Marketing textbook, chapter 7

In a study by Pabsch et al. (2000, p. 109 ff.), the significance of various price components for the choice of electricity tariff of a regional electricity supplier was empirically determined using a choice-based conjoint analysis (CBC) (see also Section 4.4.3.2). Figure 1 provides an overview of the characteristics and characteristic values considered in the study.

In the survey situation, the characteristic values were systematically combined to form holistic product concepts, which were presented to the test subjects for assessment (see Figure 2). The respondents were confronted with several selection situations one after the other and were each asked to state their preferred electricity tariff. However, there was also the option of not choosing a tariff if both alternatives in a selection situation were categorised as unacceptable. This comparison helps users to understand the trade-offs between the tariffs (e.g. lower basic price for tariff 1 vs. lower energy price for tariff 2).

In order to carry out a market simulation, it was assumed that electricity customers can choose between three different electricity tariffs. The choice shares for these three tariffs were then calculated using conjoint analysis. Figure 3 illustrates the result of this market simulation.

The most favoured tariff A would be chosen by 51.3 per cent of respondents, while tariffs B (29.6 per cent) and C (19.1 per cent) fared significantly worse. Tariff A has the lowest consumption price at € 0.09 per kWh. It is also possible to calculate the extent to which this tariff loses voting shares if the consumption price is gradually increased. The result is illustrated in the graph at the bottom of Figure 3: If the consumption price for tariff A is increased from €0.09 to €0.12 (tariffs B and C remain unchanged), for example, the proportion of respondents who would choose this tariff falls by 3.8 per cent, from 51.3 to 47.5 per cent.

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Sources:

• Pabsch, M./Scharf, A./Volkmer, P.: Entwicklung neuer Stromprodukte durch die swb Enordia GmbH mit Hilfe der Conjointanalyse; in: Scharf, A./Wolf, T. (eds.): Case studies from dynamic markets. Telekommunikation, Internetdienste, Energiewirtschaft, Wiesbaden 2000, pp. 109-144.