Po-an Hsu

Exploring the Interaction Between Incubators and Industrial Clusters: The Case of the ITRI Incubator in Taiwan

This article aims to explore the interaction between incubators and industrial clusters, which is an important linkage for local development but has not been analyzed in the literature. A model is proposed to describe this interaction. The Industrial Technology Research Institute (ITRI) Incubator within the Hsinchu industrial cluster, the core of Taiwans technology industries, is considered to be an empirical case. This case is investigated with the proposed model and methods including data analysis, in-depth interviews, manager surveys and stakeholder analysis. It was found that the clustering effect in the Hsinchu industrial cluster is main factor in the ITRI Incubators development. The ITRI Incubator in turn reinforces the cluster in some aspects as feedback. This result confirms the existence and importance of this interaction in local development. It is recommended that government officials and incubator managers take account of this interaction in operating an incubator program and utilize the proposed model to analyze the incubators contributions to its industrial cluster.

A Litterman BVAR approach for production forecasting of technology industries

Abstract Forecasting the production of technology industries is important to entrepreneurs and governments, but usually suffers from market fluctuation and explosion. This paper aims to propose a Litterman Bayesian vector autoregression (LBVAR) model for production prediction based on the interaction of industrial clusters. Related industries within industrial clusters are included into the LBVAR model to provide more accurate predictions. The LBVAR model possesses the superiority of Bayesian statistics in small sample forecasting and holds the dynamic property of the vector autoregression (VAR) model. Two technology industries in Taiwan, the photonics industry and semiconductor industry are used to examine the LBVAR model using a rolling forecasting procedure. As a result, the LBVAR model was found to be capable of providing outstanding predictions for these two technology industries in comparison to the autoregression (AR) model and VAR model.

What Affects Innovation More: Policy or Policy Uncertainty?

Motivated by a theoretical model, we empirically examine for 43 countries whether it is policy or policy uncertainty that affects technological innovation more. We find that innovation, measured by growth in patent counts, citations, and originality, is not, on average, affected by which policy is in place. Innovation, however, drops significantly during times of policy uncertainty measured by national elections. To establish causality, we use close presidential elections, whose timings are pre-determined and results are unpredictable, and ethnic fractionalization that are likely exogenous to policy and policy uncertainty. Political compromise, our paper concludes, is a plus for innovation.

The role of innovation in inventory turnover performance

How a firm utilizes technological innovation to improve operations management is an important research question in todays knowledge economy but lacks empirical evidence in the literature. We use a dataset of all non-service U.S. public firms from 1976 to 2005 to examine how a firms innovation performance is associated with its inventory turnover performance. In particular, we measure a firms innovation performance by the ratio of its patents (either citations or counts) to its research and development (R&D) expenditure. Our fixed-effect panel regression results indicate a positive relation between innovation performance and inventory turnover ratio, and such a relation varies across industries. By differentiating process and product innovation according to patent usages, we find that process innovation has a consistent and long-lasting effect, whereas product innovation has an immediate but short-lasting effect. We also find supporting evidence for industry spillovers by showing that firms in a more innovative industry are likely to better manage their inventory performance. Our results confirm the benefit of using innovation in logistics and operations management and point to the strategic importance of integrating technology and operations management. We find a positive association between a firms inventory turnover and its innovation.Process innovation has a stronger and long-lasting effect than product innovation.Although older innovation has a weaker effect, industry heterogeneity may reverse it.Firms in an innovative industry are more likely to have a superior inventory performance.

Innovative Originality, Profitability, and Stock Returns

We propose that owing to limited investor attention and skepticism of complexity, firms with greater innovative originality (IO) will be undervalued, especially for firms with higher valuation uncertainty, lower attention, and greater sensitivity of future profitability to IO. We find that IO strongly positively predicts firms’ profitability and abnormal stock returns, especially among those firms suggested by the model. The return predictive power of IO is robust to extensive asset pricing controls, to an alternative IO measure, and across sample periods. Although we do not rule out risk-based explanations, the most plausible interpretation of the evidence is that the market undervalues IO.* We thank Vikas Agarwal, Bronson Argyle (WFA discussant), Nicholas Barberis, Geert Bekaert, Hui Chen, James Choi, Lauren Cohen, Zhi Da, Karl Diether (WFA discussant), Ming Dong, Bernard Dumas, Phil Dybvig, Thierry Foucault, Paolo Fulghieri, Pengjie Gao, Thomas George, William Goetzmann, Allaudeen Hameed, Valentin Haddad, Gerard Hoberg, Harrison Hong, Kewei Hou, Danling Jiang, Marcin Kacperczyk, Matti Keloharju, Praveen Kumar, Michael Lemmon, Jonathan Lewellen, Jay Li, Kai Li, Xu Li, Sonya Lim, Gustavo Manso, Stefan Nagel, Terrance Odean, Dimitris Papanikolaou, Gordon Phillips, Joshua Pollet, Richard Sias, Mark Schankerman, Tao Shu, Ken Singleton, Noah Stoffman, René Stulz, Avanidhar Subrahmanyam, Siew Hong Teoh, Sheridan Titman, Neng Wang, Xin Wang, Kelsey Wei, Kuo-chiang Wei, Wei Xiong, and seminar and conference participants at WFA (Seattle), CityU Finance Conference, HKUST, National University of Singapore, Singapore Management University, Southwestern University of Finance and Economics, University of Arizona, University of Houston, and University of Miami for helpful discussions, and the Don Beall Center for Innovation & Entrepreneurship for financial support.

Corporate Philanthropy, Research Networks, and Collaborative Innovation

Using a unique dataset of corporate philanthropy, we find that direct giving activities are positively associated with more collaborative and original innovation. In contrast, our results do not hold for corporate foundations’ contributions. Our results suggest that much of what is ostensibly promoted as philanthropy actually reflects research-related networking activities. The effect of direct giving on innovation is more pronounced in more opaque firms and more innovative and competitive industries. These findings provide evidence of the distinct motives by which firms choose between direct giving and foundation giving. This study suggests that firms can use direct philanthropy to expand firm-boundaries by developing innovation with research partners.

Innovation Strategy of Private Firms

We compare innovation strategies of public and private firms based on a large sample over the period 1997–2008. We find that public firms’ patents rely more on existing knowledge, are more exploitative, and are less likely in new technology classes, while private firms’ patents are broader in scope and more exploratory. We investigate whether these strategies are due to differences in firm information environments, CEO risk preferences, firm life cycles, corporate acquisition policies, or investment horizons between these two groups of firms. Our evidence suggests that the shorter investment horizon associated with public equity markets is a key explanatory factor.

The Real Effects of Real Earnings Management: Evidence from Innovation

We examine the consequences of real earnings management from an innovation perspective and investigate the patent output of firms likely to be managing earnings through altering their R&D expenditures. We find that R&D cuts related to earnings management lead to fewer patents, less influential patent output, and lower innovative efficiency compared to other R&D cuts. Our results thus suggest that real earnings management may obstruct firms’ technological progress and highlight the potential costs of managerial manipulation of R&D expenditures in order to alter reported earnings.

Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-Scale, Data-Snooping Robust Analysis of Technical Trading in the Foreign Exchange Market

We carry out a large-scale investigation of technical trading rules in the foreign exchange market, using daily data over a maximum of forty years for thirty developed and emerging market currencies. Employing a stepwise test to safeguard against data-snooping bias and examining over 21,000 technical trading rules, we find evidence of substantial predictability in both developed and emerging markets, measured against a variety of returns and risk-adjusted performance metrics. We present time-series and cross-sectional variation in sub-periods and cultural and/or geographic groups, respectively, suggesting that temporarily not-fully-rational behavior and market immaturity lead to technical predictability and potential profitability.

More Cash, Less Innovation: The Effect of the American Jobs Creation Act on Patent Value

Firms can become less innovative following a sudden “inflow” of cash. Specifically, multinational firms that were eligible to repatriate (and indeed repatriated) cash to the U.S. under the American Jobs Creation Act generate less valuable patents than otherwise similar firms. They also conduct more exploratory activities. This effect only exists among firms in less competitive industries, firms with lower institutional ownership, and firms with overconfident CEOs, and is mainly driven by the reduction in the value of U.S.-originated patents. Our evidence suggests that, without appropriate governance, a cash windfall may lead managers to engage in riskier innovation strategy that can destroy value.