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Single-vendor commercial open source software projects are open source software projects that are owned by a single firm that derives a direct and significant revenue stream from the software. Single-vendor commercial open source at first glance represents an economic paradox: How can a firm earn money if it is making its product available for free as open source? This paper presents the core properties of single-vendor open source business models and discusses how they work. Using a single-vendor open source approach, firms can get to market faster with a superior product at lower cost than possible for traditional competitors. The paper shows how these benefits accrue from an engaged and self-supporting user community. Lacking any prior comprehensive reference, this paper is based on an analysis of public statements by practitioners of single-vendor open source. It forges the various anecdotes into a coherent description of revenue generation strategies and relevant business functions.

This paper analyzes a software market consisting of a freely available open source software (OSS), the commercial version of this OSS (OSS-SS), and the competing commercial proprietary software (PS). We find that in software markets characterized by low direct network benefits, the PS vendor is better off in the presence of competition from OSS-SS. Furthermore, the OSS-SS vendor in these markets is better off by having lower usability than PS. Therefore, the PS vendor has little incentive to improve the usability of their software in these markets. On the other hand, in software markets characterized by high network benefits, a PS vendor is threatened by the presence of OSS-SS and can survive only if the PS is more usable than the competing OSS-SS.

Purpose: A growing number of commercial open source software, based on free open source software, appears in many segments of software market. The purpose of this study is to investigate how commercial open source software affects proprietary software producer's pricing (market share or profit), consumer surplus and social welfare. Design/methodology: To analyze the impact of commercial open source software on proprietary software producer, this study constructs two vertical-differentiation models: the basic model considers proprietary software only competing with free open source software, and its extended one considers proprietary software competing with both free and commercial open source software. Findings: This study mainly finds that the presence of commercial open source software leads to the software price and profit for proprietary software producer decrease and the consumer surplus and social welfare increase. However, it does not necessarily cause the decline in the market share for proprietary software producer. Originality/value: The main contribution of this study is to examine the effect of commercial open source software on proprietary software producer's competitive strategy, consumer surplus and social welfare.

In the last few decades, there has been a growing interest in studying non-contact methods for full-field displacement and strain measurement. Among such techniques, Digital Image Correlation (DIC) has received particular attention, thanks to its ability to provide these information by comparing digital images of a sample surface before and after deformation. The method is now commonly adopted in the field of civil, mechanical and aerospace engineering and different companies and some research groups implemented 2D and 3D DIC software. In this work a review on DIC software status is given at first. Moreover, a free and open source 2D DIC software is presented, named py2DIC and developed in Python at the Geodesy and Geomatics Division of DICEA of the University of Rome “La Sapienza”; its potentialities were evaluated by processing the images captured during tensile tests performed in the Structural Engineering Lab of the University of Rome “La Sapienza” and comparing them to those obtained using the commercial software Vic-2D developed by Correlated Solutions Inc, USA. The agreement of these results at one hundredth of millimetre level demonstrate the possibility to use this open source software as a valuable 2D DIC tool to measure full-field displacements on the investigated sample surface.

The principles of open collaboration for innovation (and production), once distinctive to open source software, are now found in many other ventures. Some of these ventures are Internet based: for example, Wikipedia and online communities. Others are off-line: they are found in medicine, science, and everyday life. Such ventures have been affecting traditional firms and may represent a new organizational form. Despite the impact of such ventures, their operating principles and performance are not well understood. Here we define open collaboration (OC), the underlying set of principles, and propose that it is a robust engine for innovation and production. First, we review multiple OC ventures and identify four defining principles. In all instances, participants create goods and services of economic value, they exchange and reuse each other’s work, they labor purposefully with just loose coordination, and they permit anyone to contribute and consume. These principles distinguish OC from other organizational forms, such as firms or cooperatives. Next, we turn to performance. To understand the performance of OC, we develop a computational model, combining innovation theory with recent evidence on human cooperation. We identify and investigate three elements that affect performance: the cooperativeness of participants, the diversity of their needs, and the degree to which the goods are rival (subtractable). Through computational experiments, we find that OC performs well even in seemingly harsh environments: when cooperators are a minority, free riders are present, diversity is lacking, or goods are rival. We conclude that OC is viable and likely to expand into new domains. The findings also inform the discussion on new organizational forms, collaborative and communal.

OpenHSI is an initiative to lower the barriers of entry and bring compact pushbroom hyperspectral imaging spectrometers to a wider audience. We present an open-source optical design that can be replicated with readily available commercial-off-the-shelf components, and an open-source software platform openhsi that simplifies the process of capturing calibrated hyperspectral datacubes. Some of the features that the software stack provides include: an ISO 19115-2 metadata editor, wavelength calibration, a fast smile correction method, radiance conversion, atmospheric correction using 6SV (an open-source radiative transfer code), and empirical line calibration. A pipeline was developed to customise the desired processing and make openhsi practical for real-time use. We used the OpenHSI optical design and software stack successfully in the field and verified the performance using calibration tarpaulins. By providing all the tools needed to collect documented hyperspectral datasets, our work empowers practitioners who may not have the financial or technical capability to operate commercial hyperspectral imagers, and opens the door for applications in new problem domains.

Open Source Software (OSS) has become an increasingly important knowledge asset in modern economies. However, the economic impact of OSS on countries’ GDP is ambivalent due to its public good character. Using a cross-country panel from 2000 to 2018, including 25 of the largest EU countries plus the USA, Japan, Korea, Canada, China, Norway, and Switzerland, matching OSS commits to GitHub to macroeconomic data provided by the OECD, our results confirm the dual nature of OSS. On the one hand, the open-access character creates great learning potential by providing a commonly accessible productive resource for all countries. On the other hand, it creates outward-directed spillovers associated with own OSS contributions. Accordingly, on average, we find that countries experience an increase in GDP when the world stock of OSS grows. However, smaller countries experience a decline in GDP resulting from their own contributions due to knowledge spillovers. The net effect is nonetheless positive. If no country contributed to OSS development, GDP for the average country would be 2.2% lower in the long run. Moreover, the losses associated with unintended spillovers are lower for countries with a higher R&D and patenting intensity. Based on our findings, we derive implications for policies and regulations concerning OSS.

Human–Wildlife Conflict (HWC) is an increasing challenge in rapidly changing landscapes, where agricultural expansion, settlement growth, and infrastructure development intersect with critical wildlife corridors. Addressing these conflicts requires spatially explicit methods that can evaluate trade-offs among competing land uses. This study demonstrates the application of the open-source Land Use Conflict Identification Strategy (Open-LUCIS), a suitability-based framework that integrates open geospatial data, domain knowledge, and goal-driven land-use modeling. Using Pandamatenga in Botswana’s Chobe District as a case study, we identified areas of potential conflict among agriculture, human settlement, and wildlife conservation. High-conflict zones were concentrated where commercial farms overlap with transboundary wildlife corridors, highlighting the tension between agricultural development and conservation. A sensitivity analysis indicated that existing land use, road accessibility, and development constraints strongly influence conflict dynamics. The application demonstrates a clear pathway for using open-source tools to support HWC studies. By relying on open data and reproducible methods, Open-LUCIS offers a cost-effective and accessible alternative to proprietary software, with direct implications for advancing sustainable land development in regions with limited resources. Given that the dynamics observed in Chobe reflect pressures common across many parts of Africa and beyond, the framework is broadly applicable as a transferable approach for managing land-use conflicts in many rapidly developing, ecologically sensitive frontiers worldwide.

Monitoring sea level is critical due to climate change observed over the years. Global Navigation Satellite System Reflectometry (GNSS-R) has been widely demonstrated for coastal sea-level monitoring. The use of signal-to-noise ratio (SNR) observations from ground-based stations has been especially productive for altimetry applications. SNR records an interference pattern whose oscillation frequency allows retrieving the unknown reflector height. Here we report the development and validation of a complete hardware and software system for SNR-based GNSS-R. We make it available as open source based on the Arduino platform. It costs about US$200 (including solar power supply) and requires minimal assembly of commercial off-the-shelf components. As an initial validation towards applications in coastal regions, we have evaluated the system over approximately 1 year by the Guaíba Lake in Brazil. We have compared water-level altimetry retrievals with independent measurements from a co-located radar tide gauge (within 10 m). The GNSS-R device ran practically uninterruptedly, while the reference radar gauge suffered two malfunctioning periods, resulting in gaps lasting for 44 and 38 days. The stability of GNSS-R altimetry results enabled the detection of miscalibration steps (10 cm and 15 cm) inadvertently introduced in the radar gauge after it underwent maintenance. Excluding the radar gaps and its malfunctioning periods (reducing the time series duration from 317 to 147 days), we have found a correlation of 0.989 and RMSE of 2.9 cm in daily means. To foster open science and lower the barriers for entry in SNR-based GNSS-R research and applications, we make a complete bill of materials and build tutorials freely available on the Internet so that interested researchers can replicate the system.

User innovation lies at the core of a growing body of research, with a predominant focus on how individual user attributes can be associated with observed contributions to innovation. However, framing user innovation in terms of individual attributes risks neglecting important changes in behavior at the individual and community level over time. Here, our focus is on how the time that individual users spend in that community relates to innovation outcomes. We study innovation in a firm-hosted online user community for a 3D printer company, marked by their commitment to open-source hardware. We analyze a unique longitudinal dataset of 38,277 observations recording user posts to an open-access user forum from October 2011 to March 2015. We find that time spent in a user community is positively associated with contributions to innovation, as users migrate from identifying problems and needs, to contributing innovation-related modifications and hacks. Our finding emphasizes the value of user retention in open-source communities as our analysis shows that typical users can add value to firms’ innovation activities over time. Our focus on open-hardware complements many existing studies on open-source software and advances our understanding of open innovation more generally.