A maximum likelihood hierarchical disaggregate model for predicting choices of individuals

Gensch, Dennis H.; Svestka, Joseph A.

doi:10.1016/0022-2496(84)90024-5

Cited by 33 publications

(3 citation statements)

References 7 publications

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“…According to Putsis and Srinivasan (1994), the consumer selects a product from the evoked set after this set is assembled. For consideration set formation models, for example, see Gensch and Svestka (1984), Hauser and Wernerfelt (1990), Narayana and Markin (1975), and Roberts and Latin (1991). 3.…”

Section: Literature Reviewmentioning

confidence: 99%

Changes in Hotel Guests’ Willingness to Pay as the Date of Stay Draws Closer

Schwartz

2000

Journal of Hospitality & Tourism Research

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The literature on optimal room rate policies and the experience of many hoteliers suggest that guests'willingness to pay increases as time draws closer to the date of stay. Traditionally, this phenomenon is explained through changes in market segmentation: Business travelers who tend to book closer to the date of stay are willing to pay more. It is argued in this study that the same customers are willing to pay more as the date of stay nears. A simple consumer decision model that explains this phenomenon is provided. The article examines the conditions that affect the increasing demand, and the relation between time and the increase. In a controlled experiment, subjects were asked to book a room and get the best deal they could find using a simulated Internet site that specialized in discount hotel reservations. The results indicate that although willingness to pay indeed increases as time nears the date of stay, the extent of the change depends on the customers' search cost.The literature on hotel room rate optimization suggests that customers' willingness to pay changes over time. Weatherford and Bodily (1992) state that, for perishable products, willingness to pay is expected to either build or diminish as the availability date draws closer. The authors believe that one should assume a growing willingness to pay for one type of product or service (e.g., flights and room nights) and a decreasing willingness to pay for a second type (e.g., fashion items and high technology goods). According to their taxonomy of Yield Management, most of the surveyed algorithms assume a rising willingness to pay. Clear examples can be found in Belobaba (1989), Bodily and Weatherford (1995), Brumelle, McGill, Oum, Sawaki, and Tretheway (1990), and Pfeifer (1989. Discount customers, in these stochastic demand models, are assumed to arrive first, followed by full-fare customers. In line with the theoretical models, airlines tie early booking to discounts (e.g.Downloaded fromThe same approach is echoed in the lodging industry. For example, Greenberg (1985) and Relihan (1989) discuss the typical hotel booking pattern where customers with a lower willingness to pay book earlier. Hanks, Cross, and Noland (1992) report on Marriott's discounting policy for early bookings, and Raeside (1997) argues that as customers'willingness to pay full price rises, the hotelier can use a threshold curve to reduce the number of discounts available as the availability date approaches.What drives this change in guests' willingness to pay over time? Hoteliers and academics argue that, as time nears the date of stay, the hotel simply faces different people (or market segments). According to this argument, customer segments that typically book their rooms closer to the date of stay (e.g., business travelers) are characterized by a higher willingness to pay (Orkin, 1990;Relihan, 1989).There is, however, a second logical explanation to the observed increase in willingness to pay. A guest is likely to agree to pay more for a room if his or her reservation decis...

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Section: Literature Reviewmentioning

confidence: 99%

Changes in Hotel Guests’ Willingness to Pay as the Date of Stay Draws Closer

Schwartz

2000

Journal of Hospitality & Tourism Research

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“…Predecision elicitation may result in incentive-compatibility bias and strategic response bias: the former occurs when respondents are not responsible for the consequences of their selection, and the latter occurs when respondents anticipate that their responses would influence product design (13). Postdecision recall of thresholds may be inaccurate or partial (14). Observing threshold selection during the choice task (5)…”

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confidence: 99%

Two-Stage Model for Jointly Revealing Determinants of Noncompensatory Conjunctive Choice Set Formation and Compensatory Choice

Kaplan

Bekhor

Shiftan

2009

Transportation Research Record: Journal of the Transportation R

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Understanding the distribution and the determinants of search criteria thresholds helps in representing choice set formation and choice behavior. The development and estimation are presented of a two-stage model that jointly represents search criteria thresholds, within a noncompensatory choice set formation stage, and choice behavior, within a compensatory stage. Data were collected by using a custom-designed web-based choice experiment that seamlessly tracked the entire choice process by recording choice protocols. The model is applied to off-campus rental apartment choice by students as an example of a complex choice situation. The model combines three correlated ordered response models for the search criteria with a multinomial logit model for the choice among a realistically large realm of 200 alternatives. Estimates demonstrate that ( a) the thresholds are correlated and their selection can be explained by individual characteristics, preferences, and perceptions and ( b) the suggested methodology alleviates the computational complexity embedded in two-stage models by reducing the number of theoretically possible choice sets to the actually chosen ones.

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“…Από τα προϊόντα αυτά θα επιλέξει τελικά να αγοράσει. Μοντέλα αυτής της κατηγορίας έχουν προτείνει μεταξύ των άλλων οι: Narayana and Markin (1975), Day and Deutscher (1982), Gensch and Svestka, 1984;Fotheringham (1988), Hauser and Wernerfelt (1990), Roberts and Lattin (1991), Shocker et all. (1991).…”

Section: αποφάσεις μάρκετινγκunclassified

Ενα Εμπειρο Συστημα Υποστηριξης Αποφασεων Μαρκετινγκ: Μεθοδολογια Υποστηριξης Και Ολοκληρωμενη Αρχιτεκτονικη

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A maximum likelihood hierarchical disaggregate model for predicting choices of individuals

Cited by 33 publications

References 7 publications

Changes in Hotel Guests’ Willingness to Pay as the Date of Stay Draws Closer

Changes in Hotel Guests’ Willingness to Pay as the Date of Stay Draws Closer

Two-Stage Model for Jointly Revealing Determinants of Noncompensatory Conjunctive Choice Set Formation and Compensatory Choice

Ενα Εμπειρο Συστημα Υποστηριξης Αποφασεων Μαρκετινγκ: Μεθοδολογια Υποστηριξης Και Ολοκληρωμενη Αρχιτεκτονικη

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