This article offers a commentary on consumer behavior in modern telecommunications markets, based on advances in behavioral economics. An original analysis of the decision-making environment faced by telecommunications consumers identifies four specific properties of the market, of which rapid technological change is just one. The core argument is that this combination of properties, which is unique to telecommunications, is likely to foment decision-making biases established by behavioral economics. This central insight is used to address two issues of concern from a pro-consumer perspective: low levels of switching between providers and failure to select optimum tariffs. Competing explanations for low switching and accumulating evidence of consumer detriment in tariff choice are outlined. The commentary concludes by considering ways that consumers might be helped to meet the challenges identified.
It is no exaggeration to state that consumers' response to the liberalization of a range of formerly state-run markets, including networked utilities and telecommunications, has surprised economists and policymakers. In theory, the opening up of these markets to competition allows consumers to be active in choosing the best and lowest cost suppliers, producing upward pressure on quality, downward pressure on prices and an overall increase in consumer benefit and economic efficiency. To some extent this has happened. Choice has expanded and many consumers have switched suppliers to obtain better value. What has surprised, however, is the degree to which consumer behavior has departed from this ideal competitive model. To take a simple example, research in energy markets has revealed large numbers of consumers failing to switch to lower cost suppliers (e.g., Brennan 2007; Giulietti, Waddams Price, and Waterson 2005). Moreover, in a recent sample of British consumers, the majority who switched electricity supplier to make savings failed to select the best available deal, while a substantial minority actually managed to increase their bills (Wilson and Waddams Price 2010).
Explanations for such phenomena are increasingly sought in behavioral economics, which has documented a range of "biases" consisting of systematic departures from the rational choice assumptions of orthodox microeconomics (for reviews see DellaVigna 2009; Rabin 1998). Because behavioral economics is a relatively new sub-discipline with a broad and rapidly moving scientific frontier, the precise implications for consumer policy are as yet hard to determine. Yet, there is already widespread agreement that such implications may be important (Garces 2010; Micklitz, Reisch, and Hagen 2011; Rosch 2010) and, moreover, that policymakers, regulators and consumer groups need to recognize the possibility that behavioral biases cause considerable consumer detriment (Bennett et al. 2010; Lunn and Lyons 2010). If so, there may be scope for devising new interventions to protect consumers (Faure and Luth 2011).
This article addresses these issues in the specific context of the modern consumer telecommunications market. The core argument is that this consumer decision-making environment is unique and, as a consequence, likely to foment particularly strong behavioral biases. Thus, the article shares its motivation with other work that has aimed to highlight markets where biases might be especially prominent and policymakers (and others) may need to pay particular attention, such as financial services (Barr, Mullainathan, and Shafir 2008), health insurance (Liebman and Zeckhauser 2008) and insurance generally (Schwarez 2010). The analysis aims to be useful to anyone concerned with improving the experience of telecommunications consumers.
The digital revolution offers opportunities for communication and entertainment that previous generations would doubtless have envied. Nothing that follows is intended to suggest that the overall benefits of these developments are not very large. However, an initial examination of standard market indicators suggests that telecommunications may be departing significantly from the competitive market model. Offerings have become increasingly innovative, complex and difficult to compare. Survey research, consistent across a number of countries, reveals that consumers are reluctant to switch providers, with around half not even considering a switch (Xavier and Ypsilanti 2008). In at least some countries, telecommunications companies are subject to increased levels of customer complaints about service quality and bills not matching expectations, or "bill-shock" (Xavier 2011). Direct evidence has recently emerged that high proportions of consumers of internet and mobile telephone services may select suboptimal contracts (Bar-Gill and Stone 2009; Gerpott 2009; Grubb 2009; Lambrecht and Skiera 2006).
The following sections present a systematic attempt to understand these developments and to consider the potential implications for consumers and policymakers. The analysis begins by identifying four market features that represent a unique combination and raise concerns when considered alongside established findings of behavioral economics. Subsequent sections then use these insights to examine unwillingness to switch providers and suboptimal tariff choice, respectively. While issues for consumers and policymakers are mentioned throughout, the final section summarizes these and discusses the merits of policy responses, including the need for more targeted research.
THE UNIQUENESS OF TELECOMMUNICATIONS MARKETS
Four Key Characteristics of Telecommunications Markets
The development of modern telecommunications markets beyond fixed-line telephony has resulted in at least four non-standard characteristics. While it is probably the case that none is unique to telecommunications, the combination of them is.
First, developments in domestic internet services and mobile devices mean that modern telecommunications consumers often face highly complex, multidimensional judgments of value. Choosing a new telecommunications service is a decision in which equipment, associated software, access to a particular network and a tariff structure are all factors. That is, simultaneous assessments of value are required over what are, in effect, four distinct products, some of which themselves involve multiple dimensions of value (reliability, speed, user-friendliness, etc.). The complexity of simultaneous judgments required is greater still where different services are bundled, e.g., fixed-line telephone and broadband internet, or broadband and television.
Second, much of the value depends on factors unrelated to product and provider. The private value of communication depends on who you communicate with and why: vital in emergencies; higher if you form a new relationship; lower if you become too busy; immediately improved by a great new website; dependent on changes to online service provision and so on. Telecommunications products are enabling devices and their value is thus not limited to how successfully they perform, but also to what they enable: access to people, information, entertainment, services and purchase opportunities. The ultimate value to the consumer, therefore, is determined by a combination of benefits many of which are not supplied by the firm offering the product, and some of which are intangible or unpredictable.
Third, and most obviously, telecommunications offerings are subject to an extreme pace of technological advancement. Consumers make decisions in relation to equipment, software and services they are yet to experience. Size, speed, functionality, reliability and design are continually changing. Repeat purchase is rare or even impossible due to obsolescence.
Lastly, because many telecommunications offerings now enable constant mobile access to immediate experiences, consumers make multiple and varied decisions in the market on a daily or even hourly basis, requiring trade-offs between immediate costs and benefits and future ones. Depending on the precise tariff structure, contracts offer consumers the continual fight to consume immediate social contact, information and entertainment, plus further opportunities to purchase a vast range of everyday goods and services for delivery. While the advent of credit cards and telephone payment systems greatly increased possibilities for immediate consumption, the volume, variability and instantaneous nature of the available multimedia offerings in modern telecommunications make the decision-making environment distinct from any other billable service. In effect, consumers can now sign up to always-on consumption of immediate multimedia experience at zero-interest credit.
One might debate the extent to which each of these four aspects of the decision-making environment is unique to telecommunications, although the continual opportunity to consume immediate experiences is probably unprecedented. In combination, however, these four features surely are unique to this consumer market.
Psychological Demands on Consumer Decisions
What impact might these four identified characteristics of the decision-making environment have on consumer behavior? Before considering the specific issues of switching and tariff choice, it is worth considering how the four characteristics combine to create the context in which the consumer makes decisions, especially in relation to broadband and mobile offerings.
In almost all markets, consumers have a degree of uncertainty regarding the respective private values of the goods and services they consider. There is variability and hence a need for judgment with respect to the flavor of foods, the durability of durable goods, the fashionability of clothes, the punctuality and comfort of train journeys, the atmosphere in cafes and so on. Products in many markets have multiple attributes; value can be hard to judge. Yet, when assessing mobile and broadband telecommunications offerings, each of the four characteristics of the market identified in the previous section magnifies this challenge. The first, that the product combines equipment, software, network and tariff structure, means not only that four (themselves multi-attribute) products must be simultaneously judged, but also that there may be very many possible combinations from which to choose. In addition to the complexity of choice between offerings, the consumer must decide how much to spend. This brings the second characteristic into play, namely the need to value those opportunities and experiences the product ultimately enables access to. Although most internet and mobile telephone providers offer access to a similar range of services and content, such that the value of the access may be similar across the market, judging that value relative to the value of other possible consumer purchases is difficult. Rapid technological advancement, the third characteristic, means that even returning consumers lack experience with aspects of the latest offerings. Thus, the combination of these first three market features means that even where offerings are not bundled, purchase decisions involve multi-product, multi-attribute judgments, implying an exceptional degree of complexity and uncertainty over private value relative to most other consumer markets.
The fourth characteristic identified above makes the decision more uncertain still, because the consumer must also judge how much they will use the service and hence, depending on the selected tariff, what the bills will look like. The consumer can try to manage this uncertainty by opting for pre-payment options, flat-rate tariff components or a contract with opportunities for renegotiation. With pre-payment, the uncertainty transfers to the amount of time before credit runs out and a top-up is required. With flat-rates, it transfers to the likelihood of staying within usage allowances, after which higher rates apply, or to whether the service will be used sufficiently to warrant the size of flat-rate payment. Whatever approach is chosen, a good decision demands time-consistent behavior: choosing the best option for predicted usage and sticking to that usage. Yet, empirically, when consumers are asked to trade-off immediate benefits and costs against future ones, behavior typically implies time-inconsistent preferences (DellaVigna 2009; Frederick, Loewenstein, and O'Donoghue 2002). Rapid technological change is likely to make time-consistent behavior particularly difficult, because consumers must predict their usage of equipment, software, networks and, ultimately, experiences, that they may not previously have tried.
Overall, consumer decisions in the telecommunications market are made very challenging by the four market features identified. The choice set is large; offerings are complex; judgments of value are likely to be more uncertain than in other consumer markets; and consumer surplus ultimately depends on the consistency of very many decisions made over perhaps a year or more.
RESISTANCE TO SWITCHING
Numerous international surveys of telecommunications consumers record an apparent reluctance to switch providers (for review, see Xavier 2011). Since active consumers are seen as a prerequisite for effective competition, identifying barriers to switching has preoccupied analysts, regulators and policymakers. Much of the focus has been on switching costs and how they might be reduced. The previous section provides the foundations for a different analysis. Linking the properties of the decision-making environment to behavioral economic findings leads to the alternative hypothesis that low switching reflects consumers' inability to recognize superior deals. This perspective, which is also more consistent with the survey evidence, represents a different understanding of consumer behavior. Before going into detail, however, some theoretical clarification is required regarding the concept of "switching costs."
The Concept of Switching Costs
In a groundbreaking analysis of competition under oligopoly, Klemperer (1987) offered a three-way categorization of switching costs: (1) transaction costs, which covered the time and effort required to complete the administrative process; (2) learning costs, which entailed the time and effort required to research other products and to learn to exploit brand-specific attributes and (3) artificial costs imposed by firms, such as discounts for loyalty. Thus, switching costs were identified with time, effort or price. Yet subsequent influential work by Klemperer (1995) expanded the concept to cover not only actual costs in terms of time, effort and money, but also perceptions of such costs. More recent authors go so far as to define switching costs as "the perceived economic and psychological costs associated with changing" (Jones, Mothersbaugh, and Beatty 2002, 441, italics added), or "the real or perceived costs that are incurred when changing supplier" (Xavier and Ypsilanti 2008, 14, italics added).
This equivalence between actual and perceived costs is helpful to economists aiming to model how consumer loyalty might affect equilibrium prices. It keeps faith with the assumptions of orthodox economic consumer theory, especially rational utility maximization and revealed preference. If a consumer fails to make a beneficial switch, some unobserved "psychological cost" must have outweighed the potential gain, since the consumer is assumed to maximize utility according to well defined preferences. Yet there are crucial points of scientific inference at issue here. For those seeking to help consumers or simply to understand consumer behavior, whether switching costs are genuinely high or misperceived to be high is an empirical matter, not one that can be assumed away to ensure consistency with a predefined model. More importantly, the assumption that an unobserved psychological switching cost must be involved precludes other plausible explanations for consumers failing to make beneficial switches--explanations that do not involve real or perceived switching costs. Consumers may make decisions on grounds other than self-interested cost-benefit analysis. They may undertake no decision-making process at all. Consumers may simply make mistakes. Or, as will be proposed here, they may be unable to perceive potential gains with sufficient accuracy.
Empirical Evidence on Switching Costs
Given this clarification, evidence from large volumes of consumer survey data (e.g., OFCOM 2010; Xavier and Ypsilanti 2008) suggests that while switching costs and perceived switching costs have some impact, they may not be the main reason for the disinclination to switch. Across the full range of telecommunications services, the large majority of consumers who switch state that the process was relatively easy--only a small minority experience difficulty. Although some consumers (when prompted) cite hassle and not having the time as reasons for not switching, suggesting perceived switching costs may possibly play a larger part, more common reasons given surround loyalty to present suppliers and worries or uncertainty about alternative suppliers. (1) These reasons instead indicate worries about ending up with an inferior product, or perhaps a conservative preference for the existing provider. Indeed, the majority of consumers of fixed-line, mobile and internet services do not even consider switching provider over a twelve-month period.
One interesting test of the importance of switching costs is the impact of mobile number portability (MNP). Being forced to change numbers appears intuitively to be a significant cost. In an international analysis of cross-sectional time series, Lyons (2006) finds statistically significant increases in churn following the introduction of MNP, provided the switching process is sufficiently short. Yet the effect of MNP on switching has nevertheless turned out to be much smaller than anticipated (Xavier and Ypsilanti 2008). In the British market, perhaps the most regularly surveyed, switching has declined in recent years despite MNP (Xavier 2011).
Overall, it is likely that switching costs deter switching, but responses to consumer surveys and the continuing low level of activity despite falling switching costs suggest other factors. Combining the unique characteristics of the telecommunications market with established behavioral economic results, the remainder of this section considers the role of three specific types of phenomena.
Willingness to Exchange and the Status Quo
The responses to consumer surveys described contain strong echoes of the "endowment effect," which can be demonstrated in simple experiments on willingness to exchange ordinary consumer goods. Typically, we state a much higher minimum price to sell a good we own than the maximum we will pay to buy the same good (Kahneman, Knetsch, and Thaler 1990). Also, we are disinclined to trade a good we own for one we do not, but which we would prefer if offered a simple binary choice where neither good was owned (Knetsch 1989). Whatever psychological mechanism underlies this apparent unwillingness to make beneficial exchanges may also be behind consumers' unwillingness to switch suppliers. The decisions are analogous: many consumers require the prospect of large gains before they will switch and many stick with providers they might not choose were they to enter the market afresh. Moreover, one established empirical regularity is that the endowment effect strengthens with uncertainty over private value (Horowitz and McConnell 2002; Sayman and Oncular 2005), i.e., the harder people find it to value goods, the greater their unwillingness to trade. To the extent that the psychology behind the endowment effect affects switching, therefore, lower switching is implied in markets where consumers are more uncertain about the relative value of offerings. As argued above, the private value of telecommunications offerings is likely to be subject to substantial uncertainty.
The endowment effect is itself often linked to a broader class of phenomena that includes "status quo bias" and the tendency to be drawn to default options. Samuelson and Zeckhauser (1988) first reported individuals' inclination to stick with status quo choices after observing that new employees at Harvard University held retirement savings in substantially different portfolios compared with equivalent employees of longer duration. Experiments then confirmed the generality of the effect. For instance, if opinion survey respondents are asked to state which of two options is best, simply informing them as to which is the current option biases responses in that direction (Kahneman, Knetsch, and Thaler 1991). It is perhaps unsurprising that the bias arises in consumer financial markets where, as with telecommunications, products are technical and complex. The strength of the bias appears again to be linked to consumers' ability to assess products, for example in experiments concerning asset allocation in investments (e.g., Agnew and Szykman 2005).
These similarities between experimental findings and switching behavior are suggestive of common causes. From the perspective of consumer interests and regulatory policy, however, the precise nature of the causes matters. The most widely accepted explanation of the endowment effect is loss aversion--the tendency to weight losses in decisions more strongly than equivalent gains. Tversky and Kahneman's (1991) model of consumer choice assigns approximately twice as much weight to the loss when giving up an ordinary consumer good as to the gain when acquiring the same good. Do consumers give extra weight to giving up a telecommunications contract? Taken as an explanation for unwillingness to switch telecommunications providers, loss aversion implies that consumers forego substantial gains, but that this reflects genuine consumer preferences. If true, pro-consumer campaigns to encourage switching or to promote shopping around amount to accepting the conclusion that such freely formed consumer preferences are detrimental, to the extent that those seeking to advance consumer interests might seek to override them. That is, the policymaker effectively asserts that overcoming loss aversion is in consumers' long-term interests, even if that is not how consumers feel when deciding not to switch.
However, the role of loss aversion is not uncontested. Plott and Zeiler (2005, 2007) managed to overcome the endowment effect in experiments by training subjects to realize they were missing out on gains. List (2003, 2004) used field experiments to show that the endowment effect could be attenuated among experienced dealers in a real market. Kling, List, and Zhao (2010) and Lunn and Lunn (2011) have offered dynamic models of the endowment effect implying that foregone gains may be temporary, both with some empirical support. When related to switching behavior these models suggest that, when measured over a longer period, the behavior may be less disadvantageous than it initially appears from a snapshot of current offerings and market shares. There are alternative explanations also for the status quo bias that see a particular role for a certain type of switching cost, namely the uncertainty of trying something different or new. The bias may be a general defense against unintended consequences: the present option is arguably less likely to result in an unanticipated bad outcome than an untried option. This logic is echoed in switching surveys, where some non-switchers worry about unanticipated mishaps during the switching process (Xavier and Ypsilanti 2008). Another possible explanation is that status quo and default options signal the preferences of other people. Bikhchandani, Hirshleifer, and Welch (1998) coined the term "information cascades" to describe how agents facing an uncertain choice may perceive the behavior of others as helpful information, especially where an individual believes others understand the available options better. The empirical evidence for such effects is extensive (Hirschleifer and Teoh 2003). The unique combination of features that characterizes telecommunications markets, especially complexity and speed of technological change, makes them good candidates for information cascades and other forms of behavioral convergence (see Rafaat, Chater, and Frith 2009). This alternative explanation therefore predicts a bias toward established brands and suppliers with already substantial market share.
The outcome of this scientific debate about causes of the endowment effect and status quo bias and the closeness of the analogy to consumer choice has implications for whether increased switching would be in consumers' interests. Kahneman (2011, 338-339) argues that loss aversion is costly to individuals in the long run. To the extent that it presents a barrier to entry for new telecommunications providers,
limiting their ability to attract customers, loss aversion may also reduce choice and innovation. Hence, assuming loss aversion is to blame for low switching, it might be ultimately beneficial for consumers to have their freely formed but loss-averse preferences challenged. On the other hand, if uncertainty about value, concerns about unintended consequences, or behavioral convergence are to blame, then it is unclear whether encouraging switching is beneficial. Consumers may be correctly assessing their likelihood of making good choices, or perhaps taking advantage of the wisdom of the crowd. It is important to note that if this latter explanation is right, it does not imply that the market is efficient. Consumers would still be leaving money on the table even if taking a reasoned approach to their ability to locate it.
The uncertainty over private value faced by telecommunications consumers suggests another potential influence: "ambiguity aversion." It is well-known that we tend to be risk-averse, perhaps less well-known is that we are more averse to certain kinds of uncertainty. Ellsberg (1961) showed that people prefer an option where risk can be quantified to one where it cannot, even if the actual risk faced is the same, i.e., we dislike ambiguity about the level of risk. (2) Ellsberg's work on ambiguity aversion was extended by Heath and Tversky (1991) and again by Fox and Tversky (1995), who developed and tested the "competence hypothesis." The idea is that ambiguity aversion results from our feelings of competence, defined by how much we feel we know of what could be known. The competence hypothesis is supported by experimental evidence that shows we prefer to take risks in relation to familiar events rather than unfamiliar events, even if the actual level of risk is equivalent. Put simply, the more we know of the domain in question, the more willing we are to take on a given risk.
Given technological change, multiple dimensions of value and ongoing innovation in tariffs, only a few consumers are likely to feel highly competent when selecting telecommunications equipment and contracts. Consequently, consumers may be unwilling to accept risks that they might accept in markets where they feel more competent. The competence hypothesis is, in effect, a heuristic: we assume that our familiarity with a domain of reasoning is a useful guide to how accurately we will be able to judge risks in that domain. How beneficial the heuristic is depends on how good this assumption is.
Empirical work by Wilson and Waddams Price (2010) provides insight here. In this detailed study of switching decisions and related usage patterns in the residential UK electricity market, between 20 and 32% of consumers who tried to switch to a cheaper supplier in fact ended up paying more. Less than 20% switched to the supplier offering the highest saving. This means that even though the majority of switchers saved money, the chance of a costly mistake turned out to be strikingly high. It is surely higher still for more complex telecommunications products. Electricity is a standardized product with a more straightforward tariff structure. Consumers of electricity have much experience and consumption is a matter of long-term habit. Given this, consumers ought to feel less competent when assessing telecommunications offerings than when considering electricity offerings. For many, therefore, the risk of making a mistake when switching contracts may be substantial. As the next section will show, many consumers do not select the lowest cost tariff even when choosing within a limited range.
Hence, to the extent that low switching reflects ambiguity aversion, identifying the consumer interest is problematic. Even where potential benefits from switching exist, where the gains are substantial, and where consumers can be successfully urged to shop around, gains to the consumer may not be realized by increased switching. Wary of their competence in dealing with such a complex and technological offering, many consumers may be accurately assessing the likelihood of making an error.
Procrastination and Inertia
Two other behavioral findings that may also be of relevance to switching follow from the now extensively reported finding that we value immediate benefits much more highly than future ones (see Frederick, Loewenstein, and O'Donoghue 2002). The finding extends to our use of time: we are more willing to give up time in the future to do effortful tasks than we are to give up our precious time in the present. Models of procrastination (e.g., O'Donoghue and Rabin 2001) show how this "hyperbolic discounting" might lead us to decide to give up time tomorrow to complete a boring task, such as wading through competing contracts for telecommunications services, but that when tomorrow comes around we take the same decision and put the task off again, and so on. Inertia may also be produced simply by inattention: in the absence of a salient signal of the benefits, we simply do not consider switching. Thus, even consumers who believe they would gain, or would believe so if they paid the matter attention, may fail to get around to switching.
Unlike the previous biases discussed, it is not clear that procrastination and inertia are likely to afflict telecommunications more than other markets, although product complexity may arguably make the process of giving up time to consider a switch generally more arduous than in other markets. As elsewhere, the consumer interest may be advanced by the provision of salient information as to where larger consumer gains might be made, spurring into action those who are simply failing to get around to it. As with interventions to overcome loss aversion, this entails attempts to override freely formed consumer preferences. However, in this case, the preferences implied are not consistent over time and there is evidence that consumers themselves adopt strategies to overcome their own short-termism (see below). The more difficult issue is determining whether reluctance to switch reflects mere inertia, or whether the reasons for not switching are better founded.
Summary of Resistance to Switching
The behavioral economic analysis of switching offered in this section has related several empirically established phenomena of behavioral economics to the likelihood that consumers switch supplier. The uniqueness of the telecommunications market, entailing greater complexity and uncertainty over private value than other consumer markets, means that most of these effects can be expected to have a particularly strong influence in telecommunications markets. These phenomena are psychological regularities of human decision making that mostly depart from the model of the consumer as a rational utility optimizer with stable preferences. Because the causes and prevalence of these phenomena remain the subject of scientific debate, they raise a number of competing and potentially complementary explanations for unwillingness to switch. More evidence is required to determine what combination of these forces accounts for observed patterns of switching. Yet, importantly, the analysis raises the possibility that while willingness to switch might be considered an indicator of healthy competition, the widely adopted practice by those keen to promote consumer interests of encouraging consumers to switch and to shop around may not necessarily improve consumer welfare. The outcome depends on the balance between the forces identified. This thorny problem is considered further in the final section.
As with other billable services, when telecommunications consumers choose between contracts, they must estimate future usage. Ultimate usage is determined by the cumulative effect of very many separate decisions about whether to make a call, send a text, read a blog, watch a video stream, play a game and so on. Mobile telecommunications equipment means these decisions are now taken continually throughout the day. This section examines the potential implications of this unprecedented time structure of consumer decision making. In addition to demands for time-consistent decision making, it brings a further set of behavioral phenomena into play, those relating to forecasting biases.
As described above, we do not generally display time-consistent behavior. Instead, we find it hard to resist immediate temptations for which we will pay a price at a later stage--people struggle with self-control. This phenomenon has been observed in countless experiments (Frederick, Loewenstein, and O'Donoghue 2002) and a range of markets in the field (DellaVigna 2009). It is therefore likely that a proportion of telecommunications consumers will succumb to the temptation to overuse the service, such that day-by-day usage exceeds the level that they would more generally desire. In this sense the market bears a resemblance to the markets for credit cards and store cards. Some consumers in these markets are known to find it difficult to select optimal contracts because of failure to control usage (e.g., Ausubel 1999). Self-control problems are likely to be compounded by online content that may be partly addictive, such as gambling opportunities, gaming, social networking, shopping or pornography.
Yet people are frequently aware of their own self-control problems. Field evidence shows that we seek pre-commitment strategies to constrain our future behavior (Ariely and Wertenbroch 2002; DellaVigna and Malmendier 2004). From the consumer's perspective, pre-commitment may make sense but can be costly. Gym-goers pay large upfront membership fees to incentivize themselves to exercise, but some undertake fewer gym sessions than they intend and thus experience little benefit at considerable cost. Smokers buy expensive small packets to try to reduce the amount they smoke, thus paying more per cigarette than they would buying cheaper large boxes.
Given the time-structure of decisions in telecommunications, the cost of self-control might be expected to be substantial. Despite the generally lower call costs with bill-pay, pre-payment is common and offers a possible self-control mechanism--one frequently imposed on children by parents. An alternative is to opt for a tariff with a flat rate component, such as a pure flat rate, a three-pan tariff, (3) or a cost-cap tariff. (4) Theoretically, in comparison to a perfectly competitive market model, such tariffs are economically inefficient, since they contain large ranges over which consumers face zero marginal cost and hence are likely to consume suboptimal quantities. In practice, they may provide consumers with a degree of insurance against excessive usage, although the insurance principle cannot explain why so many consumers opt for three-part tariffs with steep per-unit charges above allowances.
Whether consumers pay for some insurance or otherwise, choice of optimal contract requires estimation of likely future behavior and associated probabilities. Evidence is accumulating that many telecommunications consumers are probably making suboptimal tariff choices (Bar-Gill and Stone 2009; Gerpott 2009; Grubb 2009; Lambrecht and Skiera 2006). The last of these studies estimated the cost to consumers associated with tariff choice from usage records at a German internet provider. Data covered five months and approximately 11,000 customers, choosing among three types of tariff: a flat-rate and two three-part tariffs with different download allowances. The study built on a previous debate regarding the extent of detriment due to suboptimal choice of tariff in local fixed-line telephony (e.g., Miravete 2002; Train, McFadden and Ben-Akiva 1987). It is important to note, however, that the context in which these previous studies took place preceded the development of the unique features of modern telecommunications markets identified here, which are hypothesized to have made time-consistent behavior less likely. Lambrecht and Skiera found many consumers would have had substantially lower bills on a different tariff. One-in-five on the flat rate would have paid less on another tariff in each of the five months studied. The majority of consumers on the three-part tariff with the higher fee would have fared better on one of the other two tariffs, mostly the one with the lower fee and allowance. A smaller proportion on both three-part tariffs (around 5%) would have been better on a higher fee or flat rate. Overall, the effects were very large. Over half of the consumers with a higher flat-rate component than justified by usage alone were paying more than 100% higher bills than they could have. The firm was more than doubling its customer lifetime value for consumers on the wrong tariff.
These findings, identified over a choice of just three tariffs at a single provider, are consistent with the notion that consumers struggle to estimate and control future usage. Indeed, when Lambrecht and Skiera surveyed customers of the provider, they confirmed that uncertainty and concern over future usage played a role. The preference for the flat rate was associated with a stated desire for insurance against high bills, overestimation of likely usage and enjoyment of surfing without simultaneously worrying about increasing the bill (the "taxi-meter effect"). The implication is that consumers paid for insurance against bill-shock and for the peace of mind of surfing without incremental charge.
How troubling are such findings from a pro-consumer perspective? On the face of it, many consumers appear to make suboptimal choices. Yet it might be argued that in purchasing peace of mind consumers behave rationally; they pay more for what is, in effect, an enhanced product. But they pay very much more. We do not know how the relevant consumers would respond were they to be made aware that the additional price paid was such a high proportion of what could be paid for the same level of usage--more than twice as much in Lambrecht and Skiera's study. There are other insurance markets where consumers pay surprisingly high prices for insurance against relatively small financial risks, although it is possible, perhaps likely, that consumers in such markets are also making mistakes (see Schwarcz 2010, for examples and discussion). While it is usually possible to construct a set of preferences to rationalize what appear to be consumer errors, the extent of additional cost in this case is sufficiently large that it is hard to escape the conclusion that choices are suboptimal. Bar-Gill and Stone (2009) reach a similar conclusion in their analysis of cell phone contracts, in which they also show that consumer decisions are difficult to rationalize by other means. Moreover, paying for insurance and peace of mind may not be the whole story.
Overconfidence and Miscalibration
Two related but distinct phenomena, often categorized under the umbrella term "overconfidence bias," occur when people estimate future outcomes. First, we tend to be too optimistic in relation to our own outcomes. Second, we think our assessments are more accurate than they in fact are, so that the probability of outcomes far removed from our assessments is underestimated--we "miscalibrate." Overconfidence of both types has been recorded in market settings (DellaVigna 2009).
An overly optimistic consumer will overestimate his or her ability to increase or decrease usage as desired. A miscalibrated consumer will underestimate variability in usage. Thus, overconfidence of both types means that both underestimation and overestimation of usage are more likely. Consequently, we should expect to observe, simultaneously, consumers whose usage is too low on a flat rate and other consumers who overuse on a measured rate. In other words, overconfidence offers an alternative explanation for the high proportion of consumers on tariffs that do not minimize their bill (Bar-Gill and Stone 2009; Lambrecht and Skiera 2006).
Grubb (2009) shows that overconfidence among consumers can also explain why three-part tariffs are both offered by providers and accepted by consumers. If consumers erroneously believe that they will make sufficient use of but not surpass the allowance, they will find three-part tariffs attractive. Meanwhile firms will make extra profits from those who pay for service they do not use and those who pay high rates because they exceed allowances. The popularity of three-part tariffs is hard to explain through insurance or taxi-meter effects, which do not provide a rationale for the high rates typically applied above allowances. Rather, consumers appear to think they will not end up paying these rates. Analyzing transaction data for student mobile telephone contracts, i.e., data from consumers who had recently made an active choice, Grubb (2009) found that a large proportion of consumers consumed insufficiently to justify a high flat fee. Furthermore, allowances of call minutes were also exceeded in 17% of billing periods, by an average of 43%. Bar-Gill and Stone (2009) report similar proportions for a different sample of consumers.
The existence of substantial minorities paying high rates for exceeding allowances, coupled with many consumers using only a small proportion of allowances, supports the overconfidence account. Of particular concern from the consumer perspective, overconfidence bias offers a plausible explanation for the existence and popularity of three-part tariffs that are otherwise difficult to account for. Thus, both theoretical and empirical analyses suggest that these contracts may have come to dominate many telecommunications markets because they exploit an identifiable consumer bias.
Summary of Suboptimal Choice
Although still comprising a relatively small pool of studies, evidence is accumulating that contract choice in modern telecommunications markets may be suboptimal and that the associated consumer detriment could be considerable. As predicted by the analysis of the time structure of decision making, consumers appear to struggle with self-control and with estimation of future usage. The result is that some may be paying excessively for insurance against runaway bills, while others substantially overestimate or underestimate usage. For large proportions of consumers in both internet and mobile telephone markets, present evidence suggests the size of bills frequently greatly exceeds the minimum for the level of usage. These findings are consistent with the incidence of "bill shock," which is one of the primary grounds for the increasing volume of complaints about suppliers (Xavier 2011). The popularity of three-part tariffs is arguably itself an indication of suboptimal choice. If consumers made good choices, it is hard to see a theoretical rationale for the high rates charged for exceeding allowances, which would not be collected. Thus, these tariffs appear to exploit decision-making biases.
CONCLUSIONS AND DISCUSSION
The requirements for consumers to make simultaneous judgments across multiple dimensions of value, to value hugely varied experiences, to understand the benefits of new technology, and to make many time-consistent decisions per day, make telecommunications markets unique. This decision-making environment is likely to foment empirically established behavioral biases. Consistent with this central thesis, recent evidence suggests that modern telecommunications markets, for all the product benefits they bring to consumers, operate less efficiently than many other markets. A sizable proportion of consumers forego gains and fail to opt for the lowest cost tariff. The extent of potential consumer detriment warrants attention. This final section summarizes some challenges and policy issues from a pro-consumer perspective and tentatively suggests ways that they might, if not be met, at least be approached, including via targeted research.
Encouraging consumers to shop around is a staple of pro-consumer policy and consumers' willingness to switch providers may be an indication of healthy competition. Yet the observation of low switching in a market does not necessarily imply a positive outcome from policies that successfully promote it. Such an outcome would require that marginal switchers who were spurred into action took beneficial decisions. If their reluctance to be active is a mistake or reflects pure inertia or inattention, encouraging activity may, indeed, be beneficial. But if it results from lack of confidence in their ability to make good choices, the benefit to the marginal switcher may not be worth the cost.
Two as yet unanswered empirical questions are critical. First, how much surplus are consumers sacrificing by not switching to lower-cost providers over the medium to long term? This question is, in principle, answerable through research that compares actual usage to available offerings among panels of consumers. The second question is less easy to answer. How well-founded is consumers' reluctance to switch? Loss aversion is a descriptive rather than normative account of decision-making. If its role can be firmly established, the implication is that consumers have disadvantageous preferences; they possess an arbitrary attachment to their existing provider that leads them to forego gains. If so, then encouragement to overcome this attachment and to switch, through advertising, awareness campaigns or other salient ways to promote switching, might appear reasonable. Note that such interventions adopt the position that consumers making free choices in this market do not know what is good for them.
However, while failing to switch to a better value provider is detrimental, so is switching for little or no gain. It remains possible that consumers' disinclination to switch is more reasonable than it initially appears, based on the not insignificant probability of making an error when choosing between complex deals involving products of uncertain private value dependent on uncertain future behavior. Even knowing that there are gains to be made, consumers may correctly feel that they lack the expertise to harvest them reliably. If so, interventions designed to boost activity could backfire, prompting consumers to waste time and effort trying and failing to save significant amounts, or worse still signing up to inferior deals. In such a context, the provision of comprehensible and reliable information about competing offerings, for instance via accredited price comparison sites, has not only the potential to increase consumers' perceived competence and hence activity, but simultaneously to help consumers to reach better decisions. Given the implied extent and impact of consumer uncertainty, there may also be a need to focus on ways to increase trust and guarantee quality.
Since the appropriate action depends on the cause of low switching, research that might identify that cause more clearly would be of great value. One possibility is to combine behavioral experiments and surveys with data on market behavior at the individual level. Are reluctant switchers more loss-averse individuals? In addition, research might focus more on the marginal switcher. Do those who switch provider in response to promotions or campaigns make significant gains? What proportion make a loss and what are their characteristics?
Consumers may indeed be right to be cautious regarding their own ability to identify good deals. Accumulating evidence points to problems deciding between tariffs, because of the difficulty of forecasting and controlling usage. Note that the extent of consumer detriment here could be even greater than implied by the studies cited above, which center on a single firm or population of students choosing from a limited range of products. Research is required to, first, gauge consumers' response to the gap between what they pay and the minimum they could pay for the same usage and, second, to estimate lost consumer surplus more accurately.
Flat rates and three-part tariffs can be partly justified on the grounds that consumers enjoy consumption more without a meter continually ticking away. But where bills are effectively being doubled by underuse and rates for overstepping allowances greatly exceed average per unit cost, there is a danger that flat-rate components within tariffs amount to consumer traps, exploiting consumer biases by profiting from both those who overestimate usage and those who underestimate it. Consequently, regulators might consider stronger interventions. The magnitude of higher rates relative to average per unit cost could be limited. Or particular types of salient feedback could be mandated where consumers are paying more than they could. One potential avenue for policymakers might be to exploit the available technology to assist consumer decision making. For instance, providers could be mandated to disclose easily interpretable information that can be used to monitor usage during the current billing period, in addition to feedback on previous periods. There is scope for experimentation to determine the best form of disclosure. Providers, who are already able to offer a sophisticated range of interactive services, could be required to give consumers one-click access to easily interpretable data on their remaining minutes, texts or megabytes, just as they can observe the remaining power in a phone battery. Similarly, Bar-Gill and Stone (2009) suggest that providers could be mandated to alert consumers when their usage approaches the allowance. Such simple mechanisms might aid self-control and consumer learning, and could be easily piloted for effectiveness. Given that technological advances offer such unprecedented access to innovative services and media, it would seem reasonable that they also be used to make services more "decision friendly."
Finally, one oft-repeated criticism of behavioral economics is that it supports excessive intervention in markets. Two points might be made in response. First, behavioral economics also suggests ways in which potential interventions can be assessed experimentally prior to implementation, to increase the likelihood of beneficial outcomes. Second, while the focus of the present discussion has been new solutions, the analysis also suggests there may be old regulations that are ineffective and could be scrapped. Micklitz, Reisch, and Hagen (2011,272) describe the modern consumer legal system as "saturated with information duties." Yet, given the biases discussed here, stringent requirements on firms to provide detailed information may do little to improve consumer decision making. Behavioral methods suggest ways the effectiveness of such regulations can be tested, with a view to terminating non-performing ones. Thus, behavioral economic analysis has the potential to reduce burdensome regulation, as well as to suggest beneficial interventions for consumers.
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(1.) It is possible to argue that citing loyalty and uncertainty as reasons for not switching might reflect switching costs associated with the effort required to learn about alternative offerings. But where these reasons are selected by survey respondents ahead of hassle and not having the time, which are more direct references to individual effort, it seems more likely that other motivations for not switching are being expressed.
(2.) Ellsberg showed this through examples of people's willingness to bet on the color of balls drawn from an urn. We instinctively value a bet more highly when we know that an urn contains balls of two colors split 50 50 than when we know that the urn contains balls of two colors in an unknown proportion, although the expected value of such bets is identical.
(3.) A three-part tariff involves a fixed fee in return for an allowance (or suite of allowances such as calls, texts and megabytes) of units of the product supplied at zero marginal price, with units consumed beyond the allowance charged at a positive marginal price, often a very much higher unit price.
(4.) A cost-cap tariff is a pay-per-use tariff only up to a predefined cap.
Peter D. Lunn (firstname.lastname@example.org) is a Behavioral Economist at the Economic and Social Research Institute (ESRI) in Ireland and Lecturer in the Department of Economics, Trinity College Dublin. The author is grateful to the ESRI Program of Research in Communications for funding, which in turn was funded by the Irish Department for Communications, Energy and Natural Resources and the Commission for Communications Regulation (ComReg), to Sean Lyons for helpful comments on early drafts, to seminar audiences at ComReg and the Competition Authority in Ireland, and to an anonymous reviewer for incisive comments.…