Beating the odds in the innovation arena: The role of market and technology signals classification and noise

Innovation is a risky business. Notwithstanding the attention in research on the determinants of innovation success, the estimates of the extremely high failure rates (ranging from 40% to 90%) have not come down. As a result, new approaches have to be found to address the issues that prevent organizations from reaching innovation success over a longer period of time. In this study, Signal Detection Theory (SDT) is introduced to show that it may be less important to improve innovation practices in companies, than it is to change the nature of the projects that enter the corporate innovation funnel. In our empirical study of 44 innovation projects in the pharmaceutical and electronics industry, we show that pursuing more noisy signals (uncertain technological and market opportunities) is currently beneficial for innovation success. In general, companies allocate too few resources to noisy innovation opportunities. Interestingly, we find a positive, and not an inverted U-shaped, relationship between noise/signal ratios and innovation success. This indicates that there are almost no companies that take too much risk in the current competitive environment and that many can gain from increasing their noise tolerance. The implications from this study are quite counter-intuitive in a sense that ‘risk’ is not the cause of the innovation problems, but may be a solution.     

Estimating Medicaid prenatal case management costs: the provider's perspective

Many states are faced with Medicaid fiscal constraints; therefore, reimbursable versus un-reimbursable program costs must be clearly delineated. This study demonstrates a method to measure costs for Medicaid prenatal case management.     

A hybrid selection model for emerging technology

Technology selection, which influences the advantages of an enterprise or a country, is a multi-criteria decision issue that can be improved by integrating different methods. In addition, it is more and more difficult to identify the right technologies because the technologies are increasing in number and complexity. This study proposes a technology selection process integrating fuzzy Delphi method, analytic hierarchy process (AHP), and patent co-citation approach (PCA) for technology selection. The former effectively gathers experts' judgments toward technology selection criteria and conducts the fuzziness existing in their responses. The analytic hierarchy process has the strength of identifying criteria and obtaining their relationship and their weights. The patent co-citation approach identifies the major R&D fields of a specific technology from patent data. Through this proposed process, the key technology fields can be identified in the end. The organic light emitting diode (OLED) technology in Taiwan is used to be an example to illustrate the proposed technology selection process.     

Knowledge Management Tools, Inter-Organizational Relationships, Innovation and Firm Performance

The business value of information technology is an enduring research question. This research provides new insights to better understand the mechanisms supporting this relation by analyzing the impact of knowledge management tools (KMTs) on the performances of business units involved in inter-firm collaborative innovation projects. We extend current literature by developing and empirically testing a model where: (1) the use of KMTs is affected by critical organizational variables, (2) KMTs can impact the innovation and financial performances of business units. We find that mutual trust and culture for change do not affect the extent of the use of KMTs, while collaborative experience and naturalness in using ICTs as substitutive of face-to-face contacts have a significant impact. Moreover, we show that a more intense use of KMTs has a direct positive effect on new product performance and speed to market, as well as on financial performance. Yet, only new product performance acts as an indirect conduit linking KMT use and financial performances. This article provides a discussion and perspectives of further research concerning the impact of KMTs on innovation practices in inter-firm collaborative environments.     

Quantitative mapping of scientific research—The case of electrical conducting polymer nanocomposite

This study aims to understand knowledge structure both quantitatively and visually by integrating keyword analysis and social network analysis of scientific papers. The methodology proposed in this study is capable of creating a three-dimensional “Research focus parallelship network” and a “Keyword Co-occurrence Network”, together with a two-dimensional knowledge map. The network and knowledge map can be depicted differently by choosing different information for the network actor, i.e. country, institute, paper and keyword, to reflect knowledge structures from macro, to meso, to micro-levels. A total of 223 highly cited papers published by 142 institutes and 26 countries are analyzed in this study. China and the US are the two countries located at the core of knowledge structure and China is ranked no. 1. This quantitative exploration provides a way to unveil important or emerging components in scientific development and also to visualize knowledge; thus an objective evaluation of scientific research is possible for quantitative technology management.