文献类型：期刊文献

英文题名：Coping with Uncertainties in Technological Learning

作者：Ma, Tieju[1]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China

年份：2010

卷号：56

期号：1

起止页码：192

外文期刊名：MANAGEMENT SCIENCE

收录：;EI(收录号：20100412665428);WOS:【SSCI(收录号:WOS:000273588400014)，SCI-EXPANDED(收录号:WOS:000273588400014)】；

基金：This research was sponsored by the Shanghai Shuguang Project (08SG30), the Shanghai Pujiang Project, and the National Nature Science Foundation of China (70901026). The author appreciates the help of Mary Ann Mooradian in reading the manuscript.

语种：英文

外文关键词：endogenous technological change model; uncertainty; risk-constrained optimization

摘要：To date, optimization models of endogenous technological change commonly deal with uncertainty in technological learning with risk-factor methods, i.e., by adding expected risk costs resulting from overestimating technological learning rates into an objective function with a subjective risk factor. This paper argues that another way of coping with the uncertainty, risk-constrained methods that have been ignored in existing literatures, could be more practicable (at least as a supplement) for decision support. With a simplified model, this paper explores technology development paths generated by two risk-constrained methods, and compares the two risk-constrained methods with a risk-factor method. Our study shows that comparing with the risk-factor method, the two risk-constrained methods also generate an S-shaped technology diffusion pattern, which accords with historical observations, and they can result in earlier as well as later adoption of an advanced but currently expensive technology, depending on different combinations of uncertainty levels of the technology learning rate and the upper limit on the expected risk cost. Another finding of our research is that two totally different technology development paths can both be optimal solutions, which implies that with early policy interventions there is the possibility that an economy could be led to a low-carbon economy with little additional cost.