A Live Baby or Your Money Back: The Marketing of In Vitro Fertilization Procedures. D.C. Scmittlein, D.G. Morrison. Management Science. 49(12): 1617-1635. December 2003.
Many clinics that offer in vitro fertilization (IVF) have begun to market the following options to couples: (1) an a la carte program where the couple pays $7,500 per attempt regardless of the outcome; or (2) a money-back-guarantee program where the couple pays a $15,000 fee that covers up to three attempts – however, if after three cycles there is no live birth delivery, then the full $15,000 is refunded.
We assess the a la carte vs. money-back-guarantee programs, and find the surprising result that the money-back-guarantee program appears (for the patients) to be "too good to be true." That is, the money-back guarantee yields a substantial negative expected profit per couple for the clinics. More importantly from the patients' perspective, the money-back-guarantee is the better option for all couples with less than 0.5 success probability per cycle. Virtually all traditional IVF patients have had per-cycle success probabilities below 0.5.
A detailed analysis of the key variables – i.e., success rate per attempt, heterogeneity of couples' rates of success, individual couples'; "learning&" on successive attempts, and cost to the clinic per attempt – shows that these money-back-guarantees are unprofitable for the clinics. Since presumably clinics are not in business to lose money, the standard analysis must be missing something major. We suggest that the marketing of money-back guarantees is inducing couples who would previously have used – successfully – other less invasive procedures with fewer side effects and less risk of multiple births to decide to proceed directly to IVF, and that this scenario makes the money-back-guarantees profitable for the clinics.
The implications of earlier use of IVF are then considered from an overall public policy point of view. Just as mothers everywhere tell their children, "When something looks too good to be true, then it is too good to be true!"
Do We Really Need Multiple-Item Measures in Service Research? A.L. Drolet, D.G. Morrison. Journal of Service Research. 3(3): 196-204. February 2001.
Increasingly, marketing academics advocate the use of multiple-item measures. However, use of multiple-item measures is costly, especially for service researchers. A study investigates the incremental information of each additional item in a multiple-item scale. By applying a framework derived from the forecasting literature on correlated experts, the authors show that, even with very modest error term correlations between items, the incremental information from each additional item is extremely small. The study's "information" (as opposed to "reliability") approach indicates that even the second or third item contributes little to the information obtained from the first item. Furthermore, the authors present evidence that added items actually aggravate respondent behavior, inflating across-item error term correlation and undermining respondent reliability.
A Decision Support System for Planning Manufactures' Sales Promotion Calendars. J.M. Silva-Risso, R.E. Bucklin, D.G. Morrison. Marketing Science. 18(3): 274-300. Summer 1999.
A study develops a disaggregate-level econometric model to capture the dynamics and heterogeneity of consumer response. By modeling the purchase incidence, choice, and quantity decisions of consumers, total sales are decomposed into incremental and non-incremental (baseline plus borrowed). The response model forms the basis of a market simulator that permits the search for the manufacturer's optimal promotion calendar via the simulated annealing algorithm. A sensitivity analysis was conducted on the profile of the calendar with respect to changes in market response, competitive activity, and retailer pass-through. It was found that the optimal depth, frequency, and timing of discounts are stable for price elasticities ranging from near zero to around 4. It was also found that no systematic impact of competitive promotions on the profile of the optimal calendar. Finally, changes in retailer pass through were found to have a significant effect on the optimal depth and number of weeks of trade promotion that a manufacturer should offer. This emphasizes the importance to manufacturers of having accurate estimates of pass-through for purposes of promotion budgeting and planning.
The Effect of Package Coupons on Brand Choice: An Epilogue on Profits. S.K. Dhar, D.G. Morrison, J.S. Raju. Marketing Science. 15(2): 192-203. Spring 1996.
The relative impact of package coupons on profits is examined. The relative profit impact of the following package coupons is compared: peel-off, on-pack and in-pack. Peel-off coupons must be redeemed on the same purchase occasion on which they are obtained. On-pack coupons are obtained at one purchase occasion but can only be redeemed for a discount on the couponed brand at a future purchase occasion. In-pack coupons are similar to on-pack coupons except that the consumer is unaware of the presence of these coupons when the product is purchased. Results suggest that on-pack coupons lead to the highest impact on profit. Furthermore, while peel-offs lead to a higher market share than in-packs, because in-packs stimulate repurchase among previous buyers, they lead to higher profits than peel-offs, though only for stronger brands.
Making the Cut: Modeling and Analyzing Choice Set Restriction in Scanner Panel Data. S. Siddarth, R.E. Bucklin, D.G. Morrison. Journal of Marketing Research. 32(3): 255-266. August 1995.
An approach is developed to determine and analyze choice set restriction on the basis of secondary source information on consumer purchase histories. Individual-level choice sets are estimated using a Bayesian updating procedure in conjunction with the multinomial logit model. The procedure is applied to the scanner panel data for the liquid laundry detergent category. An analysis of estimated choice sets across panelists reveals that market share does not go hand-in-hand with choice set share (the percentage of choice sets in which a brand is a member). Examining choice set membership patterns, such as the co-occurrence of brands in the same product line, also provides insight into sister-brand cannibalization. Estimation results also show that promotions can expand choice sets, providing excluded brands a means to gain entry and long-term sales benefits.
A Latent Look at Empirical Generalizations. D.G. Morrison, J. Silva-Risso. Marketing Science. 14(3, Part 2 of 2): G61-G70. Summer 1995.
All empirical data and the resulting parameters are subject to error. A lens for better viewing empirical studies in search of empirical generalizations in marketing is presented: Observed Value = True Score + Error. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful.
Probability Models for Duration: The Data Don't Tell the Whole Story. M. Vanhuele, M.G. Dekimpe, S. Sharma, D.G. Morrison. Organizational Behavior and Human Decision Processes. 62(1): 1-13. April 1995.
Probability models for duration have been applied to a wide range of individual-level and organizational phenomena. Interestingly, seemingly similar models may produce different results. Using divorce as an illustration, a hierarchy of duration models of different complexity is discussed and it is shown how an analysis of the results across models helps explain why different studies may have come to different conclusions. This analysis also leads to substantive insights that even the most complete model by itself does not provide. The main conclusions are not only applicable to marriage durations, but should also be of interest to researchers studying phenomena such as organizational mortality, the length of strikes and auditor-client relationships.
A Tactical Model for Airing New Seasonal Products. D. Kim. D.G. Morrison, C.S. Tang. European Journal of Operational Research. 84: 250-264. 1995.
A model is introduced that analyzes the impact of the length of time spent presenting new seasonal products. Specifically, a simple stochastic model for determining the optimal airing time for each product so that the net profit is maximized is developed. Cases in which there are 2 products to present, 2 channels to select for airing the products, and 2 methods of presentation to choose are considered. In each case, the problem is formulated as a mathematical program and the properties of the optimal airing time are characterized. These properties may provide managerial insights for determining airing time for each product, selecting channels to air the products, and choosing a presentation method for products. In addition, this analysis may help the management to make strategic decisions in airing products that would lead to an increase in sales.