| Author | Ramanathan, Krishnamurthy |
| Call Number | AIT Diss. no. IE-82-01 |
| Subject(s) | Diffusion of innovations
|
| Note | A dissertation submitted in partial fulfilment of the requirements for the degree of Doctor of Engineering. School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Abstract | Innovation diffusion, the process by which ideas and techniques spread through a population, is a process of social change. Thus, its study has assumed considerable importance for governments, businesses and other social organizations which take an active interest in the spread of innovations. Almost all studies of innovation diffusion are either spatially or temporally
oriented. While geographers are mostly concerned with the former, other researchers especially those from the fields of marketing and technological
forecasting find the temporal spread of an innovation more useful. This study is concerned with temporal models and examines certain features which
have hitherto been neglected, In general, most of the temporal models in innovation diffusion theory are binomial models in the sense that they tacitly assume that the population can be divided, without loss of generality, into adopters and potential adopters. While these binomial models have been
successfully used, there is a flaw in their basic structure because they assume that the potential adopter population is time invariant. This may
not be always valid. The first part of this study, therefore, addresses itself to the development of binomial models where the potential adopter
population is dynamic. The developed models are applied to some case-studies to examine and establish their relevance and superiority, The second part
of the study explores the possibilities of developing an analytical framework to study innovation diffusion processes where the population has
polynomial dimensions - polynomial in the sense that it comprises of members
who are adopters, rejecters, disapprovers and uncommitted. It is shown that exact mathematical expressions are difficult to obtain except in some
simple cases, and hence a procedure to obtain the temporal patterns is outlined using the system dynamics technique. The last section is devoted to the development of some stochastic models to complement the most commonly
used deterministic binomial models. The difficulties involved in using stochastic models are discussed. Based on the findings of the three areas that have been studied in this research, pertinent conclusions are drawn
regarding the use of temporal models in innovation diffusion studies. |
| Year | 1982 |
| Type | Dissertation |
| School | School of Engineering and Technology |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Engineering (IE) |
| Chairperson(s) | Sharif, M. Nawaz
|
| Examination Committee(s) | Tabucanon, Mario T. ; Clarke Harry R. ; Huynh, Ngoc Phien ; Martino, J.P.
|
| Scholarship Donor(s) | Japanese Government |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 1982 |