The Mental Accounting Barrier to Micropayments

Some electronic commerce projects promise dramatically lower transaction costs, so that we can achieve “micropayments,” “microintermediation,” and so forth. An even more advanced idea is the use of very small granularity markets for the allocation of computer and network resources.^[1] To what extent are such things achievable? Consider a feature fairly independent of the particular payment system: the statement of charges. Here lies a tradeoff here between completeness and complexity. On the one hand, merely summarizing charges creates the opportunity for salami frauds, allowing widely distributed false or exaggerated microcharges to go undetected. Furthermore, parties reading only the summaries get no feedback by which they can adjust their behavior to minimize costs. On the other hand, a statement too complex for customers to read also allows fraud, error, and inefficient usage to go undetected, because one or both parties cannot understand the rationale for the charges in relation to the presumed agreement on terms of service and payment. The same kind of reasoning applies to working these things out in the head instead of on paper, as is often done in small cash transactions. A basic requirement for market pricing to work is that both sides to a transaction be able to map charges to value obtained or rendered, so that they can adjust their buying or selling behavior accordingly.

There seems here to be a fundamental cognitive bottleneck. One proposed solution to this has been “intelligent agents.” But since these agents are programmed remotely, not by the consumer, it is difficult for the consumer to determine whether the agent is acting the consumers’ best interests, or in the best interests of the counterparty – perhaps, necessarily, at least as difficult as reading the corresponding full statement of charges. Furthermore, the user interface to enable consumers to simply express their sophisticated preferences to an agent is lacking, and may represent another fundamental cognitive bottleneck.

Communications companies have found billing to be a major bottleneck. By some estimates, up to 50% of the costs of a long distance call are for billing, and this is on the order of a $100 billion per year market worldwide. Internet providers have been moving to a flat fee in order to minimize these costs, even though this creates the incentive for network resource overusage.

A micropayments system assumes a solution to the mental accounting problem. If somebody could actually solve the this problem, rather than merely claiming to have solved it via some mysterious means (“intelligent agents,” et. al.), the savings would be enormous even in existing business such as long distance and Internet service – not to mention all the new possibilities possible by lower transaction costs.

Example – Electricity Bills

Sometimes statements account for transactions in gratuitously small increments, such as the 100 watt-hour resolution on some electrcity bills. There are plenty of things most folks normally don’t work out regarding their electricity bills, which could improve the value they get for their electricity payments:

• Which appliances are using more electricity with less personal benefit (not available on the electricity bill – but one can conceive of a personal accounting program tied to smart appliances that let you do this).
• How to better balance electric vs. gas heat (you could compute this in detail and save a few bucks, but you’d earn extra money faster by moonlighting).
• If the electricity company was a less reliable and widely known entity, you also might not trust them with the billing and would recompute it to the resolution you felt comfortable with, and accept fraud or fine-print trickery below that level. (Since electricity is fungible and the pricing ruleset small you could have a program check the bill, which is efficient if it catches enough fine-print shenanigans for enough people to recoup software development & marketing costs).

The reason we don’t do the things is that they’re not worth the brain cycles: we have reached the mental accounting barrier.

A Theory of Price Granularity

Here I present briefly a theory of price granularity based on a subjectivist view of prices. The function of prices, from the point of view of a shopper, is to let the shopper map his personal resources (budget) to his personal values (unique and not directly observable). This mental process requires comparison of the purchase price of a good to its personal value. This entails a significant mental cost, which sets the most basic lower bounds on transaction costs. For example, comparing the personal value of a large, diverse set of low-priced goods might require a mental expenditure greater than the prices of those goods (where mental expenditure may be measurable as the opportunity costs of not engaging in mental labor for wages, or of not shopping for a fewer number of more comparable goods with lower mental accounting costs). In this case it makes sense to put the goods together into bundles with a higher price and an initutive synergy, until the mental accounting costs of shoppers are sufficiently low.

These mental accounting costs, not the physical or computational or amortized R&D costs of payment or billing method, set the main lower bound on price granularity. Judging from pricing granularity trends such as the trend towards flat rates in online services, online pricing granularity is far above suggested micropayment levels of a few cents or even fractions of a cent. The mental accounting costs for a typical on-line consumer seem to be somewhat higher than those in more familiar areas of commerce.

One possible fix is for the shopper’s software to compare purchase prices against a “consumer reports” service. But such unbiased information is rare, and in any case takes into account only widely shared values, not personal values.

Another fix is possible for fungible commodities: charge a fixed price per unit, which the shopper can evaluate from just the accumulated number of units and price information. As a concrete example, in a current U.S. ad campaign AT&T is betting that its $0.15 flat rate more attractive than Sprint’s $0.10 – who knows variable rate – that it is worth the vendor forgoing congestion pricing, and the shopper forgoing deep discounts, in order to have a predictable rate, turning phone time into a fungible commodity, and thus saving on mental accounting costs.

Alas, most Internet commerce is not fungible: content, services, mail-order products, and so on. Some Internet Server Provider (ISP) services can be sold as fungible (e.g., disk space, connect time) only at the expense of foregoing congestion pricing and other pricing methods that, if it were not for mental accounting costs, might be quite efficient. Furthermore, even for fungible commodities each user has a unique curve of diminishing returns. Software would have to let the shopper determine and input his volume preference curve (in some intuitively familiar way, without presupposing the shopper is familiar with economic theory) before it could adequately act in his interests; not to mention the complications of temporal preferences, nonlinear interactions between commodities fungible when in isolation, and so on.

This user interface solution for the case of fungible commodities suggests a better strategy for tackling the more general problem of mental accounting in online commerce: develop better ways for the shopper to communicate his personal preferences to software. Marketers have long devised schemes to to get this kind of information: detailed surveys, tracking of user behavior and responses, etc. Arguably Web services like www.firefly.com are the most advanded in this regard. Firefly creates a kind of “subjective space” of musical preferences in which the shopper can navigate and find new music that they are more likely to prefer.

Given that software can represent certain preferences, it is a more straighforward problem for software to map these representations to specific prices (or bids), engage in shopping (or haggling), and securely complete online transactions. These easier problems have been the focus of micropayments research, but the more fundamental problem of obtaining and representing preferences in the first place has gone largely unrecognized, perhaps due to an objectivist bias that posits mathematical laws rather than subjective preferences as the basis of a working economy.

Given the solution of other transaction cost problems, mental accounting costs then become subject to the limit on the process of communicating preferences – whether via the mental accounting choice of one good over another, or through creating a unique and sufficiently accurate software simulucrum of a shopper’s preferences which then completes the budgeting, bargaining and purchasing process. To what extent and with what efficiency can (a) a shopper communicate subjective preferences to software, and (b) can software represent and act in the interests of these objectified preferences? The presence of search engines, catalog order forms, marketing surveys, and more sophisticated interactions like firefly demonstrate that such communication and representation is both feasible and important, but seems to be costly and perhaps fundamentally limited in some way(s).

Preferences and Visual Metaphors

To assess the desirability of a transaction, and to avoid being mischarged, the parties to a transaction have to count up, ie account for, the money paid for particular products and services – whether making sure that cash payments ar made as promised (e.g., looking at the display as products are scanned at the store, or the receipt afterwards), or making sure the phone bill is proper. Herein I use “accounting” in this broad sense.

I may be paying in cash, but I’d still like to keep track of how and why my cash is going in and out, for many of the same reasons that accountants reconcile and analyze book entries. Right now a transaction log (whether ecash™’s or a credit card’s) is the most useful way to do this. There may be other metaphors more appropriate for some circumstances (eg, e.g., absolute level gauges, rate gauges with high and low water marks, etc.); this is a potentially fertile new field to explore. There may be agents that can do some of the accounting (e.g., comparing payments made to terms promised, payment limits, etc.), but for the vast majority of products and services software cannot judge the quality or personal desire for the product or service, and thus the net desirability of the transaction. The user must undertake this comparison with whatever information the computer can provide via the display. The user interface and the cognition of the user thus remain the bottleneck to transaction granularity.

A big task is to use the power of GUI to come up with new metaphors to make this easier. It is the intuitive yet accurate metaphor that will lower accounting costs. Cryptographic protocols potentially lower only security-related transaction costs such as forgery and extortion. For the normal accounting transaction costs, which are currently too high for micropayments, we need better interactive visual metaphors.

For transactions free of records, we need transactions that can be fairly transacted once, immediately accounted for by the parties via a nice visual metaphor, then forgotten. The potential for unresolvable disputes in record-free systems is vast for transactions where this is not possible (probably most of desired commerce: where quality of a product or service cannot be well determined until after the purchase transaction is complete, or where credit is involved).

Price is one kind of contractual term; we also need nice metaphors to keep track of other kinds of contractual terms. Lack of observability of the protocol on the part of the user leads to the ability of the counterparty to engage in hidden actions. See “Smart Contracts: Building Blocks for Digital Markets” for further discussion of this and other computerized contracting issues.

One of the barriers to creating good contracts is determining what the parties want in the first place. People tend to think in terms of standard or stereotyped conditions: payment in dollars, investing in stocks, etc. when there exist a far wider variety of alternative contractual structures that, combined properly, could better meet the parties’ needs. I’d like to see tools which allow parties to explore their desires interactively with the computer. In finance this might include interactive personal yield curves, determining the partial order of desires (as in decision theory) for particular alternate securities, derivatives, and synthetics; and so on. Software would then analyze this input, make recommendations, and even undertake automated contracting.^[2] Metaphors should be developed so that make it easy for lay users to express such desires without extensive knowle.g., of finance or decision theory. Such metaphors would provide a friendly front end to automated exchanges, auctions, and other online contracting mechanisms.

Currently budget programs (like Quicken) provide some of the metaphors, and financial analysis programs provide extensive feedback on the cash flow properties of particular contracts, but a potentially large untapped market lies between in a combination of these two technologies.