воскресенье, 14 мая 2023 г.

Welfare economics II

 The analysis of welfare economics is built around the concept of Pareto efficiency. However, this efficiency criterion does not always represent a satisfactory answer. Other times, certain optimality conditions cannot be satisfied, and therefore Pareto efficiency simply cannot be reached. In order to solve this problem, and to find a new way to establish which allocation is best, economists have been since searching for new criteria to make a more informed decision.

In this Learning Path we’ll learn about some of these criteria, in order to understand them and being able to use them. In this LP we’ll learn about:

 Pareto efficiency, the cornerstone of welfare economics.

 Compensation criteria

Definition: what they are and how to use them. More precisely, we’ll talk about:

Kaldor’s criterionHicks’ criterionScitovsky’s criterionLittle’s criterion, and Samuelson’s criterion.

 Theory of the…

Second best, a theory by economists Kelvin Lancaster and Richard Lipsey.

Pareto efficiency


Summary

The analysis of welfare economics is built around the concept of Pareto efficiency. However, this efficiency criterion does not always represent a satisfactory answer. In order to solve this problem, and to find a new way to establish which allocation is best, economists have been since searching for new criteria to make a more informed decision. In this Learning Path we learn about some of these criteria.

his efficiency criterion was developed by Vilfredo Pareto in his book “Manual of Political Economy”, 1906. An allocation of goods is Pareto optimal when there is no possibility of redistribution in a way where at least one individual would be better off while no other individual ends up worse off.

A definition can also be made in two steps:

-a change from situation A to B is a Pareto improvement if at least one individual is better off without making other individuals worse off;

-B is Pareto optimal if there is no possible Pareto improvement.


This can be easily understood using an Edgeworth box. Starting from point C, two Pareto improvements can be made:

-from C to D: individual 1 would increase its utility, since a further indifference curve would be reached, while individual 2 will remain with the same utility;

-from C to E: individual 2 would maintain its utility while individual 2 increases theirs.

Once we are at point either D or E, no further Pareto improvements can be made. Therefore, D and E are Pareto optimal.

Following the same steps for every indifference curve, we can say that every point in which indifference curves from different individuals are tangent is Pareto optimal. The curve that links these infinite Pareto optima is called the contract curve.

Video – Edgeworth box:


Pareto efficiency is great, no doubt about it, but sometimes it is impossible to reach. That’s why we need other compensation criteria. Next, we’ll see a definition of compensation criteria: what they are, how they work, and what to expect of them.

Compensation criteria


In welfare economics, compensation criteria or the compensation principle is known as a rule of decision for selecting between two alternative states. Two states will be compared; if one state provides an improvement for one part but causes deterioration in the state of the other, it will be chosen if the winner can compensate the loser’ losses until they situation is at least as good as in the initial situation. However, this compensation may not necessarily occur.

This neo-Paretian concept was developed in order to solve the dead end in which the Pareto criterion was at the moment due to its limitations. Although, in essence, the compensation principle reduces to the Pareto criterion, it values positively a wider set that allows a positive ordering without transgressing the Pareto optimal.

To this day there has not been yet a unique and definitive compensation criterion due to its limits and some of its paradoxical implication; on the contrary, a great number of similar criterions have been formulated. From them we must highlight:

Kaldor’s criterionHicks’ criterionScitovsky’s criterionLittle’s criterion and Samuelson’s criterion.

Kaldor’s criterion


The Kaldor criterion is a compensation criterion developed by Nicholas Kaldor in his paper “Welfare Propositions of Economics and Interpersonal Comparisons of Utility”, 1939. This criterion is satisfied if state Y is preferred to state X and there is such a compensation and reassignment that Y turns to Yˈ that is at least as good as X in a Pareto sense. In the following graph we consider the utility of two individuals (A on the x-axis and B on the y-axis), which we will compare using the utility possibility frontier of two different moments. 


When moving from state X to Y, individual A’s utility decreases, while individual B’s increases. Individual B is willing to compensate individual A and move to Yˈ where both increase their initial utility. The opposite, moving from Y to X, can also occur if the winner, this time individual A, compensates the looser, individual B, and is willing to relocate to Xˈ.

When moving from state Y to Z, the utility of individual A decreases, while individual B’s increases. Individual B is willing to compensate individual A and go to Zˈ where both increase their initial utility. On this case the opposite, moving from Z to Y, would not be feasible.

Tibor Scitovsky pointed out some inconsistencies and the consequent limitations of this criterion which are known as the Scitovsky paradox. This paradox is centred in the phenomenon that while Y can be preferred to X the opposite can also be true, as it was previously explained. This does not give a truly asymmetric result as it could just mean that going back to the initial situation is preferred. Economy would therefore oscillate between both points.

Hicks’ criterion


The Hicks criterion is a compensation criterion developed by John Richard Hicks in his paper “The Valuation of the Social Income”, 1940. It is similar to that of Kaldor’s, with different implications although with the same limitations. In this criterion, state Y is preferred to X, if there is not a potential reassignment that turns X into Xˈ, that is at least as good as Y in Pareto terms. In the following graph we consider the utility of two individuals (A on the x-axis and B on the y-axis), which we will compare using the utility possibility frontier of two different moments. 


When moving from state X to Y, individual A’s utility decreases while it increases for individual B. Due to this, individual A should compensate individual B so the change of states does not happen, going from X to X’, which will increase B’s utility as much as going from X to Y, while the drop in A’s utility would not be as large. The same would happen if moving from Y to X. Since this ex-ante compensation is possible, neither X is preferred to Y nor Y will be preferred to X.

When moving from state Y to Z,  again individual A´s utility decreases while it increases for  individual B. When going from Y to Z, there is no possible compensation from individual A to individual B, since to the left of Y the utility possibility frontier is always higher. Individual A therefore can not compensate individual B, so Z is preferred to Y in Hicks’ terms. However, when comparing movement from Z to Y, the opposite logically occurs. Individual A’s utility increases while individuals B’s decreases. Individual B would compensate individual A going from Z to Z’ , and hence Y is not preferred to Z.

If we compare this with Kaldor’s criterion we see some significant changes but still both criteria fall under the Scitovsky paradox. This paradox is centred in the phenomenon that while Y can be preferred to X the opposite can also be true. This does not give a truly asymmetric result as it could just mean that going back to the initial situation is preferred. The economy would therefore oscillate between both points.

Some inconsistencies appear when using both Kaldor’s and Hicks’ criteria, known as the Scitovsky paradox. In order to solve it, we use what is known as Scitovsky’s criterion.

Scitovsky’s criterion


The Scitovsky criterion was developed by Tibor Scitosky in his paper “A Note on Welfare Propositions in Economics”, 1941, in order to solve the inconsistencies, -known as the Scitovsky paradox-, that Nicholas Kaldor’s and John Richard Hicks’ criteria presented. In order to solve these inconsistencies, he required the fulfilment of both criteria simultaneously. As an example, let’s analyse the following graph, where we consider the utility of two individuals (A on the x-axis and B on the y-axis), which we will compare using the utility possibility frontier of two different moments.


Kaldor’s criterion is met when going from X to Y, Y to X or Y to Z, but not when going from Z to Y. However, Hicks’ criterion is only met when going from Y to Z. Therefore, when comparing state Y to Z, winners can compensate the loss of the losers, but losers cannot compensate the other part in order to avoid the change. This is the only case in our example where the Scitovsky criterion is met, making Z preferred to Y.

Scitovsky considered the possibility of changes in Pareto terms caused by state changes. This justified the dual requirements. Analytically,


Although this criterion brings some positive contributions, there are still only minor changes that furthermore need to meet conditions. The estimation of a potential Pareto improvement is yet to be answered. Nevertheless, the Scitovsky criterion contributes to an intransitive organisation of different states

Little’s criterion


The Little criterion was developed by Ian M.D. Little in his paper “A Critique of Welfare Economics”, 1949, and it constitutes a further step for compensation principle theory. Little criticises the separation between efficiency and distribution and he demands as in Scitovsky’s criterion, for the Kaldor’s and Hicks’ criteria to hold. Furthermore, this criterion also requires that the income distribution is not worsened by the change of states.

This criterion however, brings some limitations, as a result of its implicit value judgement. The criterion will be met, if by a change of states the positively affected individual (winner) is poorer than the negatively affected individual (loser). As an example, let’s analyse the following graph, where we consider the utility of two individuals (A on the x-axis and B on the y-axis), which we will compare using the utility possibility frontier of two different moments.


Kaldor’s criterion is met when going from X to Y, Y to X or Y to Z, but not when going from Z to Y. However, Hicks’ criterion is only met when going from Y to Z. Therefore, when comparing state Y to Z, winners can compensate the loss of the losers, but losers cannot compensate the other part in order to avoid the change. This is the only case in our example where the Scitovsky criterion is met, making Z preferred to Y. However, Little’s criterion is only met if individual B is poorer than individual A.

Samuelson’s criterion


The Samuelson criterion, sometimes referred to as the Samuelson condition, was raised by the economist Paul A. Samuelson in his paper “Evaluation of Real National Income”, 1950, and belongs to the theory of welfare economics and used as a condition for the efficient provision of public goods. This critique provides a way to avoid intransitivity problems: state X will be preferred to Y if the alternative of X, X’, is preferred to the alternative of Y, Y’.

This criterion however, brings some limitations, since it is very similar to Pareto optimality. Samuelson explains that previous compensation criteria, such as Kaldor’sHicks’ or Little’s, hold just because they consider partial redistribution.

Now that we know everything we need about compensation criteria, let's learn about another way to avoid looking for Pareto optimality: Lancaster and Lipsey's Second Best theory.

Second best


Kelvin Lancaster and Richard G. Lipsey, in their article “The General Theory of Second Best”, 1956, following an earlier work by James E. Meade, treated the problem of what to do when certain optimality conditions (which must be considered in order to arrive at a Paretian optimum solution in a general equilibrium system) cannot be satisfied. The main idea in this article is that, when a constraint prevents the fulfilment of one of these conditions, the other conditions are in general no longer desirable. The optimum situation in this case can be attained only by neglecting the other conditions. Indeed, this new optimum is called “second best” because a Paretian optimum cannot be attained.


This can be easily understood using the diagram depicted in the article. We start by considering a typical optimization problem, with a given production possibility frontier (PPF) considered as a boundary condition, indifference curves (green curves, in this case representing a welfare function, ω) and the optimum where the PPF is tangent to ω (point P). Since this points lies on the transformation line and an indifference curve, it defines the production and consumption optima.

When we draw a new constraint condition (red curve), it can be easily seen that point P is no longer attainable. Q could be a second best solution, since it lies both on PPF and NewCC. However, as the authors point out, the second best point would be R, inside the transformation line. This is so because an improvement on welfare can be attained by moving to point R, since it lies on a further indifference curve (ω’’), and therefore means higher welfare.

The segment MN is technically more efficient than R, but since the points on this segment cannot be attained, R is the second best solution.

In this Learning Path we've learned about compensation criteria, used in order to avoid looking for Pareto efficiency when none can be reached. We've seen how Kaldor's and Hicks' criteria work well, except when Scitovsky's paradox appear. We've also learned about Little's and Samuelson's criteria, which keep in mind redistribution of wealth. Finally, we've seen how Lancaster and Lipsey's Second Best theory works.

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суббота, 13 мая 2023 г.

Search Advertising Spend Trends for 2023

 Global advertiser spend on search marketing is expected to be robust this year, despite a broader digital ad market slowdown, according to recent research from WARC.

The report was based on advertising data from organizations around the world, as well as survey data.

The researchers forecast ad spend globally on traditional search (excluding retail platforms) will increase by 6.2% year-over-year in 2023, reaching $256.5 billion.

More than half (56%) of marketers globally expect to increase their overall search spend this year. Some 53% expect to increase their spend with Google, 76% plan to increase their spend with TikTok, and 11% plan to increase their spend with Bing.


Search spend on on retail media (ads on e-commerce platforms) has steadily increased over the past few years, and it is forecast to account for 26.8% of total search advertising in 2023.

About the research: The report was based on advertising data from organizations around the world as well as survey data.

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How AI Will Affect Delivering Relevant Search Results

 Most professionals who work in roles focused on online search say artificial intelligence will be extremely or very important to delivering relevant results in the future, according to recent research from Lucidworks.

The report was based on data from a survey of 100 search practitioners (people whose jobs include some responsibility for online search, such as engineers, data scientists, and digital commerce experts).

Some 52% of search practitioners say they believe AI will be extremely important in the future for delivering relevant search results, and 36% say they believe it will be very important.


Some 40% of search practitioners say delivering relevant search results will require more effort in the future, 32% say it will require less effort, and 28% say it will require the same amount of effort.


Some 36% of search practitioners cite collecting quality signal data as the most important factor for delivering relevant search results, 34% cite data analysis, and 30% cite taking the correct actions with data.


About the research: The report was based on data from a survey of 100 search practitioners (people whose jobs include some responsibility for online search, such as engineers, data scientists, and digital commerce experts).

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What Is Disintermediation? How Digital Transforms The Value Chain


Disintermediation is talked about in most cases as a form of disruption, however, you need to understand how value is created to get the heart of it.

A typical example is how farmers can sell direct to consumers through platforms rather than distribute their products through wholesalers and retailers. Another term frequently associated with disintermediation is direct to consumer business model.

Amazon founder, Jeff Bezos, who is known for historically eliminating the middleman to benefit the customer said, “Even well-meaning gatekeepers slow innovation. If we want to continue to innovate at an accelerated rate, the gatekeepers must go.

Disintermediation Disrupts Markets

Disintermediation displaces the middlemen with the value chain and as a result, changes the dynamics with the market. These changes are classically driven changes in technology that enable value chains to be reconfigured.

The internet and the rise of digital platforms that can connect two-sides of a market have caused the displacement of many traditional intermediaries.

Benefits of Disintermediation

The opportunity is to deliver a product or service to a consumer with higher perceived value than an incumbent’s by changing the fundamental way it is delivered.

Each part of the supply involves time and money. Each intermediary will take add a margin to the product or service and hence the final cost to the consumer can have several layers of profits and costs associated with the value chain e.g. distribution, storage and transportation costs.

Cutting out the middlemen reduces the number of costs and often time to get to the consumer.

Disintermediation Examples

Disintermediation examples

The digitization of products has led to transforming physical products into zeros and ones, digits. Books, music and even money are now digitized and therefore easy to distribute.

Digital goods can be delivered over the internet either as a bundle or as a single unit (referred to as unbundling). Music tracks, video, software, newspapers, books are now easily distributed through multiple channels and viewable on a range of devices.

Disintermediation of the Newsagents and the Print industry

As the news became available online, the print and distribution of newspapers plummeted along with the number of newspaper companies. Many newsagents groups (shops selling newspapers and magazines) went out of business as a result of being disintermediated.

The decline of printed newspapers as a result of digitization of news and disintermediation of print.

Disintermediation of Travel Agencies

Travel agents used to be a familiar sight on every high street. However, the internet transformed the industry and the layers of intermediaries fell the wayside. Expedia and bookings.com made it easy for hotels to directly list their rooms on these sites and cut out the travel agents all together.

Disintermediation of Taxi Companies

Uber has grown rapidly from launch to now being a regular option for people seeking rides in over 60 Countries. The traditional taxi company and it’s associated costs of cars, an office and staff to man the phones have been replaced by the Uber app. A person seeking a ride can now find a driver easily within their vicinity. Consequently, the Uber business model results in only a fraction of markup to cover its costs and make a profit, therefore causing disintermediation in the taxi industry.

Disintermediation of Pet Stores and Wholesalers

Direct to consumer startup BarkBox identified the opportunity to serve just one demographic, die-hard dog lovers directly, with just one core product: its eponymous BarkBox. However, by doing so it cuts out the normal wholesaler and pet supply store.

Fintech and Disintermediation of Banks

Fintech through Big Data, Blockchain, Internet of Things (IoT), use of Cryptocurrencies, Artificial Intelligence (AI) and more effective exploitation of digital channels, social networking and mobile devices is disintermediating the financial services industry through innovation.

Robo Advisory is a term used to describe the automation of financial services traditionally provided by human financial advisors, which now can be done via code, and through an automated process.

Disintermediation vs Reintermediation

Disintermediation is enabled through digital platforms that connect two sides of a market and cut out the middlemen. As a result, the margins normally absorbed by the middlemen can lead to improved profits for the producer and often lower costs for consumers.

Reintermediation is the opposite of disintermediation. Reintermdiation involves the introduction of an intermediary, a middleman, between a supplier and a customer.

Quite often this happens because a company will outsource a service so that it can focus on its core activities, e.g. what it does best. Another reason for reintermediation is convenience and the ability to focus on one particular part of the value chain.

Reintermediation Examples

Levi Strauss & Co. didn’t score any points when it decided to shut out retailers from selling its blue jeans and other clothing online.

Initially, Levi Strauss thought it wanted to keep the eCommerce to itself. However, less than one year later and with declining sales, the $6 billion manufacturer, abruptly changed course.

Levi’s announced that it would quit direct sales on the Web and leave online selling of its clothing to retailers like J. C. Penney Co. and Macys.com. However, later it reintroduced its online store but maintained distribution with its retail partners.

A great example of reintermediation is Deliveroo, a company founded in 2013. Deliveroo is an online food delivery company that partners with restaurants across cities to manage the whole takeaway process from restaurant pickup to customer delivery, again through a mobile app.

Deliveroo has allowed more restaurants to offer a delivery service where the traditional internal cost of doing so proved a barrier. Also, it provided an outsourced more efficient delivery option for restaurants offering their own service.

Without Deliveroo, a delivery would require the investment costs of a vehicle(s), employment of driver(s) and logistics planning.

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55 Business Model Patterns. #15 Flat Rate

 


In this model, a single fixed fee for a product or service is charged, regardless of actual usage or time restrictions on it. The user benefits from a simple cost structure while the company benefits from a constant revenue stream.

Examples: Iconic Casesy


How they do it: Membership to access McFit’s fitness club facilities costs €19.90 per month. It includes access to every area, as well as the shower fee. Most clubs in Germany, Austria, Spain and Poland are open 24 hours a day, 365 days a week. The customer does not pay for the individual visits, but a flat rate fee is collected in form of the membership fee.


Below, the top industries for the pattern "Flat Rate" are displayed, in order to get insights into how this pattern is applied across different industries. We've collected data from 5 firms using this pattern.


Below, the pattern "Flat Rate" is analyzed based on co-occurrence, in order to get insights into how this business model pattern is applied in combination with other patterns within the firms we studied.


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What Is A Flat Rate Pricing Model? Pros & Cons Explained

These days, every time you look at a pricing page, it seems there are three to five options staring back at you. Sometimes, you can’t help but wish for an easier way to buy SaaS. After all, as consumers, we enjoy many subscriptions and services that come with a simple, one-size-fits-all bill.

It’s no secret that tiered plans are rapidly becoming the gold standard of pricing for SaaS. But is a multiple-choice approach the only option for SaaS businesses seeking to grow in an increasingly complicated market? Is there a benefit in returning to the simpler structure of flat rate pricing?

What is flat rate pricing?

Flat rate pricing is a subscription model that charges users a flat fee per month or year for all features and all levels of access. For example, if you subscribe to the New York Times, you pay a fixed rate per month or year.


Who is using a flat rate pricing strategy?

Better and cheaper technology has enabled the creation of scalable pricing structures, so you’ll rarely see examples of flat rate pricing in SaaS. This model is used primarily by businesses that sell physical products in consumer-facing contexts. Companies that offer delivery and shipping services like FedEx often offer flat rate shipping options that are attractive to small businesses and entrepreneurs. Many consumer-facing subscriptions offer a single subscription price.

But even that trend is changing. Large entertainment subscription services that once used a flat rate pricing model for monthly subscriptions are switching to their own version of tiered pricing plans. Netflix evolved from a flat rate service into a tiered pricing structure—a move that may or may not be sufficient to increase Netflix’s revenue in a saturated market. Spotify, on the other hand, added discounted tiers for Spotify Premium in a bid to increase acquisition and retention.

Basecamp, a popular business management software, is the outlier success story of flat rate pricing in the SaaS world. The reason for this success? The company built flat rate pricing into its core business philosophy.



“The problem with per-seat pricing is that it by definition makes your biggest customers your best customers. With money comes influence, if not outright power. And from that flows decisions about what and who to spend time on,” says David Heinemeier Hansson, co-founder and CTO of Basecamp. “[My co-founder and I decided] we weren’t going to have clients, we were going to have customers. And lots of them. All pretty much equal in their contribution to the business.”

So is Basecamp a unicorn, or can other SaaS companies enjoy the benefits of flat rate pricing?

 

What are the pros and cons of flat rate pricing?

As with any subscription pricing structure, there are both pros and cons. Flat rate pricing can be a tool for early monetization, but its lack of flexibility and scalability can limit your ability to grow.

 

Pros of flat rate pricing

The greatest benefits of flat rate pricing are its simplicity and predictability. A flat rate pricing plan is easy to communicate and, therefore, is easy to sell. If your ideal customer values simplicity or needs a straightforward solution for a straightforward problem, flat rate pricing might work well for you.

A perfect example of this is the inbox management software Consider. A recent addition to a crowded market, Consider targets its buyer’s need for a simpler, more focused email client. Flat rate pricing offers simplicity and works well as part of the overall brand. Whether or not Consider keeps this model long-term, this pricing strategy is a great way to establish a solid customer base for a young SaaS startup.



Flat rate pricing can also work well for companies with a narrow product and a single buyer persona. In this situation, a flat rate pricing structure frees founders to focus on monetization, acquisition, and retention instead of tailoring the pricing strategy to diverse personas that don’t yet exist.

Superhuman, another up-and-coming email app, demonstrates this principle well. While it’s still in early access, Superhuman has been generating a lot of media buzz. A major reason for this is the laser focus of the product: making people better and faster at handling email. The company employs a flat rate price structure, charging $30/month. Like everything else about their brand, Superhuman’s pricing communicates a streamlined approach to business.



Cons of flat rate pricing

Flat rate option may work for a few companies, but it’s nearly extinct in the SaaS ecosystem, and with good reason. A one-size-fits-all approach is a good way to make sure none of your users are happy. Businesses owners may choose a competitor that offers a more budget-friendly starter plan, while larger businesses may require more features or bandwidth than your flat rate subscription plan can offer.

Larger businesses also bring added risk to any SaaS using a flat rate pricing model. These businesses have the potential to strain your server resources as well as your customer support resources—and with fixed pricing, they won’t be paying you a penny more for your trouble.

Even Fortune 500 companies, companies primed for high traffic, have experienced disastrous spikes in server costs when not carefully monitoring and managing cloud resource usage. If your resource costs fluctuate from user to user, consider transitioning to a pricing model based on usage.

In addition to lost customers and bloated operating costs, flat rate pricing also limits your potential for future gains. A one-size-fits-all approach may be simple, but it blinds you to your users and the diversity of their needs. Tiered pricing allows you to segment your users and target your development and support efforts accordingly. With flat rate pricing, you lose the ability to align your pricing with your value metric, since you don’t make additional revenue for additional value.

 

Can I grow revenue with a flat rate pricing model?

The short answer is no. While there are ways to improve your pricing power on a flat rate pricing model, the effort-to-reward ratio really isn’t worth it. Expansion revenue accounts for over 30% of total sales for top SaaS companies, and this kind of revenue simply isn’t on the table with flat rate pricing.

Scaled or tiered pricing has been proved again and again to be not only more profitable in the short run but also consistent in fueling growth in the long term. Whether you scale your pricing based on features, users, or usage, the verdict is the same: scaled pricing promotes long-term revenue growth, while flat rate pricing quickly stagnates.

 

Does ProfitWell recommend flat rate pricing?

While a few companies have been able to make flat rate pricing work, there’s a very good reason that almost no SaaS company uses it. SaaS as an industry is all about flexibility and the ability to adapt quickly to change. Compared with that standard, flat rate pricing is like putting lead shoes on a dancer.

Most SaaS businesses simply can't sustain themselves with flat rate pricing, because it doesn't give them the ability to learn from their customers and adapt their strategies, values, and set prices accordingly. At ProfitWell, we recommend tiered or other scaled pricing structures that will give you the flexibility you need to grow in a fast-paced market.

 

Flat rate pricing FAQs

What is a flat-rate business model?

Flat-rate business model refers to the model where products or services are offered at a fixed price, regardless of the number of hours the product/service was used and to what extent.

 

Is flat-rate a good pricing model for eCommerce businesses?

In the majority of cases, eCommerce businesses rely on flat-rate pricing to set their shipping rates. Because eCommerce shipping charges are usually affected by the box size and weight, shipping method, transportation, and other nuances, online stores often decide to go with the flat rate packaging. It makes calculating the overall costs much easier and more predictable for online shoppers, which ultimately minimizes the abandonment rate. 

 

Is flat rate a better pricing option than an hourly rate for freelancers?

Flat rate pricing is growing in popularity among freelancers who are looking for the best way to invoice the amount of time they spent working on a particular project. Flat rate pay showed to be a much better way to charge for their services than per hours of work. Fixed rates are easier for clients to understand, plus flat rate work doesn't require keeping detailed accounts of the number of hours a freelancer has spent working.

By Patrick Campbell
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Innovation and Isomorphism

 


Written by Lorna Finlay


The late Steve Jobs once said that it is innovation that distinguishes between leaders and followers. While there are no prizes for guessing on which side of this dichotomy businesses hope to fall, innovation can be a challenge. While we often think of innovation in terms of research and development, product design or a particularly creative marketing campaign, innovation relating to the internal processes of a business can be just as important for maximising efficiency and staying ahead of the competition. But can sociological theory help to explain why this can be so difficult for businesses to achieve?

Isomorphism is a concept that was developed by DiMaggio and Powell to help explain the tendency for organisations within a similar field to adopt similar behaviours, thus reaching equilibrium and becoming increasingly similar to each other – particularly in terms of internal structure and processes. Enrique Dans, a Professor of Innovation, argues strongly that “isomorphism strangles innovation, original thought, and the development of the kinds of initiatives that can often give business a competitive edge”. But how does isomorphism, this state of conformity and habit, come about? And what can be done to fight against it?

DiMaggio and Powell identified three causes of isomorphism: coercive, normative and mimetic. Coercive isomorphism relates to homogeneity that arises across businesses that are subject to the same regulations or political influence. Normative isomorphism describes the pressure to conform to perceived norms and values in the industry – “this is the way we do things”. Finally, mimetic isomorphism occurs when organisations experiencing a period of uncertainty mimic organisations that are perceived as “successful”, and conformity ensues as a result.

It is important to note that homogeneity brought about by isomorphism is not the same as the homogeneity that results from competitors mimicking new innovations and practices from each other – an example of the latter being the recent widespread rise of Account-Based Marketing in the B2B world, which began as a real innovation but over the past year has become increasingly mainstream. It can be argued, relating back to the earlier quote from Enrique Dans, that isomorphism is what prevents these new and innovate ideas from arising in businesses in the first instance.

What can be done to resist this and continue on a path of innovation? While coercive isomorphism has a certain inevitability, as firms should not be encouraged to break rules and regulations and will thus experience a certain degree of homogeneity there, normative and mimetic isomorphism may be easier to resist by questioning and challenging industry norms and making bold decisions in response to uncertainty.

In his essay responding to DiMaggio and Powell, Koushik Dutta suggested that decision makers wanting to develop “non-isomorphic action” should exhibit three characteristics. The first of these, systems thinking, is something that should be familiar to market researchers! It is the ability to identify patterns, relationships and trends – often in areas of complexity. The second, moral agency – the adoption of standards of right or wrong – we hope would also be familiar. The third desirable characteristic to drive innovation and resist isomorphic conformity is self-efficacy – the belief an individual or team has in their ability to successfully execute innovative ideas, which are often seen as risky purely because they have never been done before.

Like any sociological theory, isomorphism is open for debate. However, it can be seen as a useful framework to understand why we sometimes stall with innovation. This understanding can in turn empower decision makers to be mindful of and fight against the pressures of conformity that want to make us all followers.

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