Simulating the adoption of fuel cell vehicles

Supply security and environmental concerns associated with oil call for an introduction of hydrogen as a transport fuel. To date, scenario studies of infrastructure build-up and sales of fuel cell vehicles (FCVs) are driven by cost estimates and technological feasibility assumptions, indicating that there is a “chicken and egg problem”: Car producers do not offer FCVs as long as there are no hydrogen filling stations, and infrastructure will not be set up unless there is a significant number of FCVs on the road. This diffusion barrier is often used as an argument for a major (public) infrastructure program, neglecting the fact that the automobile market is highly competitive and car producers, consumers, and filling station operators form an interdependent dynamic system, where taxes influence technology choice. In this paper, an agent-based model is used that captures the main interdependencies to simulate possible diffusion paths of FCVs. The results suggest that a tax on conventional cars can successfully promote diffusion even without a major infrastructure program. However, consumers and individual producers are affected differently by the tax, indicating that differently strong resistance towards such a policy can be anticipated. Moreover, there is evidence that some producers might benefit from cooperation with filling station operators to generate a faster build-up of infrastructure.

Is China uniform? Intra-country differences in the takeoff of new products

Multi-national corporations (wrongly) introduce new products in China rather late. Such a strategy arises because research treats all of China as one monolithic country, thus, finding that takeoff occurs quite late. However, for large or multi-ethnic countries, intra country diversity may be quite high, rivaling or exceeding that among inter country differences of some continents (e.g., Europe). This study examines the takeoff of new products among provinces of China based on data of 30 Chinese provinces on 10 categories over 34 years. Rooted in the theory of institutions and product network externalities, this study tests the drivers of new product takeoff using a discrete time hazard model. The major results are as follows: First, time to takeoff varies dramatically across provinces in China. Second, the average time to takeoff varies substantially between products with strong and weak network externalities. Third, time to takeoff is converging across provinces. Fourth, the intra-country differences in time-to-takeoff are explained by economic institutional variables: economic wealth, trade openness, education, media and transportation infrastructure; and product characteristics: network externalities and year of introduction. Fifth, the vast differences in takeoff of new products across provinces suggest that a waterfall strategy within China might be more profitable.     

Diffusion of multi-generational high-technology products

Previous multi-generational product diffusion (MGPD) models were developed based on the diffusion patterns at that time, but may not be adopted in today's cases. By incorporating the effect of customers' forward-looking behaviour, this paper offers a parsimonious and original model that captures the dynamics of MGPD in current high-technology markets. We empirically examine the feasibility of using previous MGPD models and our suggested model to explain the market growth of new products from high-technology industries. The results show that the new model exhibits better curve fitting and forecasting performance than the prior MGPD models in the cases of this study. For marketing researchers, our model and its results suggest customers' forward looking behaviour is perhaps one of the key sales affecting factors that are missing in previous MGPD models in explaining nowadays' cases. For marketing practitioners, this study offers a valuable tool for marketing strategies in high-tech industries.     

The challenges of pre-launch forecasting of adoption time series for new durable products

The successful introduction of new durable products plays an important part in helping companies to stay ahead of their competitors. Decisions relating to these products can be improved by the availability of reliable pre-launch forecasts of their adoption time series. However, producing such forecasts is a difficult, complex and challenging task, mainly because of the non-availability of past time series data relating to the product, and the multiple factors that can affect adoptions, such as customer heterogeneity, macroeconomic conditions following the product launch, and technological developments which may lead to the product’s premature obsolescence. This paper provides a critical review of the literature to examine what it can tell us about the relative effectiveness of three fundamental approaches to filling the data void : (i) management judgment, (ii) the analysis of judgments by potential customers, and (iii) formal models of the diffusion process. It then shows that the task of producing pre-launch time series forecasts of adoption levels involves a set of sub-tasks, which all involve either quantitative estimation or choice, and argues that the different natures of these tasks mean that the forecasts are unlikely to be accurate if a single method is employed. Nevertheless, formal models should be at the core of the forecasting process, rather than unstructured judgment. Gaps in the literature are identified, and the paper concludes by suggesting a research agenda so as to indicate where future research efforts might be employed most profitably.     

The clash of managerial and professional logics in public procurement: Implications for innovation in the health-care sector

This article addresses the enactment of public procurement and its influence on adoption and diffusion of innovation, using a case study of public procurement of a low-tech medical device innovation in Swedish healthcare. Based on interviews and documentation, the article illustrates the various perspectives of the different professions involved in the complex task of setting the requirement specification for the tender. The technology identities of the medical device (innovation) are constructed and negotiated by the actors: procurement administrators, health-care professionals and suppliers within the adoption space. Examining the enactment of the procurement process as part of the adoption space is a way to deepen our understanding of the social component within public procurement.     

Understanding the diffusion of public bikesharing systems: evidence from Europe and North America

Since the mid-2000s, public bikesharing (also known as “bike hire”) has developed and spread into a new form of mobility in cities across the globe. This paper presents an analysis of the recent increase in the number of public bikesharing systems. Bikesharing is the shared use of a bicycle fleet, which is accessible to the public and serves as a form of public transportation. The initial system designs were pioneered in Europe and, after a series of technological innovations, appear to have matured into a system experiencing widespread adoption. There are also signs that the policy of public bikesharing systems is transferable and is being adopted in other contexts outside Europe. In public policy, the technologies that are transferred can be policies, technologies, ideals or systems. This paper seeks to describe the nature of these systems, how they have spread in time and space, how they have matured in different contexts, and why they have been adopted.Researchers provide an analysis from Europe and North America. The analysis draws on published data sources, a survey of 19 systems, and interviews with 12 decision-makers in Europe and 14 decision-makers in North America. The data are examined through the lens of diffusion theory, which allows for comparison of the adoption process in different contexts. A mixture of quantitative and qualitative analyses is used to explore the reasons for adoption decisions in different cities. The paper concludes that Europe is still in a major adoption process with new systems emerging and growth in some existing systems, although some geographic areas have adopted alternative solutions. Private sector operators have also been important entrepreneurs in a European context, which has accelerated the uptake of these systems. In North America, the adoption process is at an earlier stage and is gaining momentum, but signs also suggest the growing importance of entrepreneurs in North America with respect to technology and business models. There is evidence to suggest that the policy adoption processes have been inspired by successful systems in Paris, Lyon, Montreal, and Washington, DC, for instance, and that diffusion theory could be useful in understanding public bikesharing policy adoption in a global context.     

Forecasting economic time series using targeted predictors

This paper studies two refinements to the method of factor forecasting. First, we consider the method of quadratic principal components that allows the link function between the predictors and the factors to be non-linear. Second, the factors used in the forecasting equation are estimated in a way to take into account that the goal is to forecast a specific series. This is accomplished by applying the method of principal components to ‘targeted predictors’ selected using hard and soft thresholding rules. Our three main findings can be summarized as follows. First, we find improvements at all forecast horizons over the current diffusion index forecasts by estimating the factors using fewer but informative predictors. Allowing for non-linearity often leads to additional gains. Second, forecasting the volatile one month ahead inflation warrants a high degree of targeting to screen out the noisy predictors. A handful of variables, notably relating to housing starts and interest rates, are found to have systematic predictive power for inflation at all horizons. Third, the targeted predictors selected by both soft and hard thresholding changes with the forecast horizon and the sample period. Holding the set of predictors fixed as is the current practice of factor forecasting is unnecessarily restrictive.     

Management fads and information delays: An exploratory simulation study

Management fads seem omnipresent. Adoption research that focuses on the uptake of change says little about subsequent abandonment behaviors. In this paper a simulation model is developed that extends adoption and diffusion models to consider abandonment from a dynamic perspective. Analysis of the simulation results leads to the conclusion that incomplete information and bandwagon effects can lead to fad-like behaviors.     

会计信息传播系统及其优化

本文论述了会计信息传播系统及其优化问题。笔者认为会计信息传播系统的传播过程主要由信源、信宿、传播内容、信道、反馈五个要素构成,为此,优化会计信息传播系统,就必须严把信源关、建立合理畅通的信息传播渠道和积极培育会计信息市场。     

Patent and publishing activity sequence over a technology's life cycle

The use of multiple indicators in analyzing technological developments and exploiting the increasing availability of information has been recommended widely in order to decrease systematic biases between single measures. One of the few frameworks that take multiple sources into account is the Technology Life Cycle indicators that provide a measure for the totality of sources available for analysis and take their timeliness into account, although the linear model that the framework represents is often questioned. The aim of this paper is to provide bibliometric studies with insight into the timely relevance of using different databases. To assess the reporting sequence between different databases, this paper measures the reporting activity of three case technologies in different databases and analyzes the yearly reporting volumes of a number of items that mention the technology in the databases as suggested by the TLC indicators. The results of this paper suggest that, when science is the source of new ideas and the driver for technological development and innovations, communication can happen in the order suggested by the TLC indicators. However, this model does not seem to be a general model for detecting and forecasting a technological life cycle. In addition, the results of the paper point to the possibility of studying non-linear models of innovation and contexts where this type of dynamics might take place.