5,552 research outputs found
Capturing the Forest or the Trees: Designing for Granularity in Data Crowdsourcing
Crowdsourcing is a method of completing a task by engaging a large group of heterogeneous contributors. Data crowdsourcing is crowdsourcing of data collection. In this paper, we demonstrate how data crowdsourcing projects can be differentiated along five dimensions: (1) the extent to which tasks are well-defined; (2) the duration of the task; (3) the type of value generated by the consumers of crowdsourcing data; (4) the variety of contribution allowed when completing the task; and (5) the relative value of each contribution. We argue that the quality of information created by a crowd depends on the granularity of contributions contributors are able to make. Finally, we propose a set of principles for designing crowdsourcing system to align the level of granularity of contributions with project objectives
Crowdsourcing as a tool for urban emergency management: lessons from the literature and typology
Recently, citizen involvement has been increasingly used in urban disaster prevention and
management, taking advantage of new ubiquitous and collaborative technologies. This scenario has
created a unique opportunity to leverage the work of crowds of volunteers. As a result, crowdsourcing
approaches for disaster prevention and management have been proposed and evaluated. However,
the articulation of citizens, tasks, and outcomes as a continuous flow of knowledge generation reveals
a complex ecosystem that requires coordination efforts to manage interdependencies in crowd work.
To tackle this challenging problem, this paper extends to the context of urban emergency management
the results of a previous study that investigates how crowd work is managed in crowdsourcing
platforms applied to urban planning. The goal is to understand how crowdsourcing techniques
and quality control dimensions used in urban planning could be used to support urban emergency
management, especially in the context of mining-related dam outages. Through a systematic literature
review, our study makes a comparison between crowdsourcing tools designed for urban planning and
urban emergency management and proposes a five-dimension typology of quality in crowdsourcing,
which can be leveraged for optimizing urban planning and emergency management processes
Leveraging the power of creative crowds for innovative brands: the eYeka crowdsourcing initiatives
The thesis tried to move beyond the Crowdsourcing phenomenon intended as a mere micro-task production outlining key features of the main typologies of contest which a firm could select in pursuing this Business Model. The dissertation thus advice companies on what kind of contests format is more suitable to be implemented in order to reach the desired objective, by tailoring not only challenges but also incentive mechanisms to engage the right crowd even in terms of motivational aspectsope
What the Crowd Sources: A Protocol for a Contribution-Centred Systematic Literature Review of Data Crowdsourcing Research
Data crowdsourcing is the mobilization of large groups of contributors—often volunteers via the Internet—to collect and/or analyze data. Research on data crowdsourcing often prioritizes the data consumer or project sponsor. Significant gaps remain in understanding how to address design issues from the perspective of data crowdsourcing contributors. A systematic literature review is an ideal method for identifying gaps in how researchers conceptualize contributions in data crowdsourcing. This project presents a protocol for such a systematic literature review of data crowdsourcing. We will use the protocol to guide a subsequent systematic literature review and the construction of a data-information-knowledge-wisdom chart that identifies critical gaps and opportunities for research in data crowdsourcing systems
An investigation into the role of crowdsourcing in generating information for flood risk management
Flooding is a major global hazard whose management relies on an accurate understanding of its risks. Crowdsourcing represents a major opportunity for supporting flood risk management as members of the public are highly capable of producing useful flood information. This thesis explores a wide range of issues related to flood crowdsourcing using an interdisciplinary approach. Through an examination of 31 different projects a flood crowdsourcing typology was developed. This identified five key types of flood crowdsourcing: i) Incident Reporting, ii) Media Engagement, iii) Collaborative Mapping, iv) Online Volunteering and v) Passive VGI. These represent a wide range of initiatives with radically different aims, objectives, datasets and relationships with volunteers. Online Volunteering was explored in greater detail using Tomnod as a case study. This is a micro-tasking platform in which volunteers analyse satellite imagery to support disaster response. Volunteer motivations for participating on Tomnod were found to be largely altruistic. Demographics of participants were significant, with retirement, disability or long-term health problems identified as major drivers for participation. Many participants emphasised that effective communication between volunteers and the site owner is strongly linked to their appreciation of the platform. In addition, the feedback on the quality and impact of their contributions was found to be crucial in maintaining interest. Through an examination of their contributions, volunteers were found to be able to ascertain with a higher degree of accuracy, many features in satellite imagery which supervised image classification struggled to identify. This was more pronounced in poorer quality imagery where image classification had a very low accuracy. However, supervised classification was found to be far more systematic and succeeded in identifying impacts in many regions which were missed by volunteers. The efficacy of using crowdsourcing for flood risk management was explored further through the iterative development of a Collaborative Mapping web-platform called Floodcrowd. Through interviews and focus groups, stakeholders from the public and private sector expressed an interest in crowdsourcing as a tool for supporting flood risk management. Types of data which stakeholders are particularly interested in with regards to crowdsourcing differ between organisations. Yet, they typically include flood depths, photos, timeframes of events and historical background information. Through engagement activities, many citizens were found to be able and motivated to share such observations. Yet, motivations were strongly affected by the level of attention their contributions receive from authorities. This presents many opportunities as well as challenges for ensuring that the future of flood crowdsourcing improves flood risk management and does not damage stakeholder relationships with participants
Crowdsourcing Paper Screening in Systematic Literature Reviews
Literature reviews allow scientists to stand on the shoulders of giants,
showing promising directions, summarizing progress, and pointing out existing
challenges in research. At the same time conducting a systematic literature
review is a laborious and consequently expensive process. In the last decade,
there have a few studies on crowdsourcing in literature reviews. This paper
explores the feasibility of crowdsourcing for facilitating the literature
review process in terms of results, time and effort, as well as to identify
which crowdsourcing strategies provide the best results based on the budget
available. In particular we focus on the screening phase of the literature
review process and we contribute and assess methods for identifying the size of
tests, labels required per paper, and classification functions as well as
methods to split the crowdsourcing process in phases to improve results.
Finally, we present our findings based on experiments run on Crowdflower
Developing a dominant logic of strategic innovation
Purpose: This paper aims to lay the foundations to develop a dominant logic and a common thematic framework of strategic innovation (SI) and to encourage consensus over the field’s core
foundation of main themes.
Design/methodology/approach: The paper explores the intersection between the constituent fields of strategic management and innovation management through a concept mapping process. The paper categorizes the main themes and search for common ground in order to develop the core thematic framework of SI. The paper looks at the sub-themes of SI in published research and develops a more detailed framework. The conceptual categories derived from the process are then placed in a logical sequence according to how they occur in practice or in the order of how the concepts develop from one other.
Findings: The results yield seven main themes that form the main taxonomy of SI: types of SI, environmental analysis of SI, SI planning, enabling SI, collaborative networks, managing knowledge, and strategic outcomes.
Research limitations/implications: The new thematic framework the paper is proposing for SI remains preliminary in nature and would need to be tried and tested by researchers and practitioners in order to gain acceptability. Academic rigor and methodological structure are not sufficient to determine whether our conceptual framework will become widely diffused in academia and industry. It would have to pass through an emergent, evolutionary process of selection, adoption and an
inevitable degree of change and adaptation, just like any other innovation.
Practical implications: The practical implications concern the production of instructive material and the application of strategic management initiatives in industry. The proposed themes and sub-themes can serve as a logical framework to develop and update publications, which have been instrumental in their own right to shape the field. The paper also provides a checklist of potential research projects in SI, which will improve and strengthen the field. The new framework provides a comprehensive checklist of strategic management initiatives that will help industry to initiate, plan and execute effective innovation strategies.
Originality/value: The concept mapping of the themes of SI yields a new dominant logic, which will influence the evolution of the field and its relevance to both academia and industry
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