Open Source vs Closed Source Software: Public Policies in the Software Market

This paper analyses the impact of public policies supporting open source software (OSS). Users can be divided between those who know about the existence of OSS, the "informed" adopters, and the "uninformed" ones; the presence of uniformed users yields to market failures that justify government intervention. We study three policies: i) mandatory adoption, when government forces public agencies, schools and universities to adopt OSS, ii) information campaign, when the government informs the uninformed users about the existence and the characteristics of OSS and, iii) subsidisation, when consumers are payed a subsidy when adopting OSS. We show that the second policy enhances welfare, the third is always welfare decreasing while mandatory adoption can be either good or bad for society depending on the number of informed and uninformed adopters. We extend the model to the presence of network effects and we show that strong externalities require "drastic" policies.software market, open source software, mandatory adoption, information campaign, subsidisation, network externalities

How open is open source: Software and beyond

Traditionally the protection of intellectual property is regarded as a precondition for value capture. The rise of open source (OS) software and OS tangible products, so-called open design, has challenged this understanding. Openness is often regarded as a dichotomous variable (open-source vs. closed-source) and it is assumed that online developer communities demand full opening of the product's source. In this paper we explore openness as a gradual and multi-dimensional concept. We conduct an Internet survey (N = 270) among participants of 20 open design communities in the domain of IT hardware and consumer electronics. We find that open design projects pursue complex strategies short of complete openness and that communities value openness of software more highly than openness of hardware. Our findings suggest that open design companies can successfully employ strategies of partial openness to safeguard value capture without alienating their developer community. --

Mixed Source

We study competitive interaction between profit-maximizing firms that sell software and complementary goods or services. In addition to tactical price competition, we allow firms to compete through business model reconfigurations. We consider three business models: the proprietary model (where all software modules offered by the firm are proprietary), the open source model (where all modules are open source), and the mixed source model (where a few modules are open). When a firm opens one of its modules, users can access and improve the source code. At the same time, however, opening a module sets up an open source (free) competitor. This hampers the firm's ability to capture value. We analyze three competitive situations: monopoly, commercial firm vs. non-profit open source project, and duopoly. We show that: (i ) firms may become 'more closed' in response to competition from an outside open source project; (ii ) firms are more likely to open substitute, rather than complementary, modules to existing open source projects; (iii) when the products of two competing firms are similar in quality, firms differentiate through choosing different business models; and (iv ) low-quality firms are generally more prone to opening some of their technologies than rms with high-quality products

Quality Competition or Quality Cooperation? License-Type and the Strategic Nature of Open Source vs. Closed Source Business Models

In the ICT sector, product-software is an important factor for the quality of the products (e.g. cell phones). In this context, open source software enables firms to avoid quality competition as they can cooperate on quality without an explicit contract. The economics of open source (OS) versus closed source (CS) business models are analyzed in a general two- stage model that combines aspects of non-cooperative R&D with the theory of differentiated oligopolies: In stage one, firms develop software, either as OS or CS, or as a an OS-CS-mix if the license allows. In stage two, firms bundle this with complementary products and compete à la Cournot. The model allows for horizontal product differentiation in stage two. The finding are: 1.) While CS-decisions are always strategic substitutes, OS-decisions can be strategic complements. Furthermore, CS is a strategic substitute to OS and vice versa. 2.) The type of OS-license plays a crucial role: only if the license prohibits a direct OS-CS code mix (like the GPL), then Nash-equilibria with firms producing OS code exist for all parameters. 3.) In the equilibrium of a mixed industry with restricted licenses, OS-firms offer lower quality than their CS-rivals.open source, commercial open source, Cournot, R&D

Dependency management bots in open-source systems—prevalence and adoption

Bots have become active contributors in maintaining open-source repositories. However, the definitions of bot activity in open-source software vary from a more lenient stance encompassing every non-human contributions vs frameworks that cover contributions from tools that have autonomy or human-like traits (i.e., Devbots). Understanding which of those definitions are being used is essential to enable (i) reliable sampling of bots and (ii) fair comparison of their practical impact in, e.g., developers’ productivity. This paper reports on an empirical study composed of both quantitative and qualitative analysis of bot activity. By analysing those two bot definitions in an existing dataset of bot commits, we see that only 10 out of 54 listed tools (mainly dependency management) comply with the characteristics of Devbots. Moreover, five of those Devbots have similar patterns of contributions over 93 projects, such as similar proportions of merged pull-requests and days until issues are closed. Our analysis also reveals that most projects (77%) experiment with more than one bot before deciding to adopt or switch between bots. In fact, a thematic analysis of developers’ comments in those projects reveal factors driving the discussions about Devbot adoption or removal, such as the impact of the generated noise and the needed adaptation in development practices within the project

Openness of Innovation in Services and Software - Essays on Service Innovations, Open Source, and Hybrid Licensing Models

Open Innovation—and Open Source as its particular manifestation in the software industry—have recently been touted as cornerstones of competitiveness for firms in the new service economy and of value added by public institutions involved in the gathering, processing and publishing of information. Although the basic concepts are by no means new, a considerable surge in research literature has occurred over the past decade around the keywords of open source, open innovation, value co-creation and both innovation in general and service innovation in particular. Putting breakthrough inventions aside, I consider what exactly open innovation means: What qualifies as an innovation and how is it different from the plain old product or service development? Is open inherently better than closed, and what exactly is the difference between the two? What middle ground is there, if any? Services growing in importance, is open innovation in (software) services different from (open) innovation in software products? Besides, is there any real difference between software services and software products? Particularly, what is the role of customers in that extended open community around the firm? What is the value that they see vs. the value that the firm sees? In the four research publications in Part II of this dissertation, I am addressing these questions in more detail in various contexts: both from a purely software development and software business perspective and from a more general service development and innovation perspective. The four publications have more specific research questions and detailed implications, in addition to contributing to the general themes outlined above. They elaborate on the following topics: Different perspectives to value co-creation in services and the customer/supplier value construct; Roles of customers in service innovation activities in standardised services with transactional intent; The effect of adoption of open-source tools within a commercial for-profit organisation on the organisational structure itself; and Hybrid open-closed software licensing model as a platform for reverting from commoditised product business to higher-value customer relationships. Beyond the theoretical and practical contributions of the publications in Part II, Part I of this dissertation offers a robust definition of innovation in general as well as a more defendable view of the nature of services vs. goods. In addition it clarifies what the term product means in relation to both services and goods as well as in the software industry—a topic that often causes confusion among academics and practitioners

L-Eval: Instituting Standardized Evaluation for Long Context Language Models

Recently, there has been growing interest in extending the context length of instruction-following models in order to effectively process single-turn long input (e.g. summarizing a paper) and conversations with more extensive histories. While proprietary models such as GPT-4 and Claude have demonstrated considerable advancements in handling tens of thousands of tokens of context, open-sourced models are still in the early stages of experimentation. It also remains unclear whether developing these long context models can offer substantial gains on practical downstream tasks over retrieval-based methods or models simply trained on chunked contexts. To address this challenge, we propose to institute standardized evaluation for long context language models. Concretely, we develop L-Eval which contains 411 long documents and over 2,000 query-response pairs manually annotated and checked by the authors encompassing areas such as law, finance, school lectures, lengthy conversations, news, long-form novels, and meetings. L-Eval also adopts diverse evaluation methods and instruction styles, enabling a more reliable assessment of Long Context Language Models (LCLMs). Our findings indicate that while open-source models typically lag behind their commercial counterparts, they still exhibit impressive performance. LLaMA2 achieves the best results (win 45\% vs turbo-16k) on open-ended tasks with only 4k context length and ChatGLM2 achieves the best results on closed-ended tasks with 8k input tokens. We release our new evaluation suite, code, and all generation results including predictions from all open-sourced LCLMs, GPT4-32k, Cluade-100k at {\url{https://github.com/OpenLMLab/LEval}}

The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.Peer reviewe