17A-i

APPENDIX 17A. REGULATORY IMPACT ANALYSIS SUPPORTING 

MATERIAL 

TABLE OF CONTENTS

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-3
17A-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 diverse 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 consumers.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 information exposure to a significant number of 
17A-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 17A.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 30

Market Penetration

Year

Logistic Function Modified Exponential Function

External Influence 

Internal Influence
17A-4

17A.2 UTILITY REBATE PROGRAMS 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. Rebates for this 

product by electric utilities 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_fi.htm
17A-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.