Coopetition of software firms in Open source software ecosystems

Software firms participate in an ecosystem as a part of their innovation strategy to extend value creation beyond the firms boundary. Participation in an open and independent environment also implies the competition among firms with similar business models and targeted markets. Hence, firms need to consider potential opportunities and challenges upfront. This study explores how software firms interact with others in OSS ecosystems from a coopetition perspective. We performed a quantitative and qualitative analysis of three OSS projects. Finding shows that software firms emphasize the co-creation of common value and partly react to the potential competitiveness on OSS ecosystems. Six themes about coopetition were identified, including spanning gatekeepers, securing communication, open-core sourcing and filtering shared code. Our work contributes to software engineering research with a rich description of coopetition in OSS ecosystems. Moreover, we also come up with several implications for software firms in pursing a harmony participation in OSS ecosystems.Comment: This is the author's version of the work. Copyright owner's version can be accessed at https://link.springer.com/chapter/10.1007/978-3-319-69191-6_10, Coopetition of software firms in Open source software ecosystems, 8th ICSOB 2017, Essen, Germany (2017

Oak Persistence in Mediterranean Landscapes: The Combined Role of Management, Topography, and Wildfires

Mediterranean ecosystems have been shaped by a history of human and ecological disturbances. Understanding the dynamics of these social-ecological systems requires an understanding of how human and ecological factors interact. In this study, we assess the combined role of management practices and biophysical variables, i.e., wildfire and topography, to explain patterns of tree persistence in a cork oak (Quercus suber L.) landscape of southern Portugal. We used face-to-face interviews with landowners to identify the management practices and the incentives that motivated them. We used aerial photographs and a Geographic Information System (GIS) to classify vegetation patch-type transitions over a period of 45 years (1958-2002) and logistic regression to explain such changes based on management and biophysical factors. The best model explaining vegetation transitions leading to cork oak persistence in the landscape included both biophysical and management variables. Tree persistence was more likely to occur on steeper slopes, in the absence of wildfires, and in the absence of understory management. We identified ecological, ideological, and economical barriers that preclude oak persistence and that are important to consider in implementing efficient environmental policies for adequate conservation and reforestation programs of Mediterranean cork oak landscape

Analyzing large-scale conservation interventions with Bayesian hierarchical models: a case study of supplementing threatened Pacific salmon.

Myriad human activities increasingly threaten the existence of many species. A variety of conservation interventions such as habitat restoration, protected areas, and captive breeding have been used to prevent extinctions. Evaluating the effectiveness of these interventions requires appropriate statistical methods, given the quantity and quality of available data. Historically, analysis of variance has been used with some form of predetermined before-after control-impact design to estimate the effects of large-scale experiments or conservation interventions. However, ad hoc retrospective study designs or the presence of random effects at multiple scales may preclude the use of these tools. We evaluated the effects of a large-scale supplementation program on the density of adult Chinook salmon Oncorhynchus tshawytscha from the Snake River basin in the northwestern United States currently listed under the U.S. Endangered Species Act. We analyzed 43 years of data from 22 populations, accounting for random effects across time and space using a form of Bayesian hierarchical time-series model common in analyses of financial markets. We found that varying degrees of supplementation over a period of 25 years increased the density of natural-origin adults, on average, by 0-8% relative to nonsupplementation years. Thirty-nine of the 43 year effects were at least two times larger in magnitude than the mean supplementation effect, suggesting common environmental variables play a more important role in driving interannual variability in adult density. Additional residual variation in density varied considerably across the region, but there was no systematic difference between supplemented and reference populations. Our results demonstrate the power of hierarchical Bayesian models to detect the diffuse effects of management interventions and to quantitatively describe the variability of intervention success. Nevertheless, our study could not address whether ecological factors (e.g., competition) were more important than genetic considerations (e.g., inbreeding depression) in determining the response to supplementation