Dynamic pricing in e-commerce
—Which purchase scenarios do consumers prefer?
Measuring consumers’ preference with dynamic pricing
under various online purchase scenario assumptions
Tzuyun Hsu
22th January 2020
Topic Introduction
● It is proved that dynamic pricing leads to an increase of profitability up to 25% (Garbarino and Lee 2003; Petro 2015)
● The negative consumers’ reactions on dynamic pricing raises an important question about the viability of dynamic pricing over time (Weisstein, Monroe and Kurkar-Kinney 2013).
Main question
Literature Review
Online retailer
Methodology I
● Purchase simulation is applied in the paper by adding online retailer characteristics into the analysis and adopting a choice-based conjoint model to mimic consumers’ behaviour of buying consumer electronics in a questionnaire and to simulate consumers’ comparing behavior on different shopping platforms ● Fractional factorial design
● Follows the four requirements: minimal overlap, orthogonality, balance and utility balance
● Multinomial logit model to estimate preference estimates
● Latent class analysis and Hierarchical Bayes analysis are used to estimate preference at the segment and individual level
Methodology II : Study Design
Definition Level 1 Level 2 Level 3
Online retailer Online retail brands Amazon Mediamarkt bol.com
General price level of the retailer
The general price level of consumer electronics from each retailer, compared to the weighted average price level of consumer electronics in the market
10% higher than average 10% lower than average Same as the average Price changing frequency
How often does the price change Every 2 hours Every 6 hours Every 12 hours
Price variation in percentage
How much does the price change per time Change by ±5% per time
Change by ±10% per time
Methodology III
● Survey contains two parts:
demographics and 8 choice sets
● Survey requirement:
currently living or once lived in Netherlands for over 6 months ● Data collection
Result I : Consumers’ preference differs drastically
● A large heterogeneity of consumers’ preference in dynamic pricing purchase scenarios exists
● The extent of preference difference on general price level that is 10% lower and higher is relatively large.
● The extent of preference difference on Amazon and bol.com is relatively large.
● The extent of preference difference on price variation of 25% is relatively large.
Result II: Consumers’ are not against dynamic pricing
● Lower price changing frequency and smaller size of price variation are preferred by the consumers in general, except for the preference of price variation ±25%.
● The preference of the pricing dynamics are insignificant, relative to retailer characteristics
● The extent of consumers’ preference on ±25% price variation relatively differs more across consumer.
Result III: The relative role of dynamic pricing
● Consumers tend to make their purchase decisions mostly based on the online retail brands and their general price level, especially the latter one.
Result IV : Strong preferences on general price level
● The lower the price level is, the more consumers prefer whereas the extent of preference differs across consumers.
● Asymmetry preference: Consumers’ preference on general price level that is 10% higher is negatively stronger than the preference on the one that is 10% lower
● The extent of consumers’ preference on general price level is very different based on the gender or the segment which he/she belongs
Result V : Online retail brand preference
● At the aggregate level, consumers do not have significant preference on online retailers.
● At the segment level, nearly 40% of the respondents have significant online retail brand preference
● Bol.com is more preferred by the
Inbetweeners (Class 3)
● Amazon is more preferred by the Amazon
Implication
● Conservatively adopting dynamic pricing by using smaller price changing frequency and price variation
● Customized dynamic pricing: individual estimations are necessary for the heterogeneity found in consumers’ preference of dynamic pricing scenarios. ● Online retailers are suggested to create the perception of low general price level
among consumers
Limitation
● Fatigue effect in the survey
● Transforming dynamic pricing scenarios into choice sets is abstract to understand
● Only small selection of possible dynamic pricing strategies are analysed
Reference
Garbarino, E. and Lee, O.F., 2003. Dynamic pricing in internet retail: effects on consumer trust. Psychology & Marketing, 20(6), pp.495-513.
Petro, Greg, 2015. "Dynamic Pricing: Which Customers Are Worth The Most? Amazon, Delta Airlines And Staples Weigh In." Forbes .17 April 2015,
<https://www.forbes.com/sites/vivcraske/2019/10/30/what-amazons-netherlands-launch-means-for-grocery-e-comme rce/#819be8b5a568.>
Haws, K.L. and Bearden, W.O., 2006. Dynamic pricing and consumer fairness perceptions. Journal of Consumer Research, 33(3), pp.304-311.
Li, W., Hardesty, D.M. and Craig, A.W., 2018. The impact of dynamic bundling on price fairness perceptions. Journal of Retailing and Consumer Services, 40, pp.204-212.
