2022 INFORMS Revenue Management and Pricing Section Conferenc
Measuring the willingness to pay for bundles composed of flexible products
Ralf Gössinger and Jacqueline Wand
Price bundling describes the market strategy of selling a package of different individual products to a single aggregate price, which allows to absorb a larger part of the consumer surplus. A flexible product is sold as a set of alternative products that serve the same purposes. Its final specification will only be announced in the period between purchase and provision (cf. Gallego and Phillips 2004, pp. 321). The seller can use this time to complete his information base and thus achieve a higher and more even capacity utilization. However, simultaneously, customers’ uncertainty about product performance is increased. Although this requires a lower sales price, higher revenues are achieved by attracting new customer segments (cf. Mang, Post and Spann 2012, pp. 362). In our contribution, we try to explain these aspects by the impact of flexible products and price bundling on customers’ willingness to pay (wtp).
To our knowledge, no wtp measurement approaches for flexible products and only a few for price bundling have been proposed in the literature. In the present context, those approaches are of interest that consider multivalued wtps, which can be traced back to different sources of within- and between-subject variability (cf. Jedidi, Jagpal and Manchanda 2003, p. 118). At the individual level, both preference and performance uncertainty are relevant (cf. Wang, Venkatesh and Chatterjee 2007, pp. 201) and at the customer segment level, heterogeneity of wtps is a source of variability. Therefore, we tie in with the results of Newmeyer, Venkatesh and Chatterjee (2021) who develop a method (ICEPORT) capable of determining wtp intervals for buying options included in a product portfolio. In addition to the wtp measurement, we analyze how performance uncertainty and value assessment of flexible products as well as price bundling affect the wtp in terms of expected value and interval width. For data collection, we adapt parts of ICEPORT and add specifics of flexible products. As these changes are not minor, we will discuss their impact on the approach and its results.
References
Gallego, G., Phillips, R., 2004. Revenue management of flexible products. Manuf Serv Oper Manag 6, 321-337.
Jedidi, K., Jagpal, S., Manchanda, P., 2003. Measuring heterogeneous reservation prices for product bundles. Mark Sci 22, 107-130.
Mang, S., Post, D., Spann, M., 2012. Pricing of flexible products. Rev Manag Sci 6, 361-374.
Newmeyer, C.E., Venkatesh, R., Chatterjee, R., 2021. Reservation prices for product portfo-lios under uncertainty: the ICEPORT approach. Cust Need and Solut 8, 51-65.
Wang, T., Venkatesh, R., Chatterjee, R., 2007. Reservation price as a range: An incentive-compatible measurement approach. J Mark Res 44, 200-213.