Social networks offer substantial communications value, and utilities can no longer ignore them. A successful strategy, however, requires careful management.
Ontario's Failed Experiment (Part 1)
Reliability declines after 10 years of incentive regulation.
1. Ter-Martirosyan, A., “The Effects of Incentive Regulation on Quality of Service in Electricity Markets,” George Washington University Dept. of Economics Working Paper, Presented at International Industrial Organization Conference, Northeastern University, Boston, 2003.
2. Indeed, some regulators have taken this WTP information and explicitly incorporated the customer interruption values into their distribution price regulation. One regulator has specified a goal of achieving a socially optimal level of reliability by recognizing that customer interruption costs must be considered equally with a utility’s capital and OM&A costs in utility planning and regulatory benchmarking.
3. Unfortunately, later inconsistent and ever-changing policies undermined LDCs’ performance for the next decade. Productivity losses wiped out the widespread gains over the decade from 1988 to 1997.
4. F. Cronin, S. Motluk, “Agency Costs of Third-Party Financing and the Effects of Regulatory Change on Utility Costs and Factor Choices,” Annals of Public and Cooperative Economics , 78, No.4, 2007.
5. See Report Of the OEB, PBR Implementation Task Force , May 1999, at: http://www.oeb.gov.on.ca/documents/cases/RP-1999-0034/implemnt.pdf
6. Subsequently, we examined PBRs implemented in the U.K., Australia and Europe. These PBRs generally benchmark on partial costs and examine only a minority of inefficiency. They create sizeable distortions in efficiency rankings: individual utilities could experience errors in rankings of 20, 30 or even 40 percent. See F.J. Cronin & S.A. Motluk, “Flawed Competition Policies: Designing Markets with Biased Costs and Efficiency Benchmarks,” Review of Industrial Organization , Vol.31, No. 1, Aug 2007.
7. The two reliability indicators used universally are “System Average Interruption Duration Index” (SAIDI) and "System Average Interruption Frequency Index (SAIFI). SAIDI is the average duration of a system outage calculated by adding the number of customer-hours of interruptions and dividing by the number of customers. SAIFI is the average frequency of outages and is calculated by adding the number customer interruptions divided by the number of customers.
8. Cronin, F.J., and Motluk, S., “How Effective are M&As in Distribution? Evaluating the Government’s Policy of Using Mergers and Amalgamations to Drive Efficiencies into Ontario’s LDCs,” Electricity Journal , April 2007.
9. Cullmann., A. & Hirschhausen., C.V., (2006), From Transition to Competition – Dynamic Efficiency Analysis of Polish Electricity Distribution Companies , Working paper, Dept. of International Economics, DIW Berlin, May 24, 2006. Yu, William, et al. , “Incorporating the Price of Quality in Efficiency Analysis: the Case of Electricity Distribution Regulation in the UK,” July 2007.