جایگزینی تکنولوژی و پذیرش نوآوری : موردی از بازارهای تصویربرداری و ارتباطات سیار

Technology substitution and innovation adoption are considered within the framework of evolutionary economy. The evolution hierarchical concepts of change, order, direction, progress and perfectibility are invoked to describe technological substitutions as processes that point towards the direction the economic system moves into, its rate of change giving the speed of change. Knowledge evolution and its appropriation into technological innovation are key ingredients in enhancing competition among technologies struggling towards capturing the other's market shares. We accordingly mathematically translate these evolutionary views into practice using Lotka–Volterra prey–predator model for competition and single logistic growth for the market evolution of the competing innovation. Using this formulation we studied the technological substitution of analog by digital imaging process and demonstrate how the later has disruptively displaced the former. Considering its vital importance to managing market strategies towards innovation products adoption, we redefine the takeoff time with a more realistic accounting of the innovation product adoption by consumers that is easily computed from its launching phase sales data. Our takeoff time is found to occur earlier than the one usually adopted. The new formulation is successfully tested against the consolidated innovation adoption of two economically impacting technological innovations: digital cameras and mobile phones.

Technological substitution is the hallmark of economic transformation. It is an open-end process that will last for as long as human life in our planet remains sustainable. Schumpeter [1], [2] and [3], back in the 1930's, was one of the pioneers in recognizing this important aspect in economic analysis. In fact, instead of assuming that economic systems are simply adapting to exogenous changes, the essence of the 1874 theory of general equilibrium of Walras [4], Schumpeter proposed a new view, that is, economic systems are to be interpreted as adaptive self-transforming evolutionary systems. In a seminal work, Levins and Lewontin [5] while stressing the concepts of continual change and co-determination between organism and environment, opened up a vivid scholarly discussion about the fact that the ideology of evolutionism had indeed penetrated into both natural and social sciences … (sic) “Although the concept of evolution has become firmly identified with organic evolution, (…) the theory of evolution of life is only a special case of a more general world view that can be characterized as “evolutionism”. The ideology of evolutionism (…) has permeated all the natural and social sciences including anthropology, biology, cosmology, linguistics, sociology and thermodynamics. It is a world view that encompasses the hierarchically related concepts of change, order, direction, progress and perfectability (…). Theories of the evolution of the inorganic world, like cosmology and thermodynamics, generally include only change and order, while biological and sociological theories add the ideas of progress and even perfectability as elaborations of their theoretical structure” (see Ref. 5, page 9). In quite general terms, evolutionary theories essentially account for the rate and direction in which the system changes. The traditional Darwinian mechanism for evolution rests upon three propositions: the principle of variation, meaning that members of a relevant population vary in their characteristics (physiology, morphology and behavior, in biological terms) that convey selective significance; the principle of heredity, implying that the characteristics of individual entities are copied over time (offspring resemble their parents in the average more than they resemble unrelated individuals, in biological terms); and, the principle of selection, meaning that the interaction between the entities in a specific environment results in that some entities are endowed with sets of characteristics that are better suited to their survival in said environment, thereby enhancing the growth of their population. From these three principles, the mechanics of evolution is readily obtained [5]. Provided that offspring resemble their parents more than others, if a particular variant leaves more offspring than another, the percent composition of the population in the next generation will change. In time, the population will be dominated by the surviving variant with the higher reproductive rate, and the species will change progressively. This is the kinematics of an evolutionary process. The dynamics is provided by the struggle for survival. The reason some variants leave more offspring is that they are better able to appropriate resources when supply shortens and to optimally reinvest such resources in producing offspring. This superior efficiency is a manifestation of a higher degree of engineering performance in facing the demands and challenges posed by the environment. As emphasized by Sober [6], survival and growth are characteristics of the entities and consequences of their involvement in a selection process. By combining the first two principles under the label of variation, the traditional evolutionary theory becomes essentially a two-component process involving variation and selection. Levins and Lewontin [5] emphasized this point as the embarrassing aspect of Darwin's theory: “if selection causes the differential reproduction of variants, eventually the species population should uniformly be the fit type among those available at the start. But then there would be no more variants for further evolution. Darwinian evolution by selection among variants is a self-negating process, which consumes the fuel, variation, on which it feeds and so destroys the condition for its further development”. The question of approaching evolutionary economics along these views will be considered in the next section. This paper is organized as follows. In Section 2 methodological considerations in regards to viewing technological substitution and innovation adoption under this approach are made. Section 3 bears on the results from theoretical modeling and corresponding discussions. In particular, in Sub-section 3.1, the problem of technological substitution within the framework of the logistic modeling is dealt with using two specific approaches: the logistic Lotka–Volterra competition model and the conventional, non-interacting, logistic function modeling, while in Sub-section 3.2 the closely related subject of technological adoption is taken up with particular emphasis on the analysis of the takeoff time for that process. Two important evolutionary study cases are covered, namely, digital imaging and the mobile communication. Finally, in Section 4 we present our concluding remarks.

In quite general terms, as a theoretical ground upon which we set out to analyze the market evolution of innovation products, we adopted the basic principles of evolutionary economics [5], [7], [8] and [9]. Accordingly, besides variation and selection, we assumed that, in such a context, knowledge and innovation (i.e. development, in general terms) can be identified as the third operating component of the evolution process. The technological appropriation of knowledge into innovation triggers an autocatalytic and open-ended process in which new information provides the driving force that projects the economy into a “restless”, non-equilibrium state. Selection gradually “kills” variety and the ensuing interplay between selection and development results in technological substitution whose process determines the rate and direction of the economic transformation. In short, one has technological substitution pointing towards the direction the system moves while its rate of change tells us how fast it does so. With this theoretical view frame as background, we have set out to discuss some aspects of the issue of technological substitution cases of truly worldwide social and economic impact: the digital versus analogical image capture and processing (in short, digital vs. analog imaging) and fixed versus mobile communication technologies. From our treatment of the analog-to-digital imaging technological substitution in the US from 1995 to 2010 using both the logistic Lotka–Volterra (L–V) prey–predator competition model and the conventional, single logistic function modeling we demonstrated that: (a) in the consumer photography niche, the analog vs. digital camera contest has been a characteristically disruptive process; furthermore our study of the evolution of the interaction A • D term in the L–V model allowed us to conclude that the ensuing fierce dispute for the market lasted for about five years, from 2000 to 2005, centered around mid-2003; (b) in the US digital camera yearly sales time series, the model-to-data residuals from an overall single logistic model function, the truncated sine series analysis exposed the presence of two underlying dominant harmonic modes with periods of about 3.7 and 7.5 years. Upon checking the digital photography historical timeline, in the period 1990–2006, we found events periodicities of (3.2 ± 0.37) and (8.0 ± 1.0) years, typical of Kitchin (inventorial) and Juglar (machine and equipments investments) cycles, while in Fig. 4 we see that the data is compatible with m and M peaks having peak-to-peak separations m = > M (3.3 years) and M = > m (4.2 years), averaging to 3.7 years, while the separation M < = > M (or m < = > m) averages to 7.5 years. Both findings are in reasonable agreement with the results from the residuals analysis. As a subject directly connected to the evolutionary economics of an innovation, we engaged into analyzing the process of the adoption of the new technology into the consumer market. We dealt in particular with the concept of takeoff point that signals the beginning of a stage where the customer requirements and preferences change from technical functionality to usability and reliability [28], thus indicating the moment when the dominant designs are adopted [21] and the innovation product gets full consumer acceptance. The concept of takeoff time provides outstanding critical information about the process of innovation that prompts a firm product management staff to evaluate the possible need for changes in the competitive strategies. Among the several innovation adoption S-shaped models available, logistic, Bass model and some of their modified replicas [27] stand among the most frequently used. To locate the takeoff point of an adoption process obeying any of them, one usually takes the time lag from start up to the occurrence of the inflection point, in the chosen model. However, this inflection point in the case of logistic-like curves actually signals the point at which the product sales have reached half way through its full adoption excursion, which points out more to a situation of a well consolidated product insertion into the market, than to that of an adoption takeoff. Our analysis of this situation led us to propose and develop an alternative definition for the takeoff time which resulted in locating it at an earlier time than that provided by the inflection point. In fact, inspired by Montroll [36] description of the laws of social dynamics in analogy to Newton's law of mechanics, and taking the logistic model as a representative of an S-shaped adoption process, we constructed the speed and the acceleration curves for the adoption process. We then defined as the takeoff point of technology adoption as the time where the adoption process first reaches its peak acceleration (see Eq. (9) and Fig. (7) above). We have accordingly derived an analytical expression for the takeoff time t0 (Eq. (11)) in terms of the product adoption curve parameters. It is worth mentioning, at this point, that we have answered, in an alternative way to common practice, a rather relevant question for the industry (particularly, in regards to managing marketing strategies) in dealing with the launching of an innovation product: how to ascertain whether the innovation has reached its takeoff point or not, using a practical, reliable ansatz to analyze the product sales time series since its inception. We demonstrated that our proposed takeoff point for a logistic technology adoption process occurs at a time that precedes the time taken as its usual definition, namely, the location of the inflection point of the logistic growth curve, by an amount equal to 50% of the interval between the peak acceleration and peak deceleration of the process. Under this alternative novel formulation for the takeoff time we analyzed, as case studies, the adoption processes for two outstanding innovation technologies of worldwide impact: digital imaging and wireless mobile communications. It is demonstrated that, in the US case, the innovation takeoff time for digital cameras adoption was around 5.1 years while that for the mobile phones was three time as large. We reasoned that this marked contrast in adoption times is to be credited to the different nature of the two innovation processes considered and technical requirements involved in each case. In fact, digital cameras are buy-and-use devices while a mobile phone acquisition would be rendered useless without a complex expensive infrastructure to support its use. To conclude we can state, in summary, that technological substitution can be aptly understood as an evolutionary economics process encompassing the hierarchically related concepts of change, order, direction, progress and perfectability, in accordance with the ideology of evolutionism, put forward by Levins and Lewontin [5]. Variation and selection, as the operative Darwinian principles, together with development, a third component essentially provided by knowledge and innovation, seem to be the underlying motors for the evolution of a technological substitution process. Under this framework we have been able to show, for instance, that the process of analog-for-digital imaging technological substitution was a disruptive evolution. On the other hand, for the mobile communications process the evolution seems to be better accounted for as a pure variation-selection-development process (a sequence of logistic phases) where innovation, through successive new models, controlled survival of the best fit contenders.