New paper by Professors Eva Sørensen & Jacob Torfing: “It is widely recognized that public innovation is the intelligent alternative to blind across-the-board-cuts in times of shrinking budgets, and that innovation may help to break policy deadlocks and adjust welfare services to new and changing demands. At the same time, there is growing evidence that multi-actor collaboration in networks, partnerships and interorganizational teams can spur public innovation (Sørensen and Torfing, 2011). The involvement of different public and private actors in public innovation processes improves the understanding of the problem or challenge at hand and brings forth new ideas and proposals. It also ensures that the needs of users, citizens and civil society organizations are taken into account when innovative solutions are selected, tested and implemented.
While a lot of public innovation continues to be driven by particular public employees and managers, there seems to be a significant surge in collaborative forms of innovation that cut across the institutional and organization boundaries within the public sector and involve a plethora of private actors with relevant innovation assets. Indeed, the enhancement of collaborative innovation has be come a key aspiration of many public organizations around the world. However, if we fail to develop a more precise and sophisticated understanding of the concepts of ‘innovation’ and ‘collaboration’, we risk that both terms are reduced to empty and tiresome buzzwords that will not last to the end of the season. Moreover, in reality, collaborative and innovative processes are difficult to trigger and sustain without proper innovation management and a supporting cultural and institutional environment. This insight calls for further reflections on the role of public leadership and management and for a transformation of the entire system of public governing.
Hence, in order to spur collaborative innovation in the public sector, we need to clarify the basic terms of the debate and explore how collaborative innovation can be enhanced by new forms of innovation management and new forms of public governing. To this end, we shall first define the notions of innovation and public innovation and discuss the relation between public innovation and social innovation in order to better understand the purposes of different forms of innovation.
We shall then seek to clarify the notion of collaboration and pinpoint why and how collaboration enhances public innovation. Next, we shall offer some theoretical and practical reflections about how public leaders and managers can advance collaborative innovation. Finally, we shall argue that the enhancement of collaborative forms of social innovation calls for a transformation of the system of public governing that shifts the balance from New Public Management towards New Public Governance.”
E-government and organisational transformation of government: Black box revisited?
New paper in Government Information Quarterly: “During the e-government era the role of technology in the transformation of public sector organisations has significantly increased, whereby the relationship between ICT and organisational change in the public sector has become the subject of increasingly intensive research over the last decade. However, an overview of the literature to date indicates that the impacts of e-government on the organisational transformation of administrative structures and processes are still relatively poorly understood and vaguely defined.
The main purpose of the paper is therefore the following: (1) to examine the interdependence of e-government development and organisational transformation in public sector organisations and propose a clearer explanation of ICT’s role as a driving force of organisational transformation in further e-government development; and (2) to specify the main characteristics of organisational transformation in the e-government era through the development of a new framework. This framework describes organisational transformation in two dimensions, i.e. the ‘depth’ and the ‘nature’ of changes, and specifies the key attributes related to the three typical organisational levels.”
Prospects for Online Crowdsourcing of Social Science Research Tasks: A Case Study Using Amazon Mechanical Turk
New paper by Catherine E. Schmitt-Sands and Richard J. Smith: “While the internet has created new opportunities for research, managing the increased complexity of relationships and knowledge also creates challenges. Amazon.com has a Mechanical Turk service that allows people to crowdsource simple tasks for a nominal fee. The online workers may be anywhere in North America or India and range in ability. Social science researchers are only beginning to use this service. While researchers have used crowdsourcing to find research subjects or classify texts, we used Mechanical Turk to conduct a policy scan of local government websites. This article describes the process used to train and ensure quality of the policy scan. It also examines choices in the context of research ethics.”
From funding agencies to scientific agency –
New paper on “Collective allocation of science funding as an alternative to peer review”: “Publicly funded research involves the distribution of a considerable amount of money. Funding agencies such as the US National Science Foundation (NSF), the US National Institutes of Health (NIH) and the European Research Council (ERC) give billions of dollars or euros of taxpayers’ money to individual researchers, research teams, universities, and research institutes each year. Taxpayers accordingly expect that governments and funding agencies will spend their money prudently and efficiently.
Investing money to the greatest effect is not a challenge unique to research funding agencies and there are many strategies and schemes to choose from. Nevertheless, most funders rely on a tried and tested method in line with the tradition of the scientific community: the peer review of individual proposals to identify the most promising projects for funding. This method has been considered the gold standard for assessing the scientific value of research projects essentially since the end of the Second World War.
However, there is mounting critique of the use of peer review to direct research funding. High on the list of complaints is the cost, both in terms of time and money. In 2012, for example, NSF convened more than 17,000 scientists to review 53,556 proposals [1]. Reviewers generally spend a considerable time and effort to assess and rate proposals of which only a minority can eventually get funded. Of course, such a high rejection rate is also frustrating for the applicants. Scientists spend an increasing amount of time writing and submitting grant proposals. Overall, the scientific community invests an extraordinary amount of time, energy, and effort into the writing and reviewing of research proposals, most of which end up not getting funded at all. This time would be better invested in conducting the research in the first place.
Peer review may also be subject to biases, inconsistencies, and oversights. The need for review panels to reach consensus may lead to sub‐optimal decisions owing to the inherently stochastic nature of the peer review process. Moreover, in a period where the money available to fund research is shrinking, reviewers may tend to “play it safe” and select proposals that have a high chance of producing results, rather than more challenging and ambitious projects. Additionally, the structuring of funding around calls‐for‐proposals to address specific topics might inhibit serendipitous discovery, as scientists work on problems for which funding happens to be available rather than trying to solve more challenging problems.
The scientific community holds peer review in high regard, but it may not actually be the best possible system for identifying and supporting promising science. Many proposals have been made to reform funding systems, ranging from incremental changes to peer review—including careful selection of reviewers [2] and post‐hoc normalization of reviews [3]—to more radical proposals such as opening up review to the entire online population [4] or removing human reviewers altogether by allocating funds through an objective performance measure [5].
We would like to add another alternative inspired by the mathematical models used to search the internet for relevant information: a highly decentralized funding model in which the wisdom of the entire scientific community is leveraged to determine a fair distribution of funding. It would still require human insight and decision‐making, but it would drastically reduce the overhead costs and may alleviate many of the issues and inefficiencies of the proposal submission and peer review system, such as bias, “playing it safe”, or reluctance to support curiosity‐driven research.
Our proposed system would require funding agencies to give all scientists within their remit an unconditional, equal amount of money each year. However, each scientist would then be required to pass on a fixed percentage of their previous year’s funding to other scientists whom they think would make best use of the money (Fig 1). Every year, then, scientists would receive a fixed basic grant from their funding agency combined with an elective amount of funding donated by their peers. As a result of each scientist having to distribute a given percentage of their previous year’s budget to other scientists, money would flow through the scientific community. Scientists who are generally anticipated to make the best use of funding will accumulate more.”
Design in public and social innovation
New paper by Geoff Mulgan (Nesta): “What’s going right and what’s going wrong? Is design a key to more efficient and effective public services, or a costly luxury, good for conferences and consultants but not for the public?
This paper looks at the elements of the design method; the strengths of current models; some of their weaknesses and the common criticisms made of them; and what might be the way forward.
Contents:
- Strengths of the design method in social innovation and public service
- Social design tools table
- Weaknesses of design projects and methods
- The challenge
- Design in the context of innovation”
Social media in crisis events: Open networks and collaboration supporting disaster response and recovery
Paper for the IEEE International Conference on Technologies for Homeland Security (HST): “Large-scale crises challenge the ability of public safety and security organisations to respond efficient and effectively. Meanwhile, citizens’ adoption of mobile technology and rich social media services is dramatically changing the way crisis responses develop. Empowered by new communication media (smartphones, text messaging, internet-based applications and social media), citizens are the in situ first sensors. However, this entire social media arena is unchartered territory to most public safety and security organisations. In this paper, we analyse crisis events to draw narratives on social media relevance and describe how public safety and security organisations are increasingly aware of social media’s added value proposition in times of crisis. A set of critical success indicators to address the process of adopting social media is identified, so that social media information is rapidly transformed into actionable intelligence, thus enhancing the effectiveness of public safety and security organisations — saving time, money and lives.”
E-government research in the United States
Paper by JT Snead, E Wright in Government Information Quarterly: “The purpose of this exploratory study is to review scholarly publications and assess egovernment research efforts as a field of study specific to the United States e-government environment. Study results reveal that researchers who focus on the U.S. e-government environment assess specific e-government topics at the federal, state, and local levels; however, there are gaps in the research efforts by topic areas and across different levels of government, which indicate opportunities for future areas of research. Results also find that a multitude of methodology approaches are used to assess e-government. Issues, however, exist that include lack of or weak presentations of methodologies in publications, few studies include multi-method evaluation approaches for data collection and analysis efforts, and few studies take a theory-based approach to understanding the U.S. e-government environment.”
Protecting personal data in E-government: A cross-country study
Paper by Yuehua Wu in Government Information Quarterly: “This paper presents the findings of a comparative study of laws and policies employed to protect personal data processed in the context of e-government in three countries (the United States, Germany, and China) with rather different approaches. Drawing on governance theory, the paper seeks to document the mechanisms utilized and to understand the factors that shape the governance modes adopted. The cases reveal that national government regulations have not kept pace with technological change and with the current information practices of the public sector. Nonetheless, traditional government regulation remains the major governance mode for the issue under discussion. Self-regulation and code-based regulation serve supplementary roles to traditional government regulation. National context is found to impact the form and level of data protection and the choice of governance modes.”
Introduction to Linked Open Data (LOD)
Paper by Ivan Herman, presented at the International Conference on Dublin Core and Metadata Applications 2013: “The goal of the tutorial is to introduce the audience into the basics of the technologies used for Linked Data. This includes RDF, RDFS, main elements of SPARQL, SKOS, and OWL. Some general guidelines on publishing data as Linked Data will also be provided, as well as real-life usage examples of the various technologies.”
Full Text: PDF (Description) | PDF (Presentation)
A World Of Wikipedia And Bitcoin: Is That The Promise Of Open Collaboration?
Science 2.0: “Open Collaboration, defined in a new paper as “any system of innovation or production that relies on goal-oriented yet loosely coordinated participants who interact to create a product (or service) of economic value, which they make available to contributors and non-contributors alike” brought the world Wikipedia, Bitcoin and, yes, even Science 2.0.
But what does that mean, really? That’s the first problem with vague terms in an open environment. It is anything people want it to be and sometimes what people want it to be is money, but hidden behind a guise of public weal.
TED’s lesser cousin TEDx is a result of open collaboration but there is no doubt it has successfully leveraged the marketing of TED to sell seats in auditoriums, just as it was designed to do. Generally, Open Collaboration now is less like its early days, where a group of like-minded people got together to create an Open Source tool, and more like corporations. Only they avoid the label, they are not quite non-profits and not quite corporations.
And because they are neither they can operate free of the cultural stigma. Despite efforts to claim that Wikipedia is a hotbed of misogyny and blocks out minorities, the online encyclopedia has endured just fine. Their defense is a simple one; they have no idea what gender or race or religion anyone is and anyone can contribute – it is a true open collaboration. Open Collaboration is goal-oriented, they lack the infrastructure to obey demands that they become about social justice, so the environments can be less touchy-feely than corporations and avoid the social authoritarianism of academia.
Many open collaborations perform well even in ‘harsh’ environments, where some minorities are underrepresented and diversity is lacking or when products by different groups rival one another. It’s a real puzzle for sociologists. The authors conclude that open collaboration is likely to expand into new domains, displacing traditional organizations, because it is so mission-oriented. Business executives and civic leaders should take heed – the future could look a lot more like the 1940s.”
See also: Sheen S. Levine, Michael J. Prietula, ‘Open Collaboration for Innovation: Principles and Performance’, Organization Science December 30, 2014 DOI:10.1287/orsc.2013.0872