10,125 research outputs found

    Living labs as a driver for change in regional television

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    Traditional television production and distribution organizations are increasingly being challenged by a rapidly changing technological environment. These evolutions force the television industry to leave their comfort zone. This context in mind, regional television broadcasters often lack the resources, knowledge and organizational flexibility to cope with this external pressure. In this paper, we discuss the use of Living Labs as ‘innovation intermediaries’ and ‘change facilitators’ that foster and enable user-centric innovation development processes, both inside and outside the organization. This phenomenon is approached from both an open innovation and a user innovation point of view. This paper considers Living Labs as open innovation ecosystems, enabling organizations to reach out and collaborate with their (potential) audience and other external actors, but also as an open ‘battle arena’ for the organization itself. The Living Lab process governs different expectations and enables conflicting opinions to come together and to steadily grow towards a mutual solution. Moreover, the innovation development process in the Living Lab seems to have innovation spill-over effects on the organizational level, catalyzing a broader organizational change

    Modeling User-Affected Software Properties for Open Source Software Supply Chains

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    Background: Open Source Software development community relies heavily on users of the software and contributors outside of the core developers to produce top-quality software and provide long-term support. However, the relationship between a software and its contributors in terms of exactly how they are related through dependencies and how the users of a software affect many of its properties are not very well understood. Aim: My research covers a number of aspects related to answering the overarching question of modeling the software properties affected by users and the supply chain structure of software ecosystems, viz. 1) Understanding how software usage affect its perceived quality; 2) Estimating the effects of indirect usage (e.g. dependent packages) on software popularity; 3) Investigating the patch submission and issue creation patterns of external contributors; 4) Examining how the patch acceptance probability is related to the contributors\u27 characteristics. 5) A related topic, the identification of bots that commit code, aimed at improving the accuracy of these and other similar studies was also investigated. Methodology: Most of the Research Questions are addressed by studying the NPM ecosystem, with data from various sources like the World of Code, GHTorrent, and the GiHub API. Different supervised and unsupervised machine learning models, including Regression, Random Forest, Bayesian Networks, and clustering, were used to answer appropriate questions. Results: 1) Software usage affects its perceived quality even after accounting for code complexity measures. 2) The number of dependents and dependencies of a software were observed to be able to predict the change in its popularity with good accuracy. 3) Users interact (contribute issues or patches) primarily with their direct dependencies, and rarely with transitive dependencies. 4) A user\u27s earlier interaction with the repository to which they are contributing a patch, and their familiarity with related topics were important predictors impacting the chance of a pull request getting accepted. 5) Developed BIMAN, a systematic methodology for identifying bots. Conclusion: Different aspects of how users and their characteristics affect different software properties were analyzed, which should lead to a better understanding of the complex interaction between software developers and users/ contributors

    Third-Party SDKs and Mobile App Performance

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    To create attractive mobile apps in the competitive mobile market, developers are increasingly leveraging third-party software development kits (SDKs) in app development. However, little is known about how using third-party toolkits affects app performance. Drawing on the platform literature and the boundary object theory, we conceptualize third-party SDK utilization as a boundary-spanning activity. Based on this, we theorize its impact on app performance, considering the mobile platform and app developers as contextual factors. We examine the causal influence of third-party SDKs on app performance by conducting difference-in-difference-style analyses on a longitudinal dataset of mobile apps released on the Apple App Store and Google Play. We find empirical evidence supporting our theoretical conjectures that utilizing more third-party SDKs increases active users. More interestingly, platform updates and developer platform-specific experience attenuate this positive impact. This study contributes to the platform-based innovation and governance literature and provides managerial implications in mobile domains

    Essays on Business Value Creation in Digital Platform Ecosystems

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    Digital platforms and the surrounding ecosystems have garnered great interest from researchers and practitioners. Notwithstanding this attention, it remains unclear how and when digital platforms create business value for platform owners and complementors. This three-essay dissertation focuses on understanding business value creation in digital platform ecosystems. The first essay reviews and synthesizes literature across disciplines and offers an integrative framework of digital platform business value. Advised by the findings from the review, the second and third essays focus on the value creation for platform complementors. The second essay examines how IT startups entering a platform ecosystem at different times can strategically design their products (i.e., product diversification across platform architectural layers and product differentiation) to gain competitive advantages. Longitudinal evidence from the Hadoop ecosystem demonstrates that product diversification has an inverted U-shaped relationship with complementors success, and such an effect is more salient for earlier entrants than later entrants. Earlier entrants should develop products that are similar to other ecosystem competitors to reduce uncertainty whereas later entrants are advised to explore market niche and differentiate their products.The third essay investigates how platform complementors strategies and products co-evolve over time in the co-created ecosystem network environment. Our longitudinal analysis of the Hadoop ecosystem indicates that complementors technological architecture coverage and alliance exploration strategies increase their product evolution rate. In turn, complementors with faster product evolution are more likely to explore new partners but less likely to cover a wider range of the focal platforms technological layers in subsequent periods. Network density, co-created by all platform complementors, weakens the effects of complementors strategies on their product evolution but amplifies the effects of past product evolutions on strategies.This three-essay dissertation uncovers various understudied competitive strategies in the digital platform context and enriches our understanding of business value creation in digital platform ecosystems

    Investigating the Relationship between the Effectiveness of App Evolution and App Continuance Intention: An Empirical Study of the U.S. App Market

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    Researchers have shown app evolution to continuously lead to app success from the developer perspective. However, few studies have explored app success from the user perspective, which limits our knowledge about the role that app evolution has in app success. Building on app evolution literature and the technology acceptance model (TAM), we investigate the influence that effectiveness of app evolution has on perceived app usefulness, perceived ease of use, and app continuance intention (a proxy for app success from the user perspective). We collected survey data from 299 app users on both the Google Play and Apple’s App Store platforms in the United States. Our findings indicate that effectiveness of strategic evolution and effectiveness of evolution speed directly affect perceived app usefulness, while effectiveness of operational evolution and effectiveness of evolution speed directly affect perceived app ease of use. In addition, perceived app usefulness and perceived app ease of use constitute two key factors that lead to app continuance intention. Perceived ease of use affects users’ app continuance intention both directly and indirectly through perceived app usefulness. This study enhances our knowledge about the relationship between effectiveness of app evolution and app continuance intention. Such knowledge has particular importance in helping small firms or startups with limited resources understand how to retain app users. We also discuss limitations and directions for future research

    Investigating the Relationship between Effectiveness of App Evolution and App Continuance Intention: An Empirical Study of the U.S. App Market

    Get PDF
    App evolution has been shown to continuously lead to app success from the developer perspective. However, few studies have explored app success from the user perspective, which limits our understanding of the role of app evolution in app success. Building on app evolution literature and the technology acceptance model (TAM), the authors investigate the influence of the effectiveness of app evolution on users’ perceived app usefulness and ease of use and their app continuance intention, which is a proxy of app success from the user perspective. Survey data were collected from 299 app users on both the Google Play and AppStore platforms in the U.S. The findings indicate that the effectiveness of strategic evolution and effectiveness of evolution speed directly affect a user’s perceived app usefulness, while effectiveness of operational evolution and effectiveness of evolution speed directly affect a user’s perceived app ease of use. In addition, perceived app usefulness and perceived app ease of use are two keys that lead to users’ app continuance intention. A user’s perceived app ease of use affects app continuance intention both directly and indirectly through perceived app usefulness. This study enhances our understanding of the relationship between effectiveness of app evolution and app continuance intention. This is especially important in helping app developers that are small firms or startups with limited resources understand how to retain app users. Limitations and directions for future research are also discussed

    Does diversification pay in the app market? Evidence from Apple's App Store and Google Play

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    In this paper we address the study of the effects of product line diversification on firm performance in the mobile application market. Specifically, we shed light on whether the distribution platform ecosystem where developers commercialize their apps influence the effect of product line diversification, i.e., diversification across different app categories, on developer sales performance. To these purposes, we compare the sales performance of diversified developers with that of category-specialized developers in the two major app stores (namely, Apple’s App Store and Google Play). Our results show that the diversification strategy has a positive impact on developer sales in Google Play, while no significant impact emerges in the Apple’s App Store. The cross-platform differences in consumer willingness to pay are the rationale behind the different effect of diversification on sales performance across platform ecosystems. Our results have an important implication for developers as they suggest that developers should factor in the app ecosystem where they operate when making the decision on whether to diversify or not
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