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.     

Multigeneration diffusion model for economic assessment of new technology

In the era of 21st century, development of emerging information technology is the essence of the advancement. This kind of new technology, however, often requires a great deal of amount of initial investment for both procedures of R&D and commercialization. As cost invested in developing the specified technology is increasing, investors are paying more attention to cost to benefit analysis (CBA). One of the basic elements of CBA for new technological development is the diffusion pattern of demand of such technology. Typically, it would be hard to presume the diffusion pattern of demand when the new product or the technology is under development. In this case, a simulation study is necessary. Many studies of technology evaluation have adopted a single generation model to simulate the diffusion pattern of demand. This approach, however, considers the diffusion of the new technology itself, not taking into account newer generation, which can replace the one just invented. In the real market situation, one must consider the competition and substitution phenomena between old and new technologies. In this paper, we show how multigeneration technology diffusion model can be applied for more accurate CBA for information technology. Additionally, Monte Carlo simulation is performed to find influential factors on the CBA of a cybernetic building system (CBS).     

IS model: A general model of forecasting and its applications in science and the economy

Expanding the work of Marchetti and Modis on Lotka-Volterra competition systems, a general model of Interaction Systems (IS) is introduced to describe the dynamics of multiple member interactions among different populations concerning not only biological systems but other types of systems as well. The new IS model provides us with a general framework of analysis and forecasting, where all parameters, variables, and interactions have real meaning, by using basic knowledge of each system.The proposed model can be applied to many different fields covering economic, business, social, physical, and other phenomena giving us both numerical estimates and qualitative insights of the system's dynamics. This is illustrated in two case studies. In the first case, the IS model is applied to elementary chemical reactions in order to quantify the reactions' kinetics. The result is the well known rate law of chemical reactions kinetics thus providing evidence of the proposed model's validity. In the second case, the IS model is applied to the global economy. The resulting model is tested against real global GDP data. The new IS model gave reliable estimates and proved to be considerably more accurate as compared to a similar forecast of global GDP based on the logistic growth model. Furthermore, the new model presented a basic framework of understanding the nature of major economic shifts, including the recent global recession of 2009, by studying the dynamic relationship between demand and supply.     

Modelling a dynamic market potential: A class of automata networks for diffusion of innovations

Innovation diffusion processes are generally described at aggregate level with models like the Bass Model (BM) and the Generalized Bass Model (GBM). However, the recognized importance of communication channels between agents has recently suggested the use of agent-based models, like Cellular Automata. We argue that an adoption or purchase process is nested in a communication network that evolves dynamically and indirectly generates a latent non-constant market potential affecting the adoption phase.Using Cellular Automata we propose a two-stage model of an innovation diffusion process. First we describe a communication network, an Automata Network, necessary for the “awareness” of an innovation. Then, we model a nested process depicting the proper purchase dynamics. Through a mean field approximation we propose a continuous representation of the discrete time equations derived by our nested two-stage model. This constitutes a special non-autonomous Riccati equation, not yet described in well-known international catalogues. The main results refer to the closed form solution that includes a general dynamic market potential and to the corresponding statistical analysis for identification and inference. We discuss an application to the diffusion of a new pharmaceutical drug.     

A technology replacement model with variable market potential — An empirical study of CRT and LCD TV

The rapidly changing economic environment and increasingly fierce competition indicate that companies must innovate in both their products and marketing strategies if they are to continue to flourish. Specifically, the ability to accurately predict the demand for products is crucial when firms decide to allocate their resources, especially in the fast moving high technology industries, where there is very high investment in R&D and production facilities. This study establishes a forecast model for technology replacement based on the diffusion model with population growth used for the variable market potential. The proposed model is then applied to investigate the CRT and LCD TV market.The results suggest that the new model is more accurate than the constant market potential model in fitting and forecasting performance. Consumers who purchase a TV for the first time are likely more attracted to LCD TV rather than CRT TV. As for those individuals who already own a CRT TV, the attraction is not strong enough to encourage them to replace their current CRT TV with a new LCD TV. Moreover, it is noted that the falling price of LCD TV is an essential factor in encouraging purchases.     

Ecological and economic sustainability in fishery management: A multi-agent model for understanding competition and cooperation

Recent studies have shown that many marine ecosystems are experiencing an accelerating loss of population and biodiversity. It is apparent that there is a growing disparity between the available supply of fish and the desire of the growing world population to catch them. Although studies have begun to question the ecological sustainability of managed fishery systems, they often omit the corresponding effects on the economic sustainability of fishery industries. This is particularly important in rural coastal areas where the fishing industry is often a dominant employer. In this article, we analyze the interactions between economic and ecological dynamic systems using a multi-agent dynamic model of fishery management. Multiple agents (fishers) harvest multiple fish species and adapt the amount and allocation of their effort to their value functions, which are given as net profits of the fish harvest sold for a market price. This is largely unique in fishery models, since many econometric studies view fishers as represented by homogenous ‘average’ agents. We introduce and compare two different decision rules governing the behavior of fishers engaged in a competitive market. We demonstrate a situation where both behaviors lead to a decline of all fish stocks, as well as profits for most fishers. As an alternative, we introduce a cooperative approach in which fisheries jointly set sustainable limits for total harvest and effort that are then distributed to the fishers according to distribution rules. The simulation reveals that fish stocks and profits can stabilize at significantly higher levels in the cooperative case, leading to a continuous accumulation of capital for all fishers. This model demonstrates key aspects of overfishing conflicts that can be overcome through planned fishing quotas and cooperative market mechanisms. It also demonstrates a novel approach for simulating the dynamic behavior of heterogeneous fishers.     

A grey dynamic model for the evaluation of regional sustainable development and its emoirical study

Currently,traditional development issues,such as economic stagnation,as well as new challenges like environmental degradation and globalization,need attention.Sustainable development,including economic,environmental,and social elements,is a main goal of decision-makers.The key to sustainable decision-making is to evaluate and forecast the status quo of sustainable development.Policy makers need a tool based on scientific information to forecast the effects of future actions on sustainability and make policies for sustainable development.This paper analyzes the relation of the economy,environment and social welfare by the grey dynamic model.The proposed method use time series and basic indicators of ecological system,including economic,environmental and social sub-systems.It is applied to Heilongfiang Province and Jiangsu Province.The results have proved different status quo of sustainable development in these two regions,and suggestions are proposed,such as optimization of industrial structure and eco-industrial development.The conclusion is that there is no unique sustainable path,and accordingly,policy makers shouM choose different criteria and strategies to make efficient sustainable decisions for each region.     

A grey dynamic model for the evaluation of regional sustainable development and its empirical study

Currently, traditional development issues, such as economic stagnation, as well as new challenges like environmental degradation and globalization, need attention. Sustainable development, including economic, environmental, and social elements, is a main goal of decision-makers. The key to sustainable decision-making is to evaluate and forecast the status quo of sustainable development. Policy makers need a tool based on scientific information to forecast the effects of future actions on sustainability and make policies for sustainable development. This paper analyzes the relation of the economy, environment and social welfare by the grey dynamic model. The proposed method uses time series and basic indicators of ecological system, including economic, environmental and social sub-systems. It is applied to Heilongjiang Province and Jiangsu Province. The results have proved different status quo of sustainable development in these two regions, and suggestions are proposed, such as optimization of industrial structure and eco-industrial development. The conclusion is that there is no unique sustainable path, and accordingly, policy makers should choose different criteria and strategies to make efficient sustainable decisions for each region.     

A dynamic CGE model for jointly accounting ageing population,automation and environmental tax reform. European Union as a case study

We develop a dynamic Computable General Equilibrium model based on the combination of different versions of GTAP utilities where alternative scenarios on ageing population trends are combined with projections on the incidence of automation into production processes and the adoption of unilateral decarbonisation policies. By simultaneously controlling for these different challenges that especially developed countries should face in the next decades, it is possible to disentangle non-linear mechanisms that will influence sustainability of public budget when the three issues are jointly combined. The European Union is taken as a case study. The first result is that ageing trends will impact fiscal sustainability reducing the EU capacity to respect the Stability and Growth Pact parameters. Second, when also considering technical change related to automation and robotics in the production process, fiscal sustainability will improve only in the case of input-neutral technological change. On the contrary, if biased technical change produces unemployment impact, negative impacts of ageing population are reinforced by automation. Third, the adoption of an environmental tax, here modelled in the form of a carbon price, leads to an improvement in environmental sustainability but has non-linear effects of fiscal sustainability.