Explaining slow diffusion of energy-saving technologies; a vintage model with returns to diversity and learning-by-using

This paper studies the adoption and diffusion of energy-saving technologies in a vintage model. An important characteristic of the model is that vintages are complementary: there are returns to diversity of using a mix of vintages. We analyse how diffusion patterns and adoption behaviour are affected by complementarity and learning-by-using. It is shown that the stronger the complementarity between different vintages and the stronger the learning-by-using, the longer it takes before firms scrap old vintages. We argue that this is a relevant part of the explanation for the observed slow diffusion of energy-saving technologies. Finally, we show that an energy price tax reduces energy consumption, because it speeds up the diffusion of new energy-saving technologies and induces substitution from capital to labour.     

A model of advertising with application to the German automobile industry

This paper develops a dynamic duopolistic model of advertising and price competition. Advertising accumulates a stock of goodwill which enters directly into the demand functions and both the cooperative and predatory effects of advertising are considered. It is shown that firms invest more in advertising the higher the degree of cooperativeness of advertising and some comparative static results are provided. In the second, empirical part of the article, estimations of the demand equations are presented using data from the German automobile industry. The main conclusion drawn is that advertising plays an important role in this market and has a predatory nature.     

Sustained endogenous growth driven by structured and evolving general purpose technologies

We address two interrelated issues: structured technology and non-stationary equilibrium growth. We do this by modelling multiple, co-existing, non-identical general purpose technologies (GPTs). Three sectors producing pure and applied research and consumption goods, employ different, evolving, technologies. Agents within each sector operate under conditions of Knightian uncertainty and path dependence, employing technologies that differ in specific parameter values. This behaviour produces a non-stationary (non-ergodic) growth process. Important characteristics of structured technology, previously only described historically, are successfully modelled, including co-existing GPTs some of which compete with each other while others complement each other in varying degrees. Because changes in technology are partial causes of, but not contemporaneous with, GDP changes, their separate evolutions can be studied.     

International diffusion of steel technologies: Time-lag and the speed of diffusion

The article deals with the diffusion of two major innovations in the world's steel industry, the oxygen steel process and continuous casting. Twenty-one countries, including the socialist countries of Eastern Europe, are analyzed from the point of view of their ability to adopt technology from pioneering countries. Among capitalist countries, Great Britain and the United States appear to be slower than others. Eastern European countries and the Soviet Union as a group show a lower ability to adopt technologies than capitalist countries, even the slowest ones. G. Ray's hypothesis that countries that are late-comers in adopting a particular technology benefit from that and are faster in spreading it over their industry is challenged. The correlation analysis shows that at least in one case, the oxygen steel process, the late-comers are not faster in diffusion than countries that were first in introducing new technology. It is concluded from empirical findings that late-comers may not be faster in diffusion if there is a lack of good communication (the Eastern European countries case) or when the technology in question is relatively simple and benefits from being late are insignificant (the case of oxygen steel process).     

A product diffusion model incorporating repeat purchases

A logistic-based model for forecasting the rate of product diffusion given aggregate time series data was constructed. The model differs from earlier models based on fitting the logistic to aggregate data in that it includes a submodel to separate replacement demand from first-time sales. We fit the theoretical model to data and show that forecasts will be significantly more accurate using this model instead of the logistic curve.     

Forecasting technology diffusion with the Richards model

The Richards model has a shape parameter m that allows it to fit any sigmoidal curve. This article demonstrates the ability of a modified Richards model to fit a variety of technology diffusion curvilinear data that would otherwise be fit by Bass, Gompertz, Logistic, and other models. The performance of the Richards model in forecasting was examined by analyzing fragments of data computed from the model itself, where the fragments simulated either an entire diffusion curve but with sparse data points, or only the initial trajectory of a diffusion curve but with dense data points. It was determined that accurate parameter estimates could be obtained when the data was sparse but traced out the curve at least up to the third inflection point (concave down), and when the data was dense and traced out the curve up to the first inflection point (concave up). Rogers' Innovation I, II and III are discussed in the context of the Richards model. Since m is scale independent, the model allows for a typology of diffusion curves and may provide an alternative to Rogers' typology.     

A model of the linked adoption of complementary technologies

This paper presents a dynamic feedback model of the technology diffusion process in which each firm's technology adoption decisions maximize the net present value of its anticipated cash flow, taking into account the direct cost savings, the number of linked firms expected to adopt complementary technologies, and anticipated changes in adoption costs. The adoption of complementary technologies need not be simultaneous, but linked technologies can induce a rapid industrial regime shift without explicit coordination or planning.     

A model to optimize investments in health technologies,quality of care and research

Funds for health technologies compete with funds for implementing health technologies as well as funds for conducting research to reduce uncertainty around treatment and implementation cost-effectiveness. No study has yet shown how to allocate a combined budget for health technologies, implementation and research. The purpose of this work was to present an allocation model with the goal to maximize health. Based on a constrained optimization formulation, we show that considering opportunities to invest in implementation and research may justify considerable disinvestment in health technologies. This may reduce the willingness to pay for new health technologies significantly.     

A stochastic cellular automata model of innovation diffusion

A stochastic cellular automata model of new product diffusion is proposed. It is found that the growth for a given market potential can be determined by a parameter that quantifies chance preferences of individuals for the product and can be estimated from field surveys. It is also found that the “takeover time” in a given seed region is almost independent of the number of innovators. The results suggest possible strategies for the successful introduction of a new product.     

A non-homogeneous non-uniform influence model of innovation diffusion

A model of innovation diffusion which gives unequal weightage to the adopters of different temporal stages and captures commonly observed ups and downs in new product diffusion is proposed. It is shown that our model possesses features of the existing flexible diffusion models and shows better fit which is indicated by the values of R²_adj, mean absolute deviation, and mean percentage error and estimates a larger market potential, M. It has an interesting feature of conversion factors, first increasing then vanishing, much before we approach market saturation, implying that there is a scope of new thrust in converting remaining potential adopters.     

A choice-based multi-product diffusion model incorporating replacement demand

This study proposes an integrated forecasting model that incorporates both first purchase diffusion and replacement component of sales in predicting multi-product diffusion patterns. The model consists of a two-stage procedure that customers undertake during purchase occasions according to a diffusion process or replacement process, and at each occasion, they make purchase incidence decisions and product choices according to a choice model. By incorporating various exogenous factors in the choice model, the model can identify the impact of each factor on customers' purchase incidence decisions and choice decisions among various product sub-categories. This approach enables us to understand the overall process of customers' purchasing behavior and to separate total sales amount into sales to three consumer segments: first-time buyers, customers who repurchase the same product category and customers who change their previous product category. We applied the proposed model in the forecasting multi-product framework; forecasting sub-category level automobile sales and brand level mobile terminal sales in the South Korean market. The results of the empirical studies showed that incorporating the replacement components into the multi-product diffusion framework is useful not only in understanding the demand interaction among automobile categories and among mobile handset brands, but also in producing more accurate long-term sales forecasts compared to previous multi-product diffusion models.     

The diffusion of new information technologies and productivity growth

This paper investigates the effects of the rates of diffusion of the cluster of new information technologies on the growth of output and total factor productivity in the main OCED and industrializing countries in the late eighties. This diffusion approach contrasts the technology production function framework. It predicts that the rates of generation of new technologies are much less effective than the rates of diffusion and the investment efforts in determining the growth of labor productivity especially when capital-intensive technologies which command high levels of investments are considered. The results make it possible to elaborate and assess empirically the notion of key-technologies that provide positive externalities to the rest of the system.A preliminary version of this paper has been presented at the European Conference of the International Telecommunications Society held at the Stenungsbaden Yacht Club.     

Estimating exchange rate dynamics with diffusion processes: an application to Greek EMU data

Recently various exchange rate models capturing the dynamics during the transition from an exchange rate arrangement of floating rates into a currency union have been derived. Technically, these stochastic equilibrium models are diffusion processes which have to be estimated by discretely sampled observations. Using daily exchange rate data prior to the Greek EMU-entrance on 1 January 2001, we develop a rigorous estimation procedure. Our estimates point to an increasing interventionist economic policy in the run-up to the Greek EMU entrance. A comparison of this econometric indication with policy information provided (ex-post) by the Bank of Greece (BoG) in its Annual Report 2000 reveals that the BoG indeed pursued such an active policy stance (so-called institutional frontloading strategies).      

A model of multiple-unit ownership as a diffusion process

This paper develops and tests a new model for multiple-unit adoptions of durable goods based on the diffusion modeling tradition. Multiple-unit adoptions are a major component of sales for many consumer durable product categories. For instance, sales of multiple-unit adoptions for televisions have been higher than both first adoptions and replacement purchases since 1977, while for automobiles, they have represented more than 20% of sales since 1966 in Australia. The structural drivers of multiple-unit adoptions are quite different from either first purchase or replacement purchase. Hence, identifying and modeling the multiple-unit component of sales is important for aggregate sales forecasts. Moreover, consumer requirements for additional units of a product are likely to be considerably different than for the other components of sales (first purchases and replacement purchases). As such, the ratio of the first, multiple, and replacement sales components will strongly influence the product mix requirements of the market.

While forecasting and influencing multiple-unit sales are an important managerial issue, very little attention has been given to multiple-unit ownership in the diffusion modeling literature. The only model available was developed for the purpose of modeling relatively short-term behavior of multiple-unit adoptions, rather than the longer-term pattern of sales. We propose a model of multiple-unit adoptions as a diffusion process.

We apply the model to both color television and automobiles. Analysis of the model's long-term fit and forecasts in these applications provide support for the structure of the new model.     

The diffusion of hospital technologies: some econometric evidence.

This paper examines the diffusion of five hospital technologies that have spread widely since 1950: the postoperative recovery room, the intensive care unit, the respiratory therapy department, diagnostic radioisotope facilities, and electroencephalograph. The regressions show that the logistic function describes the diffusion of hospital innovations as well as it does the diffusion of innovations in other industries, that the rates of diffusion for these technologies fall within the range established by work on other industries, and that the rates for technologies that were not yet widespread in the middle 1960s increased with the advent of Medicare and Medicaid.     

Spatial random utility model with an application to recreation demand

The paper examines the relevance of unobserved spatial dependence between individual decision-makers in the analysis of discrete choices. To incorporate spatial interdependencies in the behavioral analysis, we propose a spatial random utility model of recreation demand. The model combines the set-theoretic concept of spatial neighborhood, endogeneity of spatial interdependencies, and unobservable individual preferences. Our estimation procedure uses an efficient pseudo maximum likelihood estimator. We apply the model to the study of recreational travel demand in Iowa and evaluate the significance of unobserved spatial interdependencies between individual households in recreational travel choices.     

A hedonic-output-index-based approach to modeling polluting technologies

Despite some recent criticisms, the conventional radial distance function, which treats undesirable by-products as either frontier shifters or inputs, remains a popular go-to formulation of polluting production processes among practitioners. This unfading popularity is arguably driven by the ability of radial distance functions, unlike alternative directional distance functions, to allow for unit-free multiplicative changes in arguments as well as, by implicitly postulating the radial direction, to free researchers from the dilemma of having to explicitly choose the directional vector. In this paper, we offer a generalization of the standard radial distance function to polluting technologies that can accommodate undesirable by-products in a more economically meaningful way. Specifically, we propose modeling undesirable outputs via a hedonic output index, which is meant to ensure that pollutants are treated as outputs, as opposed to inputs or theoretically unregulated frontier shifters, while also recognizing their undesirable nature. By using a radial input distance function generalized to encompass an (unobservable) hedonic output index of desirable and undesirable outputs, we are able to meaningfully describe relationships between different products (including the complementarity of desirable and undesirable outputs) within producible output sets as well as to represent technically feasible polluting production possibilities given inputs. An empirical application of our methodology to the case of Dutch dairy farms in 2001–2009 demonstrates the complexity of interactions between outputs, thereby attesting to the value of more elaborate representations of production possibilities.     

A dynamic diffusion model for managing customer's expectation and satisfaction

The paper aims at answering the generic question on how suppliers make the suitable and well-timed decisions in diffusing new technology effectively to adopters. Three major attempts are made for the study: First, investigating the entire process of the adoption and diffusion of technology innovation with reasonably well-accepted models in each areas. Second, proposing an integrated model by concatenating in structured manner the three prominent models for the management of technology innovation such as diffusion model, adoption model, and customer satisfaction model. Third, exploring the dynamic mechanism underlying outward behaviors of the integrated model proposed in the study which depicts the causal relationships that influence technology adoption and diffusion behaviors. An exploration of the dynamic mechanism underlying outward behaviors of the integrated model is presented in the study by introducing the system dynamics simulation technique. These attempts made for the study and the results perhaps allow both researchers and practitioners to gain insight into the causal factors influencing customers' adoption decision making processes and thereby into the potential diffusion patterns resulting from those adoption processes.     

A general equilibrium model of structural change and economic growth,with application to south Korea

This paper presents a computable general equilibrium model for South Korea. It is a dynamic input-output model solved by assuming equal sectoral growth rates. Its solution gives output and price relatives which measure the structural ‘distance’ of the economy from the ‘turnpike’. Comparisons of these model solutions with actual output proportions and relative prices provide insights into the South Korean industrialization process. However, the model's strict assumptions limit its applicability and provide problems of interpretation, especially in open economies.