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Surge pricing is a variant of dynamic pricing (also known as variable pricing). The dynamics of prices means that prices can now change much more frequently and vary across customers, time and place at ever higher resolution; a price surge or hike at peak moments in demand can be described as an outcome of dynamic pricing. Surge pricing received great attention due to Uber’s application of this strategy, and not least because of the controversial way that Uber implemented it. But dynamic pricing, and surge pricing within it, is a growing field with various forms of applications in different domains.

A price surge is generally attributed to a surge in demand. In the case of Uber, when the number of customer requests for rides (‘hailing’) critically exceeds the number of drivers available in a given geographic area, Uber enforces a ‘surge multiplier’ of the normal (relatively low) price or tariff (e.g., two times the normal price). The multiplier remains in effect for a period of time until demand can be reasonably met. The advantages, as explained by Uber, are that through this price treatment (1) drivers can be encouraged to join the pool of active drivers (i.e., ready to receive requests on Uber app), as well as  pulling drivers from adjacent areas; and (2) priority can be given to a smaller group of those customers who are in greater need of prompt service and are willing to pay the higher price. Consequently, waiting times for customers willing to pay the price premium will be shorter.  (Note: Lyft is applying a similar approach.)

There are some noteworthy aspects to the modern surge pricing. A basic tenet of economic theory says that when demand surpasses the supply of a good or service, its price will rise until a match is reached between the levels of demand and supply so as to ‘clear the market’. Yet the neo-classic economic theory also assumes that the equilibrium price applies to all consumers (and suppliers) in the market for a length of time that the stable equilibrium prevails; it does not account well for temporary ‘shocks’. Proponents of surge pricing argue that this pricing strategy is an appropriate correction to a market failure caused by short-term ‘shocks’ due to unusual events in particular places. There is room in economic theory for more complex situations that allow for price differentials such as seasonality effects or gaps between geographic regions (e.g., urban versus rural, central versus peripheral). Still, seasonal prices are the same “across-the-board” for all; and regions of different geographic markets are usually well separated. On the other hand, in surge pricing, and in dynamic pricing more broadly, it is possible through advanced technology to isolate and fit a price to a very specific group of consumers in a given time and space.

One of the concerns with surge pricing in ride e-hailing is that the method could take advantage of consumers-riders when they have little choice, cannot afford to wait too long (e.g., hurry to get to a meeting or to the airport) or cannot afford a price several times higher than normal (e.g., multipliers of more than 5x). The problem becomes more acute as surge pricing seems to ‘kick in’ at worst times for riders, when they are in distress [1a](e.g., in heavy rain, late at night after a party). The method seems to screen potential riders not based on how badly they need the service but on how much they are willing to pay. The method may fix a problem for the service platform provider more than for its customers. Suppose hundreds of people are coming out at the same time from a hall after a live music concert. If the surge multiplier shown in the app at the time the prospect rider wants to be driven home is too high because of the emerging peak in demand, he or she is advised to wait somewhat longer until it slides down again. How long should riders wait for the multiplier to come down? Often enough, so it is reported, it takes just a few minutes (e.g., minor traffic fluctuations). But in more stubborn situations the rider may be able to catch a standard taxi by the time the multiplier declines, or if the weather permits, walk some distance where one can hail a taxi or get onto another mode of public transport.

Another pitfall is reduced predictability of the occurrence of surge pricing. Consumers know when seasons start and end and can learn when to expect lower and higher prices  accordingly (though it used to be easier thirty years ago). In public transport, peak hours (e.g., morning, afternoon) are usually declared in advance, wherein  travel tariffs could be elevated during those periods. Since surge pricing is based on real-time information available to the service platform provider, it is harder to predict the occasions when surge pricing will be activated, and furthermore the extent of price increase. Relatedly, drastic price changes (e.g., due to high frequency of updates, strong fluctuations) tends to increase the uncertainty for service users [1b].

The extent of price surge or hike is a particular source of confusion. Users are notified before hailing a Uber driver if surge is on, and a surge multiplier in effect at that time should appear on the screen. The multiplier keeps being updated on the platform. It is sensible, however, for the multiplier to stay fixed for an individual rider after the service is ordered. Thus the rider can make a decision based on a known price level for the duration of the ride (or an estimate of the cost to expect). Otherwise, the rider may be exposed to a rising price rate while being driven to destination — but the rider should also benefit if the multiplier starts to slide down (or entering another area where surge is off). The first scenario resembles more a situation of bidding whereas the latter scenario looks more like gambling. Stories and complaints from Uber users reveal recurring surprises and unclarity about the cost of rides (e.g., claims the multiplier was 9x, a ride of 20 minutes that cost several hundreds of dollars, a claim the multiplier dropped but the total price did not go down in accordance). Users may not pay attention sufficiently to the multiplier before hailing a ride, do not comprehend how the pricing method works, or they simply lose track of the cost of the ride (i.e., the charge is automatic and appears later on the user’s account).

Discontent of customers may also be raised by a sharp contrast experienced between the relatively low normal price rate (e.g., compared with a standard taxi) and the high prices produced by surge multipliers [1c].  A counter argument contends that the price hikes or surges allow for low rates at normal times by subsidising them [2]. More confusion about Uber’s pricing algorithm could stem from reports on additional factors that the company might use as input (e.g., people are more receptive of surge prices when the battery of their mobile phone is low, and customers are more willing to accept a rounded multiplier number than a close non-rounded figure just below or above it (MarketWatch.com, 28 December 2017).

  • Not even a strategy of surge pricing appears to be completely immune to attempts of manipulation. It was revealed in 2019 that drivers with Uber (and also Lyft’s) have tried to game the surge mechanism. The ‘trick’ is to turn off the app at a given time in a coordinated manner among drivers, let the surge multiplier rise, and then turn on the app again to gain quickly enough from the higher rate as long as it prevails. The method seems to have been used especially at airports in anticipation of incoming passengers, based on the knowledge of drivers of several flights scheduled to land during a short interval. The motivation for taking this action: the drivers claim they are not paid enough at normal times by the platform operators (BusinessInsider, 14 June 2019).

Uptal Dholakia, a professor of marketing at Rice University (also see [1]), suggested four remedies to the kinds of problems described above. First, he advised to set a cap (maximum) on surge multipliers and notify customers more clearly about them (greater transparency). In addition, he recommended curbing the volatility of price fluctuations and communicating better the benefits of the method (e.g., reduced waiting times). Dholakia also raised an issue about a negative connotation of the term ‘surge’ that perhaps should be replaced in customer communications [3].

Various forms of dynamic pricing, including surge pricing, are already utilised in multiple domains. It is noted, for instance, that the strategy of Uber was not initiated to resolve problems of traffic congestion; ‘surge’ may be activated as its result but the purpose is to resolve the interruptions that congestion may cause to the service. For dealing with traffic congestion and overload in roads, other types of surge pricing are being used by public authorities. First, a fast lane is dedicated on a highway or autoroute (e.g., entering a large city) for a fee — the amount of ‘surge’ fee is determined by the density of traffic on the other regular lanes. Drivers who wish to arrive faster should pay this fee that is displayed on a signboard as one approaches entry to the lane (a few moments are allowed to decide whether to stay or abort). Second, a congestion fee, which could actually be a variable surge fee, may be imposed on non-residents who seek to enter the municipal area of a city at certain hours of the day.

As indicated earlier, public transportation systems in large cities may charge a higher tariff during peak or rush hours. The time periods that a raised tariff applies are usually declared in advance (i.e., they are fixed). Peak and off-peak rates may apply to different types of travel fares. The scheme is employed to encourage passengers who do not really need to travel at those hours to change their schedule and not further load the mass transportation system. There is of course a downside to this approach for passengers who must travel on those hours, such as for getting to work (employers who cover travel expenses should set the amount according to the cost of the more expensive rate). Using surge pricing in this case would mean that passengers cannot tell for certain and in advance when a higher tariff applies, but the scale of ‘surge prices’ can be pre-set with a limited number of ‘steps’, and thus reduce resentment and opposition.

Other types of dynamic (variable) pricing involve strong technological and data capabilities, including demand at an aggregate level and customer preferences and behaviour (search, purchase) at the individual level. A company like Amazon.com keeps updating its prices around the clock based on data of demand for products sold on its e-commerce platform. A more specific type of dynamic pricing entails the customisation of prices quoted to individual users-customers (i.e., different prices for the same book title offered to different customers). The approach maintains that a higher price could be set, for instance, for books in a category in which the customer purchases books more frequently and even based on search for titles in categories of interest. This form of price customisation is debatable because it aims to absorb a greater portion of the consumer’s value surplus (i.e., how much value a consumer assigns to a product above its monetary price requested by the seller), raising concerns of unfairness and discrimination. The risk to sellers is of making products less worthwhile to consumers to buy at the higher customised prices. (Note: Amazon was publicly blamed of using some form of price customisation in the early 2000s after customers discovered they had paid different prices from their friends; however the practice has not been banned and it is suspected to be in use by companies in different domains.)

  • Take for example the air travel sector: Airlines may use any of these methods of variable pricing: (a) Offering the same seat on the aircraft at different price levels (‘sub-classes’) depending on the timing of reservation before the scheduled flight: the earlier a reservation is made, the lower the price; (b) Changing fares for flights to different destinations based on fluctuations in demand for each destination and time of flight; (c) There are claims that airlines also adjust upwards the fares on flights to destinations that prospect travellers check more frequently in the online reservation system.

More companies in additional sectors are expected to join by applying varied forms of dynamic pricing. Retailers with physical stores are expected foremost to use dynamic pricing more extensively to tackle the growing challenges they face particularly from Amazon.com in the Western world (e.g., supermarkets will employ digital price displays that will allow them to change prices more continuously during the day and week according to visitor traffic levels). Restaurants may set higher prices during more busy hours at their premises, and hotels are likely to vary their room rates more intensively, taking into consideration not only seasonal fluctuations but also special events like conferences, festivals and fairs (e.g., see “The Death of Prices”, Axios, 30 April 2019).

Dynamic pricing, and surge pricing in particular, is the new reality in pricing policy, with applications getting increasingly pervasive. As technological and analytical capabilities only improve, the pricing models and techniques are likely to be enhanced and become furthermore sophisticated. Moreover, methods of artificial intelligence will improve in learning patterns of market and consumer behaviour, expected to enable companies to set prices with greater specificity and accuracy. At the same time, businesses need to take greater caution not to deter their customers by causing excessive confusion and aggravation. The question then becomes: What bases of discrimination — among consumers, at different times, and in different locations — would be considered fair and legitimate? This promises to be a major challenge for both enterprises that set prices and for the consumers who have to judge and respond to the dynamic prices.

Ron Ventura, Ph.D. (Marketing)

Notes:

[1a-c] “Uber’s Surge Pricing: Why Everyone Hates It?”, Uptal M. Dholakia, Government Technology (magazine’s online portal), 27 January 2016

[2] “Frustrated by Surge Pricing? Here’s How It Benefits You in the Long Run”, Knowledge @Wharton (Management), 5 January 2016. A talk with Ruben Lobel and Kaitlin Daniels at Wharton Management School at the University of Pennsylvania.

[3] “Everyone Hates Uber’s Surge Pricing — Here’s How to Fix It”, Uptal M. Dholakia, Harvard Business Review (Online), 21 December 2015

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Health insurance, financial investments, telecom service plans — consumers frequently find it harder to make choice decisions in these exemplar domains. Such domains are more susceptible to exhibiting greater complexity: details, many and technical, to account for, multiple options difficult to differentiate and to choose from, and unclear consequences. In products, we may refer in particular to those involving digital technology and computer-based software that some consumers are likely to find more cumbersome to navigate and operate. When consumers are struggling to make any choice, they develop a stronger tendency to delay or avoid the decision at all. They need assistance or guidance in making their way towards a choice that more closely matches their needs or goals and preferences.

Handel and Schwartzstein (2018) are distinguishing between two mechanism types that obstruct or interfere with making rational decisions: frictions and mental gaps.

Frictions reflect costs in acquiring and processing information. They are likely to occur in earlier stages of a decision process when consumers are encountering difficulties in searching for and sorting through relevant information (e.g., what options are more suitable, what attributes and values to look at), and they have to invest time and effort in tracing the information and organising it. Furthermore, frictions may include the case when consumers fail to see in advance or anticipate the benefits from an available alternative  (e.g., consider the difficulty of older people to realise the benefits they may gain from smartphones).

Mental gaps are likely to make an impact at a more advanced stage: the consumer already has the relevant information set in front of him or her but misinterprets its meanings or does not understand correctly the implications and consequences of any given option (e.g., failing to map correctly the relation between insurance premium and coverage). Mental gaps pertain to “psychological distortions” that generally may occur during information-gathering,  attention and processing, but their significance is primarily in comprehension of the information obtained. In summary, it is “a gap between what people think and what they should rationally think given costs.”

In practice, it is difficult to identify which type of mechanism is acting as an obstacle on the way of consumers to a rational decision.  Research techniques are not necessarily successful in separating between a friction and a mental gap as sources of misinformed choices (e.g., choosing a dominated option instead of a dominating one apparent to the rational decision-maker). Notwithstanding, Handel and Schwartzstein are critical of research practices that focus on a single mechanism and ignore alternative explanations. In their view, disregard to the distinction between mechanisms can lead to spurious conclusions. They suggest using counterfactual approaches that test a certain mechanism, or a combination of explanations, and then argue against it with a ‘better’ prospective mechanism explanation. They also refer to survey-based and experimental research methods for distinguishing frictions and mental gaps. The aim of these methods is to track the sources of misinformed decisions.

Consumers often run into difficulty with financial investments and saving plans. In some countries policy makers are challenged with driving consumers-employees towards saving for retirement during the working years. Persuasion per se turns out to be ineffective and other approaches for directing or nudging consumers into saving are designed and implemented (e.g., encouraging people to “roll into saving” through a scheme known as ‘Save More Tomorrow’ by Thaler and Sunstein).

Confronting employees with a long list of saving plans or pension funds may deter them from duly attending to the alternatives in order to make a decision, and even risks their aborting the mission. When consumers-employees have a hard time to recognise differences between the plans or funds (e.g., terms of deposit, assets invested in, returns), they are likely to turn to heuristics that brutally cut through the list. Crucially, even if information on key parameters is available for each option, decision-makers may use only a small part of it. Similar difficulties in choosing between options may arise in financial investments, for instance when choosing between equity and index funds or bond funds. One may be assisted by suggesting a default plan (preferably, recommending a personally customised plan) or sorting and grouping the proposed plans and funds into classes (e.g., by risk level or time horizon). However, it should be acknowledged that consumer responses as described above may harbour frictions as well as mental gaps, and it could help to identify which mechanism has the greater weight in the decision process.

A key issue with health insurance concerns the mapping of relationship between an insurance premium and the level of deductibles or cost-sharing between the insurer and the insured. For example, consumers fall into a trap of accepting an insurance policy offered with a lower premium while not noticing a higher deductible they would have to pay in a future claim. An additional issue consumers have to attend to is the coverage provided for different medical procedures such as treatments and surgeries (given also the deductible level or rate). Consumers may stumble in their decision process while studying health insurance plans as well as while evaluating them.

  • Public HMOs (‘Kupot Holim’) in Israel offer expanded and premium health insurance plans as supplementary to what consumers are entitled to by the State Health Insurance Act. Yet in recent years insurance companies are prompting consumers to get an additional private health insurance plan from them — their argument is that following changes over the years in the HMOs’ plans and reforms by the government, those plans do not offer adequate coverage, or none at all, for more expensive treatments and surgeries. The coverage of private insurance plans is indeed more generous, but so are the much higher premiums , affordable to many only if paid for by the employer.

In addressing other aspects of healthcare, Handel and Schwartzstein raise the issue of consumer preference for a branded medication (non-prescription) over an equivalent and less costly generic or store-branded medication (e.g., buying Advil rather than a store-branded medication that contains the same active ingredient [ibuprofen] for pain relief as in Advil). Another vital issue concerns the tendency of patients to underweight the benefits of treatment by medications prescribed to them, and consequently do not take up medications satisfactorily as instructed to them by their physicians (e.g., patients with a heart condition, especially after a heart attack, who do not adhere as required to the medication regime administered to them).

Customers repeatedly get into feuds with their telecom service providers — mobile and landline phone communication , TV and Internet. Customers of mobile communications (‘cellular’), for example, often complain that the service plan they  had agreed to did not match their actual usage patterns or they did not understand properly the terms of the service contract they signed to. As a result, they have to pay excessive charges (e.g., for minutes beyond quota), or they are paying superfluous fixed costs.

With the advancement of technology the structure of mobile service plans has changed several times in the past twenty years. Mobile telecom companies today usually offer ‘global’ plans for smartphones that include first of all larger volumes of data (5GB, 10GB, 15GB etc.), and then practically an infinite or outright unlimited use of outgoing talking minutes and SMSs. While appealing at first, customers end up paying a fixed inclusive monthly payment that is too high relative to the traffic volume they actually make use of. On the one hand customers refrain from keeping track of their usage patterns because it is costly (a friction). On the other hand, customers fail in estimating their actual usage needs that will match the plan assigned to them (a mental gap). In fact, information on actual usage volumes is more available now (e.g., on invoices) but is not always easily accessible (e.g., more detailed usage patterns). It should be noted, however, that companies are not quick to replace a plan, not to mention voluntarily notifying customers of a mismatch that calls for upgrading or downgrading the plan.

A final example is dedicated here to housing compounds of assisted living for seniors. As people enter their retirement years (e.g., past 70) they may look for comfortable accommodation that will relieve them from the worries and troubles of maintaining their home apartment or house and will also provide them a safe and supportive environment. Housing compounds of assisted living offer residence units, usually of one or two rooms of moderate space, with an envelope of services: maintenance, medical supervision and aid, social and recreational activities (e.g., sports, games, course lectures on various topics). The terms for entering into assisted living housing can be nevertheless consequential and demanding. The costs involve mainly a leasing payment for the chosen residence and monthly maintenance fee payments.

Making the decision can be stressing and confusing. First, many elderly people cannot afford taking residence in such housing projects without selling their current home or possibly renting it (e.g., to cover a loan). In addition the value of the residence is depreciated over the years. Second, the maintenance fee is usually much higher than normal costs of living at home. Hence residents may need generous savings plus rental income in order to finance the luxury and comfort of assisted living. Except for the frictions that are likely to occur while looking for an appropriate and affordable housing compound, the prospect residents are highly likely to be affected by mental gaps in correctly understanding the consequences of moving into assisted living (and even their adult children may find the decision task challenging).

Methods of intervention from different approaches attempt to lead consumers to make decisions that better match their needs and provide them greater benefits or value. Handel and Schwartzstein distinguish between allocation policies that aim to direct or guide consumers to a recommended choice without looking into reasons or sources of the misinformed decisions (e.g., nudging techniques), and mechanism policies that attempt to resolve a misguided or misinformed choice decision by tackling a specific reason causing it, such as originating from a mechanism of friction or mental gap. From a perspective of welfare economics, the goal of an intervention policy of either type is to narrow down a wedge between the value consumers obtain from actual choices subject to frictions and mental gaps, and the value obtainable from a choice conditional on being free of frictions and mental gaps (i.e., assuming a rational decision). (Technical note: The wedge is depicted as a gap in value between a ‘demand curve’ and a ‘welfare curve’, respectively.)

Policies and methods of either approach have their advantages and disadvantages. An allocation policy has a potential for greater impact, that is, it can get farther in closing the welfare wedge.  Yet, it may be too blunt and excessive: while creating a welfare gain for some consumers, it may produce an undesirable welfare loss to consumers for whom the intervention is unfitting. Without knowing the source of error consumers make, it is argued that a nudging-type method (e.g., simplifying the structure of information display of options) could be insufficient or inappropriate to fix the real consumer mistake. A fault of allocation policies could particularly be, according to the authors, that they ignore heterogeneity in consumer preferences. Furthermore, and perhaps as a consequence, such policies overlook the presence of informed consumers who may contribute by leading to the introduction of far better products at lower prices.

Mechanism policies can in principle be more precise and effective while targeting specific causes of consumers’ mistakes, and hence correcting the costs of misinformed decisions without generating unnecessary losses to some of them. The impact could be more limited in magnitude, yet it would be measured. But achieving this outcome in practice, the authors acknowledge, can be difficult and complicated, requiring the application of some costly research methods or complex modelling approaches. They suggest that “[as] data depth and scope improve, empirically entangling mechanisms in a given context will become increasingly viable”.

The analysis by Handel and Schwarztsein of the effects of intervention policies — mechanism versus allocation — could come as too theoretical, building on familiar concepts of economic theory and models, furthermore being difficult and complicated to implement. Importantly, however, the authors open up a door for us to a wider view on sources of mistakes consumers make in decision-making and the differences between approaches aimed at improving the outcomes of their decisions. First, they clarify a distinction between mechanisms of frictions and mental gaps. Second, they contrast allocation policies (e.g., nudging) versus mechanism policies which they advocate. Third, to those less accustomed to the concepts of economic analysis, they demonstrate their ideas with practical real-world examples. Handel and Scwharzstein present a perspective well deserving to learn from.

Ron Ventura, Ph.D. (Marketing)

Reference:

Frictions or Mental Gaps: What’s Behind the Information We (Don’t) Use and When Do We Care?; Benjamin Handel and Joshua Schwartzsetein, 2018; Journal of Economic Perspectives, Vol. 32 (1 – Winter), pp. 155-178. (doi: 10.1257 / jep.32.1.155)

 

 

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The decision of the British people in a referendum on 23 June (2016) to leave the European Union (EU) — known as ‘Brexit’ — promises to emerge as a most profound event in the nation’s recent history. The result of the referendum in favour of Brexit, by a majority of 52% against 48%, was decisive yet not by a large margin; moreover, the striking differences in voting patterns between England and Scotland, and even within England, between London and other parts of the country, invoke deep tensions (In Scotland and London the Remain camp had a clear majority).

The effects of Brexit are still very early to call and are hard to predict because a departure of a member country, let alone the United Kingdom, from the EU has never been experienced so far. The effects also are expected to impact multiple areas, including politics, economics, business, social welfare and standard-of-living. This article focuses on the area of retailing; it reviews and contemplates early assessments of the plausible effects that leaving the EU can have on retailers and consumers in Britain. However, due to the early stage of the process, the ambiguity that surrounds the implications of leaving the EU, and the fact that the new British government is not enacting yet an exit from the EU (i.e., Article 50 of the EU Lisbon Treaty), one should be cautious in taking these assessments as concrete predictions about the (probable) outcomes of Brexit.

Uncertainty mixed with pessimism has claimed an immediate toll on the value of the pound sterling (particularly its exchange rate against the US dollar); stock prices have also moderately declined in London Stock Exchange, but further declines are foreseen as the process unfolds. The devaluation of the British pound is a critical factor whose effect is expected to roll for several more years. Retailers are concerned that rising prices of imported goods (e.g., food, clothing) will deter consumers. In addition, increased cost of imported raw materials and components used in production is likely to contribute to rising prices of local goods, further exerting an inflationary pressure. Positive effects that may arise from this devaluation on exports will be discussed later. The sense of “bad news” is not escaping consumers either, manifested in a quick and rather sharp decline in consumer confidence as reported by GfK marketing research firm. This could mean that consumers become hesitant and more inclined to “wait and see”, thus postponing their more costly purchases, particularly of discretionary and leisure products and services.

The Centre for Retail Research (CRR) considers multiple aspects wherein retailers and consumers are likely to be affected while entering a post-Brexit era. It is suggested that a decline of 5% in the value of the pound against the euro would be enough to compensate for new tariff barriers imposed by the EU, and the steeper decline that already occurred is a very good thing — it would help exports (e.g., e-commerce), transitioning from imports to local production, and tourism. The CRR argues that the pound was already over-priced and needed correction (note that  right after the referendum the pound declined 8% against the dollar and euro, but a slide down occurred earlier, at the beginning of this year, so against values of late 2015 the pound declined by as much as 15%). But there are additional important factors with structural implications that are noteworthy: need to fulfill changing jobs and a drive for automation; need for new worker and consumer protection laws and regulations; re-settling (digital) data protection regulation and mechanisms.

There is broad agreement that in order for Britain to retain relations with the European Single Market, it will have to continue and abide to product and data protection standards of the EU. Britain will also not be able to completely restrict worker migration from the EU. The difference will be, however, that Britain will have to work by those rules but will not have a say about them — a warning the Remain campaigners continue to critically voice. Different models are contemplated for the relations of Britain with the EU in the post-Brexit era, notably by joining Norway in the European Economic Area (EEA) or replicating the special relations of Switzerland with the EU. But the EU council nervously hurried to warn Britain, or any other country that contemplates to follow, that it should not allude itself of receiving an advantageous status as of Switzerland’s.

  • Another avenue for resolution may consider the trade arrangements of Israel as a non-member country with the EU, and its participation in Horizon 2020, a programme for science and technology research and development.

References made in the media to changes in retail sales in June seem too soon and hardly indicative of a real effect of the Brexit decision, primarily given that only ten days remained to the end of the month after the referendum (some sources suggest waiting for July’s figures). Figures also vary, depending on the basis of comparison (e.g., volume or value, last month or same month last year, all or like-for-like [same stores]). For example, sales by volume decreased 0.9% in June compared with May (2016), yet compared with June of last year (2015) they increased 4.3% (by value, sales increased just 1.5% [Britain’s Office for National Statistics (ONS): Retail Industry-Sales Index]). Different figures were published by KPMG consulting firm together with the British Retail Consortium (BRC): Their Retail Sales Monitor shows that sales grew just 0.2% in June year-on-year, but when compared on a like-for-like basis they dropped 0.5%. The BRC-KPMG monitor furthermore indicates that non-food sectors, especially fashion, were hit harder than the food or grocery sector.

Recent observed changes may be attributed at most to so-called ‘Brexit-sentiment’ . If we were to look already for a more reliable indication of an immediate post-referendum shock, the KPMG’s press release reports that sales fell particularly in the last week of June. The Financial Times (13 July ’16) indicates that according to its Brexit Barometer, day-to-day spending “may have bounced back to just slightly below what it was immediately before the June 23 referendum”. The number of visits to stores (‘footfall’) declined in the week immediately after the referendum (10% year-on-year for weekdays – especially on High Street), recovered a little in early July, followed by another a drop in visits. The fluctuations are not consistent and it is hard to conclude a trend at this time. The picture for Saturdays is even less bright: “high-street footfall on Saturdays, the most important shopping day, has now fallen year-on-year for three consecutive weeks”.

The Economist Intelligence Unit published just before the referendum a special, rather negative, report on Brexit (“Out and Down: Mapping the Impact of Brexit”). It relates to key implications of Brexit in regard to retailing: a fall of the pound, inflation in line with rise of import prices, consumer purchasing hesitation, and more complex supply chains for retailers. According to their projection, the year 2017 will be the worst for retailing; recovery will be felt during 2018-2020 as growth of retail sales volume resumes, but it will happen intermittently and sales will not return to the pre-Brexit level.

In order to better grasp how Brexit may change the direction for British economy, and for the well-being of consumers and retailers in particular, it would help to take a little longer look backwards (i.e., as far as 2007) at retail sales and some additional  indicators.

The ONS Retail Sales Index by volume (seasonally adjusted, excluding fuel): After a long period, from 2006 (shortly before the financial crisis) until late 2013, when sales volume (index) was almost stagnant at just about 100, it started lifting since early 2014 and until June this year (2016) to a level of 112.5. It has been a positive sign for return to the expansion years of a previous decade (~1996-2006). But the implementation of Brexit (i.e., at least while negotiating new trade agreements) threatens to halt the climb and impede a continued recovery of the sector from the lingering effects of the financial and economic crisis of 2007-2008 (including a ‘second spell’ in 2011-2013).

Growth in pay compared with inflation (ONS: UK Perspectives 2016 Personal & Househod Finances [Section 4]): This is an indicator of the cost of living (or the purchasing power of income from work). We may notice three distinct periods: (a) A ‘shock’ response to the financial crisis ~2008-2009 included a steep rise in consumer prices while growth in regular pay dissipated, and then a ‘correction’ of slowing price increases; (b) Inflation rate higher than growth in pay ~2010-2013 — during this period of the hardest burden on consumers, growth in pay remained at a bottom level of 1-2% while inflation climbed as high as 5% (2011) and subsequently “cooled” to 2-3%; (c) Renewal of real rise in pay ~2014-2016 as inflation starts to subdue, falling to near 0%, and pay growth reaches 2-3%. Worsening market conditions due to Brexit could lead to erosion once again of  regular (weekly) pay and suppressed consumer spending.

Household spending (ONS: UK Perspectives 2016 as above [Section 5]): The average household expenditure, inflation-adjusted, decreased from 2006 through 2012 from ~£550 to about £510 per week; then spending started to recuperate in 2013 and 2014, reaching £530. Improvement may have continued up to this year: On the one hand, regular pay increased in real terms in the past two years; on the other hand, the real disposable household income in Britain has been hovering just above £17,000 since 2006 (after a climb in previous years), though lifting its head a little in 2015. Now there is higher risk that such improvement in spending will not be possible to continue.

Consumer Confidence Index (GfK): The research firm GfK conducted a one-off special survey in the week following the referendum to measure its Consumer Confidence Barometer (CCB) (normally updated on a monthly basis). It provides a sharp demonstration of the impact of ‘Brexit-sentiment’: The (net) index value dropped from -1 in the previous survey to -9 after learning of the referendum result. The last time a similar decline (8 points) in a single month was measured occurred in 2011, and only in 1994 had a larger single drop been measured. Those belonging in the Remain camp are more negative (-13) than those in the Leave camp (-5). Respondents to the barometer are asked about the current state of the economy and their expectations over the next twelve (12) months — 60% expect the economic situation to worsen (an increase of 14% from pre-referendum). Also, 33% expect prices to rise sharply.

The Financial Times presents in its Brexit follow-up a chart of the history of GfK’s Confidence Index from 2007 to 2016: The chart shows how CCB dropped from just below 0 to -40 during the 2007-2008 crisis, recovered to -20, declined again to around -30 during the ‘second-spell’ of the economic crisis in 2011-2013, and then climbed back to a little above 0 before the referendum. A decline of CCB actually already started earlier this year, and then came the steep single drop following the Brexit referendum. Consumer confidence was already at lower (net) levels and has experienced continuous descents in the past ten years; it may likewise continue to deteriorate below -20 again after the recent drop in CCB.

A map by GfK shows variation across regions and demographic segments. Interestingly, the strongest ‘demoralising’ effect was found among the young group of ages 18-29 (decline of 13 points) compared with older groups (6-8 points off), yet the younger remain overall more positive and optimistic about the economy (index +6), especially compared with those of 50-64 of age (index -21).

  • After three years of decline in the number of retail companies in the UK running into financial difficulties, since the last peak of 2012 (54), it seems to be rising again in the first half of 2016, according to data gathered and reviewed by the Centre for Retail Research (note that not all companies going into legal administration necessarily go bankrupt and cease to operate). Growing pressure on retailers during the process of leaving the EU may put even more medium and large retailers (in number and size of stores) at risk of failure.

After a significant drop last year, number of retailers in trouble looks to be rising again in 2016

The depriciation of the British pound is expected to facilitate selling and increase exports to foreign consumers in other countries through e-commerce (i.e., retailing or shopping websites) by retailers residing in the UK. Especially during the period that existing trade agreements are still valid, it would be the best time for British retailers operating online to fill their coffers with cash. They will need to refrain from updating pound-nominated prices upwards as long as possible. When new trade agreements are reached, the terms for purchasing abroad online from British retailers may also change and new adjustments will be required.

  • Ido Ariel of Econsultancy recommends three supporting marketing methods for encouraging international customers to purchase online at the interim period on UK retail websites: inducing a sense of urgency and initiating pro-active targeted prompting messages; offering targeted promotions to increase personalization (e.g., geo-targeting); and enacting limited-time discounts.

However, the condition in which the British Economy arrives to this historic junction is concerning, having reduced its manufacturing sector too much over the years and relying too heavily on a services economy. This situation may mitigate the country’s ability to exploit its currency advantage in the short- to medium-term by increasing exports of goods, and may also put it in a less advantageous position as a strong producing economy in negotiations for future trade deals. The condition of the British economy could become even weaker if, as projected by the Economist Intelligence Unit, service companies — financial and banking of most — will lose their “passport” to act from the UK in the other EU member-countries (e.g., France, Germany), and thus they will choose to cut their operations in the country or leave altogether.

  • The contribution of the production sector to the economic output (Generated Value Added [GVA]) decreased in the UK from 41% in 1948, through 25% in 1990, and down to 14% in 2013 (‘production’ includes manufacturing, oil and gas extraction, and water and energy utilities);
  • The relative contribution of the services sector grew during that period from 46% to 79% (67% in 1990);
  • The growth of the sub-sector of business and financial services is most noticeable, expanding from 13% in 1978, through 22% in 1990, and reaching 32% in 2013.
  • A World Bank comparison referring specifically to manufacturing shows that its contribution to output in Britain is 10% versus 22% in Germany (UK’s is the lowest [with France] and Germany’s the highest among all G7 countries, 2012).
  • (Source: ONS review, April 2014: “International Perspective on the UK — Gross Domestic Product”. For main points see The Guardian’s Economics blog.)

In the long-term Britain may well succeed in re-establishing a strong position in business and trade. But it will come at a high cost in the short- and medium-term (next three to five years) for the economy overall, businesses and consumers, and this process is not free of risks. Is it that much necessary? Another contentious question is: How much has the EU really held the UK back? Answers to these questions remain in deep dispute. Having stayed in the EU, the UK might have been able to help stabilise the European economy while resolving its existing failures, and then grow faster with the EU. But too many Britons stopped believing this will ever be possible, or simply lost their patience. The EU leadership in Brussels bears much responsibility for arriving to this predicament. But that matters little now.

It is now a time for taking an opportunity to resolve weaknesses in the British economy — industry and trade. It will have to prove itself as an independent viable economy, less reliant directly on the EU but more like many other countries trading with the EU. Retailers may have to make changes to their mixtures between imported and locally manufactured products; to form trading ties with different and additional countries; and more vigorously refresh and update their trading, merchandising and pricing techniques and tactics to be competitive on the local stage, and where relevant on an international stage. The Centre for Retail Research has expressed most pointedly what is expected of retailers: “Retail post-Brexit will have to be more agile, more digital, capital-intensive and more responsive to change”. Retailers and consumers will have to adjust to new market conditions and adapt to new game rules.

Ron Ventura, Ph.D. (Marketing)

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