Abstract
In order to overcome the perverse incentives of excessive maintenance reductions and insufficient network investments arising with incentive regulation of electricity distribution companies, regulators throughout Europe have started regulating service quality. In this paper, we explore the impact of incorporating customers’ willingness-to-pay for service quality in benchmarking models on cost efficiency of distribution networks. Therefore, we examine the case of Norway, which features this approach to service quality regulation. We use the data envelopment analysis technique to analyse the effectiveness of such regulatory instruments. Moreover, we discuss the extent to which this indirect regulatory instrument motivates a socially desired service quality level. The results indicate that internalising external or social cost of service quality does not seem to have played an important role in improving cost efficiency in Norwegian distribution utilities.
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Notes
- 1.
For a detailed overview of the different indicators employed in European countries, please refer to CEER (2008).
- 2.
System Average Interruption Duration Index, which gives the amount of time per year that the supply to a customer is interrupted.
- 3.
System Average Interruption Frequency Index, which gives the average number of time per year that the supply to a customer is interrupted.
- 4.
For other instruments to regulate the different dimensions of service quality, such as publication of data on company performance, (minimum) quality standards or premium quality contracts, please refer to Fumagalli et al. (2007).
- 5.
In the remainder of the paper, we focus on ENS since this is the regulatory indicator employed in our case-study Norway.
- 6.
For further discussion on the choice of the regulated indicator, please refer to Fumagalli et al. (2007).
- 7.
Some of these countries such as the UK or the Netherlands also employ other instruments of service quality regulation. The Netherlands for instance additionally apply compensation payments in case a predetermined continuity of supply standard is breached, whereas the UK also sets guaranteed standards for commercial quality.
- 8.
In the remainder of this paper, we use incentive based service quality regulation, WTP-based service quality regulation, and CENS-regulation as synonyms.
- 9.
Alternatively the SAIDI may be used as regulatory indicator to represent the companies’ performance in terms of service quality. A discussion on the difference between ENS and SAIDI can be found at Fumagalli et al. (2007). Within the scope of our paper, we focus on ENS only.
- 10.
Another regulatory challenge is to adequately approximate the CENS for the regulatory formula with the customer WTP for service quality. A number of regulators have found consumer surveys of WTP for network reliability useful in setting service quality incentives. Different methods can be used to measure WTP. For an overview of the most prominent, please refer to Growitsch et al. (2009).
- 11.
Different incentive rates are used for notified and non-notified interrupstions (see Table 4.1).
- 12.
Recently the Norwegian regulator NVE has conducted a new survey on consumer valuation of interruptions and voltage problems (Kjølle et al. 2008). The survey finds a significant increase in the customers’ costs since the 1991 survey for all customer groups and particularly for the agricultural group. Amongst others, the newly identified CENS for short interruptions ≤3 min will be incorporated in the CENS-arrangement as from 2009 (see footnote 13).
- 13.
Kjølle et al. (2009) describe the latest changes to service quality regulation in Norway. The motivation for this was to achieve the most optimal level of continuity of supply for the society as a whole. Given the fact that recent customer surveys in the Norwegian electricity distribution sector found that annual costs for short interruptions ≤3 min were associated with the same WTP as for long interruptions >3 min, short interruptions are incorporated in the CENS-arrangement as from 2009. Moreover, customer surveys indicated that time dependency in interruption costs was found to be significant. Therefore, cost functions are corrected by monthly, weekly and daily variations in order to stimulate more cost-efficient maintenance activities, this is e.g. in periods where the interruption cost is low. However, the temporal value of CENS is not taken into account in our analysis since the related regulatory instruments only became effective in 2009, whilst our data sample ends with the year 2004.
- 14.
For the following discussion, it should be noted that the time horizon of the analysed data ends at 2004. Hence, the companies within our sample could not react to the latest features of quality regulation that were introduced in the second regulatory period, this is basically the mandatory reporting of interruptions and the introduction of compensation payments The enhancements to the regulatory model as discussed in Sect. 3.2 cannot be tested.
- 15.
The Norwegian TSO Statnett SF is not part of any vertically integrated undertaking. With regard to our analysis, transmission data in any respect is excluded since it is out of the control of a single DNO, therefore.
- 16.
- 17.
NVE uses a variable returns to scale (VRS) model. However, Kittelsen (1994) suggested to use CRS in order to encourage cost saving restructuring also in terms of network size.
- 18.
NVE’s original model is a little more complex, dividing the input side into different kinds of cost (wages, other OPEX, network losses and CAPEX). For analytical reasons, we have combined the various inputs to a single private cost input (TOTEX), as we are not focusing on optimal factor allocation within the firm, but of private and social cost efficiency.
- 19.
For an overview of the descriptive statistics per year, see Appendix.
- 20.
The Wilcoxon ranksum test, also Mann-Whitney-U-Test, is a non-parametric test that analyses whether two independent groups belong to the same population (see Cooper et al. 2006)
- 21.
In the year 2001 TOTEX scores are marginally but significantly higher, in the years 2002 and 2004 significantly but marginally lower than the SOTEX scores. In 2003, there are no significant differences.
- 22.
To control for possible scale effects, we also calculated the annual efficiency averages under VRS. The results differ in levels, but not in their economic interpretation. Detailed information may be obtained from the authors upon request.
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Growitsch, C., Jamasb, T., Müller, C., Wissner, M. (2016). Social Cost Efficient Service Quality: Integrating Customer Valuation in Incentive Regulation—Evidence from the Case of Norway. In: Zhu, J. (eds) Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 238. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7684-0_4
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