Living Innovation Laboratory Model Design and Implementation

Living Innovation Laboratory (LIL) is an open and recyclable way for multidisciplinary researchers to remote control resources and co-develop user centered projects. In the past few years, there were several papers about LIL published and trying to discuss and define the model and architecture of LIL. People all acknowledge about the three characteristics of LIL: user centered, co-creation, and context aware, which make it distinguished from test platform and other innovation approaches. Its existing model consists of five phases: initialization, preparation, formation, development, and evaluation. Goal Net is a goal-oriented methodology to formularize a progress. In this thesis, Goal Net is adopted to subtract a detailed and systemic methodology for LIL. LIL Goal Net Model breaks the five phases of LIL into more detailed steps. Big data, crowd sourcing, crowd funding and crowd testing take place in suitable steps to realize UUI, MCC and PCA throughout the innovation process in LIL 2.0. It would become a guideline for any company or organization to develop a project in the form of an LIL 2.0 project. To prove the feasibility of LIL Goal Net Model, it was applied to two real cases. One project is a Kinect game and the other one is an Internet product. They were both transformed to LIL 2.0 successfully, based on LIL goal net based methodology. The two projects were evaluated by phenomenography, which was a qualitative research method to study human experiences and their relations in hope of finding the better way to improve human experiences. Through phenomenographic study, the positive evaluation results showed that the new generation of LIL had more advantages in terms of effectiveness and efficiency.Comment: This is a book draf

PREM: Prestige Network Enhanced Developer-Task Matching for Crowdsourced Software Development

Many software organizations are turning to employ crowdsourcing to augment their software production. For current practice of crowdsourcing, it is common to see a mass number of tasks posted on software crowdsourcing platforms, with little guidance for task selection. Considering that crowd developers may vary greatly in expertise, inappropriate developer-task matching will harm the quality of the deliverables. It is also not time-efficient for developers to discover their most appropriate tasks from vast open call requests. We propose an approach called PREM, aiming to appropriately match between developers and tasks. PREM automatically learns from the developers’ historical task data. In addition to task preference, PREM considers the competition nature of crowdsourcing by constructing developers’ prestige network. This differs our approach from previous developer recommendation methods that are based on task and/or individual features. Experiments are conducted on 3 TopCoder datasets with 9,191 tasks in total. Our experimental results show that reasonable accuracies are achievable (63%, 46%, 36% for the 3 datasets respectively, when matching 5 developers to each task) and the constructed prestige network can help improve the matching results

Case Studies on the Exploitation of Crowd-Sourcing with Web 2.0 Functionalities

Crowd-sourcing appears more promising with Web 2.0 functionality and businesses have started using it for a wide range of activities, that would be better completed by a crowd rather than any specific pool of knowledge workers. However, relatively little is known about how a business can leverage on collective intelligence and capture the user- generated value for competitive advantage. This empirical study uses the principle of interpretive field research to validate the case findings with a descriptive multiple case study methodology. An extended theoretical framework to identify the important considerations at strategic and functional levels for the effective use of crowd-sourcing is proposed. The analytic framework uses five Business Strategy Components: Vision and Strategy, Human Capital, Infrastructure, Linkage and Trust, and External Environment. It also uses four Web 2.0 Functional Components: Social Networking, Interaction Orientation, Customization & Personalization, and User- added Value. By using these components as analytic lenses, the case research examines how successful e-commerce firms may deploy Web 2.0 functionalities for effective use of crowd-sourcing. Prioritization of these functional considerations might be favorable in some cases for the best fit of situations and limitations. In conclusion, it is important that the alignment between strategy and functional components is maintained

Worse Than Spam: Issues In Sampling Software Developers

Background: Reaching out to professional software developers is a crucial part of empirical software engineering research. One important method to investigate the state of practice is survey research. As drawing a random sample of professional software developers for a survey is rarely possible, researchers rely on various sampling strategies. Objective: In this paper, we report on our experience with different sampling strategies we employed, highlight ethical issues, and motivate the need to maintain a collection of key demographics about software developers to ease the assessment of the external validity of studies. Method: Our report is based on data from two studies we conducted in the past. Results: Contacting developers over public media proved to be the most effective and efficient sampling strategy. However, we not only describe the perspective of researchers who are interested in reaching goals like a large number of participants or a high response rate, but we also shed light onto ethical implications of different sampling strategies. We present one specific ethical guideline and point to debates in other research communities to start a discussion in the software engineering research community about which sampling strategies should be considered ethical.Comment: 6 pages, 2 figures, Proceedings of the 2016 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2016), ACM, 201

Motivasi Pengguna Dalam Menggunakan Metode Crowdsourcing Pada Pembuatan Perangkat Lunak

Perkembangan metode pada pengembangan perangkat lunak telah meningkat pada akhir-akhir ini, dengan meningkatnya teknologi dan kebutuhan pasar, metode crowdsourcing telah berkembang dan mendapat tingkat popularitas yang tinggi dikalangan masyarakat. Metode crowdsourcing lebih condong mengandalkan kekuatan orang banyak sebagai kemampuan utama dalam produksinya. Meskipun begitu, sejak crowdsourcing menjadi kekuatan utama baru dan merambah ke dunia pembuatan perangkat lunak, kualitas pada perangkat lunak menjadi dipertanyakan. Crowdsourcing memiliki perbedaan dengan alur pembuatan perangkat lunak secara tradisional seperti Software Life Development Cycle maupun Waterfall Model, selain itu metode crowdsourcing mengandalkan kekuatan keramaian pada saat pembuatanya. Beberapa studi dan jurnal sebelumnya beranggapan bahwa motivasi merupakan kunci utama kesuksesan ketika metode crowdsourcing digunakan untuk memproduksi sebuah produk. Pada studi ini diajukan model yang dikombinasikan dari dua teori utama untuk menjawab pertanyaan tentang motivasi penggunaan crowdsourcing untuk pembuatan software yaitu teori self-determination, dan IS success model untuk lebih mengerti tentang hubunganya intensitas pengguna dengan kepuasan pada pengguna pada kasus pengembangan perangkat lunak dengan metode crowdsourcing ==================================================================== Software Development has increased emerging new methods in its development, with the advancement of digitalization, technology and global networking, Crowdsourcing has been developed and gaining popularity among the people. Unlike the outsourcing, crowdsourcing is more emphasis on the power of crowds as major power production. This study will discuss crowdsourcing activity that focused on software development. Software engineering is a process which software is written a complex process without compromising the quality of the software. However, since crowdsourcing software engineering relies on its robust method to produce a software and entirely different from traditional software engineering, their quality are questionable. A major issue in of crowdsourcing is how to attract and to sustain for development. Motivation is a matter that should be investigated further by the researchers for better crowdsourcing development to bring right crowds to the table so it can sustain the crowdsourcing activity. This study discusses more a several factors motivation that can be an impact, an influence to the development of crowdsourcing in software development. To improve these study findings, this study also combines two major theories about self-determination and IS Success Model to investigate further about motivation the users joined crowdsourcing on software development and to understand the impact of user satisfaction in case of crowdsourcing on software developmen