting” their profiles to other networking sites. 2. Loyalty schemes: Payment cards use rewards programs to encourage exclusive usage on the part of consumers. (Example: A bank gives reward points to customers of the bank when they use the bank’s card and these points can be used to redeem goods like TVs, mobile phones, home appliances and many more) 3. Exclusive contracts: Game console manufacturers will sometimes contract with developers to write exclusive games. (Example: The HALO franchise is available exclusively on Microsoft’s Xbox consoles, therefore if customers want to play HALO, they would have to purchase an Xbox)
Human Capital and Knowledge[edit | edit source]
Human capital is stored as neural connections in the brain. It is, in essence, the skills and knowledge a person has that can be used by an organisation to reach targets and goals. Human capital is important in order to be innovative and competitive across the market. Often times it's this capital that allows organisations to create revolutionising innovations.
- Rival and excludable: it means that people this information good has the properties of being exhaustive and excludability. A person's human capital is fully excludable as long as people have legal control over their bodies.
- An input to produce new ideas or knowledge: this information or knowledge good can be used as as inspiration or input into developing or creating new outputs into the real world. Intangible assets where not everyone has the same skill sets or knowledge. This is normally the spark towards research and development.
Knowledge is produced using human capital and codified in books and the internet is a nonrival good
- If there is no legal protection that prevents sharing ideas then knowledge is also nonexcludable
Human capital → Knowledge → Human capital round trip:
- A person reading a book increases their own human capital, and through research can create new knowledge that increases someone else's human capital.
Invention (Discovery or production of new idea) → Installation (normally commercialisation into the real world) → Diffusion (Marketing, distribution, absorption and adoption of the innovation)
- Human history is full of successful efforts at scaling up the knowledge round trip. The adaptation of speech allowed humans to convey their ideas to others in the vicinity. Printing presses allowed for a permanent transfer of knowledge without the presence of the initial person. The internet, while similar to printing presses, does so on a much larger scale.
- Are there limits to human ingenuity? If not, (infinite) progress is possible.
- This infinite progress allows for human capital to constantly innovate new products or technology. Human capital in forms of group production allows knowledge sharing between human capital, allowing for potential to innovate. These intangible assets of human capital are a resource firms tapped into for future growth as overtime, knowledge in human capital becomes experience which is invaluable for a firm.
Asymmetric Information[edit | edit source]
Asymmetric information occurs when one party of a transaction knows more about the characteristics of the good or service in question than the other. Asymmetric information can lead to inefficiencies in markets, as exemplified within the "Lemons Model" which demonstrates how asymmetric information can lower the average quality of goods for sale in particular markets. The second-hand car market is usually used to describe the Lemons Model as buyers of second-hand cars know less about the characteristics of the car than the seller, for example how well it was looked after and crash history. Due to this and the risk of buying a below average car (a lemon), the buyer often lowers their reservation price. At lower prices people with good cars no longer wish to sell, this leads to only people selling poor cars (lemons) to sell, lowering the average quality of the good.
|1. Information Asymmetry||Both||Parties negotiate with an imperfect balance of information. Often the seller will have greater knowledge of the goods /history|
|2. Risk Aversion||Buyer||Buyer reduces their reservation price/willingness to pay due to concerns of over-paying and lack of trust.|
|3. Undervaluation||Seller||Lower prices resulting from information asymmetry prompt sellers to leave the market due to perceptions of undervaluation|
|4. Market Inefficiency||Market||The average quality of goods deteriorates as only poor goods (lemons) remain on the market for transaction|
- Adverse Selection (before contractual clause) Adverse selection occurs when an individual holds the upper hand in the knowledge based market and uses it to his/her advantage, allowing them to exploit the less informed party. This action tends to cause a decrease in the quality of the said goods or service in the transaction. An example would be in automotive sales, car salesman have the tendency to make a sale where they have the chance to acquire the highest commission for themselves and not the the upmost interest of the consumer needs. This reflects the difference between the informed and the uninformed. which can be further explained in principal agent problem.
- Moral Hazard (after contractual clause) A moral hazard in information economics the propensity in an individual to alter their precursory behaviour or mentality post legalisation of a contract. A simple example would be for a driver to have the tendency to be more reckless after the employment of car or health insurance. As they have 'less to lose' after the initiation of the insurance.
Principal Agent Problem[edit | edit source]
This is another inefficiency which can arise from information economics. This problem is when the agent makes decisions which do not lead to the best outcome for the principal. This occurs when an agent's incentives are not aligned with that of the principal and their actions are costly to monitor. For instance, in a publicly listed company the shareholders want to maximise profits whereas the managers running the company want to maximise their own wages.
What is Economics?[edit | edit source]
One of the most common definitions of economics is a study of the allocation of scarce resources (limited resources). Subsequently, economics is a study of how people make choices when facing the economic problem (limited resources versus unlimited wants) and of the results of those choices for society.
However, in relation to information, scarcity isn’t as relevant as opposed to other goods. The world has an abundance of information and ideas, a culture of sharing and cooperation, open access and open source, which increases the public good of knowledge.
Therefore, the resource that is scarce in the information economy is attention.
Economics of Attention[edit | edit source]
The supply of information grows exponentially due to the open access and open source of information and ideas whereas the amount that is consumed grows linearly. Attention economy treats human information as a scarce commodity to solving information management problems by applying economic theory to solve various information management problems. Put simply by Matthew Crawford, "Attention is a resource and a person has only so much of it". Attention becomes the limiting factor in the consumption of information. Attention is the necessary tool used to filter important information by the human brain from the abundance of information available to us. This is of major importance since low-quality information can cause difficulties for providers of high-quality information.
Herbert A. Simon was the first person to conceptualise the idea of attention in an economic model. One of his quotes read, "wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it." (Simon 1971, pp. 40–41)
The problem within designers of information isn't information scarcity but rather attention scarcity, where systems designed to provide large amounts of information failed lacking measures put in place to filter out what is unimportant or irrelevant information. This paradigm of information overload gives rise to the “Law of Surfing” wherein the likelihood of a user exploring a specific information source diminishes as the total number of sources increases. This emphasis on attention creates opportunities for companies able to organise and/or curate the vast body of information tailored to the needs of the individual. This is most aptly represented in the context of Google, YouTube and Spotify, services which create value for users by respectively sorting search results, videos and music according to the preferences of the individual user. On the other side of this value chain, by providing these organisational/curation services, the platform is able to mine valuable data for consumer preferences and broader market demands. Both of these insights can be profitably sold or deployed to further enhance services, sell targeted advertising and create tailored value-added products.
Summary[edit | edit source]
The below section aims to briefly summarise the key takeaways of the topic:
Information Economy: an economy based on the effective dissemination, acquisition, and use of information, rather than on the means of production.
Information Goods: a type of commodity whose market value is derived from the information it contains (i.e. music, movies, books, etc.), which are in contrast to material goods (i.e. clothes, cars, foods, etc.). The 3 main properties of information than cause difficulties for market transactions:
- Experience Good: you must experience an information before you know what it is.
- Returns to Scale: high fixed (and typically sunk) costs of production, however low marginal costs of reproduction.
- Public Goods: information goods are non-rivalrous and sometimes non-excludable commodities or services (i.e. lighthouse, national defence, streetlights, etc.) provided without profit to all members of society, by governments or private individuals/organisations.
Network Effects: a phenomenon whereby the value of a product or service increases due to an increase in the number of others using it.
Consumer Expectations: information attained through reflections on both past and current user experiences and product evaluations that provide consumers with the ability to evaluate value and quality and give products and services the ability to meet consumer needs and expectations.
Critical Mass: a point at which a growing company no longer requires additional investments to remain economically viable as they have become self-sustaining. Threshold or tipping point where adoption of new technology becomes a dominant strategy.
Multi-sided Platforms (MSP): products, services, or technologies that create value primarily by coordinating agents and enabling direct interactions between multiple participant groups or customers. Reduces economic friction and transactions costs to overcome barriers to productive and efficient interaction.
Gig-Economy: a general workforce environment in which, independent contracting, short-term engagements and temporary contracts are commonplace. Also referred to as a 'sharing economy', 'freelancer economy', 'independent 'workforce', or 'agile workforce'.
Transaction Costs: costs incurred by market participants when engaging in economic trade. Transaction costs reduced by MSP's that lower information and search costs and other transaction costs associated with market interaction by enabling direct interaction between participant groups.
Strategies for the Platform - Starting Up: Starting up a new platform is a highly complicated issue requiring both sides of the market to be brought into the platform. Difficult to determine what strategies to use in order to get the platform to reach critical mass.
Pricing Strategy: methods through which firms set their prices in order to achieve certain goals or targets, such as; maximising profitability for each unit sold, defending existing markets from new entrants, entering new markets or increasing market share.
Single/Multi Homing: the practice of economic agents engaging in the use of either single or multiple platforms within a particular industry.
Human Capital and Knowledge: the skills and knowledge an individual has stored in their brain as neural connections that can be used by organisations to reach goals and targets. Human capital is necessary in order to be innovative and competitive across the market.
Asymmetric Information: occurs when one party is more or better informed about a transaction than the other party. Asymmetric information can lead to market inefficiencies such as the 'Lemons Model'. Moral hazard and adverse selection are types of information asymmetry.
Reference/s[edit | edit source]
- Zhang, Yi-Cheng (2017-01-24). The Information Economy. pp. 149–158. ISBN 9783319424224. https://www.researchgate.net/publication/312597255_The_Information_Economy.
- Law, J., 2016. information goods. A Dictionary of Business and Management, pp.A Dictionary of Business and Management.
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- Ruffle, B.J., Weiss, A. & Etziony, A., 2015. The role of critical mass in establishing a successful network market: An experimental investigation. Journal of Behavioral and Experimental Economics, 58(C), pp.101–110.
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- AI Group, The Emergence of the Gig Economy, August 2016
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- Plutarch. (2014). Symposiacs. Retrieved from The University of Adelaide: https://ebooks.adelaide.edu.au/p/plutarch/symposiacs/complete.html#section15
- Dowling, A. (2019). About Stitch Ambassadors. Retrieved from Stitch Help Center: https://support.stitch.net/en/articles/3300683-about-stitch-ambassadors
- Bernardo A. Huberman and Fang Wu (2008) “The Economics of Attention: Maximising User Value in Information Rich Environments” Advances in Complex Systems 11(4) 487–496
- Chunlei Tang (2016) Business Models in the Data Industry in “The Data Industry: The Business and Economics of Information and Big Data” Chunlei Tang (Ed) pp 135 – 146.