Contexts and Individual Differences as Influences on Consumers Delay Discounting

Transcription

1 The Psychological Record, 2011, 61, Contexts and Individual Differences as Influences on Consumers Delay Discounting Gordon R. Foxall, John R. Doyle, and Mirella Yani-de-Soriano Cardiff University Victoria K. Wells University of Durham Delay discounting is often considered a universal feature of human choice behavior, but there is controversy over whether it is an individual difference that reflects an underlying psychological trait or a domain-specific behavior. Trait influence on discounting would manifest in (a) highly correlated discount rates for all decisions, regardless of context, and (b) the reflection of discounting behavior in psychometric measures of individual difference. We examined these propositions for consumers making hypothetical decisions with respect to financial returns, health outcomes, and vacation alternatives. Questionnaires were employed to assess discounting rates, and respondents (N = 74) cognitive styles were measured by the Kirton Adaption-Innovation Inventory (KAI). Results suggested that discounting is a domain-specific behavior rather than a single trait. Individual discounting rates differed markedly among product contexts; moreover, individual differences in cognitive style were not related to discounting behavior. Key words: discounting, individual differences, consumers, domain specific, cognitive style, adaption-innovation Delay discounting, the tendency to prefer a smaller reward that is available immediately or soon to a larger reward that is delayed, is often used as an index of impulsivity or impatience (e.g., Ainslie, 1992; Bickel & Marsch, 2001; Foxall, 2010; Green & Myerson, 2010; Heyman, 2009; Rachlin, 2000; Ross, Sharp, Vuchinich, & Spurrett, 2008). The apparent lack of self-control inherent in impulsive behavior often indicates a willingness not only to settle for a smaller financial gain when a larger one could be had for the waiting, but also to incur sacrifices to one s health or leisure pursuits. There is considerable evidence that human consumers discount hyperbolically, Research for this article was funded by a pump-priming grant from Cardiff Business School to the first author. Correspondence concerning this article should be addressed to Gordon Foxall, Cardiff Business School, Cardiff University, Aberconway Building, Colum Drive, Cardiff, CF10 3EU, UK. Foxall@cf.ac.uk

2 600 Foxall et al. such that a reward that will soon be available assumes a value out of all proportion to that ascribed to it when it was temporally distant (Ainslie, 2001; Dittmar & Bond, 2010; Chapman & Elstein, 1995; Smith & Hantula, 2003). These findings raise the question of whether impulsivity is a state induced by current circumstances, such that discounting rates are subject to change from situation to situation, or alternatively, whether impulsivity is a trait that engenders a high degree of consistency in discounting from place to place and time to time (Odum & Baumann, 2010). The association of steep delay discounting with addiction and other behaviors that are apparently marked by impulsiveness (for a review, see Reynolds, Richards, & de Wit, 2006) adds emphasis to the need to isolate the factors that determine the incidence and pattern of discounting for individuals. The success of interventions into the lives of individuals who exhibit such extreme decision-making tendencies depends heavily on the source of influences on such behaviors. The answer to whether these are predominantly internal (implying a personality trait) or external (suggesting situational specificity) has ramifications for the treatment of addiction and related behaviors as either diseases or choices (Heyman, 2009), yet there is comparatively little empirical evidence with which this issue might be resolved (Odum & Baumann, 2010). In the current article, we report an investigation of individual differences in delay discounting that considered a broad conceptualization of individual difference, Kirton s (2003) adaption-innovation theory. Adaptive-innovative cognitive style correlates with an extensive range of personality traits and has been validated in many contexts of human behavior, including consumer decision making (Kirton, 2003; Foxall & James, 2009; Goldsmith & Foxall, 2003). Individual and Domain Differences Three consumption contexts, previously researched by behavioral economists, lend themselves to the investigation of the roles played by context and individual differences: financial decision making, the assignment of personal health priorities, and the allocation of time to leisure pursuits such as vacationing (Chapman & Elstein, 1995). These contexts present sufficient differences to constitute a suitable range of situations across which the expectation of consistent discounting rates may be tested. An essential situational difference between money and health, for instance, is that health, unlike money, cannot be saved for future consumption or invested to increase capital. Chapman (1996) found not only that the average temporal discounting rates for money and health differed significantly, but also that there was little correlation between individual discounting rates for money and health. These results are inconsistent with a single trait, but given the importance of the issue, more research and particularly research examining additional domains is needed. There are undoubtedly individual differences in rates of discounting: heavy drug users and addicts in general typically discount more steeply than non-drug users and nonaddicts, for instance (Bickel & Vuchinich, 2000; Dixon, Marley, & Jacobs, 2003; Kirby, Petry, & Bickel, 1999; Ross, Kincaid, Spurrett, & Collins, 2010; Vuchinich & Heather, 2003). However, these demonstrations of individual differences in behavior are not matched by evidence for distinctions at the level of personality and cognition. In a recent review,

3 INFLUENCES ON DELAY DISCOUNTING 601 Odum and Baumann (2010) discussed a number of studies reporting contradictory results with respect to the relation between trait measures of impulsivity and delay discounting. In part, the finding that psychometric studies of trait impulsiveness and delay discounting do not show a consistent association may reflect the diverse measurements of this trait and the wide range of meanings that are applied to impulsivity in everyday life (Madden & Bickel, 2010). Plunkett and Buehner s (2007) finding that discounting was less steep among respondents with a more internal locus of control is consistent with a personality style that stresses inner-direction and personal responsibility for making the most of one s economic resources. This might imply a willingness to exercise patience in order to realize an economic advantage. Conversely, external locus of control, or other-directedness, implies a more fatalistic approach to economic gain and thus a greater demand for higher returns if immediate gratification is to be relinquished. However, Ostaszewksi s (1996, 1997) finding that extraversion, but not sensation seeking, was associated with steeper discounting of financial values is a somewhat surprising result that requires further investigation. Adaptive-Innovative Cognitive Style A theory regarding cognitive style and a resulting measure that have demonstrable merit in the analysis of personality dimensions of consumption behavior stem from Kirton s (1976) notion of adaptive-innovative cognitive style (for a review, see Foxall & James, 2009). Cognitive style is an individual s characteristic way of reaching decisions and solving problems. Kirton s (2003) theory posits two extreme cognitive styles. Those close to the adaptive pole of the continuum are typically prudent in their decision making, employing tried and tested means of solving problems and excelling in finding practical solutions to relatively familiar problems. The extreme innovator, by contrast, appears reckless in his or her proposals for solving problems. Their proposed solutions may appear to be outlandish, requiring not only a reevaluation of the problem but also a reconceptualization of the context in which it has become obvious. Adaption-innovation, as measured by the Kirton Adaption-Innovation Inventory (KAI; Kirton, 1976), is an approximately normally distributed trait in general populations, such that most individuals are not as extreme as these examples. Rather, their decisions styles exhibit greater or lesser tendencies toward one or the other style. As a measure of intellectual style rather than level, KAI scores are orthogonal to IQ scores. If delay discounting is wholly or principally the outcome of a personality trait, it ought to correlate directly with the KAI, because this measure is itself correlated with the very traits of personality that are widely assumed to underlie discounting. The personality trait most strongly associated with adaption-innovation is introversion/extraversion. This is combined in the KAI measure with conceptually related traits such as self-esteem, which suggests an internal locus of control, and sensation seeking, which includes risk taking, although the situation is actually more complicated than this (Kirton, 2003). In situations of purchase and consumption, innovators evince greater impatience than adaptors, sampling a greater number and wider variety of

4 602 Foxall et al. new products and services and showing comparatively little loyalty to any particular product or brand. Adaptors, in contrast, adopt fewer innovations and are more likely to remain steadfast consumers of products and brands that have proven satisfactory. Innovators also show a higher optimum level of stimulation and greater extraversion, as well as higher degrees of sensation- seeking behavior, tolerance of ambiguity, and self-esteem, all of which would presumably act to free the individual from any particular situational context and encourage the same relatively high level of impulsivity in a variety of domains. Generalizing this behavioral tendency, the implication for the current study is that innovators are more likely to show impatience, impulsivity, and consistently steeper discounting rates across domains than are adaptors (Foxall & James, 2009; Wang, Doong, & Foxall, 2010). Method Participants Data were collected from a convenience sample of British consumers. A total of 74 participants completed questionnaires and provided demographic information. Data were gathered at 12 sample points in the cities of Cardiff, Birmingham, and Derby in the UK. The sample points consisted of two universities, four business organizations, a hospital, and five residential areas. The questionnaires were administered in person, and each participant was asked to fill in two separate questionnaires. The first was the Kirton Adaption-Innovation Inventory, which consisted of 32 questions rated on a 5-point scale, and the second was the discounting questionnaire, which comprised a total of 35 questions divided into three parts, one for each of the products tested: financial, health, and vacations. Respondents received 10 cash (approximately US$15) for their effort. Participants ages ranged from 19 to 62 years, with an average age of 32.2; 63% were female. Eighty percent of the participants held a university degree. Thirty-five percent had professional jobs, 20% clerical, and 2% technical; 43% were graduate students. Materials and Procedure Discounting questionnaire. The discounting questionnaire (see the Appendix) was designed to measure discounting rates for each person in three distinct areas of interest: (a) financial, (b) health, and (c) vacations. Financial. The 27 financial questions were taken from Kirby et al. (1999, Table 3; cf. Kirby & Marakovic, 1996). Currency was changed to British pounds ( ) from U.S. dollars to be relevant to a British sample. Kirby et al. s Question 18 ( $24 today or $35 in 29 days ) was incorrectly transcribed such that $24 became 14. Each choice consisted of a smaller, sooner reward and a larger, later reward, for example, Would you prefer 10 today, or 50 in 19 days? To avoid response-set bias, the order of the questions was fixed in a way that it did not correlate with the amounts, their ratio, their difference, the delay to the larger reward, or the discount rate corresponding to indifference between the two rewards (Kirby et al., 1999).. The health questions were based on those used by Chapman and Elstein (1995). Participants were provided a description of poor health and asked to imagine that they had been in such a state for 2 years and that

5 INFLUENCES ON DELAY DISCOUNTING 603 without treatment this state would continue for the rest of their lives. They were further told that two new treatments, A and B, could return them to full health for a limited period of time. In all questions, Treatment A would provide 1 year of respite beginning immediately. In separate questions, the effect of Treatment B would be delayed for either 6 months, 1 year, 2 years, or 4 years. Participants were instructed to indicate how many years of respite from illness would have to be provided by Treatment B in order to make it just as attractive as Treatment A. Vacations. The questions regarding vacation choices were also modified from those used by Chapman and Elstein (1995). Participants were asked to imagine they had won a prize that enabled them to choose between vacation packages that we designed to be approximate equivalents of those used by Chapman and Elstein but adapted for participants in the UK. The location and duration of each vacation and the time at which it would begin were specified. Both of the vacations were in the same city, but one of them was postponed for 1 month and the other was postponed for 1 year. In separate questions, the shorter, sooner vacation was a 2-night trip to Brecon in Wales, a 3-night trip to Paris, a 7-night trip to New York, and a 14-night trip to Tokyo. As with the health questions, participants were asked to specify how long the delayed outcome would have to be in order to make the two options equally attractive. Kirton Adaption-Innovation Inventory. Respondents also completed the KAI, a 32-item scale that measures adaptive-innovative cognitive style (i.e., the extent to which individuals report being able to comfortably sustain selected adaptive and innovative behaviors). Each of the situations tested is rated on a 5-point scale; some items are reverse scored. The inventory provides a measure ranging from extreme adaption to extreme innovativeness and provides scores for three subscales: Rule/Group Conformity (R), Efficiency (E), and Sufficiency Versus Proliferation of Originality (SO). Results Given that there are a number of models of temporal discounting (Doyle, 2010), and that it is still a matter for debate which discounting function best describes human behavior (Killeen, 2009; McKerchar, Green, Myerson, Pickford, Hill, & Stout, 2009; Rachlin, 2006; Scholten & Read, 2010), we chose to measure people s impulsivity atheoretically in the following way: For the financial choice questions, we computed the proportion of questions on which a participant chose the immediate rewards. In addition, we computed separate proportions for those questions on which Kirby et al. (1999) designated the delayed reward as small, medium, and large. For the questions concerning health, we computed the mean duration of the larger, later rewards that a person judged would make them just as attractive as the smaller, sooner rewards; for some analyses, we used the duration for each of the four health questions separately. Similarly, we calculated the mean duration of the larger, later rewards that a person judged would make them just as attractive as the smaller, sooner rewards for the vacation questions, and also used the duration for each of the four vacation questions separately for some analyses. The intercorrelations among the measures for small, medium, and large financial rewards as well as the durations selected on the four different

6 604 Foxall et al. health questions and the four vacation questions are presented in Table 1. The Cronbach alphas within the domains of finance, health, and vacations were.89,.98, and.76, respectively. Table 1 Correlations Between Submeasures of Impulsivity Finance small Finance medium Finance large Q1 Q2 Q3 Q4 Vacation Q1 Vacation Q2 Vacation Q3 Finance small * Finance medium 0.69 * Finance large * Q * Q * Q * Q * Vacation Q * Vacation Q * Vacation Q * Vacation Q Structure of Impulsivity We performed a principal components analysis (PCA), followed by varimax rotation, on the proportions of immediate choices involving small, medium, and large delayed financial rewards as well as the durations selected on the four different health questions and the four vacation questions. The results of this PCA are presented in Table 2. Only three factors were extracted with eigenvalues greater than 1. The questions within a domain (financial, health, vacations) all loaded together, and more importantly, there was very little cross loading on the components, indicating that each of the three components was uniquely associated with a domain. Cognitive Style and Discounting Behavior No relation was found between KAI scores and discounting rates for any of the three domains. Each of the overall discounting measures for the finance, health, and vacation domains (i.e., the overall proportion of immediate financial choices and the mean durations of the larger, later health and vacation options) was regressed on the three KAI components: SO, E, and R. Neither the participants scores on the three KAI components nor

7 INFLUENCES ON DELAY DISCOUNTING 605 their full-scale KAI score predicted their discounting in any of the three domains (all Fs < 1.0). Similar results were obtained when factor scores associated with finance, health, and vacations were used as the dependent discounting measures. Table 2 Principal Components Analysis With Varimax Rotation Component Q Q Q Q Finance large 0.92 Finance small 0.92 Finance medium 0.87 Vacation Q Vacation Q Vacation Q Vacation Q Eigenvalues % variance explained Cumulative % variance explained Note. Blank spaces indicate loadings < 0.3. Discussion We examined the relations among temporal discounting in three different domains: health, finance, and vacations. Our results were consistent with the hypothesis that discounting behavior is domain specific. Like Chapman (1996), we found that individuals discounting in one context is reliable within that context but may be independent of their discounting in other contexts. In addition, we found that individuals cognitive styles, as measured by the KAI, were not related to their discounting behavior in any of the three domains. The lack of association between discounting behavior and either overall KAI scores (for adaption-innovation as a unidimensional measure) or any of its factorized subscales was unexpected because the KAI is not only a robust measure of cognitive style in itself but also correlates with numerous personality traits that might be construed as indicative of impulsivity (Foxall & James, 2009). We would note an important difference between our methodological approach and the approaches used in previous studies. Some previous research has employed a single method of assessing discounting rates by asking respondents to react in a similar fashion to consumption alternatives in all the contexts or product domains examined. Although this may increase the possibility of finding strong correlations, our methodology avoids the potential common-methods bias (i.e., shared-method variance) inherent in adopting the same method of data collection across domains by using methods that

8 606 Foxall et al. differed from domain to domain. In the financial domain, respondents chose between smaller, immediate amounts of money and larger, delayed amounts (Kirby et al., 1999); in the health domain, we used a production method in which respondents reported how long a delayed return to full health would have to last in order to make a treatment as attractive as one that produced an immediate result; similarly, in the vacation domain, participants reported how long a delayed vacation would have to be in order to make it as attractive as one that they could take immediately. This approach (see the Appendix) encouraged respondents to approach the discounting tasks in each of the domains in a different manner, thereby hopefully minimizing the overlap between the strategies that the respondents used and ensuring that any correlation across domains was due to the discounting process itself. A caveat needs to be offered with respect to the comparisons between contexts or domains. Perhaps unsurprisingly, only one type of reward (i.e., money) was used for financial discounting. However, relief from only one type of illness was used for health discounting, whereas multiple types could have been studied, just as multiple destinations were studied in the vacation domain. In this regard, we would note that the correlations among the vacation questions were often less than half of those among the health questions. As a result, it might be questioned whether the four destinations represented multiple versions (brands) of a single product or whether they should be better portrayed as separate products. Thus, although our findings argue for the domain specificity of discounting behaviors and are consistent with previous findings (Chapman, 1996) there remain avenues for further investigation and clarification. One of these avenues entails the thorny problem of defining precisely what a reward or product domain is. For example, Tsukayama and Duckworth (2010) recently examined the correlations among the discounting rates for candy, chips, beer, and money, and they found a gradation of independence among these items but never a complete absence of dependence. It might be argued that in the present study we have identified a degree of domain dependence, as exemplified by the correlations between health and vacations, as well as domain independence, as exemplified by the lack of correlation between money and the other two types of reward. Moreover, even within the vacation reward or product domain, which involved four different destinations, one might argue based on the correlations that there are at least three different products, with trips to Paris and New York much more highly correlated with each other than with the other two destinations, which were relatively weakly correlated with each other. Thus, the question of what constitutes a domain is unlikely to be answerable in terms of what manufacturers and marketers imagine they are producing; rather, it is answerable only by consumers whose needs are being met, perhaps in ways not obvious to the producers but that may be revealed in the consumers behavior. References Ainslie, G. (1992). Picoeconomics. Cambridge: Cambridge University Press. Ainslie, G. (2001). Breakdown of will. Cambridge: Cambridge University Press. Bickel, W. R., & Marsch, L. A. (2001). Toward a behavioral economic understanding of drug dependence: Delay discounting processes. Addiction, 96,

9 INFLUENCES ON DELAY DISCOUNTING 607 Bickel, W. R., & Vuchinich, R. E. (Eds.). (2000). Reframing health behavioural change with behavioural economics. Mahwah, NJ: Erlbaum and Associates. Chapman, G. B. (1996). Temporal discounting and utility for health and money. Journal of Experimental Psychology: Learning, Memory and Cognition, 22, Chapman, G. B., & Elstein, A. S. (1995). Valuing the future: Temporal discounting of health and money. Medical Decision Making, 15, Dittmar, H., & Bond, R. (2010). I want it and I want it now : Using a temporal discounting paradigm to examine predictors of consumer impulsivity. British Journal of Psychology, 101(4), Dixon, M. R., Marley, J., & Jacobs, E. A. (2003). Delay discounting by pathological gamblers. Journal of Applied Behavior Analysis, 36, Doyle, J. R. (2010). Survey of time preference, delay discounting models. Retrieved from Social Science Research Network: abstract= Foxall, G. R. (2010). Accounting for consumer choice: Inter-temporal decision-making in behavioral perspective. Marketing Theory, 10(4), Foxall, G. R., & James, V. K. (2009). The style/involvement model of consumer innovativeness. In T. Rickards & S. Moger (Eds.), Routledge companion to creativity (pp ). London: Routledge. Goldsmith, R. E., & Foxall, G. R. (2003). The measurement of innovativeness. In L. Shavinina (Ed.), The international handbook of innovation (pp ). Oxford: Pergamon Press. Green, L., & Myerson, J. (2010). Experimental and correlational analyses of delay and probability discounting. In G. J. Madden & W. K. Bickel (Eds.), Impulsivity: The behavioral and neurological science of discounting (pp ). Washington, DC: American Psychological Association. Heyman, G. M. (2009). Addiction: A disorder of choice. Cambridge, MA: Harvard University Press. Killeen, P. R. (2009). An additive utility model of delay discounting. Psychological Review, 116, Kirby, K. N., & Marakovic, N. N. (1996). Delay-discounting probabilistic rewards: Rates decrease as amounts increase. Psychonomic Bulletin & Review, 3, Kirby, K. N., Petry, N. M., & Bickel, W. K. (1999). Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls. Journal of Experimental Psychology: General, 128, Kirton, M. J. (1976). Adaptors and innovators: A theory and measure. Journal of Applied Psychology, 61, Kirton, M. J. (2003). Adaption-innovation in the context of diversity and change. London: Routledge. Madden, G. J., & Bickel, W. K. (Eds.). (2010). Impulsivity: The behavioral and neurological science of discounting. Washington, DC: American Psychological Association. McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. Behavioural Processes, 81,

10 608 Foxall et al. Odum, A. L., & Baumann, A. A. L. (2010). Delay discounting: State and trait variable. In G. J. Madden & W. K. Bickel (Eds.), Impulsivity: The behavioral and neurological science of discounting (pp ). Washington, DC: American Psychological Association. Ostaszewski, P. (1996). The relation between temperament and rate of temporal discounting. European Journal of Personality, 10, Ostaszewski, P. (1997). Temperament and the discounting of delayed and probabilistic rewards. European Psychologist, 2, Plunkett, H. R., & Buehner, M. J. (2007). The relation of general and specific locus of control to intertemporal monetary choice. Personality and Individual Differences, 42, Rachlin, H. (2000). The science of self-control. Cambridge, MA: Harvard University Press. Rachlin, H. (2006). Notes on discounting. Journal of the Experimental Analysis of Behavior, 85, Reynolds, B., Richards, J. B., & de Wit, H. (2006). Acute alcohol effects on laboratory measures of impulsive behavior in humans. Pharmacology, Biochemistry and Behavior, 83, Ross, D., Kincaid, H., Spurrett, D., & Collins, P. (2010). What is addiction? Cambridge, MA: MIT Press. Ross, D., Sharp, C., Vuchinich, R. E., & Spurrett, D. (2008). Midbrain mutiny: The picoeconomics and neuroeconomics of disordered gambling. Cambridge, MA: MIT Press. Scholten, M., & Read, D. (2010). The psychology of intertemporal tradeoffs. Psychological Review, 117(3), Smith, C. L., & Hantula, D. A. (2003). Pricing effects on foraging in a simulated Internet shopping mall. Journal of Economic Psychology, 24, Tsukayama, E., & Duckworth, A. L. (2010). Domain-specific temporal discounting and temptation. Judgment and Decision Making, 5, Vuchinich, R. E., & Heather, N. (Eds.). (2003). Choice, behavioural economics and addiction. Amsterdam: Pergamon Press. Wang, H.-C., Doong, H.-S., & Foxall, G. R. (2010). Consumers intentions to remain loyal to online reputation systems. Psychology and Marketing, 27,

11 INFLUENCES ON DELAY DISCOUNTING 609 Appendix The Discounting Questionnaire Introduction This research is designed to estimate your discounting rate. This will determine the effects of any delay in receiving a reward and whether this differs according to the length of time and value of the reward. There are three parts to the questionnaire. Please answer all of the questions in all parts. Example questions to demonstrate how questions should be answered are included in each part of the questionnaire. Part A (This section of the questionnaire was based on Table 3 of Kirby et al., 1999.) Part B Instructions: Please read the scenario below carefully and for each question fill in the blank with the amount of time in full health Treatment B would have to provide to make Treatment B just as attractive as Treatment A. Please read the whole of each question before answering. Scenario: Imagine that, for the past 2 years, your state of health has fit this description: Because of your doctor s instructions, you need to take medication (pills) once a day. You must also be very careful about what foods you eat, so you spend a lot of time keeping track of what you eat. You find it necessary to visit the bathroom quite often to urinate. You often feel tired and sometimes feel light-headed. You sometimes have trouble falling asleep and sometimes have nightmares when you do sleep. Your mouth sometimes feels dry, and foods do not seem to have as much taste as they used to. You don t have as much desire for sex as you used to, and you do not find sex as enjoyable as you used to. You often feel angry or irritated, and it is difficult to concentrate. Imagine that this state of health will continue unchanged for the rest of your life. Example question: Treatment A would return you to full health for 1 year and would take effect today. Treatment B would return you to full health for 10 years; however, the treatment would not take effect until 5 years from today.

12 610 Foxall et al. Questions: 1. Treatment A would return you to full health for 1 year and would take effect today. Treatment B would return you to full health for years; however, the treatment would not take effect until 1 year from today. 2. Treatment A would return you to full health for 1 year and would take effect today. Treatment B would return you to full health for years; however, the treatment would not take effect until 4 years from today. 3. Treatment A would return you to full health for 1 year and would take effect today. Treatment B would return you to full health for years; however, the treatment would not take effect until 2 years from today. 4. Treatment A would return you to full health for 1 year and would take effect today. Part C Treatment B would return you to full health for years; however, the treatment would not take effect until 6 months from today. Instructions: Please read the scenario below carefully and for each question please fill in the blank with the number of nights the holiday in Prize B would have to provide to make Prize B just as attractive as Prize A. Example Question: Prize A: You receive a coupon that can be exchanged for: a 3-night trip for two to the city of York. Travel and accommodation in a bed and breakfast and other meals are included. Enjoy the beautiful city and surrounding beautiful countryside. This coupon is valid only if you begin your travel in a month s time. Prize B: You receive a coupon that can be exchanged for: a trip lasting 4 nights for two to the city of York. Travel and accommodation in a bed and breakfast and other meals are included. Enjoy the beautiful city and surrounding beautiful countryside. This coupon is good only if you begin your travel the weekend exactly 1 year from now.

13 INFLUENCES ON DELAY DISCOUNTING 611 Questions: 1. Prize A: You receive a coupon that can be exchanged for: a 2-night trip for two to the charming town of Brecon. Travel and accommodation in a bed and breakfast and other meals are included. Enjoy the pretty town and surrounding beautiful countryside and national parks. This coupon is valid only if you begin your travel in a month s time. Prize B: You receive a coupon which can be exchanged for: a trip lasting nights for two to the charming town of Brecon. Travel and accommodation in a bed and breakfast and other meals are included. Enjoy the pretty town and surrounding beautiful countryside and national parks. This coupon is good only if you begin your travel the weekend exactly 1 year from now. 2. Prize A: You receive a coupon that can be exchanged for: a 3-night weekend trip for two to Paris. Travel, hotel accommodation, and meals are included. Enjoy the sights, culture, wonderful cuisine, and nightlife. This coupon is valid only if you begin your travel in a month s time. Prize B: You receive a coupon that can be exchanged for: a trip lasting nights for two to Paris. Travel, hotel accommodation, and meals are included. Enjoy the sights, culture, wonderful cuisine, and nightlife. This coupon is good only if you begin your travel the weekend exactly 1 year from now. 3. Prize A: You receive a coupon that can be exchanged for: a 7-night holiday for two to New York. Air travel, first-class hotel accommodation, and meals at fine restaurants are included. Enjoy the sights, museums, shopping, and nightlife. This coupon is valid only if you begin your travel in a month s time. Prize B: You receive a coupon that can be exchanged for: a trip lasting nights for two to New York. Air travel, first-class hotel accommodation, and meals at fine restaurants are included. Enjoy the sights, museums, shopping, and nightlife. This coupon is good only if you begin your travel the weekend exactly 1 year from now. 4. Prize A: You receive a coupon that can be exchanged for: a 14-night holiday for two to Tokyo. First-class air travel, 5-star hotel accommodation, fine dining, and spending money are all included. Enjoy museums, culture, city sights, and sounds and nightlife. This coupon is valid only if you begin your travel in a month s time. Prize B: You receive a coupon that can be exchanged for: a trip lasting nights for two to Tokyo. First-class air travel, 5-star hotel accommodation, fine dining, and spending money are all included. Enjoy museums, culture, city sights and sounds, and nightlife. This coupon is good only if you begin your travel the weekend exactly 1 year from now.

14 612