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Posts Tagged ‘Choice’

Interfaces of knowledge management (KM) systems can be applied to support and empower customer service via two key channels: (1) directly — used by customers (e.g., adjunct to self-service utilities, web-based or mobile app), or (2) indirectly — used by employees (customer service representatives [CSR]) to help them provide a better service to customers (e.g., more effective, timely, and accurate). These channels have some very different implications in form, scope and intensity of use of KM capacities.

The ‘library’ of a KM system should provide the customer with relevant background information that can help him or her make decisions (e.g., choosing between product attribute options, selecting among investment assets). The knowledge resource may also assist in completing technical tasks at one’s home or office (e.g., setting-up a software or device).  The content may include explanations on specific concepts or procedures, product reviews, and articles on related topics (e.g., an overview of a technology, medical condition, class of financial assets).

A crucial question is how the customer gets exposed to information relevant for the task at hand. General search queries often lead to many and spurious results requiring the customer to work hard to find and collate relevant information. The system has to do better than that in recommending truly useful information, to bring the user more precisely and quickly to a set of relevant knowledge sources. The customer may start by filling a short questionnaire that lets him specify his interests and goals. But as the customer accumulates more experience in using a KM portal and accessing some documents, the system can learn from his or her behaviour and update its recommendations. Alternatively, references to a KM resource may be embedded within a self-service facility (e.g., application for travel insurance) so that the system can refer the customer to supplementary information based on his or her progress in the service process (e.g., explanation of healthcare procedures in the country of destination, recommended features of coverage for the planned trip). As the system learns it may add a visual display of relevant statistics for guidance (e.g., distribution of options chosen by similar customers or in similar situations). Furthermore, a company can use its discretion to provide premium customers secured access to resources available only to its employees within the organisation.

Knowledge management portals for customers are not so common. References are more likely to be implicit, such as being embedded within the self-service platform of the company. More companies now provide an interface for interaction (chat) with an intelligent virtual agent (IVA) to get assistance. Such a robotic agent may give a brief answer and perhaps add a single resource for further reading; if the customer insists on asking a follow-up question, the agent may refer the customer to 1-3 more documents. Sometimes this kind of help is not sufficient and the customer has to make extra effort to drill more useful information from the IVA (a face wearing a smile to the customer is not always comforting). In more complex, sensitive and risk-prone domains, it is advisable to accompany the IVA with a portal that will display more resources in a coherent and viewer-friendly format, explicating what each resource would be most helpful for.

Having said that, there are circumstances in which the customer cannot manage on his own and needs to talk to a skilled person to resolve an issue. It may be because the customer encounters difficulties in fulfilling the task using the computer-based self-service tools or because the domain at issue is relatively complex and involves more significant personal implications (e.g., financial investment, insurance, medical conditions, sophisticated technological products). Researchers Shell and Buell of Harvard Business School suggest in a recent working paper [1] that having customers know that access to human contact is available to them for assistance, even without their taking advantage of it, can improve their feelings, particularly mitigating anxiety, and in turn recuperate their satisfaction and confidence in decisions they make during a self-service session; this will show especially in situations of heightened anxiety. Hence, making notice of access to human contact salient is essential.

Of course in some cases customers will choose to actually turn to a human agent for assistance and guidance; on many other occasions, however, merely knowing that human assistance is reachable may instill some more confidence and encourage the customer to continue independently to the extent that he or she can avoid calling for assistance (i.e., knowledge that human contact is available acts as a safety net). A company can offer human assistance from an agent by phone or chat (not an IVA/chatbot), yet as Shell and Buell propose, the company may also enable customers to get advice from customer-peers (though with more limited effect). Mitigating anxiety through offering human assistance as needed can help to reduce negative effects of customer anxiety on choice satisfaction and subsequently on trust in the company.

The utilisation of knowledge management portals by company’s CSRs aims to work at a different, professional level, to enable the CSRs address concerns and issues raised by customers in a more proficient and timely manner. For instance, it should save CSRs the time and effort of referring to a number of platforms (e.g., marketing, CRM, product) by bringing together different types of relevant and practical information onto one place from which the human agent can access it more easily and quickly. A KM portal display may integrate most recent history of interactions with the customer, relevant offers of products or service packages, or links to additional background articles (e.g., product profiles, technical materials). The KM portal may include essential customer information (e.g., identification and key flags) but it may not free the CSR completely from turning to a CRM system for more information (e.g., previous purchases); likewise, it may not free the CSR from turning to the billing system or a product database resource. The challenge of a KM system is to pull together those portions of information deemed most relevant and useful to the issue at stake from the broad knowledgebase of the company and lay them closer to the service agent (e.g., in a portal or dashboard display). An agent who listens to the ‘story’ told by the customer can give the KM system more clues to allow it to make the best recommendations. Information may be presented explicitly or as links to recommended documents and other external resources. This is expected to be part of the future mode of operation of contact centres, and it is already in motion.

It is important, nevertheless, to take into consideration the time a human service agent needs to review some of the information proposed in the KM portal, in relation to a customer’s enquiry during a live interaction with the customer. The CSR may have to trace, learn, judge and extract relevant information before delivering his or her insight, recommendation or solution to the customer, and all that within a few minutes. Some of the knowledge may be included, as suggested above, in resources like articles that the agent should access and read — think for instance of an article on a new travel insurance offer: the agent has to understand the terms before communicating it to the customer, and being able to answer questions. Three observations are in order on this matter:

  1. Human service agents (CSRs) should receive adequate training on choice, comprehension and evaluation of materials from the company’s knowledgebase, and also should be allocated paid “off-duty” time for reviewing new and updated content (e.g., products and service offers, technical support procedures) to reduce learning ‘time-breaks’ during customer interactions;
  2. The CSR agents should be ready and willing to learn and assimilate information they utilise as their own knowledge, together with experiences they accumulate, to be able to use that knowledge again with subsequent customers without having to process information from the KM portal every time and again — a KM system will be much less effective if CSRs rely heavily on what they see on the screen in every event, rather than using it as an aid and supporting tool;
  3. A key capacity of KM systems is to allow employees share among them experiences, lessons and information they have learned which proved pertinent to the service events they have been treating — by adding notes or updating a special forum, service agents can turn implicit knowledge into explicit knowledge that can help their colleagues in handling similar events in their own future customer encounters.

According to a research report by Aberdeen Group [2], companies that have a formal agent experience management programme gain a higher rate of annual increase in customer retention, above two times more than in other companies (12% versus 5%). These companies can also expect to benefit from about two times higher rates of year-over-year increases in revenues and customer satisfaction. At the same time, agent productivity is also likely to be better with a formal programme for supporting and enhancing the agent working experience (11% annual increase versus 7% in other companies without such a programme). Greater service agent satisfaction is linked to greater customer satisfaction; it requires that the agents feel they can do their work serving customers more easily and successfully with proper guidance and direction.

The Aberdeen report identifies three top factors influencing the agent experience. First, the prospect agent should bring to the job good technology knowledge and skills as well as strong communication skills to be fit for the job assigned. Second, the company should provide on its part the means in technology tools that will facilitate the ability of agents to perform their day-to-day tasks. A smart and effective knowledge management system that can quickly and pointedly lead agents to relevant information (e.g., instructive articles) should have a great role to play in improving the agent experience. Making agents spend extended valuable time seeking background knowledge and insights and delaying their handling of customer enquiries are key deterrents to agent productivity; it may be added that these impediments also are likely to lead to increased agent frustration. Nevertheless, side by side with the skills agents bring with them and the information and technology tools the company provides, agents should be given more autonomy while interacting with a customer (e.g., offer discounts, account credit, free shipping etc.). Aberdeen describes this third factor as providing agents the “sense of empowerment in addressing customer needs”. Employees-agents could be made to feel empowered when respecting their judgement in utilising knowledge resources and allowing them leeway in deciding how best to help the customers.

A knowledge management system incorporates knowledge resources with different types of information and technology tools to access that knowledge. The tools are expected to become powered more extensively by artificial intelligence and machine learning capabilities, to enable users to access relevant and practical information or knowledge more quickly and precisely. However, it should be appreciated that knowledge is most often what people make of information made available to them, and also the knowledge they can return and add to the system for the benefit of others. Whether the interface is used by any company’s service agents or the customers themselves (e.g., applying self-service facilities), the support and guidance of a KM system can enhance the service quality in important ways.

Ron Ventura, Ph.D. (Marketing)

Notes: 

[1] “Mitigating the Negative Effects of Customer Anxiety Through Access to Human Contact”; Michelle A. Shell & Ryan W. Buell [2019]; Harvard Business School Working Paper 19-089 (unpublished paper).

[2] “Agent Experience Management: Customer Experience Begins with Your Agents”, Aberdeen Group [Omer Minkara], September 2017

 

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A classic view regarding decision-making holds that attention serves foremost to acquire the information most relevant and important for choosing between alternatives. Thereby the role of attention is largely a passive one. However, an alternative view that is gaining traction in recent years, especially due to the help of eye tracking research, argues that attention plays a more active role in decision processes, influencing the construction of decisions.

This is a key message delivered by Orquin and Mueller Loose (2013) in their review on the role of attention in decision-making, as can be learnt from tracking of eye movements and subsequent fixations [1]. The approach taken by the researchers, however, is less usual: They do not constrain themselves concretely to the domain of decision-making; instead, they start their review and analysis of evidence from theories or models of tasks similar or related to decision-making (e.g., perception, information processing, visual search, working memory, top-down and bottom-up processes, problem solving).  Then they try to project how the functions of attention in such tasks may project to or be expressed in decision processes.

Furthermore, Orquin and Mueller Loose examine the extent to which the evidence coincides with four alternative theories and associated models of decision-making (i.e., whether empirical evidence substantiates or refutes assumptions or conclusions in each theory). They review evidence from previous research on similar or related tasks that could also be traced specifically in decision tasks, based on eye tracking in decision-making research, and evaluate this evidence in the context of the alternative decision-making theories.

The theories and related models considered are: (1) rational models; (2) bounded rationality models; (3) evidence accumulation models (e.g., the attention drift diffusion model [aDDM] posits that a decision-maker accumulates evidence in favour of the alternative being fixated upon at a given time); and (4) parallel constraint satisfaction models (a type of dual process, neural network model based on the conception of System 1’s fast and intuitive thinking [first stage] and System 2’s slow and deliberate thinking [second stage]). Rational models as well as bounded rationality models more explicitly contend that the role of attention is simply to capture the information needed for making a decision. ‘Strong’ rational models hold that all relevant, available information about choice alternatives would be attended to and taken into account, whereas ‘relaxed’ rational models allow for the possibility of nonattendance to some of the information (e.g., attributes or object [product] features). Bounded rationality models suggest that information is acquired just as required by the decision rules applied. The two other categories of models are more flexible in regard to how information is acquired and used, and its effect on the decision process and outcome. However, the authors argue that all four theories are found to be in deficit to a smaller or larger degree in their consideration of the role and function of attention in decision processes, having at least some of their assumptions being rejected by the evidence evaluated.

Selected insights drawn from the review of Orquin and Mueller Loose are enlisted here only briefly to shed light on the significance of attention in consumer decision-making.

A crucial question in decision-making is how information enters the decision process and is being utilised in reaching a choice decision: information may be acquired through attention guided by a top-down (goal-driven) process, yet information may also be captured by a bottom-up (stimulus-based) attentional process. The entanglement of both types of processes when making a decision is a prime aspect in this domain and has multiple implications. A more efficient selection process may be driven by greater experience with a task (e.g., more important information cues have a higher probability of being fixated on) and increased expertise in comprehension of visualisations (e.g., more fixations to relevant areas, and inversely fewer fixations to irrelevant areas, requiring shorter fixation durations, and longer saccades [‘jumps’ between more distant elements of information in a scene]). The interaction between bottom-up and top-down processing can amplify attention capture and improve the visual acuity of objects perceived. Bottom-up attention in particular is likely to be influenced by the saliency of a visual stimulus; however, it may not take effect when the task demands on attention are high, wherein priority is given to top-down directives for attention. Decision-making research has shown that visually salient alternatives or attributes are more likely to capture attention and furthermore affect the decision in their favour.

An interplay occurs between working memory and ‘instant’ attention: As the load of information fixated becomes larger, more elements are passed to working memory, and information is accessed from there for processing; however, as the strain on working memory increases, consumers turn to re-fixating information elements and consider them instantly or just-in-time (i.e., fixations are thus used as external memory space). This type of interplay has been identified in tasks of problem solving. Toggling between working memory and fixations or re-fixations in decision tasks can be traced, for instance, in alternative comparisons. Greater demands imposed by information complexity and decision difficulty (due to greater similarity between alternatives) may require greater effort (operations) in acquiring and processing information, yet the process may be shortened on the other hand through learning.

  • Another area with interesting implication is processing of visual objects: Previous research has shown that visual objects are not encoded as complete representations (e.g., naturalistic product images) and the binding of features is highly selective. Thereof, encoding of particular features during an object-stimulus fixation may be goal-driven, and a re-fixation may be employed to refer just-in-time to specific object [product] features as needed in a decision task, thus saving on working memory capacity.

Consumers have a tendency to develop a bias during a decision task towards a favoured alternative. This alternative would get more fixations, and there is also a greater likelihood for the last alternative fixated to be the one chosen (put differently, consumers are likely to re-affirm the choice of their favourite alternative by re-fixating it just before making the decision). A desired or favoured attribute can also benefit from a similar effect by receiving more frequent attention (i.e., fixations). The authors point, however, to a difficulty in confirming evidence accumulation models: whether greater likelihood of a more fixated alternative to be chosen is due to its higher utility or greater exposure to it. They suggest a ‘soft’ model version in support for a greater effect of extended mere exposure leading to choice of an alternative. They add that a down-stream effect of attention from perception onto choice through a bottom-up process may play a role of gatekeeping the alternatives entering a consideration set. It is noted that a down-stream effect, arising from a bottom-up process, is clearly distinguishable from a utility effect, since the former is stimulus-driven and the latter is goal-driven.

Consistent with bounded rationality theory, heuristics shape patterns of attention, directed by the information that a heuristic calls for (e.g., by alternative or by attribute). Yet, eye-tracking studies conducted to trace the progression of decision processes could not corroborate the patterns of heuristics used as proposed in the literature. More formally, studies failed to substantiate the assumption that heuristics in use can be inferred from the patterns of attention recorded. Transitions of consumers between alternative-wise and attribute-wise rules during a decision task make inferences especially difficult. Not only decision rules influence what information is attended to, but information cues met with during the decision process can modify the course of the decision strategy applied — consider the potential effect that salient stimuli captured unexpectedly in a bottom-up manner can have on the progression of the decision strategy.

In summary, regarding the decision-making theories, Orquin and Mueller Loose conclude: (a) firmer support for the relaxed rational model over the strong model (nonattendance is linked to down-stream effects); (b) a two-way relationship between decision rules and attention, where both top-down and bottom-up processes drive attention; (c) the chosen alternative has a higher likelihood of fixations during the decision task and also of being the last alternative fixated — they find confirmation for a choice bias but offer a different interpretation of the function of evidence accumulated; (d) an advantage of the favoured alternatives or most important attributes in receiving greater attention, and advantage of salient alternatives receiving more attention and being more likely to be chosen (concerning dual process parallel constraint satisfaction models).

Following the review, I offer a few final comments below:

Orquin and Mueller Loose contribute an important and interesting perspective in the projection of the role of [visual] attention from similar or related tasks onto decision-making and choice. Moreover, relevance is increased because elements of the similar tasks are embedded in decision-making tasks. Nevertheless, we still need more research within the domain because there could be aspects specific or unique to decision-making (e.g., objectives or goals, structure and context) that should be specified. Insofar as attention is concerned, this call is in alignment with the conclusions of the authors. Furthermore, such research has to reflect real-world situations and locations where consumers practically make decisions.


In retail stores, consider for example the research by Chandon, Hutchinson, Bradlow, and Young (2009) on the trade-off between visual lift (stimulus-based) and brand equity (memory-based); this research combined eye tracking with scanner purchase data [2]. However, it is worth looking also into an alternative approach of video tracking as used by Hui, Huang, Suher, and Inman (2013) in their investigation of the relations between planned and unplanned considerations and actual purchases (video tracking was applied in parallel with path tracking)[3].

For tracing decision processes more generally, refer for example to a review and experiment with eye tracking (choice bias) by Glaholt and Reingold (2011)[4], but consider nonetheless the more critical view presented by Reisen, Hoffrage and Mast (2008) following their comparison of multiple methods of interactive process tracing (IAPT)[5]. Reisen and his colleagues were less convinced that tracking eye movements was superior to tracking mouse movements (MouseLab-Web) for identifying decision strategies while consumers are acquiring information (they warn of superfluous eye re-fixations and random meaningless fixations that occur while people are contemplating the options in their minds).


 

It should be noted that a large part of the research in this field, using eye-tracking measurement, is applied with concentrated displays of information on alternatives and their attributes. The most frequent and familiar format is information matrices (or boards), although in reality we may also encounter other graphic formats such as networks, trees, layered wheels, and more art-creative diagram illustrations. Truly, concentrated displays can be found in shelf displays in physical stores and also in screen displays online and in mobile apps (e.g., retailers’ online stores, manufacturers’ websites, comparison websites). However, on many occasions of decision tasks (e.g., durables, more expensive products), consumers acquire information through multiple sessions while constructing their decisions. That is, the decision process extends over time. In each session consumers may keep some information elements or cues for later processing and integration, or they may execute an interim stage in their decision strategy. If information is eventually integrated, consumers may utilise aides like paper notes and electronic spreadsheets, but they do not necessarily do so.

Orquin and Mueller Loose refer to effects arising from spatial dispersion of information elements in a visual display as relevant to eye tracking (i.e., distance length of saccades), but these studies do not account for temporal dispersion of information. Studies may need to bridge data from multiple sessions to accomplish a more comprehensive representation of some decision processes. Yet, smartphones today can help in closing somewhat the gap since they permit shoppers to acquire information in-store while checking more information from other sources on their smartphones — mobile devices of eye tracking may be used to capture this link.

Finally, eye tracking provides researchers with evidence about attention to stimuli and information cues, but it cannot tell them directly about other dimensions such as meaning of the information and valence. The importance of information to consumers can be implied from measures such as the frequency and duration of fixations, but other methods are needed to reveal additional dimensions, especially from the conscious perspective of consumers (vis-à-vis unconscious biometric techniques such as coding of facial expressions). An explicit method (Visual Impression Metrics) can be used, for example, to elicit statements by consumers as to what areas and objects in a visual display that they freely observe they like or dislike (or are neutral about); if applied in combination with eye tracking, it would enable to signify the valence of areas and objects consumers attend to (unconsciously) in a single session with no further probing.

The review of Orquin and Mueller Loose opens our eyes to the versatile ways in which [visual] attention may function during decision tasks: top-down and bottom-up processes working in tandem, toggling between fixations and memory, a two-way relation between decision strategies and visual attention, choice bias, and more. But foremost, we may learn from this review the dynamics of the role of attention during consumer decision-making.

Ron Ventura, Ph.D. (Marketing)

References: 

[1] Attention and Choice: A Review of Eye Movements in Decision Making; Jacob L. Orquin and Simone Mueller Loos, 2013; Acta Psychologica, 144, pp. 190-206

[2] Does In-Store Marketing Work? Effects of the Number and Position of Shelf Facings on Brand Attention and Evaluation at the Point of Purchase; Pierre Chandon, J. Wesley Hutchinson, Eric T. Bradlow, & Scott H. Young, 2009; Journal of Marketing, 73 (November), pp. 1-17

[3] Deconstructing the “First Moment of Truth”: Understanding Unplanned Consideration and Purchase Conversion Using In-Store Video Tracking; Sam K. Hui, Yanliu Huang, Jacob Suher, & J. Jeffrey Inman, 2013; Journal of Marketing Research, 50 (August), pp. 445-462.

[4] Eye Movement Monitoring as a Process Tracing Methodology in Decision Making Research; Mackenzie G. Glaholt and Eyal M. Reingold, 2011; Journal of Neuroscience, Psychology and Economics, 4 (2), pp. 125-146

[5] Identifying Decision Strategies in a Consumer Choice Situation; Nils Reisen, Ulrich Hoffrage, and Fred W. Mast, 2008; Judgment and Decision Making, 3 (8), pp. 641-658

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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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Choosing reading books can be a serious undertaking. Even the choice of a novel or a detective book may not be taken lightly by readers. There are different ways in which consumers may get into choosing a book; some search and selection patterns in the decision process carried out by consumers can be observed in bookstores. It is possible to infer from observations, with some limitations, styles of shopping for books, involving certain tactics or rules utilised in the process. Book fairs especially offer an interesting and vibrant venue for book shopping with options not regularly available at stores. Such events may also provide an opportunity to detect new or distinctive patterns and styles of shopping that arise from the dynamic happening and busy environment.

The open-air Hebrew Book Fair has been taking place in a main central square in Tel-Aviv for over forty years in every June. Originally the book fair was held for a week but in recent years it has been extended by three more days due to its high popularity. It must immediately be noted that the book fair is an event reserved for publishers. It is a kind of ‘direct-sales’ event in which publishers meet face-to-face with readers to present their book collections to them for purchase on special discounts (the main bookstore chains run their own parallel competitive events with discounts in-store or near their stores). Visitors at the book fair can find Hebrew-native books and books translated to Hebrew from English and other languages; topical categories cover, for instance, prose, poetry  and novels; detective and thrillers; history, science, and other areas of knowledge; and last but not least children & youth books. Such an enormous selection of books is not available ordinarily at bookstores in the country. The larger publishing houses may occupy ten or more counters in-line.

The visitor traffic at the event, as in this year, suggests that print books are still highly desired by people. Nevertheless, to attract even more visitors, particularly families with children, the organisers added in the past few years food and drink stands and a sitting area with tables in the square’s centre. It may help to increase the convenience to visitors and festivity of the event though it could sacrifice a bit the respectability of this literary event. However, it may be a matter of necessity or priority to make the event more popular and vibrant so as to bring larger reader audiences back to books.

As suggested above, this book fair is a busy event with tens of thousands of books of numerous titles on display from different publishers and across a wide range of topics. It retains also a long tradition wherein Israeli authors attend to sign their books for visitors-buyers. Some book counters may become crowded with shoppers during certain hours through the afternoon and evening (i.e., after work and school hours) which can make it harder to access books and check them out more deeply. Hence it may require shoppers to apply tactics for choosing books of their interest and taste a little differently than they would while shopping in a bookstore. Yet visitors find their ways to browse books, sometimes more loosely, sometimes more meticulously; it seems to happen overall in an orderly manner, each visitor getting his or her place at a book counter or desk.

Visitors can be seen walking along counters of a given publisher, staying at a counter for a while to observe its books, then moving along. After selecting a few books from separate but adjacent counters of the same publisher, the visitor often returns to a previous counter to pay. However, visitors-buyers are also offered the option to keep books already selected behind the counter (a combination of convenience and security for both sellers and customers).

Three forms of browsing candidate books of interest can be primarily noticed: Firstly, eye-scanning the front covers of books from top. Secondly, lifting a book, turning it over and reading its back cover — an abstract, short review recommendations, or a brief biography of the author(s). A visitor may examine a few books from a counter this way, but being able to do so comfortably may truly depend on how many people are already at the counter. Hence, visitors who cannot find a free spot at a counter are often seen looking over a counter-top quickly, moving to the next counter, then coming back if perhaps there was a book that had caught their attention previously to check on the book more closely. But visitors generally do not have to wait too long to find a free spot at a counter. Thirdly, one gets to open a book and sample-read sections from its pages, or looking at photographs, charts or maps inside the book. Instances of reading inside books were observed much less frequently.

Examining a book’s content more deeply to form a better founded impression or opinion of it is more difficult and hence is less likely than would be seen at bookstores. Yet, if time and space at the counter allow, it is possible to find a visitor examining a book more meticulously. It appears to be particularly relevant and appropriate for ‘knowledge books’ such as in history, sciences and technology, the social sciences, economics and business. For example, a visitor in his ~70s was leaning over an open book on the history of WW2 by Max Hastings, appearing concentrated in reading and observing maps and photographs (‘Inferno/All Hell Let Loose’, translated). He seemed interested overall in history of the two world wars of the 20th century, judging from other books he browsed; after nearly ten minutes he handed three chosen books to keep, and continued searching [A].

  • Please be advised that the age estimates of visitors are based on observation alone in best judgement of the author.

Comparing books on a given topic can be an even more difficult task to perform at a counter. It is hardly practical to hold two books open simultaneously for comparison, but visitors may examine books sequentially in attempt to evaluate and choose which one is more suitable to their objectives. For instance, a visitor (male, ~60) looked into a book — its introduction, inner pages, and content — on the history of the state of Israel (by Michael Bar-Zohar), but he apparently did not find what he was looking for as he asked the seller if there were books on the period preceding the establishment of the state. The seller brought him two books (concerning the Arab-Israeli conflict): he opened one of them, went through its pages, and put it aside, then browsed at greater length pages in the other book and looked at photographs. Eventually he chose the first book on the state of Israel, after looking into it again, and the third book (total time 15 minutes, [B]).

The search and examination of books sometimes involves moments of deliberation. In some cases, as above [B], the visitor may ask for advice from a seller. Alternately, as in another case observed, a seller who noticed a visitor (female, 30-35) hesitating, offered her help with recommendations. The visitor-shopper was already holding two books and the seller brought her more books the latter thought may suit the shopper accordingly in prose or novels by Israeli authors. They continued talking about the books as the shopper browsed loosely inside some of the books or read from the back cover [C].

Deliberation can take some additional forms. For example, a female visitor (~45) was considering the purchase of a book on equity investments. She was checking in particular a book purporting to be adapted and designated for women. The visitor went through some book pages, being unsure it was a good choice, and seemed recoiled upon noticing the book was from 2011 (i.e., ‘Is it still valid and relevant?’). But eventually, following a short exchange with the (female) seller, the visitor-shopper decided to take it anyway [D]. A visitor (male, 25-30) at another publisher has shown an intriguing shopping process with deliberation to the last moment: He was already holding a book when moving to another counter to look over books of prose, selected one of them, then browsed some science and knowledge books (e.g., by an Israeli scholar, lecturer and prolific writer on sciences and philosophy, Haim Shapira), but collected none. Subsequently the shopper moved to a more remote counter where he picked-up instantly a book, came back to the previous counter of science and knowledge books to purchase three books. However, after he had already paid and the books were put in a bag by the seller and handed over to him, he took out one of the books and picked-up instead a different book in front of him on biblical philosophy (by Shapira, 10 minutes, [E]).

Shopping patterns can range from exploratory, looking for opportunities with little idea pre-conceived in mind, to being pre-minded, that is, having a goal to find a particular book. Moreover, visitors-shoppers may mix styles at different levels of search, examination and choice while shopping from the same publishing house. Mixed tactics could be seen above in the shopping of visitors [E] and [C]. Following are two more examples of this kind: (1) A young visitor (female, ~17-18) was browsing prose or fiction books, going through pages and reading inside some of the books or reading from the back covers of others, then passed to looking from top at books in adjacent counters of the publisher (a more haphazard quick scan), finally returning to the first counter to buy [F]; (2) A visitor (male, ~45, at a counter of books on history and politics) took a cursory look over a biography of one of Israel’s prominent leaders of the past, kept searching and shortly after found a book on the history of Sephardic Jews (‘Marranos’, Yirmiyahu Yovel) and looked into the book more dedicately; the visitor, who seemed overall interested in Israeli and Jewish history, picked up a book at the last moment by an Israeli historian on the commanders of the Nazi concentration camps (‘Soldiers of Evil’) and purchased it with the book on Marranos [G].

  • In a curious brief episode, demonstrating an apparent pre-determined choice of book, a visitor in his mid-40s approached a counter, stood pausing or looking over the books, then instantly extended his hand to pick-up three copies of a book on the Bitcoin, which he purchased; one of the sellers seemed so impressed that she asked to take a photo of him holding the books with her mobile phone to which he smilingly agreed [H].

The main publishing houses presenting at the book fair offered deals of ‘3 for 100’, that is, three books for 100 shekels (~$28 in June). One publisher even offered five books for 150 shekels. These deal offers were displayed on signage boards above counters. A fourth book could be purchased for 50% of its list price, but this offer was not displayed. Visitors-shoppers who had already selected three books enquired whether there would be a discount for additional books, and were replied with the 50% offer. For instance, visitor [A] so enquired before continuing his search. Another visitor (male, ~30) who was holding four books by Ken Follett seemed unable to make up his mind which three to buy, posed the question about a fourth book discount, deliberated a little longer while shuffling the books in his hand, and finally passed all four to the seller to purchase [I]. In some cases, however, it was the seller who initiated the offer of discount on a fourth book in hope to increase the sale. Visitor [C], for example, accepted an offer as such and bought four books, probably in appreciation of, and perhaps feeling obliged to reciprocate, the advice she received from the seller. Conversely, another visitor (~30), who selected three books in history and politics on his own refused the offer by the seller when submitting his books to purchase [J].

Visitors were induced by these deals to buy more books from any single publisher. A single book could usually be bought with a 20% discount but this offer was not made public, proposed by a seller only on request of the visitor. This policy makes it simply unworthy economically for visitors to cherry-pick the books they most require or desire from different publishers (consider that many of the books cost 80-120 shekels each!). The greater problem, however, is that it may drive consumers to buy books they do not care for or do not have time to read soon. Henceforth, visitors could end up buying a pack of books, collected from several publishers, for the whole year to read. It puts quantity before quality in buying books. The ones standing to suffer from this policy are of course the book retailers who will likely see fewer shoppers at their stores in the coming months. From a publisher’s viewpoint, they may see it as only a reprisal to similar deals offered at bookstores throughout the year.

Visitors-shoppers at the book fair appear to use composite decision strategies for choosing books at the counters of a publisher: a different type of rule or method may be fitted to choose among different books (e.g., picking-up a book planned ahead to purchase, using book titles or author names as memory cues for books they have considered recently, examining inside books with greater scrutiny to evaluate them). Furthermore, the book shoppers are searching for informational cues, starting from the front cover of a book, going to the back cover, then getting inside the book. They could be extending the search for cues about a book as they feel is needed (e.g., cut the search short if sufficient information has been retrieved) or are stimulated to learn more about the book (e.g., intrigued by information on the back cover to look inside).

The difference in shopping for books at the book fair compared with bookstores seems to be not so much in the types of rules or tactics used as in the extent and frequency they are used. Book shoppers may feel at greater ease to search for a book at a store with a print of a book review cut from a newspaper (as observed in a store) than they would in the book fair (surely the same applies if one seeks guidance from his or her smartphone). One may also feel more comfortable and free to browse inside a book at a bookstore, at a quiet corner to stand or perhaps on a couch or sofa to sit and read, than at the book fair. Yet, visitors of the book fair seemed to adapt quite well to the conditions at the counters; they appear to use rules or methods similar to those that can be seen at bookstores, only adjusting them to search and choose more efficiently, particularly by restricting deeper examinations to situations where a book demands it.

  • Additional research methods can aid in identifying and verifying more accurately the book images and information viewed by visitors and the decision rules they use. Those methods include particularly eye-tracking and a real-time protocol of the shopping decision process (‘think aloud’). But executions of such methods may be inconveniently intrusive and interfere with the natural course of the shopping trip for visitors. Another method to consider with less intervention is an interview with a visitor-shopper after concluding a shopping episode.

Gaining greater insight into shopping for books and understanding the decision processes visitors-shoppers follow at a book fair can help in devising new designs of book displays (e.g., better organise books by topics or themes, easier-to-find) and improved practices to accommodate the visitors at the event. The organisers and publishing houses may also come up with a new co-operative scheme that would allow visitors to accomplish more effectively their objective in selecting and buying the books that interest them most or they desire to read.

Ron Ventura, Ph.D. (Marketing)

 

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The strength, impact and value of a brand are embodied, fairly concisely, in the concept of ‘brand equity’. However, there are different views on how to express and measure brand equity, whether from a consumer (customer) perspective or a firm perspective. Metrics based on a consumer viewpoint (measured in surveys) raise particular concern as to what actual effects they have in the marketplace. Datta, Ailawadi and van Heerde (2017) have answered to the challenge and investigated how well Consumer-Based metrics of Brand Equity (CBBE) align with Sales-Based estimates of Brand Equity (SBBE). The CBBE metrics were adopted from the model of Brand Asset Valuator (Y&R) whereas SBBE estimates were derived from modelling market data of actual purchases. They also examined the association of CBBE with behavioural response to marketing mix actions [1].

In essence, brand equity expresses an incremental value of a product (or service) that can be attributed to its brand name above and beyond physical (or functional) attributes. Alternately,  brand equity is conceived as the added value of a branded product compared with an identical version of that product if it were unbranded. David Aaker defined four main groups of assets linked to a brand that add to its value: awareness, perceived quality, loyalty, and associations beyond perceived quality. On the grounds of this conceptualization, Aaker subsequently proposed the Brand Equity Ten measures, grouped into five categories: brand loyalty, awareness, perceived quality / leadership, association / differentiation, and market behaviour. Kevin Keller broadened the scope of brand equity wherein greater and more positive knowledge of customers (consumers) about a brand would lead them to respond more favourably to marketing activities of the brand (e.g., pricing, advertising).

The impact of a brand may occur at three levels: customer market, product market and financial market. In accordance, academics have followed three distinct perspectives for measuring brand equity: (a) customer-based — an attraction of consumers to the “non-objective” part of the product offering (e.g., ‘mindset’  as in beliefs and attitudes, brand-specific ‘intercept’ in a choice model); (b) company-based — additional value accrued to the firm from a product because of a brand name versus an equivalent product but non-branded (e.g., discounted cash flow); financial-based — brand’s worth is the price it brings or could bring in the financial market (e.g., materialised via mergers and acquisitions, stock prices)[2]. This classification is not universal:  for example, discounted cash flows are sometimes described as ‘financial’; estimates of brand value derived from a choice-based conjoint model constitute a more implicit reflection of the consumers’ viewpoint. Furthermore, models based on stated-choice (conjoint) or purchase (market share) data may vary greatly in the effects they include whether in interaction with each competing brand or independent from the brand ‘main effect’ (e.g., product attributes, price, other marketing mix variables).

A class of attitudinal (‘mindset’) models of brand equity may encompass a number of aspects and layers: awareness –> perceptions and attitudes about product attributes and functional benefits (+ overall perceived quality), ‘soft’ image associations (e.g., emotions, personality, social benefits) –> attachment or affinity –> loyalty (commitment). Two noteworthy academic studies have built upon the conceptualizations of Aaker and Keller in constructing and testing consumer-based measures:

  • Yoo and Donthu (2001) constructed a three-dimension model of brand equity comprising brand loyalty, brand awareness / associations (combined), and perceived quality (strength of associations was adopted from Keller’s descriptors of brand image). The multidimensional scale (MBE) was tested and validated across multiple product categories and cultural communities [3].
  • Netemeyer and colleagues (2004) demonstrated across products and brands that perceived quality, perceived value (for the cost), and uniqueness of a given brand potentially contribute to willingness to pay a price premium for the brand which in turn acts as a direct antecedent of brand purchase behaviour [4]. Price premium, an aspect of brand loyalty, is a common metric used for assessing brand equity.

Datta, Ailawadi and van Heerde distinguish between two measurement approaches: the consumer-based brand equity (CBBE) approach measures what consumers think and feel about the brand, while the sales-based brand equity (SBBE) approach is based on choice or share of the brand in the marketplace.

The CBBE approach in their research is applied through data on metrics from the Brand Asset Valuator model developed originally by Young and Roubicam (Y&R) advertising agency (the brand research activity is now defined as a separate entity, BAV Group; both Y&R and BAV Group are part of WPP media group). The BAV model includes four dimensions: Relevance to the consumers (e.g., fits in their lifestyles); Esteem of the brand (i.e., how much consumers like the brand and hold it in high regard); Knowledge of the brand (i.e., consumers are aware of and understand what the brand stands for); and  Differentiation from the competition (e.g., uniqueness of the brand)[5].

The SBBE approach is operationalised through modelling of purchase data (weekly scanner data from IRI). The researchers derive estimates of brand value in a market share attraction model (with over 400 brands from 25 categories, though just 290 brands for which BAV data could be obtained were included in subsequent CBBE-SBBE analyses) over a span of ten years (2002-2011). Notably, brand-specific intercepts were estimated for each year; an annual level is sufficient and realistic to account for the pace of change in brand equity over time. The model allowed for variation between brands in the sensitivity to their marketing mix actions (regular prices, promotional prices, advertising spending, distribution {on-shelf availability} and promotional display in stores) — these measures are not taken as part of SBBE values but indicate nonetheless expected manifestation of higher brand equity (impact); after being converted into elasticities, they play a key role in examining the relation of CBBE to behavioural outcomes in the marketplace.


  • Datta et al. seem to include in a SBBE approach estimates derived from (a) actual brand choices and sales data as well as (b) self-reported choices in conjoint studies and surveys. But subjective responses and behavioural responses are not quite equivalent bases. The authors may have aimed reasonably to distinguish ‘choice-based’ measures of brand equity from ‘attitudinal’ measures, but it still does not justify to mix between brands and products consumers say they would choose and those they actually choose to purchase. Conjoint-based estimates are more closely consumer-based.
  • Take for instance a research by Ferjani, Jedidi and Jagpal (2009) who offer a different angle on levels of valuation of brand equity. They derived brand values through a choice-based conjoint model (Hierarchical Bayes estimation at the individual level), regarded as consumer-level valuation. Vis-à-vis the researchers constructed a measure of brand equity from a firm perspective based on expected profits (rather than discounted cash flows), presented as firm-level valuation. Nonetheless, in order to estimate sales volume they ‘imported’ predicted market shares from the conjoint study, thus linking the two levels [6].

 

Not all dimensions of BAV (CBBE) are the same in relation to SBBE: Three of the dimensions of BAV — relevance, esteem, and knowledge — are positively correlated with SBBE (0.35, 0.39, & 0.53), while differentiation is negatively although weakly correlated with SBBE (-0.14). The researchers reasoned in advance that differentiation could have a more nuanced and versatile market effect (a hypothesis confirmed) because differentiation could mean the brand is attractive to only some segments and not others, or that uniqueness may appeal to only some of the consumers (e.g., more open to novelty and distinction).

Datta et al. show that correlations of relevance (0.55) and esteem (0.56) with market shares of the brands are even higher, and the correlation of differentiation with market shares is less negative (-0.08), than their correlations with SBBE (correlations of knowledge are about the same). The SBBE values capture a portion of brand attraction to consumers. Market shares on the other hand factor in additional marketing efforts that dimensions of BAV seem to account for.

Some interesting brand cases can be detected in a mapping of brands in two categories (for 2011): beer and laundry detergents. For example, among beers, Corona is positioned on SBBE much higher than expected given its overall BAV score, which places the brand among those better valued on a consumer basis (only one brand is considerably higher — Budweiser). However, with respect to market share the position of Corona is much less flattering and quite as expected relative to its consumer-based BAV score, even a little lower. This could suggest that too much power is credited to the name and other symbols of Corona, while the backing from marketing efforts to support and sustain it is lacking (i.e., the market share of Corona is vulnerable).  As another example, in the category of laundry detergents, Tide (P&G) is truly at the top on both BAV (CBBE) and market share. Yet, the position of Tide on SBBE relative to BAV score is not exceptional or impressive, being lower than predicted for its consumer-based brand equity. The success of the brand and consumer appreciation for it may not be adequately attributed specifically to the brand in the marketplace but apparently more to other marketing activities in its name (i.e., marketing efforts do not help to enhance the brand).

The degree of correlation between CBBE and SBBE may be moderated by characteristics of product category. Following the salient difference cited above between dimensions of BAV in relation to SBBE, the researchers identify two separate factors of BAV: relevant stature (relevance + esteem + knowledge) and (energized) differentiation [7].

In more concentrated product categories (i.e., the four largest brands by market share hold a greater total share of the category), the positive effect of brand stature on SBBE is reduced. Relevance, esteem and knowledge may serve as particularly useful cues by consumers in fragmented markets, where it is more necessary for them to sort and screen among many smaller brands, thus to simplify the choice decision process. When concentration is greater, reliance on such cues is less required. On the other hand, when the category is more concentrated, controlled by a few big brands, it should be easier for consumers to compare between them and find aspects on which each brand is unique or superior. Indeed, Datta and colleagues find that in categories with increased concentration, differentiation has a stronger positive effect on SBBE.

For products characterised by greater social or symbolic value (e.g., more visible to others when used, shared with others), higher brand stature contributes to higher SBBE in the market. The researchers could not confirm, however, that differentiation manifests in higher SBBE for products of higher social value. The advantage of using brands better recognized and respected by others appears to be primarily associated with facets such as relevance and esteem of the brand.

Brand experience with hedonic products (e.g., leisure, entertainment, treats) builds on enjoyment, pleasure and additional positive emotions the brand succeeds in evoking in consumers. Sensory attributes of the product (look, sound, scent, taste, touch) and holistic image are vital in creating a desirable experience. Contrary to expectation of Datta and colleagues, however, it was not found that stature translates to higher SBBE for brands of hedonic products (even to the contrary). This is not so good news for experiential brands in these categories that rely on enhancing relevance and appeal to consumers, who also understand the brands and connect with them, to create sales-based brand equity in the marketplace. The authors suggest in their article that being personally enjoyable (inward-looking) may overshadow the importance of broad appeal and status (outward-looking) for SBBE. Nevertheless, fortunately enough, differentiation does matter for highlighting benefits of the experience of hedonic products, contributing to a raised sales-based brand equity (SBBE).

Datta, Ailawadi and van Heerde proceeded to examine how strongly CBBE corresponds with behavioural responses in the marketplace (elasticities) as manifestation of the anticipated impact of brand equity.

Results indicated that when relevant stature of a brand is higher consumers respond favourably even more strongly to price discounts or deals  (i.e.,  elasticity of response to promotional prices is further more negative or inverse). Yet, the expectation that consumers would be less sensitive (adverse) to increased regular prices by brands of greater stature was not substantiated (i.e., expected positive effect: less negative elasticity). (Differentiation was not found to have a positive effect on response to regular prices either, and could be counter-conducive for price promotions.)

An important implication of brand equity should be that consumers are more willing to pay higher regular prices for a brand of higher stature (i.e., a larger price premium) relative to competing brands, and more forgiving when such a brand sees it necessary to update and raise its regular price. The brand may benefit from being more personally relevant to the consumer, better understood and more highly appreciated. A brand more clearly differentiated from competitors with respect to its advantages could also benefit from a protected status. All these properties are presumed to enhance attachment to a brand, and subsequently lead to greater loyalty, making consumers more ready to stick with the brand even as it becomes more expensive. This research disproves such expectations. Better responsiveness to price promotions can help to increase sales and revenue, but it testifies to the heightened level of competition in many categories (e.g., FMCG or packaged goods) and propensity of consumers to be more opportunistic rather than to the strength of the brands. This result, actually a warning signal, cannot be brushed away easily.

  • Towards the end of the article, the researchers suggest as explanation that they ignored possible differences in response to increases and decreases in regular prices (i.e., asymmetric elasticity). Even so, increases in regular prices by stronger brands are more likely to happen than price decreases, and the latter already are more realistically accounted for in response to promotional prices.

Relevant stature is positively related to responsiveness to feature or promotional display (i.e., consumers are more inclined to purchase from a higher stature brand when in an advantaged display). Consumers also are more strongly receptive to larger volume of advertising by brands of higher stature and better differentiation in their eyes (this analysis could not refer to actual advertising messages and hence perhaps the weaker positive effects). Another interesting finding indicates that sensitivity to degree of distribution (on-shelf availability) is inversely associated with stature — the higher the brand stature from consumer viewpoint, larger distribution is less attractive to the consumers. As the researchers suggest, consumers are more willing to look harder and farther (e.g., in other stores) for those brands regarded more important for them to have. So here is a positive evidence for the impact of stronger brands or higher brand equity.

The research gives rise to some methodological questions on measurement of brand equity that remain open for further deliberation:

  1. Should the measure of brand equity in choice models rely only on a brand-specific intercept (expressing intrinsic assets or value of the brand) or should it include also a reflection of the impact of brand equity as in response to marketing mix activities?
  2. Are attitudinal measures of brand equity (CBBE) too gross and not sensitive enough to capture the incremental value added by the brand or is the measure of brand equity based only on a brand-intercept term in a model of actual purchase data too specific and narrow?  (unless it accounts for some of the impact of brand equity)
  3. How should measures of brand equity based on stated-choice (conjoint) data and actual purchase data be classified with respect to a consumer perspective? (both pertain really to consumers: either their cognition or overt behaviour).

Datta, Ailawadi and van Heerde throw light in their extensive research on the relation of consumer-based equity (CBBE) to behavioural outcomes, manifested in brand equity based on actual purchases (SBBE) and in effects on response to marketing mix actions as an impact of brand equity. Attention should be awarded to positive implications of this research for practice but nonetheless also to the warning alerts it may signal.

Ron Ventura, Ph.D. (Marketing)

Notes:

[1] How Well Does Consumer-Based Brand Equity Align with Sales-Based Brand Equity and Marketing-Mix Response?; Hannes Datta, Kusum L. Ailawadi, & Harald J. van Heerde, 2017; Journal of Marketing, 81 (May), pp. 1-20. (DOI: 10.1509/jm.15.0340)

[2] Brands and Branding: Research Findings and Future Priorities; Kevin L. Keller and Donald R. Lehmann, 2006; Marketing Science, 25 (6), pp. 740-759. (DOI: 10.1287/mksc.1050.0153)

[3] Developing and Validating a Multidimensional Consumer-Based Brand Equity Scale; Boonghee Yoo and Naveen Donthu, 2001; Journal of Business Research, 52, pp. 1-14.

[4]  Developing and Validating Measures of Facets of Customer-Based Brand Equity; Richard G. Netemeyer, Balaji Krishnan, Chris Pullig, Guangping Wang,  Mahmet Yageci, Dwane Dean, Joe Ricks, & Ferdinand Wirth, 2004; Journal of Business Research, 57, pp. 209-224.

[5] The authors name this dimension ‘energised differentiation’ in reference to an article in which researchers Mizik and Jacobson identified a fifth pillar of energy, and suggest that differentiation and energy have since been merged. However, this change is not mentioned or revealed on the website of BAV Group.

[6] A Conjoint Approach for Consumer- and Firm-Level Brand Valuation; Madiha Ferjani, Kamel Jedidi, & Sharan Jagpal, 2009; Journal of Marketing Research, 46 (December), pp. 846-862.

[7] These two factors (principal components) extracted by Datta et al. are different from two higher dimensions defined by BAV Group (stature = esteem and knowledge, strength = relevance and differentiation). However, the distinction made by the researchers as corroborated by their data is more meaningful  and relevant in the context of this study.

 

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Fifteen years have passed since a Nobel Prize in economics was awarded to Daniel Kahneman to this time (Fall 2017) when another leading researcher in behavioural economics, Richard Thaler, wins this honourable prize. Thaler and Kahneman are no strangers — they have collaborated in research in this field from its early days in the late 1970s. Moreover, Kahneman together with the late Amos Tversky helped Thaler in his first steps in this field, or more generally in meeting economics with psychology. Key elements of Thaler’s theory of Mental Accounting are based on the value function in Kanheman and Tversky’s Prospect theory.

In recent years Thaler is better known for the approach he devised of choice architecture and the tools of nudging, as co-author of the book “Nudge: Improving Decisions About Health, Wealth and Happiness” with Cass Sunstein (2008-9). However, at the core of the contribution of Thaler is the theory of mental accounting where he helped to lay the foundations of behavioural economics. The applied tools of nudging are not appropriately appreciated without understanding the concepts of mental accounting and other phenomena he studied with colleagues which describe deviations in judgement and behaviour from the rational economic model.

Thaler, originally an economist, was unhappy with predictions of consumer choice arising from microeconomics — the principles of economic theory were not contested as a normative theory (e.g., regarding optimization) but claims by economists that the theory is able to describe actual consumer behaviour and predict it were put into question. Furthermore, Thaler and others early on argued that deviations from rational judgement and choice behaviour are predictable.  In his ‘maverick’ paper “Toward a Positive Theory of Consumer Choice” from 1980, Thaler described and explained deviations and anomalies in consumer choice that stand in disagreement with the economic theory. He referred to concepts such as framing of gains and losses, the endowment effect, sunk costs, search for information on prices, regret, and self-control (1).

The theory of mental accounting developed by Thaler thereafter is already an integrated framework that describes how consumers perform value judgements and make choice decisions of products and services to purchase while recognising psychological effects in making economic decisions (2).  The theory is built around three prominent concepts (described here only briefly):

Dividing a budget into categories of expenses: Consumers metaphorically (but sometimes physically) allocate the money of their budget into buckets or envelopes according to type or purpose of expenses. It means that they do not transfer money freely between categories (e.g., food, entertainment). This concept contradicts the economic principle of fungibility, thus suggesting that one dollar is not valued the same in every category. A further implication is that each category has a sub-budget allotted to it, and if expenses in the category during a period surpass its limit, a consumer will prefer to give up on the next purchase and refrain from adding money from another category. Hence, for instance,  Dan and Edna will not go out for dinner at a trendy restaurant if that requires taking money planned for buying shoes for their child. However, managing the budget according to the total limit of income in each month is more often unsatisfactory, and some purchases can still be made on credit without hurting other purchases in the same month. On the other hand, it can readily be seen how consumers get into trouble when they try to spread too many expenses across future periods with their credit cards, and lose track of the category limits for their different expenses.

Segregating gains and integrating losses: In the model of a value function by Kahneman and Tversky, value is defined upon gains and losses as one departs from a reference point (a “status quo” state). Thaler explicated in turn how properties of the gain-loss value function would be implemented in practical evaluations of outcomes. The two general “rules”, as demonstrated most clearly in “pure” cases, say: (a) if there are two or more gains, consumers prefer to segregate them (e.g., if Chris makes gains on two different shares on a given day, he will prefer to see them separately); (b) if there are two or more losses, consumers prefer to integrate them (e.g., Sarah is informed of a price for an inter-city train trip but then told there is a surcharge for travelling in the morning — she will prefer to consider the total cost for her requested journey). Thaler additionally proposed what consumers would prefer doing in more complicated cases of “mixed” gains and losses, whether to segregate between the gain and loss (e.g., if the loss is much greater than the gain) or integrate them (e.g., if the gain is larger than the loss so that one remains with a net gain).

Adding-up acquisition value with transaction value to evaluate product offers: A product or service offer generally exhibits in it benefits and costs to the consumer (e.g., the example of a train ticket above overlooked the benefit of the travel to Sarah). But value may arise from the offering or deal itself beyond the product per se. Thaler recognised that consumers may look at two sources of value, and composing or adding them together would yield the overall worth of a product purchase offer: (1) Acquisition utility is the value of a difference between the [monetary] value equivalent of a product to the consumer and its actual price; (2) Transaction utility is the value of a difference between the actual price and a reference price. In the calculus of value, hides the play of gains and losses. This value concept was quite quickly adopted by consumer and marketing researchers in academia and implemented in means-end models that depict chains of value underlying the purchase decision process of consumers (mostly in the mid-1980s to mid-1990s). Thaler’s approach to ‘analysing’ value is getting more widely acknowledged and applied also in practice, as expressions of value as such in consumer response to offerings can be found in so many domains of marketing and retailing.

A reference price may receive different representations, for instance: the price last paid; price recalled from a previous period; average or median price in the same product class; a ‘normal’ or list price; a ‘fair’ or ‘just’ price (which is not so easy to specify). The transaction value may vary quite a lot depending on the form of reference price a consumer uses, ceteris paribus, and hence affect how the transaction value is represented (i.e., as a gain or a loss and its magnitude). Yet, it also suggests that marketers may hint to consumers a price to be used as a reference price (e.g., an advertised price anchor) and thus influence consumers’ value judgements.

We often observe and think of discounts as a difference between an actual price (‘only this week’) and a higher normal price — in this case we may construe the acquisition value and transaction value as two ways to perceive gain on the actual price concurrently. But the model of Thaler is more general because it recognizes a range of prices that may be employed as a reference by consumers. In addition, a list price may be suspected to be set higher to invoke in purpose the perception of a gain vis-à-vis the actual discounted price which in practice is more regular than the list price. A list price or an advertised price may also serve primarily as a cue for the quality of the product (and perhaps also influence the equivalent value of the product for less knowledgeable consumers), while an actual selling price provides a transaction value or utility. In the era of e-commerce, consumers also appear to use the price quoted on a retailer’s online store as a reference; then they may visit one of its brick-and-mortar stores, where they hope to obtain their desired product faster, and complain if they discover that the price for the same product in-store is much higher. Where customers are increasingly grudging over delivery fees and speed, a viable solution to secure customers is to offer a scheme of ‘click-and-collect at a store near you’. Moreover, when more consumers shop with a smartphone in their hands, the use of competitors’ prices or even the same retailer’s online prices as references is likely to be even more frequent and ubiquitous.


  • The next example may help further to illustrate the potentially compound task of evaluating offerings: Jonathan arrives to the agency of a car dealer where he intends to buy his next new car of favour, but there he finds out that the price on offer for that model is $1,500 higher than a price he saw two months earlier in ads. The sales representative claims prices by the carmaker have risen lately. However, when proposing a digital display system (e.g., entertainment, navigation, technical car info) as an add-on to the car, the seller proposes also to give Jonathan a discount of $150 on its original price tag.
  • Jonathan appreciates this offer and is inclined to segregate this saving apart from the additional pay for the car itself (i.e., ‘silver-lining’). The transaction value may be expanded to include two components (separating the evaluations of the car offer and add-on offer completely is less sensible because the add-on system is still contingent on the car).

Richard Thaler contributed to the revelation, understanding and assessment of implications of additional cognitive and behavioural phenomena that do not stand in line with rationality in the economic sense. At least some of those phenomena have direct implications in the context of mental accounting.

One of the greater acknowledged phenomena by now is the endowment effect. It is the recognition that people value an object (product item) already in their possession more than when having the option of acquiring the same object. In other words, the monetary compensation David would be willing to accept to give up on a good he holds is higher than the amount he would agree to pay to acquire it —  people principally have a difficulty to give up on something they own or endowed with (no matter how they originally obtained it). This effect has been most famously demonstrated with mugs, but to generalise it was also tested with other items like pens. This effect may well squeeze into consumers’ considerations when trying to sell much more expensive properties like their car or apartment, beyond an aim to make a financial gain. In his latest book on behavioural economics, ‘Misbehaving’, Thaler provides a friendly explanation with graphic illustration as to why fewer transactions of exchange occur between individuals who obtain a mug and those who do not, due to the endowment effect vis-à-vis a prediction by economic theory (3).

Another important issue of interest to Thaler is fairness, such as when it is fair or acceptable to charge a higher price from consumers for an object in shortage or hard to obtain (e.g., shovels for clearing snow on the morning after a snow storm). Notably, the perception of “fairness” may be moderated depending on whether the rise in price is framed as a reduction in gain (e.g., a discount of $2o0 from list price being cancelled for a car in short supply) or an actual loss (e.g., an explicit increase of $200 above the list price) — the change in actual price is more likely to be perceived as acceptable in the former case than the latter (4). He further investigated fairness games (e.g., Dictator, Punishment and Ultimatum). Additional noteworthy topics he studied are susceptibility to sunk cost and self-control.

  • More topics studied by Thaler can be traced by browsing his long list of papers over the years since the 1970s, and perhaps more leisurely through his illuminating book: “Misbehaving: The Making of Behavioural Economics” (2015-16).

The tactics of nudging, as part of choice architecture, are based on lessons from the anomalies and biases in consumers’ procedures of judgement and decision-making studied by Thaler himself and others in behavioural economics. Thaler and Sunstein looked for ways to guide or lead consumers to make better choices for their own good — health, wealth and happiness — without attempting to reform or alter their rooted modes of thinking and behaviour, which most probably would be doomed to failure. Their clever idea was to work within the boundaries of human behaviour to modify it just enough and in a predictable way to put consumers on a better track to a choice decision. Nudging could mean diverting a consumer from his or her routine way of making a decision to arrive to a different, expectedly better, choice outcome. It often likely involves taking a consumer out of his or her ‘comfort zone’. Critically important, however, Thaler and Sunstein conditioned in their book ‘Nudge’ that: “To count as a mere nudge, the intervention must be easy and cheap to avoid. Nudges are not mandates“. Accordingly, nudging techniques should not impose on consumers the choice of any designated or recommended options (5).

Six categories of nudging techniques are proposed: (1) defaults; (2) expect errors; (3) give feedback; (4) understanding “mappings”; (5) structure complex choices; and (6) incentives. In any of these techniques, the intention is to allow policy makers to direct consumers to choices that improve the state of consumers. Yet, the approach they advocate of ‘libertarian paternalism’ is not received without contention —  while libertarian, that is without coercing a choice, a question remains what gives an agency or policy maker the wisdom and right to determine which options should be better off for consumers (e.g., health plans, saving and investment programmes). Thaler and Sunstein discuss the implementation of nudging mostly in the context of public policy (i.e., by government agencies) but these techniques are applicable just as well to plans and policies of private agencies or companies (e.g., banks, telecom service providers, retailers in their physical and online stores). Nevertheless, public agencies and even more so business companies should devise and apply any measures of nudging to help consumers to choose the better-off and fitting plans for them; it is not for manipulating the consumers or taking advantage of their human errors and biases in judgement and decision-making.

Richard Thaler reviews and explains in his book “Misbehaving” the phenomena and issues he has studied in behavioural economics through the story of his rich research career — it is an interesting, lucid and compelling story. He tells in a candid way about the stages he has gone through in his career. Most conspicuously, this story also reflects the obstacles and resistance that faced behavioural economists for at least 25-30 years.

Congratulations to Professor Richard Thaler, and to the field of behavioural economics to which he contributed wholesomely, in theory and in its application.    

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) Toward a Positive Theory of Consumer Choice; Richard H. Thaler, 1980/2000; in Choices, Values and Frames (eds. Daniel Kahneman and Amos Tversky)[Ch. 15: pp. 269-287], Cambridge University Press. (Originally published in Journal of Economic Behaviour and Organization.)

(2) Mental Accounting and Consumer Choice; Richard H. Thaler, 1985; Marketing Science, 4 (3), pp. 199-214.

(3) Misbehaving: The Making of Behavioural Economics; Richard H. Thaler, 2016; UK: Penguin Books (paperback).

(4) Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias; Daniel Kahneman, Jack L. Knetsch, & Richard H. Thaler, 1991/2000; in Choices, Values and Frames (eds. Daniel Kahneman and Amos Tversky)[Ch. 8: pp. 159-170], Cambridge University Press. (Originally published in Journal of Economic Perspectives).

(5) Nudge: Improving Decisions About Health, Wealth, and Happiness; Richard H. Thaler and Cass R. Sunstein, 2009; UK: Penguin Books (updated edition).

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A new film this year, “Sully”, tells the story of US Airways Flight 1549 that landed safely onto the water surface of the Hudson River on 15 January 2009 following a drastic damage to the plane’s two engines. This article is specifically about the decision process of the captain Chesley (Sully) Sullenberger with the backing of his co-pilot (first officer) Jeff Skiles; the film helps to highlight some instructive and interesting aspects of human judgement and decision-making in an acute crisis situation. Furthermore, the film shows how those cognitive processes contrast with computer algorithms and simulations and why the ‘human factor’ must not be ignored.

There were altogether 155 people on board of the Airbus A320 aircraft in its flight 1549 from New-York to North Carolina: 150 passengers and five crew members. The story unfolds whilst following Sully in the aftermath of the incident during the investigation of the US National Transportation Safety Board (NTSB) which he was facing together with Skiles. The film (directed by Clint Eastwood, featuring Tom Hanks as Sully and Aaron Ackhart as Skiles, 2016) is based on Sullenberger’s autobiographic book “Highest Duty: My Search for What Really Matters” (2009). Additional resources such as interviews and documentaries were also used in preparation of this article.

  • The film is excellent, recommended for its way of delivering the drama of the story during and after the flight, and for the acting of the leading actors. A caution to those who have not seen the film: the article includes some ‘spoilers’. On the other hand, facts of this flight and the investigation that followed were essentially known before the film.

This article is not explicitly about consumers, although the passengers, as customers, were obviously directly affected by the conduct of the pilots as it saved their lives. The focus, as presented above, is on the decision process of the captain Sullenberger. We may expect that such an extraordinary positive outcome of the flight, rescued from a dangerous circumstance, would have a favourable impact on the image of the airline US Airways that employs such talented flight crew members. But improving corporate image or customer service and relationships were not the relevant considerations during the flight, just saving lives.

Incident Schedule: Less than 2 minutes after take-off (at ~15:27) a flock of birds (Canada geese) clashed into both engines of the aircraft. It is vital to realise that from that moment, the flight lasted less than four minutes! The captain took control of the plane from his co-pilot immediately after impact with the birds, and then had between 30 seconds to one minute to make a decision where to land.  Next, just 151 seconds passed from impact with the birds and until the plane was approaching right above the Hudson river for landing on the water. Finally, impact with water occurred 208 seconds after impact with the birds (at ~15:30).

Using Heuristics: The investigators of NTSB told Sully (Hanks) about flight calculations performed in their computer simulations, and argued that according to the simulation results it had not been inevitable to land on the Hudson river, a highly risky type of crash-land. In response, Sully said that it had been impossible for himself and Skiles to perform all those detailed calculations during the four minutes of the flight after the impact of the birds with the aircraft’s engines; he was relying instead on what he saw with his eyes in front of him — the course of the plane and the terrain below them as the plane was gliding with no engine power.

The visual guidance Sully describes as using to navigate the plane resembles a type of ‘gaze heuristic’ identified by professor Gerd Gigerenzer (1). In the example given by Gigerenzer, a player who tries to catch a ball flying in the air does not have time to calculate the trajectory of the ball, considering its initial position, speed and angle of projection. Moreover, the player should also take into account wind, air resistance and ball spin. The ball would be on the ground by the time the player makes the necessary estimations and computation. An alternative intuitive strategy (heuristic) is to ‘fix gaze on the ball, start running, and adjust one’s speed so that the angle of gaze remains constant’. The situation of the aircraft flight is of course different, more complex and perilous, but a similar logic seems to hold: navigating the plane in air safely towards the terrain surface (land or water) when there is no time for any advanced computation (the pilot’s gaze would have to be fixed on the terrain beneath towards a prospect landing ‘runway’). Winter winds in New-York City on that frozen day have probably made the landing task even more complicated.  But in those few minutes available to Sully, he found this type of ‘gaze’ or eyesight guiding rule the most practical and helpful.

Relying on Senses: Sullenberger made extensive use of his senses (visual, auditory, olfactory) to collect every information he could get from his surrounding environment. To start with, the pilots could see the birds coming in front of them right before some of them were clashing into the engines — this evidence was crucial to identifying instantly the cause of the problem though they still needed some time to assess the extent of damage. In an interview to CBS’s programme 60 Minutes (with Katie Couric, February 2009), Sully says that he saw the smoke coming out from both engines, smelled the burned flesh of the birds, and subsequently heard a hushing noise from the engines (i.e., made by the remaining blades). He could also feel the trembling of the broken engines. This multi-modal sensory information contributed to convincing him that the engines were lost (i.e., unable to produce thrust) in addition to failure to restart them. Sully also utilised all that time information from the various meters or clocks in the cockpit dashboard in front of him (while Skiles was reading to him from the manuals). The captain was thus attentive to multiple visual stimuli (including and beyond using a visual guidance heuristic) in his decision process, from early judgement to action on his decision to land onto the water of the Hudson river.

Computer algorithms can ‘pick-up’ and process all the technical information of the aircraft displayed to the pilots in the cockpit. The algorithms may also apply in the computations additional measurements (e.g., climate conditions) and perhaps data from sensors installed in the aircraft. But the computer algorithms cannot ‘experience’ the flight event like the pilots. Sully could ‘feel the aircraft’, almost simultaneously and rapidly perceive the sensory stimuli he received in the cockpit, within and outside the cabin, and respond to them (e.g., make judgement). Information available to him seconds after impact with the birds gave him indications about the condition of the engines that algorithms as used in the simulations could not receive. That point was made clear in the dispute that emerged between Sully and the investigating committee with regard to the condition of one of the engines. The investigators claimed that early tests and simulations suggested one of the engines was still functioning and could allow the pilots to bring the plane to land in one of the nearby airports (returning to La Guardia or reverting to Teterboro in New-Jersey). Sully (Hanks) disagreed and argued that his indications were clear that the second engine referred to was badly damaged and non-functional — both engines had no thrust. Sully was proven right — the committee eventually updated that missing parts of the disputed engine were found and showed that the engine was indeed non-functional, disproving the early tests.

Timing and the Human Factor: The captain Sullenberger had furthermore a strong argument with the investigating committee of NTSB about their simulations in attempt to re-construct or replicate the sequence of events during the flight. The committee argued that pilots in a flight simulator ‘virtually’ made a successful landing in both La Guardia and Teterboro airports when the simulator computer was given the data of the flight. Sully (Hanks) found a problem with those live but virtual simulations. The flight simulation was flawed because it made the assumption the pilots could immediately know where it was possible to land, and they were instructed to do so. Sully and Skiles indeed knew immediately the cause of damage but still needed time to assess the extent of damage before Sully could decide how to react. Therefore, they could not actually turn the plane towards one of those airports right after bird impact as the simulating pilots did. The committee ignored the human factor, as argued by Sully, that had required him up to one minute to realise the extent of damage and his decision options.

The conversation of Sully with air controllers demonstrates his assessments step-by-step in real-time that he could not make it to La Guardia or alternatively to Teterboro — both were effectively considered — before concluding that the aircraft may find itself in the water of the Hudson. Then the captain directed the plane straight above the river in approach to crash-landing. One may also note how brief were his response statements to the air controller.  Sully was confident that landing on the Hudson was “the only viable alternative”. He told so in his interview to CBS. In the film, Sully (Hanks) told Skiles (Ackhart) during a recuperating break outside the committee hall that he had no question left in his mind that they have done the right thing.

Given the strong resistance of Sully, the committee ordered additional flight simulations where the pilots were “held” waiting for 35 seconds to account for the time needed to assess the damage before attempting to land anywhere. Following this minimum delay the simulating pilots failed to land safely neither at La Guardia nor at Teterboro. It was evident that those missing seconds were critical to arriving in time to land in those airports. Worse than that, the committee had to admit (as shown in the film) that the pilots made multiple attempts (17) in their simulations before ‘landing’ successfully in those airports. The human factor of evaluation before making a sound decision in this kind of emergency situation must not be ignored.

Delving a little deeper into the event helps to realise how difficult the situation was.  The pilots were trying to execute a three-part checklist of instructions. They were not told, however, that those instructions were made to match a situation of loss of both engines at a much higher altitude than they were at just after completing take-off. The NTSB’s report (AAR-10-03) finds that the dual engine failure at a low altitude was critical — it allowed the pilots too little time to fulfill the existing three-part checklist. In an interview to Newsweek in 2015, Sullenberger said on that challenge: “We were given a three-page checklist to go through, and we only made it through the first page, so I had to intuitively know what to do.”  The NTSB committee further accepts in its report that landing at La Guardia could succeed only if started right after the bird strike, but as explained earlier, that was unrealistic; importantly, they note the realisation made by Sullenberger that an attempt to land at La Guardia “would have been an irrevocable choice, eliminating all other options”.

The NTSB also commends Sullenberger in its report for operating the Auxiliary Power Unit (APU). The captain asked Skiles to try operating the APU after their failed attempt to restart the engines. Sully decided to take this action before they could reach the article on the APU in the checklist. The operation of the APU was most beneficial according to NTSB to allow electricity on board.

Notwithstanding the judgement and decision-making capabilities of Sully, his decision to land on waters of the Hudson river could have ended-up miserably without his experience and skills as a pilot to execute it rightly. He has had 30 years of experience as a commercial pilot in civil aviation since 1980 (with US Airways and its predecessors), and before that had served in the US Air Force in the 1970s as a pilot of military jets (Phantom F-4). The danger in landing on water is that the plane would swindle and not reach in parallel to the water surface, thus one of the wings might hit water, break-up and cause the whole plane to capsize and break-up into the water (as happened in a flight in 1996). That Sully succeeded to safely “ditch” on water surface is not obvious.

The performance of Sullenberger from decision-making to execution seems extraordinary. His judgement and decision capacity in these flight conditions may be exceptional; it is unclear if other pilots could perform as well as he has done. Human judgement is not infallible; it may be subject to biases and errors and succumb to information overload. It is not too difficult to think of examples of people making bad judgements and decisions (e.g., in finance, health etc.). Yet Sully has demonstrated that high capacity of human judgement and sound decision-making exists, and we can be optimistic about that.

It is hard, and not straightforward, to extend conclusions from flying airplanes to other areas of activity. In one aspect, however, there can be some helpful lessons to learn from this episode in thinking more deeply and critically about the replacement of human judgement and decision-making with computer algorithms, machine learning and robotics. Such algorithms work best in familiar and repeated events or situations. But in new and less familiar situations and in less ordinary and more dynamic conditions humans are able to perform more promptly and appropriately. Computer algorithms can often be very helpful but they are not always and necessarily superior to human thinking.

This kind of discussion is needed, for example, in respect to self-driving cars. It is a very active field in industry these days, connecting automakers with technology companies for installing autonomous computer driving systems in cars. Google is planning on creating ‘driverless’ cars without a steering wheel or pedals; their logic is that humans should not be involved anymore in driving: “Requiring a licensed driver be able to take over from the computer actually increases the likelihood of an accident because people aren’t that reliable” (2). This claim is excessive and questionable. We have to carefully distinguish between computer aid to humans and replacing human judgement and decision-making with computer algorithms.

Chesley (Sully) Sullenberger has allowed himself as the flight captain to be guided by his experience, intuition and common sense to land the plane safely and save the lives of all passengers and crew on board. He was wholly focused on “solving this problem” as he told CBS, the task of landing the plane without casualties. He recruited his best personal resources and skills to this task, and in his success he might give everyone hope and strength in belief in human capacity.

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) “Gut Feelings: The Intelligence of the Unconscious”, Gerd Gigerenzer, 2007, Allen Lane (Pinguin Books).

(2) “Some Assembly Required”, Erin Griffith, Fortune (Europe Edition), 1 July 2016.

 

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