Computer Simulation of Innovation D

Computer Simulation of Innovation Diffusion
Diffusion researchers have traditionally been bound by their research tools to examinations of slices or cross-sections of the process at one point in time. Methodological limits have necessitated slow-motion analyses that hold a slice of the process stationary while the dynamics of diffusion may be observed. Now, with the flexible time considerations provided by the computer, it is possible to fuse the stationary analysis with the continuing process and capture the important variables in action. This can be achieved with the technique of computer simulation.
The result of computer simulation is the reproduction of the social process that one seeks to mimic. If the simulated process does not correspond to reality data, one knows that adjustments are needed in the model (or set of rules) governing the simulated process.
Torsten Hagerstrand, a quantitative geographer at the University of Lund, Sweden, is the father of diffusion simulation research. His work on computer simulation began in the early 1950s, but was published only in Swedish so that for many years the language barrier prevented the diffusion of his important work to U.S. researchers. From the mid-1960s, however, Hagarstrand's work has been carried forward in a series of interesting investigations by quantitative geographers and others. Examples of such simulations are the diffusion of deep well drilling in Colorado (Bowden, 1965a, 1965b) and of agricultural innovations in Colombia (Hanneman, 1969, 1971) and Brazil (Carroll, 1969). These studies and others like them suggest that computer simulation of diffusion holds promise as a means to explore the complexities of the diffusion process as it unfolds over time. This potential, however, has not yet been fully realized.
In the typical example of the Hagerstrand approach to diffusion simulation, the process begins with the first adopter of an innovation. The simulation's rules predict that the next adopter (1) will be relatively homophilous with the previous adopter in personalsocioeconomic characteristics (Hagerstrand, 1952, 1953, 1965, and 1969). These rules of simulated diffusion are carried out by a computer program that repeats them in a sequence of "generations," each of which is a period of time such as a month or a year (Pitts, 1967). Then, the simulated diffusion process is compared with data about the actual rate of adoption in order to determine the effectiveness of the simulation model.*
One of the contemporary intellectual leaders in diffusion simulation research is Professor Lawrence A. Brown of Ohio State University; his results and those of his colleagues (Brown, 1966; Brown and Moore, 1969; Brown et al, 1976; Garst, 1973, 1974, and 1975) demonstrate the important role of spatial distance in the person-toperson diffusion of an innovation. Unfortunately, nongeographical diffusion scholars have not paid sufficient attention to space as an important variable affecting the diffusion of innovations. In fact, space is probably one of the least-studied variables in the diffusion process (Brown, 1981).

Results (Indonesian) 1:

Simulasi komputer difusi inovasi Difusi peneliti telah secara tradisional terikat oleh alat riset mereka ke ujian irisan atau lintas-bagian dari proses pada satu titik dalam waktu. Batas-batas metodologis memiliki mengharuskan gerak lambat analisis yang memegang sepotong proses stasioner sementara dinamika difusi dapat diamati. Sekarang, dengan pertimbangan waktu yang disediakan oleh komputer, mungkin untuk sekering analisis stasioner dengan proses yang berkelanjutan dan menangkap variabel penting dalam tindakan. Hal ini dapat dicapai dengan teknik simulasi komputer.Hasil simulasi komputer adalah reproduksi proses sosial yang seseorang berusaha untuk meniru. Jika proses simulasi tidak sesuai dengan kenyataan data, yang tahu bahwa penyesuaian yang diperlukan dalam model (atau seperangkat aturan) mengatur proses simulasi. Torsten Hagerstrand, a quantitative geographer at the University of Lund, Sweden, is the father of diffusion simulation research. His work on computer simulation began in the early 1950s, but was published only in Swedish so that for many years the language barrier prevented the diffusion of his important work to U.S. researchers. From the mid-1960s, however, Hagarstrand's work has been carried forward in a series of interesting investigations by quantitative geographers and others. Examples of such simulations are the diffusion of deep well drilling in Colorado (Bowden, 1965a, 1965b) and of agricultural innovations in Colombia (Hanneman, 1969, 1971) and Brazil (Carroll, 1969). These studies and others like them suggest that computer simulation of diffusion holds promise as a means to explore the complexities of the diffusion process as it unfolds over time. This potential, however, has not yet been fully realized. In the typical example of the Hagerstrand approach to diffusion simulation, the process begins with the first adopter of an innovation. The simulation's rules predict that the next adopter (1) will be relatively homophilous with the previous adopter in personalsocioeconomic characteristics (Hagerstrand, 1952, 1953, 1965, and 1969). These rules of simulated diffusion are carried out by a computer program that repeats them in a sequence of "generations," each of which is a period of time such as a month or a year (Pitts, 1967). Then, the simulated diffusion process is compared with data about the actual rate of adoption in order to determine the effectiveness of the simulation model.*One of the contemporary intellectual leaders in diffusion simulation research is Professor Lawrence A. Brown of Ohio State University; his results and those of his colleagues (Brown, 1966; Brown and Moore, 1969; Brown et al, 1976; Garst, 1973, 1974, and 1975) demonstrate the important role of spatial distance in the person-toperson diffusion of an innovation. Unfortunately, nongeographical diffusion scholars have not paid sufficient attention to space as an important variable affecting the diffusion of innovations. In fact, space is probably one of the least-studied variables in the diffusion process (Brown, 1981).