Event Abstract

Neuroergonomic Analysis of Dynamic Vs. Flat Rate Pricing on Consumers

  • 1 LeBow College of Business, Drexel University, United States
  • 2 School of Biomedical Engineering, Science and Health Systems, Drexel University, United States
  • 3 Department of Family and Community Health, University of Pennsylvania, United States
  • 4 Division of General Pediatrics, Children’s Hospital of Philadelphia, United States

In 1991 when Coca-Cola experimented with raising prices on their vending machines during hot days, consumers retaliated and Coca-Cola abandoned its project. However, with advent in technology, today’s consumers are getting comfortable with prices fluctuating with demand (e.g., Uber during a late-night “surge”; airline and hotel prices) or context (matinee vs. regular pricing for theater tickets), several times over the course of a single day. A deployment of this type of dynamic pricing mechanism is advantageous to firms as they harvest consumer surplus more efficiently. Also consumers are now more aware that prices may fluctuate and are becoming more accepting of such dynamic prices for products that they buy periodically. The question is whether consumers will be more accepting of price changes if they happened more frequently for products that they need and have less competing options for like utilities. Trials of time-of use rates, demand charges and time varying pricing are now playing a important role in the transformation of the electric power sector but little is known about consumers’ response to such pricing approaches and if framing of dynamic prices may indeed make consumers more accepting of such fluctuations. Understanding the impact of such a new pricing approach on how consumers perceive dynamic prices and how utilities can effectively communicate them to consumers is critical. In this study we approach our understanding of dynamic prices for utilities using both a standard assessment performed via self-reported measures that incorporates methods such as surveys, focus groups, and phone and online interviews are the first step. These methods though require large sample sizes and respondents often find it harder to articulate their response to aspects of their behavior to which there is no prior and easy reference. Despite the biases, these methods provide us subjective measurements that can be further triangulated by the use on neuroimaging tools. With the rise of non-invasive and non-clinical functional neuroimaging, an opportunity to access a more direct and objective measurement of the consumer’s response to dynamic prices and different ways to communicate such prices effectively to consumers is now available. Neuroimaging tools, such as functional magnetic resonance imaging (fMRI) and Electroencephalogram (EEG), have been utilized in initial neuromarketing studies (Ariely & Berns, 2010), however various limiting factors such as high operational cost, restrictions on the participant during data collection, and the speed and ease of sensor setup limit use of these in large scale deployment as well as in actual field conditions. Functional near infrared spectroscopy (fNIRS) as a portable and wearable neuroimaging technique that utilizes near infrared light to measure oxygenation changes in outer cortex. Latest generation of optical brain imaging utilizes wireless sensor pads to enable measurement of brain activity in non-tethered and ambulatory settings (Ayaz et al., 2013). This research investigated the evaluation of dynamic pricing approach for utilities. Participants in two focus groups and a phone survey showed preference for flat rate pricing over dynamic pricing. There was greater uncertainty and perceptions of unfairness when evaluating a dynamic price. From the two versions of dynamic pricing -- real time (RTP) vs. time of use pricing-- the time of use pricing (TOU), was the preferred dynamic pricing approach. One of the reasons was that its peak and non-peak times were generally fixed (Figure 1). Figure 1. Liking ratings for price plans from the phone survey. To investigate consumers’ opinions towards flat rate and dynamic prices further, and to prepare for the imaging study, an online survey on Amazon MTurk platform was sent to 503 participants in different U.S markets. This study compares differences in preferences for consumer segments for the two pricing plans---TOU vs. fixed pricing. Further, a conjoint analysis determines preferences for different attributes of the TOU plan (start time, length, and rate). Also, ten interventions assess framing effects, social distance, and environmental proclivity on consumers’ attitudes toward the TOU plan. The first intervention was “based on the information you provided earlier, we find that residences similar to yours will pay less each month by enrolling in TOU plan”. Before participants saw the intervention, they were asked to choose between a flat rate plan and a TOU plan. Next, they saw the intervention and indicated their choice again. A Chi-square test of independence was performed to examine whether there was a difference in choice before and after intervention. The Chi-square revealed a significant difference in choice (X2 (1, N = 52) = 12.46, p =.00). Before the intervention, 35 participants preferred the flat rate plan and 17 preferred TOU. After intervention, 17 participants preferred the flat rate plan and 35 preferred the TOU (Figure 2). The study is still ongoing and will be used to create the design for the fNIRS based neuroimaging study. Figure 2. Choice before and after intervention (intervention 1)

Figure 1
Figure 2


Ariely, D., & Berns, G. S. (2010). Neuromarketing: the hope and hype of neuroimaging in business. Nature reviews neuroscience, 11(4), 284.

Ayaz, H., Onaral, B., Izzetoglu, K., Shewokis, P. A., McKendrick, R., & Parasuraman, R. (2013). Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development. Frontiers in human neuroscience, 7, 871.

Keywords: dynamic pricing, consumer behavior, utility, framing effect, fNIRS

Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018.

Presentation Type: Poster Presentation

Topic: Neuroergonomics

Citation: Ye H, Bhatt S, Ayaz H, Srivastava P and Suri R (2019). Neuroergonomic Analysis of Dynamic Vs. Flat Rate Pricing on Consumers. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00051

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Received: 10 Apr 2018; Published Online: 27 Sep 2019.

* Correspondence: Ms. Hongjun Ye, LeBow College of Business, Drexel University, Philadelphia, United States, hy368@drexel.edu