Institutional Elasticity as a Significant Driver of IT Functionality Development

Abstract

Institutions drive innovation and stimulate broad diffusion. Not surprisingly, national systems of innovation are influenced by their institutional elasticity in response to changing market conditions. As nations move from industrial to information-based societies, a key factor governing institutional elasticity is how institutions integrate IT. Since IT functionality is intimately connected with institutional dynamics, unlike simple manufactured products such as refrigerators, IT's specific functionality is formed through dynamic interaction with institutional systems. Consequently, institutional elasticity is a critical factor in the functionality of IT and its subsequent self-propagating behavior.

This paper analyzes one possible mechanism of IT functionality formation, with special attention to the interaction of the technology with institutional systems.

Reprinted from Technological Forecasting and Social Change 71, No. 7, C. Watanabe, R. Kondo, N. Ouchi, H. Wei and C. Griffy-Brown, Institutional Elasticity as a Significant Driver of IT Functionality Development, pages: 723–750, copyright (2004), with permission from Elsevier.

Appendices

Appendix. Data Construction and Sources

Appendix 1. TFP and IT Intensity

In order to measure TFP and IT intensity, the following production function was used:

$$V = F (L,K,I,T,t),$$

where A, scale coefficient; L, labor; K, capital; I, IT production factor; I _l , IT labor; I _k , IT capital; T, technology stock; and t, time trend. Duplication among each production element was deducted.⁷

IT production factor was constructed using the data from the Ministry of International Trade and Industry's (MITI).⁸ “Current Status of Japanese Information Processing,” which referred the “Survey on Information Processing in Japan” by Japan Information Processing Development Center. “Capital Matrix of the Input–Output Tables” was also used to supplement the IT related investment that is not covered by the Survey. The resultant IT production factor is explained by the IT related investment listed in Table 3.4.

Table 3.4 IT related investment

Appendix 2. Epidemic Behavior

In the analysis of the epidemic behavior of six innovative goods, trends in the cumulative number of adopters were analyzed using an epidemic function.

Provided that the “pregnancy” period is short enough to neglect this timing and the depreciation rate can be treated as a reverse of the lifetime, the cumulative number is measured by the following equation:

$$\begin{array}{rcl}N_t & = & P_t + (1-\rho) N_{t-1}, \\ N_0 & = & \frac{P_1}{g+\rho}, \\ \rho & = & \frac{1}{{\rm LT}}, \end{array}$$

where N _t , cumulative number of adopters at time t; P _t , number of shipment for domestic use at time t; g, increase rate of production in the initial period; ρ, depreciation rate; and LT, life time (average years in use).

A.2.1 Refrigerators (1951–1999)

The annual shipment volume of refrigerators from the year 1951 to 1999 was obtained from the “Report on Machinery Statistics” (Ministry of International Trade and Industry (MITI), annual issues). Since the ratio of imports and exports of refrigerators to their shipment as a whole has not been changing greatly, the annual shipment volume was used for the analysis.

The depreciation rate was measured by multiplying the rate of obsolescence of technology in the electrical machinery industry [25] and the ratio of depreciation rate of refrigerators (“Consumer Confidence Survey” (Cabinet Office, 1998–2001)) and electrical machinery industry in 1998.

A.2.2 Fixed Telephones (1953–1999)

The cumulative number of fixed telephones subscribers from 1953 to 1999 was obtained from NTT's annual reports.

A.2.3 Japanese Word Processors (1982–1997)

The annual domestic production volume of Japanese word processors from the year 1982 to 1997 was obtained from “Industry in Japan: A Graphical Look at 1626 Goods and Services” (Development Bank of Japan, Economic & Industrial Research Department, 1999).

The depreciation rate was measured by multiplying the rate of obsolescence of technology in the electrical machinery industry [25] and the ratio of depreciation rate of Japanese word processors (“Consumer Confidence Survey” (Cabinet Office, 1998–2001)) and the electrical machinery industry in 1998.

A.2.4 Color TV Sets (1966–2000)

The annual domestic shipment volume of color TV sets for domestic use from the year 1966 to 2000 was obtained from the “Survey of Japan Electronics and Information Technology Industries Association” (JEITA, annual issues).

The depreciation rate was measured by multiplying the rate of obsolescence of technology in electrical machinery industry [25] and the ratio of depreciation rate of color TV sets (“Consumer Confidence Survey”. (Cabinet office government of Japan, 1998–2001)) and electrical machinery industry in 1998.

A.2.5 Personal Computers (1987–2000)

The 32-bit personal computer was analyzed as the PC. The quarterly shipment of the 32-bit PC for domestic use from 1987 to 2000 was obtained from the “Personal Computers Statistics” (Japan Electronics and Information Technology Industries Association (JEITA), annual issues).

The depreciation rate from 1998 to 2000 was estimated 20% p.a. by using the reverse of legal life time defined by the Corporate Tax law. The rate before 1998 was measured by multiplying the rate of obsolescence of technology in electrical machinery industry [25] and the ratio of depreciation rate of PC and electrical machinery industry in 1998.

A.2.6 Cellular Telephones (1996–2001)

The cumulative number of cellular telephones contracts from September 1996 to March 2001 (monthly statistics) was obtained from monthly reports issued by Telecommunications Carriers Association (TCA).