Information and Rivalry: How Do Firms Respond to Competitors’ Investment Decision under Environmental Uncertainty? -- Evidence from the U.S. Electric Utility Companies’ Adoption of Solar Energy

Business: 3rd Place (The Ohio State University Edward F. Hayes Graduate Research Forum)A broad literature in strategy examines how competitors’ presence affects the focal firm’s strategic decision making. This stream of research identifies imitation and deterrence as two distinct patterns, and concludes with an inverted U-shaped relationship. Yet, we propose in this study that under environmental uncertainty competition could both strengthen and undermine the benefits of imitation, and consequently lead to a U-shaped relationship. Combining both information- and competition-based theories, we develop stylized models of how firms update their beliefs and make strategic decision under environmental uncertainty. The analytical results suggest a U-shaped relationship, and we find empirical evidence consistent with our predictions using data on the U.S. electric utility companies’ commitment to develop utility-scale solar projects.A five-year embargo was granted for this item

An effective cost distance calculation based on raster data model improved algorithm

<span class="MedBlackText">In many applications of geographic information science, we often need to calculate the shortest path from the source point to the target points. Network data model can be computed using the graph theory algorithm, when faced with raster data model, the grid cells of raster will be treated as network model nodes in general, and the eight neighborhood unit of each grid cell will be treated as the direct neighbor nodes in network model. Some scholars have pointed out that this algorithm which network model directly transplanted easily lead to the wrong direction in path finding and the high cumulative cost value problem, and gives the improved algorithm called wave spread cost distance algorithm. In this paper, we research and make experiments with the wave spread cost distance algorithm and then carried out further improvements, making the analysis of exception handling and the algorithm overall efficiency has been improved. </span

A Semipersistent Plant Virus Differentially Manipulates Feeding Behaviors of Different Sexes and Biotypes of Its Whitefly Vector.

It is known that plant viruses can change the performance of their vectors. However, there have been no reports on whether or how a semipersistent plant virus manipulates the feeding behaviors of its whitefly vectors. Cucurbit chlorotic yellows virus (CCYV) (genus Crinivirus, family Closteroviridae) is an emergent plant virus in many Asian countries and is transmitted specifically by B and Q biotypes of tobacco whitefly, Bemisia tabaci (Gennadius), in a semipersistent manner. In the present study, we used electrical penetration graph (EPG) technique to investigate the effect of CCYV on the feeding behaviors of B. tabaci. The results showed that CCYV altered feeding behaviors of both biotypes and sexes of B. tabaci with different degrees. CCYV had stronger effects on feeding behaviors of Q biotype than those of B biotype, by increasing duration of phloem salivation and sap ingestion, and could differentially manipulate feeding behaviors of males and females in both biotype whiteflies, with more phloem ingestion in Q biotype males and more non-phloem probing in B biotype males than their respective females. With regard to feeding behaviors related to virus transmission, these results indicated that, when carrying CCYV, B. tabaci Q biotype plays more roles than B biotype, and males make greater contribution than females

An effective algorithm for spatial query using spatial adaptive grid index filter

IEEE Geoscience and Remote Sensing Society (IEEE GRSS); East China Norm. Univ., Sch. Resour. Environ. Sci.; Shanghai Urban Dev. Inf. Res. Cent.; The Geographical Society of Shanghai; East China Univ. Sci. Technol., Bus. Sch.<span class="MedBlackText">Spatial query is the core function of GIS analysis, the query data is mostly geometric point, line, polygon which has the location information and formatted query condition is a variety of spatial relationships. We focus on the spatial query efficiency improvement with the query data in case of large and complex, and propos an effective spatial adaptive grid index filter algorithm for spatial query. It is different from the commonly used uniform grid index algorithm as it constructs the adaptive grid index of data using the spatial distribution information then it can radically improve the efficiency of spatial query. This algorithm contains four steps, including boundary grid index construction, internal grid index construction, primary spatial query and advanced spatial query. It is realized by C++ language and verified by experiments, the spatial query efficiency than the traditional uniform grid index algorithm has significantly increased.</span