17 A

- i APPENDIX 17A. REGULATORY IMPACT ANALYSIS SUPPORTING

MATERIAL

TABLE OF CO NTENTS

17A.1 BACKGROUND ON MARKET PENETRATION CURVES DEVELOPED

BY XENERGY

..................................................................................................... 17A-2

17A.2 UTILITY REBATE PROGRAMS FOR DISTRIBUTION TRANSFORMERS

. 17A-4

LIST OF FIGURE

Figure 17A.1.1 Comparison of Exponential and Logistic Curves Showing External and

Internal Influences on Consumers ............................................................ 17A-317A

- 2 APPENDIX 17A. REGULATORY IMPACT ANALYSIS SUPPORTING MATERIAL

17A.1 BACKGROUND ON MARKET PENETRATION CURVES DEVELOPED BY

XENERGY

Xenergy , Inc. developed a re

- parameterized, mixed -source information diffusion model to estimate market impacts induced by financial incentives for energy

- efficient appliances. The basic premise of this mixed -source model is that information diffusion drives technology adoption.

There is extensive economic literature on the diffusion process of new products as technologies evolve. Some of the literature focuses primarily on the development of analytical models of diffusion patterns of new products for individual consumers or for technologies from
competing firms. 1

, 2

, 3 One study records researchers’ attempts to investigate underlying factors that drive diffusion processes. 4 Because of the distinct characteristics of diver se new products, few studies have conclusively developed a universally -applicable model. Some key findings, however, have seemed to gain wide recognition in academia and industry.

First, new technologies may not be adopted by all potential users, regardless of their economic benefits and technological merits. Therefore, a ceiling on the adoption rate exists for many products. Second, not all adopters purchase new products at the same time; some act earlier after the introduction of a new product, while others respond slowly, waiting for products to become more mature. Third, diffusion processes can be approximately characterized by asymmetric S -curves, depicting three stages of diffusion: starting, accelerating, and decreasing as the adoption ceiling is being reached.

An important diffusion model, the epidemic model , is widely used in marketing and social studies on diffusion. It assumes that a) consumers value the benefits of a new product identically and b) the cost of a new product is constant or declines monotonically over time. What induces a consumer to purchase the new product is information about the availability and the benefits of the product. In other words, it is information diffusion that drives new product adoption by individual cons umers. 3 The model incorporates information diffusion from both internal sources (news spread by word of mouth from early adopters) and external sources (the “announcement effect” by government, other institutions, or commercial advertising) by superimposing a logistic function with an exponential function. 1,4

The relative degree of influence by internal or external sources determines the general shape of the diffusion curve of a specific product. 1,4 For instance, if the adoption of one particular product is more influenced by external sources of information diffusion (announcement effect) than by internal sources (word of mouth among earlier adopters to prospective adopters), the rate of diffusion at the beginning stage of the diffusion process is much higher. This reflects the immediate in formation exposure to a significant number of17A

- 3 prospective adopters brought about by external sources, in contrast to the more gradual exposure to internal sources such as news propagation by earlier adopters, a small proportion of the population, to other prospective adopters. Graphically speaking, a relatively dominant external source of information diffusion gives an immediate jump-start to the adoption of a new product in the first years, forming a concave curve with respect to the Y axis (see the exponential curve in Figure A.1). Adoption of a new product with a stronger influence by internal sources of information diffusion (such as a socially-tightened network formed by prospective adopters) may start with a few early adopters and gradually increase as the number of adopters grows, and thus form a convex curve (see the logistic curve in Figure 17 A. 1.1).

Figure 17A.1.1 Comparison of Exponential and Logistic Curves Showing External

and Internal Influences on Consumers 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 5 10 15 20 25 30Market Penetration

Year Logistic Function Modified Exponential Function

External Influence

Internal Influence17A

- 4 17A.2 UTILITY REBATE PROGR AMS FOR DISTRIBUTION TRANSFORMERS

The following two tables present a summary of rebate program amounts offered throughout the U.S. for distribution transformers

.

DOE found 4 agencies with programs for distribution transformers. R ebates for this product by electric utilit ies and municipal utilities and are generally offered under programs that

cover the installation of new energy efficiency equipments up to a specified amount . These

entities offer rebates for distribution transformers meeting efficiency criteria that usually greater
then the current standard

. The following list shows the agency names, States, and program websites of utilities with energy efficiency programs that cover distribution transformers.

**•** Anaheim Public Utilities, California http://www.anaheim.net/articlenew2222.asp?id=4136

**•** Austinenergy, Texas http://www.austinenergy.com/Energy%20Efficiency/Programs/Rebates/Commercial/Commercial%20 Energy/transformerGuidelinesApp.pdf

**•** PECO, Pennsylvania https://www.pecosmartideas.com/programsandrebates/business/equipmentincentives.html

**•** Seattle City Light, Washington http://www.seattle.gov/light/conserve/business/cv5_f i.htm17A

- 5 REFERENCES

1 Geroski, P.A., Models of Technology Diffusion. 2000. Research Policy. 29, 603-625.

2 Hall, B. H. and B. Khan. “Adoption of New Technology.” 2003. Working Paper No.E03- 330. Department of Economics, University of California, Berkeley, CA.

3 Lekvall, P. and C. Wahlbin. “A Study of Some Assumptions Underlying Innovation

Diffusion Functions.” 1973. Swedish Journal of Economics.

4 Van den Bulte, C. “Want to Know How Diffusion Speed Varies Across Countries and Products? Try a Bass Model.” PDMA Vision, October 2002. Product Development and Management Association. XXVI No 4.