Technology Adoption Indicators Applied to the ATP Flow-Control Machining Project

NISTIR 6888
Technology Adoption Indicators Applied to the ATP Flow-Control Machining Project

In its 1995 General Competition, the Advanced Technology Program funded the Flow-Control Machining Project, a four-year $7.9 million research joint venture involving Extrude Hone Corporation, a small company in Irwin, PA, General Motors, the University of Pittsburgh, and the University of Nebraska at Lincoln to develop two new automated finishing processes and make them cost effective for large-production manufacturing. The Flow-Control Machining processes advance the state-of-the-art in manufacturing finishing by allowing manufacturers to more effectively fabricate parts for their intended functional performance. It uses neural-network algorithms, process control methods, and new abrading techniques to develop manufacturing processes that are economically compatible with high-volume, relatively low-value engines.

This report presents a case study of the economic impact of applying flow-control machining technology-first developed for the automobile industry-to the lawnmower industry. A Technology Adoption Indicator methodology is used to provide a structure for analysis of the adoption of technology by an industry. These indicators assist in the analysis of the potential for adoption of the Flow-Control Machining technology by the lawnmower industry.

The TAI framework has other applications for ATP. First, it can be used to identify promising case studies for project evaluation. Second, it offers a consistent and effective methodology for conducting case studies. Third, it can assist in evaluating the business plans of ATP proposers. Fourth, it can be used to advise ATP awardees on which industries are more likely to be potential adopters of their technologies.

The Technology Adoption Indicators: Development and Application to the Case Study

A significant amount of economic research shows that some industries adopt new technologies faster than others. For example, economic studies of industry R&D projects based on the structure-conduct-performance model have found that industry characteristics such as the number and size distribution of firms and quality of competition affect rates of technology adoption. Since the model is widely used for organizing and analyzing industry characteristics and behavior, we apply it to develop a set of indicators that assess the likelihood of technology adoption.

According to the structure-conduct-performance model, market structure affects market conduct, which in turn affects market performance. Industry characteristics, such as the numbers of sellers and buyers, affect selling and buying conduct, such as production, research and innovation, pricing behavior, advertising, investment, and legal tactics. Market conduct, in turn, affects the overall performance of the industry-that is, price and production levels. Public policy (such as taxes, subsidies, and regulations) affects both industry market structure and conduct. In the long run, all these conduct and performance activities affect the market structure.

Market structure is evidenced by industry concentration ratio measures such as four- and eight-firm concentration ratios and the Herfindahl-Hirshman Index. Industries characterized by mid-sized, competitive firms tend to adopt technology more than industries characterized by either many small firms by a few, very large firms (oligopolies). In short, economic research suggests there is an optimal range of industry concentration in which technology adoption is most likely.

The numbers of patents and research joint ventures provide indicators of market conduct and the supply of technology. Through regulation, public policy affects market conduct by serving as a driver of technology adoption.

In this study, we are not only concerned about the adoption of technology in general, but with the adoption of a specific technology. All else being constant, the fewer the number of competing technologies, the greater the likelihood of any one technology innovation being adopted. Specifically, if there is a great demand for technological innovation but few sources of technological innovation, then new innovations will be rarer and will have a greater chance of adoption. The lawnmower industry has fewer patents and research joint ventures than the airplane engine industry while having higher technology demand. Therefore, the likelihood for adoption of the FCM technology by the lawnmower industry is judged to be higher than the airplane engine industry.

In the case of the lawnmower industry, a specific public policy, in the form of an impending EPA regulation, is a key factor in likely market conduct. Pending EPA regulations aim to reduce small-engine emissions by 59% by 2007. No pending regulations affecting technology adoption by aircraft engine manufacturers have been identified.

Economic Case Study on the Impact of the Adoption of FCM in the Lawnmower Industry

An economic case study was performed of the impact of adoption of Flow-Control Machinery technology in the lawnmower engine application. This required first investigating the economic feasibility of lawnmower engine manufacturers using the FCM technology to meet the new EPA regulations for different types of engines. Then, for engines where adoption was economically feasible, a macroeconomic projection was made of the broader impact on U.S. economic output.

Engineering tests performed by Extrude Hone, the lead company in the ATP-funded research joint venture and inventor of the Flow-Control Machining technology, confirmed that the technology can be used to meet EPA's Phase 2 emissions requirements for 2007. Extrude Hone engineers also provided detailed data on the costs of applying the Flow-Control Machining technology to the full range of lawnmower engines.

An analysis of the total costs to the industry of the Extrude Hone FCM process was performed for each of four engine market segments and compared with the costs of meeting the EPA Phase 2 regulations with conventional technology, as estimated by the EPA.

For "large, side-valve engines," the FCM technology is the lower-cost option relative to the conventional technology both initially and over time because both the fixed costs and the ongoing variable costs are lower than for the conventional technology.
For "small, side-valve engines," the Flow-Control Machining technology is estimated to be significantly less expensive than the conventional technology in 2007 but slightly more expensive in later years. In particular, fixed costs are concentrated in that initial year of use, and the Flow-Control Machining technology has lower fixed costs than conventional technology. On the other hand, the Flow-Control Machining technology has slightly higher variable costs that make it less attractive over time.
For "small, overhead-valve engines" and for "large, overhead-valve engines," the Flow-Control Machining technology is more expensive in terms of both fixed and variable costs than the conventional technology.

The Regional Economic Models, Inc. (REMI) macroeconomic model was used to simulate the total national impact of adoption of the Flow-Control Machining technology for large and small side-valve engines. The macroeconomic model computes the total effect over time on the economy resulting from a change to a component of the economy. The model is based on economic theory, input-output (I/O) accounting, and econometrically estimated, time-dependent relationships between components of the economy.

The model captures the following effects across the economy: An increase in production costs in the lawnmower industry-by adopting either the Flow-Control Machining technology or conventional technology-will cause an increase in the selling price of lawnmowers. This in turn will cause a decrease in the number of units sold. As production costs rise, firms that seek to maintain current profit levels must increase their selling prices and/or reduce other production costs, including the costs of labor and capital (machinery). Decreased sales and cutting costs will reduce employment in the lawnmower industry and in industries that supply parts and services to it, thereby reducing aggregate income and the broad set of purchases this income supports (such as for purchasing cars, homes, services, and travel).

A comparison of the combined macroeconomic effects across the economy of Flow-Control Machining technology versus conventional technology shows the following:

For both small, side-valve engines and large, side-valve engines, adoption of Flow-Control Machining technology is less costly to GDP, employment, and income in meeting the EPA regulations compared with adoption of conventional technology.
For small, side-valve engines, there is a savings of $261 million in GDP, and $244 million in personal income over the three years 2007 to 2009 from using Flow-Control Machining technology.
For large, side-valve engines, there is a savings of $982 million in GDP and $878 million in personal income over the five years 2003 to 2007. For these engines, the Flow-Control Machining technology saves 93% of GDP, employment, and personal income that would be lost using conventional technologies to address the EPA regulations.
For large, side-valve engines, there is a savings of $982 million in GDP and $878 million in personal income over the five years 2003 to 2007. For these engines, the Flow-Control Machining technology saves 93% of GDP, employment, and personal income that would be lost using conventional technologies to address the EPA regulations.

The case study analysis performed clearly demonstrates the economic advantage of the FCM technology over conventional technologies for small and large side-valve lawnmower engines. The Technology Adoption Indicators methodology provides a useful framework for assessing whether a particular industry will adopt new technologies, and further assists in the investigation
of industry characteristics affecting technology adoption. In this case study, EPA regulation was the decisive factor indicating the likelihood of adoption of the FCM technology.

There are widespread differences across U.S. industries in the size and distribution of firms, in patents, in research joint ventures, and in the use of new technologies. Increased understanding of the relationships between these variables will help ATP assess the likelihood of adoption and the potential economic impact of the proposed projects.