Category Archives: Public Management

Predictive Analytics in the Public Sector

shutterstock_218879485-700x467My colleague Rainer Kattel (Tallinn University of Technology, Tallinn) and I are in the process of conducting interviews on digital transformation in the Estonian government. By coincidence we came across an interesting practice: the use of Big Data to review customs and financial data streams with the goal to reduce corruption. I wrote this up as a short contribution for the German Behörden Spiegel – a newspaper for public managers.

Here is the text (adapted from the German version – scroll down for the original text):

Big Data are Internet-generated data from online interactions of humans with websites or passive data collection by computer networks or physical sensors.The resulting data sets are usually defined as “big” because of its size, the speed in which they are generated, and the possibilities for predictive analytics and real-time insights into behavioral preferences of citizens.

Traditionally, public sector organizations are operating mostly with administratively designed and collected that results out of the direct interactions with citizens, includes other government records, and mostly includes data sets, such as open data, or other transactional data. It usually goes through an extensive cleaning and analysis process until it is made available with significant time delays (in the case of census data even years of delay). Oftentimes, the use of this ‘old’ data is used for predictive analytics to project the potential needs of citizens. Big Data however are automatically generated data sets, unstructured, and matching it with administrative data requires significant effort to match them with administrative data for the use by public managers.

Using the example of the Estonian customs and tax services, Big Data analytics can help to fight corruption in near real-time. Based on standardize cash flows, the Estonian tax and customs analysts have created risk profiles for different types of organizations. Every company is matched up with one of the profiles. These are continuously compared to cash flows and daily updates and adjustments are done in case of minor deviations. In addition to the risk profiles, so-called Key Performance Indicators in combination with additional data sets, such as banking transactions, invoices, business registers, lang register entries,, etc. In addition, data from online auction sites are used to find out if sellers are paying their sales taxes.

In case of anomalies between the expected tax incomes and the risk profiles of companies, based on a predefined algorithm, warnings are sent to the analytics team. After a first review, they decided what Information to forward to the specialists who will conduct their own ad hoch investigations. Using the analytical assessment in combination with the specialists’ experiences and assessments, a more detailed risk assessment is derived. As a result, either the risk profile is adjusted, or auditors are launching a tax examination on site on the same day.

This type of real-time analysis and timely interpretation of large-scale data sets allows the Estonian tax and customs authorities to assess information about the current tax situation and potential corruption cases in real time.

In the future, predictive analytics tool can be used to identify patterns about the health of individual companies. Predictive analytics can be used to understand the potential economic and social impact in case of impending bankruptcies. Using big data analytics can help government make more effective and efficient decisions, be potentially better prepared and act preventatively.

===================

Here is the full text in German and a link to scanned in article:

Big Data sind Internet-generierte Daten, die sich aus den Onlineinteraktionen von Menschen mit Webseiten und physischen Sensoren ergeben. Die resultierenden Datensätze, die allgemein aufgrund ihrer Größe, der Schnelligkeit ihrer Erstellung und den daraus resultierenden Möglichkeiten zur Echtzeitanalyse definiert werden, erlauben der öffentlichen Verwaltung Einsichten in die Bedürfnisse und tatsächlichen Handlungen von Bürgern. Sie stellen eine Kombination aus Social Media-Daten wie geteilten Videos und Fotos, likes/shares, Onlinebanking, Onlineeinkäufen, und Mobilfunkdaten dar.

Traditionell arbeitet die öffentliche Veraltung mit administrativ designten und aufwendig gesammelten Datensätzen, die vor allem aus den direkten Interaktionen mit Bürgern entstehen. Administrative Daten können einem Vorgang und individuellen Personen oder Haushalten zugeordnet werden. Beispiele dafür sind Zensusdaten, oder bisherige bearbeitete Fälle, die in Kombination mit professionellem Verständnis der Beamten für sogenannte predictive analytics dazu genutzt werden zukünftige Trends vorherzusagen. Dagegen werden Big Data-Datensätze automatisch generiert, sind unstrukturiert, und bedürfen hohem Einsatz um die Daten für die öffentliche Verwaltung nutzbar zu machen.

In Kombination können Big Data und administrative Daten dazu beitragen die Fachaufgabe der öffentlichen Verwaltung effizienter und effektiver zu gestalten. Dies zeigt sich am Beispiel der Estländischen Steuerbehörden, die Big Data-Analysen einsetzen um schnell Steuerhinterziehung zu identifizieren um möglichst noch am gleichen Tag die Ermittlungen vor Ort einzuleiten.

Die Zoll- und Finanzbeamten haben basierend auf standardisierten Finanzströmen für unterschiedliche Unternehmensformen zunächst sogenannte Risikoprofile angelegt, die mit echten Finanzdaten getestet werden, und kontinuierlich – wenn notwendig sogar täglich – dem tatsächlichen Geschäftsgebaren angepasst werden. Zusätzlich zu den Risikoprofilen dienen sogenannte Key Performance Indicators – Leistungskennzahlen – in Kombination mit den weiteren Datensätzen wie z.B. Banküberweisungen, Rechnungen, Unternehmensregister, Grundbucheinträgen. Aber auch Daten von Internet-Autobörsen werden miteinbezogen, um herauszufinden ob Verkäufer ihre Einkommen versteuern.

Sobald sich Abweichungen zu den steuerpflichtigen Finanzströmen ergeben, die dem Profil des Unternehmens nicht entsprechen, werden aufgrund der vordefinierten Algorithmen Warnungen an das Analyseteam geschickt, die die Daten mit ihrer eigenen Einschätzung an die Fachabteilung weitergeleiten. In Kombination mit den fachlichen Einschätzungen der Fachbehörden und den durch die Risikoanalyse entsteht somit eine klarere Risikoeinschätzung, die die Steuer- und Zollbehörden nutzen um weitere Schritte einzuleiten. Entweder werden die Risikoprofile des Unternehmens auf die neue Situation angepasst, so dass keine Warnungen mehr entstehen, oder Betriebsprüfer leiten Kontrollen noch am gleichen Tag ein.

Diese Art der Echtzeitanalyse und –interpretation von großen Datenströmen erlaubt es den Estnischen Steuer- und Zollbehörden Informationen über die gegenwärtige Steuersituation des Landes zu ermitteln. Zukünftig können die bereits etablierten Tools auch dafür genutzt werden um aus den in den Finanzströmen erkennbaren Mustern vorherzusehen, ob es einem Unternehmen schlecht gehen wird. Predictive analytics können dann auch dazu beitragen die Belastungen des Staates und das Aufkommen potentieller sozialer Probleme frühzeitig zu erkennen und eventuell präventiv einzugreifen – zumindest vorbereitet zu sein.

 

Professor Dr. Ines Mergel ist Professorin für Public Administration an der Universität Konstanz wo sie zu Themen der Digitalen Transformation der öffentlichen Verwaltung forscht und lehrt. Kontakt: ines.mergel@uni-konstanz.de

LSE Impact of Social Sciences blog: What does Big Data mean to public affairs research? Understanding the methodological and analytical challenges

The following text was originally prepared for LSE’s Impact of Social Sciences Blog and reposted here.

===

The term ‘Big Data’ is often misunderstood or poorly defined, especially in the public sector. Ines Mergel, R. Karl Rethemeyer, and Kimberley R. Isett provide a definition that adequately encompasses the scale, collection processes, and sources of Big Data. However, while recognising its immense potential it is also important to consider the limitations when using Big Data as a policymaking tool. Using this data for purposes not previously envisioned can be problematic, researchers may encounter ethical issues, and certain demographics are often not captured or represented.

In the public sector, the term ‘Big Data’ is often misused, misunderstood, and poorly defined. Public sector practitioners and researchers frequently use the term to refer to large data sets that were administratively collected by a government agency. Though these data sets are usually quite large and can be used for predictive analytics, administrative data does not include the oceans of information that is created by private citizens through their interactions with each other online (such as social media or business transaction data) or through sensors in buildings, cars, and streets. Moreover, when public sector researchers and practitioners do consider broader definitions of Big Data they often overlook key political, ethical, and methodological complexities that may bias the insights gleaned from ‘going Big’. In our recent paper we seek to provide a clearer definition that is current and conversant with how other fields define Big Data, before turning to fundamental issues that public sector practitioners and researchers must keep in mind when using Big Data.

Defining Big Data for the public sector

Public affairs research and practice has long profited from dialogue with allied disciplines like management and political science and has more recently incorporated insights from computational and information science. Drawing on all of these fields we define Big Data as:

“High volume data that frequently combines highly structured administrative data actively collected by public sector organizations with continuously and automatically collected structured and unstructured real-time data that are often passively created by public and private entities through their internet.”

This definition encompasses the scale of newly emerging data sets (many observations with many variables) while also addressing data collection processes (continuous and automatic), the form of the data collected (structured and unstructured), and the sources of such data (public and private). The definition also suggests the ‘granularity’ of the data (more variables describing more discrete characteristics of persons, places, events, interactions, and so forth), and the lag between collection and readiness for analysis (ever shorter).

Methodological and analytical challenges

Defined thus Big Data promises access to vast amounts of real-time information from public and private sources that should allow insights into behavioral preferences, policy options, and methods for public service improvement. In the private sector, marketing preferences can be aligned with customer insights gleaned from Big Data. In the public sector however, government agencies are less responsive and agile in their real-time interactions by design – instead using time for deliberation to respond to broader public goods. The responsiveness Big Data promises is a virtue in the private sector but could be a vice in the public.

Moreover, we raise several important concerns with respect to relying on Big Data as a decision and policymaking tool. While in the abstract Big Data is comprehensive and complete, in practice today’s version of Big Data has several features that should give public sector practitioners and scholars pause. First, most of what we think of as Big Data is really ‘digital exhaust’ – that is, data collected for purposes other than public sector operations or research. Data sets that might be publicly available from social networking sites such as Facebook or Twitter were designed for purely technical reasons. The degree to which this data lines up conceptually and operationally with public sector questions is purely coincidental. Use of digital exhaust for purposes not previously envisioned can go awry. A good example is Google’s attempt to predict the flu based on search terms.

Second, we believe there are ethical issues that may arise when researchers use data that was created as a byproduct of citizens’ interactions with each other or with a government social media account. Citizens are not able to understand or control how their data is used and have not given consent for storage and re-use of their data. We believe that research institutions need to examine their institutional review board processes to help researchers and their subjects understand important privacy issues that may arise. Too often it is possible to infer individual-level insights about private citizens from a combination of data points and thus predict their behaviors or choices.

Lastly, Big Data can only represent those that spend some part of their life online. Yet we know that certain segments of society opt in to life online (by using social media or network-connected devices), opt out (either knowingly or passively), or lack the resources to participate at all. The demography of the internet matters. For instance, researchers tend to use Twitter data because its API allows data collection for research purposes, but many forget that Twitter users are not representative of the overall population. Instead, as a recent Pew Social Media 2016 update shows, only 24% of all online adults use Twitter. Internet participation generally is biased in terms of age, educational attainment, and income – all of which correlate with gender, race, and ethnicity. We believe therefore that predictive insights are potentially biased toward certain parts of the population, making generalisations highly problematic at this time.

In summary, we see the immense potential of Big Data use in the public sector, but we also believe that it is context-specific and must be meaningfully combined with administratively collected data and purpose-built ‘small data’ to have value in improving public programmes. Increasingly, public managers must know how to collect, manage, and analyse Big Data, but they must also be fully conversant with the limitations and potential for misuse.

This blog post is based on the authors’ article, ‘Big Data in Public Affairs’, published in Public Administration Review (DOI: 10.1111/puar.12625).

Note: This article gives the views of the author, and not the position of the LSE Impact Blog, nor of the London School of Economics. Please review our comments policy if you have any concerns on posting a comment below.

About the authors

mergelInes Mergel is full professor of public administration at the University of Konstanz’s Department of Politics and Public Administration. Mergel focuses her research and teaching activities on topics such as digital transformation and adoption of new technologies in the public sector. Her ORCID id is 0000-0003-0285-4758 and she may be contacted at ines.mergel@uni-konstanz.de.

rethemeyerKarl Rethemeyer is Interim Dean of the Rockefeller College of Public Affairs & Policy, University at Albany, State University of New York. Rethemeyer’s primary research interest is in social networks and their impact on political and policy processes. His ORCID iD is 0000-0002-5673-8026 and he may be contacted at kretheme@albany.edu.

isett_portraitKimberley R. Isett is Associate Professor of Public Policy at the Georgia institute of Technology. Her research is centred on the organisation and financing of government services, particularly in health.  Her ORCID id is 0000-0002-7584-0181 and she may be contacted at isett@gatech.edu.

New paper: #BigData in Public Affairs published in PAR

screen-shot-2016-09-13-at-8-03-17-amKarl Rethemeyer, Kim Isett, and I just published a new paper in Public Administration Review with the title “Big Data in Public Affairs“.

Our goal for this article is to define what big data means for our discipline and raising interesting research questions that have not been explored yet. Here is the abstract of our article. Please email me if you can’t access the full paper:

This article offers an overview of the conceptual, substantive, and practical issues surrounding “big data” to provide one perspective on how the field of public affairs can successfully cope with the big data revolution. Big data in public affairs refers to a combination of administrative data collected through traditional means and large-scale data sets created by sensors, computer networks, or individuals as they use the Internet. In public affairs, new opportunities for real-time insights into behavioral patterns are emerging but are bound by safeguards limiting government reach through the restriction of the collection and analysis of these data. To address both the opportunities and challenges of this emerging phenomenon, the authors first review the evolving canon of big data articles across related fields. Second, they derive a working definition of big data in public affairs. Third, they review the methodological and analytic challenges of using big data in public affairs scholarship and practice. The article concludes with implications for public affairs.

Reference:

Mergel, I., Rethemeyer, R. K., Isett, K. (forthcoming): Big Data in Public Affairs, in: Public Administration Review, DOI: 10.1111/puar.12625.

Award: Research stipend from IBM’s The Center for the Business of Government

 

IBM – The Center for the Business of Government has announced a new round of winners of their research stipends. I won an award to write about my research on digital service transformation in the U.S. federal government.

Here is the announcement text:

The Center for The Business of Government continues to support research by recognized thought leaders on key public management issues facing government executives today.

The Center for The Business of Government continues to support reports by leading thinkers on key issues affecting government today.  We are pleased to announce our latest round of awards for new reports on key public sector challenges, which respond to priorities identified in the Center’s research agenda. Our content is intended to stimulate and accelerate the production of practical research that benefits public sector leaders and managers.

My report will focus on the following topic: “Implementing Digital Services Teams Across the U.S. Federal Government”

In 2014, the White House created the U.S. Digital Service team and the General Services Administration’s 18F group. Both groups are using agile software development processes to design and implement high-profile software projects. The results of this report include lessons learned during the scaling up efforts of digital service teams across the departments of the U.S. federal government. These will focus on managerial design aspects, organizational challenges, motivations of digital swat teams and their department-level counterparts, as well as first outcomes in the form of digital service transformations in each department. This research report aims to support the presidential transition team’s efforts by outlining the current efforts of scaling-up digital service teams and their lessons learned, as well as observable outcomes of digital service teams across the U.S. federal government.

New IBM Report: A Manager’s Guide to Assessing the Impact of Government Social Media Interactions

IBM’s Center for the Business of Government has published a new report: “A Manager’s Guide to Assessing the Impact of Government Social Media Interactions“.IBM Center for the Business of Government: A Manager’s Guide to Assessing the Impact of Government Social Media Interactions

This new report addresses the key question of how government should measure the impact of its social media use.

Social media data – as part of the big data landscape – has important signaling function for government organizations. Public managers can quickly assess what citizens think about draft policies, understand the impact they will have on citizens or actively pull citizens ideas into the government innovation process. However, big data collection and analysis are for many government organizations still a barrier and it is important to understand how to make sense of the massive amount of data that is produced on social media every day.

This report guides public managers step-by-step through the process of slicing and dicing big data into small data sets that provide important mission-relevant insights to public managers.

First, I offer a survey of the social media measurement landscape showing what free tools are used and the type of insights they can quickly provide through constant monitoring and for reporting purposes. Then I review the White House’s digital services measurement framework which is part of the overall Digital Government Strategy. Next, I discuss the design steps for a social media strategy which will be basis for all social media efforts and should include the mission and goals which can then be operationalized and measured. Finally, I provide insights how the social media metrics can be aligned with the social media strategic goals and how these numbers and other qualitative insights can be reported to make a business case for the impact of social media interactions in government.

I interviewed social media managers in the federal government, observed their online discussions about social media metrics, and reviewed GSA’s best practices recommendations and practitioner videos to understand what the current measurement practices are. Based on these insights, I put together a comprehensive report that guides managers through the process of setting up a mission-driven social media strategy and policy as the basis for all future measurement activities, and provided insights on how they can build a business with insights derived from both quantitative and qualitative social media data.

 

Media coverage:

 

Public Administration Review article: A Three-Stage Adoption Process for Social Media Use in Government

Together with my co-author Professor Stuart Bretschneider I wrote an article that was just published for early view in the Public Administration Review (PAR). In this article, we develop a model of social adoption in the public sector. Here is the abstract:

Social media applications are slowly diffusing across all levels of government. The organizational dynamics underlying adoption and use decisions follow a process similar to that for previous waves of new information and communication technologies. The authors suggest that the organizational diffusion of these types of new information and communication technologies, initially aimed at individual use and available through markets, including social media applications, follows a three-stage process. First, agencies experiment informally with social media outside of accepted technology use policies. Next, order evolves from the first chaotic stage as government organizations recognize the need to draft norms and regulations. Finally, organizational institutions evolve that clearly outline appropriate behavior, types of interactions, and new modes of communication that subsequently are formalized in social media strategies and policies. For each of the stages, the authors provide examples and a set of propositions to guide future research.

Full reference:

Mergel, I. and Bretschneider, S. I. (2013), A Three-Stage Adoption Process for Social Media Use in Government. Public Administration Review. doi: 10.1111/puar.12021

Our paper won the Emerald Group’s Citations of Excellence winner 2016 award!

New article: Networks in Public Administration in PMR

CoverSheet PMR articleMy co-authors Jesse Lecy (GSU), Hans Peter Schmitz (SU) and I have published an article in Public Management Review:

Lecy, J., Mergel, I., Schmitz, H. P. (2013): Networks in Public Administration, published online DOI:10.1080/14719037.2012.743577, in: Public Management Review. [Link to pre-publication version on SSRN]

Here is the abstract:

Network-focused research in public administration has expanded rapidly over the past two decades. This rapid growth has created come confusion about terminology and approaches to research in the field. We organize the network literature in public administration using compact citation networks to identify coherent subdomains focused on (1) policy formation, (2) governance and (3) policy implementation. We trace how these domains differ in their approach to defining the role of networks, relationships and actors and to what extent the articles apply formal network analysis techniques. Based on a subsequent content analysis of the sample articles, we identify promising research avenues focused on the wider adoption of methods derived from social network analysis and the conditions under which networks actually deliver improved results.

Please email me in case you want to read the article!

New article “The social media innovation challenge in the public sector”, in: Information Polity

Albert Meijer, Frank Bannister and Marcel Thaens edited a special issue of “Information Polity” with the topic “ICT, Public Administration and Democracy in the Coming Decade”. They put together a tremendous group of international e-Government researchers and today the special issue was posted online. The articles included in the special issue include:

  1. ICT, Public Administration and Democracy in the Coming Decade, by Albert MeijerFrank Bannister and Marcel Thaens
  2. Forward to the past: Lessons for the future of e-government from the story so far, by Frank Bannister and Regina Connolly
  3. The Information Polity: Towards a two speed future? by John A. Taylor
  4. E-Government is dead: Long live Public Administration 2.0 by Miriam Lips
  5. Surveillance as X-ray by C. William R. Webster
  6. Towards a smart State? Inter-agency collaboration, information integration, and beyond by J. Ramon Gil-Garcia
  7. The social media innovation challenge in the public sector by Ines Mergel
  8. A good man but a bad wizard. About the limits and future of transparency of democratic governments by Stephan Grimmelikhuijsen
  9. The Do It Yourself State by Albert J. Meijer
  10. Five trends that matter: Challenges to 21st century electronic government by Hans Jochen Scholl
  11. Why does e-government looks as it does? looking beyond the explanatory emptiness of the e-government concept by Victor Bekkers
  12. Big questions of e-government research by Mete Yıldız

My own article focuses on the innovation challenges government agencies are facing when they are implementing social media:

Abstract: The use of social media applications has been widely accepted in the U.S. government. Many of the social media strategies and day-to-day tactics have also been adopted around the world as part of local Open Government Initiatives and the worldwide Open Government Partnership. Nevertheless, the acceptance and broader adoption of sophisticated tactics that go beyond information and education paradigm such as true engagement or networking strategies are still in its infancy. Rapid diffusion is challenged by informal bottom-up experimentation that meets institutional and organizational challenges hindering innovative tactics. Going forward governments and bureaucratic organizations are also facing the challenge to show the impact of their social media interactions. Each of these challenges is discussed in this article and extraordinary examples, that are not widely adopted yet, are provided to show how government organizations can potentially overcome these challenges.

Full reference: 

Mergel, I. (2012): The social media innovation challenge in the public sector, in: Information Polity,  Vol. 17, No. 3-4, pp. 281–292, DOI 10.3233/IP-2012-000281

Feel free to email me (ines_mergel (at) yahoo dot com) in case you can’t access a digital copy through your library!

New book published: “Social Media in the Public Sector”

I am excited to announce the release of my first sole-authored book: “Social media in the public sector“. It will be officially introduced to the public at the annual NASPAA conference in Austin, TX, on October 18, 2012.

The book is based on my research that started about three years ago. My initial interest started with the success of  Obama’s Internet strategy to reach audiences via social media who are unlikely to interact with politicians or government in general. As the open government initiative developed in the U.S. federal government, I started to interview public managers to understand how they are (re)organizing their standard operating procedures to use social media for regular governing operations in support of the mission of their organizations. The book provides insights into the strategic, managerial, and administrative aspects of social media adoption in the public sector.

The publisher’s book page includes resources for professors who would like to use the book in their e-government classes, including week-by-week Powerpoint slides and an article published in the Journal of Public Affairs Education that outlines my teaching approach and learning experiences.

The book went through a thorough double-blind peer-review process and I would like to thank the three anonymous reviewers for their invaluable feedback.

Next month an accompanying field guide will be released.

Here is a link to the instructor resources on Jossey-Bass/Wiley’s website.

Blurb:

In today’s networked world, the public sector is tapping into new media applications to increase government organizations’ participation, transparency and collaboration. The book contains a review of the current state of the public administration literature and shows how Government 2.0 activities can potentially challenge or change the existing paradigms. It includes an overview of each of the tools used to increase participation, transparency and collaboration. The book also highlights case examples at the local, state, federal and international levels. The author offers recommendations for the implementation processes at the end of each chapter and includes suggested readings and references.

Endorsements

Comprehensive and compelling, Social Media in the Public Sector makes the case that to achieve Government 2.0, agencies must first adopt Web 2.0 social technologies. Ines Mergel explains both how and why in this contemporary study of traditional institutions adopting and adapting to new technologies.
Beth Simone Noveck, United States Deputy Chief Technology Officer (2009-2011)

Ines Mergel moves beyond the hype with detailed, comprehensive research on social media technologies, use, management and policies in government. This book should be required reading for researchers and public managers alike.
Jane Fountain, Professor and Director, National Center for Digital Government, University of Massachusetts Amherst

Professor Mergel has produced a foundational work that combines the best kind of scholarship with shoe-leather reporting and anthropology that highlights the debates that government agencies are struggling to resolve and the fruits of their efforts as they embrace the social media revolution. Social Media in the Public Sector is a first and sets a high standard against which subsequent analysis will be measured.
Lee Rainie, Director, Pew Research Center’s Internet & American Life Project

Dr. Mergel is an award-winning author who again wields her story skills in this book. She excels in explaining in concrete, practical terms how government managers can use social media to serve the public. Her book puts years of research into one handy guide. It’s practical. It’s readable. And it’s an essential read.
John M. Kamensky, Senior Fellow, IBM Center for The Business of Government

JVWR: MuniGov 2.0, A New Residency Requirement: Local Government Professionals in Second Life

Michelle Garder, Pam Broviak, Bill Greeves and I have just published a paper in the Journal of Virtual World Research. Here is the abstract and link to the pdf file:

The virtual world Second Life allows social interactions among avatars  – online representations of real-life people – and is slowly adopted in the public sector as a tool for innovative ways to interact with citizens, interorganizational collaboration, education and recruitment (Wyld 2008). Governments are setting up online embassies, voting simulations, interactive learning simulations and virtual conferences. While there are  very prominent and elaborate examples on the federal and state level of government, we have seen only a handful of applications on the local level. One of these local examples is  MuniGov2.0  – a collaboration of municipal government professionals who regularly  meet in Second Life. The goal of the group is  to  support each others geographically  distributed implementation attempts to incorporate new technologies in the public sector. Interviews with the founding members and core group show clear mission-specific needs  that Second Life collaboration can support, but that there are also technological and behavioral challenges involved using this highly interactive environment. The article will highlight the challenges, how they were met, lessons learned, future directions of the  project and ends with recommendations for the use of Second Life in local government.

Full reference:

Mergel, I., Gardner, M., Broviak, P., Greeves, B. (2011): MuniGov20, A New Residency Requirement: Local Government Professionals in Second Life, in: Journal of Virtual World Research, Volume 4, Number 2: Goverment & Military.

Keywords: Virtual worlds, Second Life, online collaboration, local government, Gov 2.0, Web   2.0