Learning from Winners: A Strategic Perspective of Improving Freelancers’ Bidding Competitiveness in Crowdsourcing

The rapid growth of crowdsourcing grants freelancers unprecedented opportunities to materialize their expertise by bidding in specific tasks. Despite lowering freelancers’ participation costs, the bidding mechanism meanwhile induces intense competition, rendering it difficult for freelancers to submit competitive bids. Although previous research has disentangled several bidding strategies, scant attention was paid to whether and how freelancers should learn to adjust their bidding strategies and improve bidding competitiveness during the journey of participating in multiple tasks. To fill in this gap, we adapt a set of bidding strategies from auction literature into the crowdsourcing context. Leveraging the lens of vicarious learning, we advance that freelancers’ learning from winners on bidding strategies will enhance their bidding competitiveness, which is moderated by task complexity. Our preliminary results suggest a significant relationship between strategic learning and bidding competitiveness, along with the moderating effect of task complexity. Expected contributions and future schemes are discussed finally

How creative versus technical constraints affect individual learning in an online innovation community

Online innovation communities allow for a search for novel solutions within a design space bounded by constraints. Past research has focused on the effect of creative constraints on individual projects, but less is known about how constraints affect learning from repeated design submissions and the effect of the technical constraints that are integral to online platforms. How do creative versus technical constraints affect individual learning in exploring a design space in online communities? We analyzed ten years of data from an online innovation community that crowdsourced 136,989 design submissions from 33,813 individuals. We leveraged data from two types of design contests-creatively constrained and unconstrained-running in parallel on the platform, and we evaluated a natural experiment where a platform change reduced technical constraints. We find that creative constraints lead to high rates of learning only if technical constraints are sufficiently relaxed. Our findings have implications for the management of creative design work and the downstream effects of the technical constraints of the information systems that support online innovation communities

Harvesting Wisdom on Social Media for Business Decision Making

The proliferation of social media provides significant opportunities for organizations to obtain wisdom of the crowds (WOC)-type data for decision making. However, critical challenges associated with collecting such data exist. For example, the openness of social media tends to increase the possibility of social influence, which may diminish group diversity, one of the conditions of WOC. In this research-in-progress paper, a new social media data analytics framework is proposed. It is equipped with well-designed mechanisms (e.g., using different discussion processes to overcome social influence issues and boost social learning) to generate data and employs state-of-the-art big data technologies, e.g., Amazon EMR, for data processing and storage. Design science research methodology is used to develop the framework. This paper contributes to the WOC and social media adoption literature by providing a practical approach for organizations to effectively generate WOC-type data from social media to support their decision making

Which Positive Feedback Matters? The Role of Language Concreteness and Temporal Effect in Continuous Contribution in Open Innovation Community

The feedback mechanism is the basis for motivating users to make continuous contributions in the Open Innovation Community (OIC). Although previous studies have revealed the overall role of positive feedback in promoting continuous user contribution, it is not clear which type of positive feedback is more effective and how it changes over time. To solve these problems, we constructed a research model based on reinforcement theory and took Lego Ideas, a typical OIC, as the research object to crawl users’ ideas and feedback data for empirical analysis. The results confirmed the effect of positive feedback and further demonstrated that, the effectiveness of positive feedback varies based on feedback concreteness and the tenure of the focal user. Our study contributes to the literature on how feedback affects user contributions in online communities by refining the classifications of feedback, and provide practical guidance for companies to motivate users to contributing ideas continuously

The Impact and Evolution of Individual’s Learning: An Empirical Study in Open Innovation Community

Learning is critical for individuals to increase their performance. However, this benefit of learning is not always realized. Previous studies have distinguished different classifications of learning approaches and reached inconsistent results. Therefore, this study further refines the classification of learning approaches in an open innovation community and explore the individual’s learning curve from a dynamic perspective. Specifically, we focus on whether and under what conditions learning can increase individual’s performance, and how individual\u27s learning curve changes over the tenure. To examine our hypotheses, we collect a dataset includes 48,820 game mods developed by 6,141 creators spanning 7-years from an open game innovation community. The results not only show the significant curve relationship between the four learning approaches and performance, but also demonstrate individual’s learning curve evolves over the tenure. This paper provides valuable suggestions and implications for individuals to choose appropriate learning approaches and obtain better performance under different tenures

The Geography of Open Source Software: Evidence from GitHub

Open Source Software (OSS) plays an important role in the digital economy. Yet although software production is amenable to remote collaboration and its outputs are easily shared across distances, software development seems to cluster geographically in places such as Silicon Valley, London, or Berlin. And while recent work indicates that OSS activity creates positive externalities which accrue locally through knowledge spillovers and information effects, up-to-date data on the geographic distribution of active open source developers is limited. This presents a significant blindspot for policymakers, who tend to promote OSS at the national level as a cost-saving tool for public sector institutions. We address this gap by geolocating more than half a million active contributors to GitHub in early 2021 at various spatial scales. Compared to results from 2010, we find a significant increase in the share of developers based in Asia, Latin America and Eastern Europe, suggesting a more even spread of OSS developers globally. Within countries, however, we find significant concentration in regions, exceeding the concentration of workers in high-tech fields. Social and economic development indicators predict at most half of regional variation in OSS activity in the EU, suggesting that clusters of OSS have idiosyncratic roots. We argue that policymakers seeking to foster OSS should focus locally rather than nationally, using the tools of cluster policy to support networks of OSS developers

THE POWER OF OBSERVATION. ALMOST FORGOTTEN POTENTIALITIES OF THE COGNITIVE-SOCIAL LEARNING MODEL

Na sua origem a teoria cognitivo-social foi uma resposta importante para ultrapassar as limitações das teorias comportamentalistas. Contudo, nos tempos mais recentes, o seu poder heurístico tem sido relativamente esquecido. Este artigo procura recuperar algumas das teses do modelo da aprendizagem por observação, para ilustrar o potencial dos mecanismos de auto-regulação para a compreensão do comportamento humano.Originally, the cognitive-social theory was an important answer to overcoming the limitations of behaviorist theories. However, in recent times, its heuristic potential has been relatively forgotten. This paper seeks to recover some of the theses of the observational learning model to illustrate the power of self-regulatory mechanisms for understanding human behavior.Grupo de Investigación HUM 672-AREA (Análisis de la Realidad EducativA

Three Essays on Digital Innovation from an Intellectual Property Rights Perspective

This dissertation uses the lens of intellectual property rights (IPR) to challenge the Information Systems (IS) field’s conventional view of a patent as a knowledge asset. It shows how IS scholars can leverage the IPR perspective to generate insights into digital innovation and how those insights can inform innovation policy, which establishes the regulatory governance framework for the digital innovation ecosystem. Essay 1 aims to shift the focus of the literature on the production of digital innovation to the examination of digital patents. It surfaces (a) the critical beneficial influence of patent examiners’ feedback—that is, why the claims of inventors’ past applications have been rejected—on inventors’ success in gaining subsequent digital patents and (b) how that benefit is subject to two key aspects of examiners’ feedback—temporal and technological. Essay 1 therefore informs a debate among scholars and policy makers regarding the expertise of patent examiners in digital patents. Essays 2 and 3 turn to the value creation of digital innovation, in which patent owners generate rent from their patents at the expense of social welfare. Specifically, Essay 2 joins the discussion on patent thickets—the overlapping of firms’ IPR that may restrict their commercialization of their own inventions—while addressing the formation of patent thickets in the IT industry, in which firms are racing to assemble large patent portfolios. Results indicate that the knowledge spillover to competitors generated by a focal IT firm’s patent disclosure can increase the level of patent thickets. Such impact depends on two key characteristics—the value of the focal firm’s disclosure and the absorptive capacity of that firm’s competitors. Essay 2 therefore uncovers the crucial role of disclosure for the optimal policy design to address patent thickets. Essay 3 connects with the recent conversation on the role of crowdfunding in democratizing venture capital (VC) financing, while differentiating itself by addressing the IPR threat from a patent assertion entity (PAE), which is in the business of asserting digital patents. Results indicate that state anti-PAE laws are crucial in realizing two crowdfunding benefits: attracting VC investment into the state and diversifying the investments across industries within the state. Essay 3 thus surfaces the critical role that institutional governance of IPR risk plays in achieving crowdfunding benefits