Creativity, Coordination & Knowledge co-Creation on a Global Scale- The Process Perspective

In very recent times new tools and technologies for peer-to-peer collaboration and coordination became easily and readily available taking knowledge creation processes outside of the organizational boundaries. This paper proposes to extend the existing boundaries of Business Process Management (BPM) to include an emerging category of processes; here termed Global Knowledge-Intensive Business Processes (GKIBP). These processes differ from other global processes, such as supply chains and collaborative cross-organizational business processes (BPs), as their main outcome is a commercial knowledge artifact, co-created trough coordinated activities of knowledge agents, that may or may not come from an organizational setting. Drawing from, and combining the state-of-the art research findings from three disciplines: i) BPM (ii) Global Digital Collaboration and more recently (iii) Crowdsourcing and Collective Intelligence processes, this research aims to investigate the main characteristics of these processes through an exploratory case study. Our findings are then placed in the context of the current developments in BPM field, in particular the frameworks used to inform and guide BP Management today, demonstrating a need for their extension

Social gamification in enterprise crowdsourcing

Enterprise crowdsourcing capitalises on the availability of employ-ees for in-house data processing. Gamification techniques can help aligning employees’ motivation to the crowdsourcing endeavour. Although hitherto, research efforts were able to unravel the wide arsenal of gamification techniques to construct engagement loops, little research has shed light into the social game dynamics that those foster and how those impact crowdsourcing activities. This work reports on a study that involved 101 employees from two multinational enterprises. We adopt a user-centric approach to ap-ply and experiment with gamification for enterprise crowdsourcing purposes. Through a qualitative study, we highlight the importance of the competitive and collaborative social dynamics within the enterprise. By engaging the employees with a mobile crowdsourc-ing application, we showcase the effectiveness of competitiveness towards higher levels of engagement and quality of contributions. Moreover, we underline the contradictory nature of those dynam-ics, which combined might lead to detrimental effects towards the engagement to crowdsourcing activities

Beyond AMT: An Analysis of Crowd Work Platforms

While many competitor platforms to Amazon’s Mechanical Turk (AMT) now exist, little research has considered them. Such near-exclusive focus on AMT risks its particular vagaries and limitations overly shaping our understanding of crowd work and our field’s research questions and directions. To address this, we present a qualitative content analysis of seven alternative platforms. After organizing prior AMT studies around a set of key problem types encountered, we define our process for inducing categories for qualitative assessment of platforms. We then contrast the key problem types with AMT vs. platform features from content analysis, informing both methodology of use and directions for future research. Our cross-platform analysis represents the only such study by researchers for researchers, intended to enrich diversity of research on crowd work and accelerate progress.ye

Towards an integrated crowdsourcing definition

Crowdsourcing is a relatively recent concept that encompasses many practices. This diversity leads to the blurring of the limits of crowdsourcing that may be identified virtually with any type of internet-based collaborative activity, such as co-creation or user innovation. Varying definitions of crowdsourcing exist, and therefore some authors present certain specific examples of crowdsourcing as paradigmatic, while others present the same examples as the opposite. In this article, existing definitions of crowdsourcing are analysed to extract common elements and to establish the basic characteristics of any crowdsourcing initiative. Based on these existing definitions, an exhaustive and consistent definition for crowdsourcing is presented and contrasted in 11 cases.Estelles Arolas, E.; González-Ladrón-De-Guevara, F. (2012). Towards an integrated crowdsourcing definition. Journal of Information Science. 32(2):189-200. doi:10.1177/0165551512437638S189200322Vukovic, M., & Bartolini, C. 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Journal of Information Science, 35(6), 758-765. doi:10.1177/0165551509346786Andriole, S. J. (2010). Business impact of Web 2.0 technologies. Communications of the ACM, 53(12), 67. doi:10.1145/1859204.1859225Denyer, D., Tranfield, D., & van Aken, J. E. (2008). Developing Design Propositions through Research Synthesis. Organization Studies, 29(3), 393-413. doi:10.1177/0170840607088020Egger, M., Smith, G. D., & Altman, D. G. (Eds.). (2001). Systematic Reviews in Health Care. doi:10.1002/9780470693926Tatarkiewicz, W. (1980). A History of Six Ideas. doi:10.1007/978-94-009-8805-7Cosma, G., & Joy, M. (2008). Towards a Definition of Source-Code Plagiarism. IEEE Transactions on Education, 51(2), 195-200. doi:10.1109/te.2007.906776Brabham, D. C. (2009). Crowdsourcing the Public Participation Process for Planning Projects. Planning Theory, 8(3), 242-262. doi:10.1177/1473095209104824Alonso, O., & Lease, M. (2011). Crowdsourcing 101. 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(2010). Collaborative Workforce, Business Process Crowdsourcing as an Alternative of BPO. Lecture Notes in Computer Science, 425-430. doi:10.1007/978-3-642-16985-4_40Liu, E., & Porter, T. (2010). Culture and KM in China. VINE, 40(3/4), 326-333. doi:10.1108/03055721011071449Oliveira, F., Ramos, I., & Santos, L. (2010). Definition of a Crowdsourcing Innovation Service for the European SMEs. Lecture Notes in Computer Science, 412-416. doi:10.1007/978-3-642-16985-4_37Porta, M., House, B., Buckley, L., & Blitz, A. (2008). Value 2.0: eight new rules for creating and capturing value from innovative technologies. Strategy & Leadership, 36(4), 10-18. doi:10.1108/10878570810888713Ribiere, V. M., & Tuggle, F. D. (Doug). (2010). Fostering innovation with KM 2.0. VINE, 40(1), 90-101. doi:10.1108/03055721011024955Sloane, P. (2011). The brave new world of open innovation. Strategic Direction, 27(5), 3-4. doi:10.1108/02580541111125725Wexler, M. N. (2011). Reconfiguring the sociology of the crowd: exploring crowdsourcing. International Journal of Sociology and Social Policy, 31(1/2), 6-20. doi:10.1108/01443331111104779Whitla, P. (2009). Crowdsourcing and Its Application in Marketing Activities. Contemporary Management Research, 5(1). doi:10.7903/cmr.1145Yang, J., Adamic, L. A., & Ackerman, M. S. (2008). Crowdsourcing and knowledge sharing. Proceedings of the 9th ACM conference on Electronic commerce - EC ’08. doi:10.1145/1386790.1386829Brabham, D. C. (2010). MOVING THE CROWD AT THREADLESS. Information, Communication & Society, 13(8), 1122-1145. doi:10.1080/13691181003624090Giudice, K. D. (2010). Crowdsourcing credibility: The impact of audience feedback on Web page credibility. Proceedings of the American Society for Information Science and Technology, 47(1), 1-9. doi:10.1002/meet.14504701099Stewart, O., Huerta, J. M., & Sader, M. (2009). Designing crowdsourcing community for the enterprise. 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The Future of Outsourcing in the Asia-Pacific Region: Implications for Research and Practice—Panel Report from PACIS 2014

This paper summarizes a panel discussion held at the 18th Pacific Asia Conference on Information Systems (PACIS) in Chengdu, China, 2014, with the same title. The panel discussed the future of outsourcing in the Asia-Pacific region (specifically the importance of outsourcing, new trends, and issues in outsourcing). This paper provides directions for future research that surpasses regional specificity (i.e., the Asia-Pacific region), and contributes to research interests on outsourcing in general

Simulating the Cost of Cooperation: A Recipe for Collaborative Problem-Solving

Collective problem-solving and decision-making, along with other forms of collaboration online, are central phenomena within ICT. There had been several attempts to create a system able to go beyond the passive accumulation of data. However, those systems often neglect important variables such as group size, the difficulty of the tasks, the tendency to cooperate, and the presence of selfish individuals (free riders). Given the complex relations among those variables, numerical simulations could be the ideal tool to explore such relationships. We take into account the cost of cooperation in collaborative problem solving by employing several simulated scenarios. The role of two parameters was explored: the capacity, the group’s capability to solve increasingly challenging tasks coupled with the collective knowledge of a group, and the payoff, an individual’s own benefit in terms of new knowledge acquired. The final cooperation rate is only affected by the cost of cooperation in the case of simple tasks and small communities. In contrast, the fitness of the community, the difficulty of the task, and the groups sizes interact in a non-trivial way, hence shedding some light on how to improve crowdsourcing when the cost of cooperation is high

Conceptualisation of "crowdsourcing" term in management sciences

Background. Crowdsourcing is a relatively new concept, nonetheless it has been raising more and more interest with researchers. This is a result of its potential since it enables improving business processes, creating open innovations, building of competitive advantage, access to experience, information, crowd skills and work, problem solving, crisis management, expanding the organisation's existing activity and offer, creating the organisation's image, improving communication with the surroundings, optimising costs of the organisation's activity. However, although the subject of crowdsourcing constitutes one of the currently emerging directions of research on the basis of management sciences, one observes a peculiar exploration difficulty. It may result from incoherence in conceptualisation or explication of this term. Research aims. The aim of this article is an attempt, basing on the existing research efforts, to conceptualise crowdsourcing based on management sciences. In the article a proposal of conceptualising the notion of crowdsourcing was presented including its levels. Methodology. For the needs of specifying, evaluation, and identification of the existing state of knowledge on crowdsourcing, a systematic literature review was conducted. It enabled getting familiar with the results of similar research, its selection and critical analysis and based on that it was used for expanding the earlier findings of other researchers. The biggest, full text databases i.e Ebsco, Elsevier/Springer, Emerald, Proquest, Scopus, and ISI Web of Science, which include the majority of journals on strategic management were analysed. In order to establish the state of knowledge and existing findings a review of databases in Poland: BazEkon and CEON was also conducted. 54 elaborations of English language databases and 41 from Polish language databases from the period of 2006-2017 were analysed. Key findings. A review of the scientific output revealed incoherence in the conceptualisation of the term of crowdsourcing. The approaches proposed in the existing literature are inadequate and do not allow for full understanding of crowdsourcing

Automation, AI and the Future of Work in India

This research contributes to current debates on automation and the future of work, a much-hyped but under researched area, in emerging economies through a particular focus on India. It assesses the national strategy on Artificial Intelligence and explores the impact of automation on the Indian labour market, work and employment to inform policy. The study shows that technology is not free from the wider dynamics that surround the world of work. The adoption of new technologies is likely to occur in niches in the manufacturing and services sectors, while its impact on employment and the labour market more broadly, and in addressing societal inequalities will be limited. The national strategy, however, does not take into account the nature of capital accumulation and structural inequalities that stem from a large informal economy and surplus labour context with limited upskilling opportunities. This raises doubts about the effectiveness of the current policy. This study is the first to examine the impact of automation on work and employment in India. It provides a critical intervention in current debates on future of work from the point of view of an important emerging economy defined by labour surplus and a large informal economy