Examining Contributions to a Corporate Microblog as a Basis for an Employee Incentive System
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Jochen Adler
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Examining Contributions to a Corporate Microblog as a Basis for an Employee Incentive System
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Anchor Academic Publishing
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9783954895182
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1
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CHF 31.20
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Informatik
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English
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89
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kein Kopierschutz/DRM
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PC/MAC/eReader/Tablet
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Social media and social networks seem to be conquering human relationships. Corporations increasingly expect business benefits from such platforms for employee-to-employee networking and internal collaboration. Firstly, however, social software platforms have to be introduced into an organization successfully, which often requires strategic and cultural changes before the new technology effectively supports everyday work tasks and corporate procedures. Companies will thus be looking for ways to promote usage of the new platforms and influence employee behavior accordingly. After a review of selected relevant scientific theory and practical examples of social software analysis, this publication analyzes over 50,000 employee contributions to an internal microblogging platform used over a period of two years in a global corporation. The subsequent analysis tries to find a metric for organizationally desired behavior. The nature of microblogging - short text messages that propagate across a network by means of very basic mechanisms, like subscription, repeats or responses - seems very well suited for such a purpose. Two metrics, describing an employees' influence across the network and the utility of their contributions as recognized by peers, were combined in a single numerical score. Such scoring could be used as a factor within an employee incentive system intended to reward extraordinarily active or useful contributors.
Jochen Adler, born 1975, began his career as a self-starter in software engineering in the early 1990s and has since worked as a business analyst, project manager and IT/management consultant across Europe and in the U.S. In 2007, he joined the IT organiz
Text Sample: Chapter 2, Social Software and Enterprise 2.0: Microblogging is a rather new phenomenon. In March 2006, for example, the now omnipresent social networking service Facebook introduced a feature allowing its users to share brief status updates among their friends. July the same year, the dedicated microblogging service Twitter was launched. Twitter is now immensely popular, its name being defacto synonymous to microblogging in popular perception. Adoption of the Twitter service is seemingly evergrowing . Due to the intensity of innovation in this area, the object of investigation changes rapidly and scientific analysis becomes relatively difficult. Meanwhile, however, there seems to be a broad consensus to classify microblogging as a social technology (a social medium or, more generally, social software), and, as such, as a Web 2.0 phenomenon. Since this research examines the use of microblogging in a corporate context, it is also necessary to present a definition of Enterprise 2.0, an umbrella term that has been coined to characterize business applications of Web 2.0 technology and principles. For the purpose of this treatment, it thus seems practical to define these categories - Web 2.0, social software, Enterprise 2.0 - prior to examining microblogging as a specific technique. 2.1, The Web 2.0: The term Web 2.0 is quite frequently used, but controversial. In a stricter sense, Web 2.0 is not a scientific definition, but rather the outcome of a brainstorming with practitioners : At an industry conference in 2005, attendants were asked to name novel, remarkably successful internet services since the burst of the dotcom bubble in 2001. A broad, seemingly diverse range of contributions arose, but upon closer examination, there were also striking similarities. On the one hand, all those Internet offerings were broadly soliciting and encouraging contributions from their users, allowing participation while not requiring the possession of any technical skills. On the other hand, and by contrast to traditional web software, they seemed to facilitate the combination of data from various sources and applications from various areas in an open fashion and in a rather playful way . Another common characteristic of Web 2.0 applications is their openness with respect to the data and services that they provide: In many cases, application programming interfaces (APIs) were provided for unrestricted access, spawning unforeseen, creative uses; allowing the consumption of those services on a wide range of devices and operating system platforms. Resulting from the heuristic definition, arguably, the term Web 2.0 does not seem to be used and understood consistently. The choice of terminology could in fact be criticized: Contrary to what the analogy to a software product's version number (2.0) suggests, no upgrade or enhancement of WWW technology is involved. Technological advances in fact play only a marginal role to constitute this new generation of Internet services: The underlying innovations are supplements or enhancements of conventional Web technology. 2.2, Social Software: An apparently more precise term than Web 2.0 is social software . 'Social software applications are supporting, as part of a socio-technical system, human communication, interaction and collaboration. The actors are thereby leveraging the potential and contributions of a network of active participants.' In this definition, the idea of a system in both the social and the technical senses is crucial: The active inclusion and utilization of participant contributions is the single most important characteristic for social software. For an early example of how an application of this principle has significantly influenced the course of Internet history, let us look at Google's PageRank algorithm: With Page Rank, priority for any given search result does not at all depend on attributes of the page in question, but rather on the quality and number of links from other, external documents to the page in question. PageRank effectively applied the technique of academic citation to Internet search. Rather than considering the properties of the web content itself, the new algorithm assessed how other contributions considered its relevance (assuming that hyperlinks are only placed to content that is considered relevant). PageRank, in essence, was based on relationships between web pages rather than their content. Building on this idea, Google could deliver better and more useful search results than any other Internet search engine at the time: With the introduction of PageRank, search rankings were much harder to manipulate. Nowadays, the social software principle is reaching a lot further. There are countless practical examples of platforms built around substantial contributions from participants, in the Internet as well as for internal corporate use (Intranet). The most popular and successful Internet example for a service built upon community contributions, arguably, is Wikipedia, but there are also examples of corporate Intranet platforms based on Wiki software to provide collections of employee knowledge.
Examining Contributions to a Corporate Microblog as a Basis for an Employee Incentive System
1
Abstract
3
Acknowledgments
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Table of Contents
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Table of Figures
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List of Abbreviations
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1 Introduction
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1.1 Research Thesis
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1.2 Document Structure
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2 Social Software and Enterprise 2.0
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2.1 The Web 2.0
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2.2 Social Software
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2.3 Enterprise 2.0
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2.4 Microblogs and Microblogging
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2.5 Corporate Uses for Microblogging
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2.6 Adoption and Change
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3 Change Management and Incentives
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3.1 Globalization
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3.2 Organizational Change Management (John P. Kotter)
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3.3 Management By Objectives (Peter F. Drucker)
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3.4 Balanced Scorecard (Kaplan and Norton)
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3.5 Technology Acceptance Models
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3.6 Strategic Alignment and Incentive Systems
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4 Conventional Media and Media Reception
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4.1 Print Media
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4.2 Broadcast Media
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4.3 The Internet and Website Analytics
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4.4 Consumer Feedback and Customer Reviews
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4.5 User-Generated Content, Citizen Journalism and Prosumers
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4.6 Impact
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5 Social Software Analysis and Information Diffusion
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5.1 Klout
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5.2 Socialmention
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5.3 Facebook Insights
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5.4 Practical Relevance of Klout and Facebook Insights
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5.5 Information Diffusion
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6 The Data Set
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6.1 Notices
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6.2 Subscription and the Timeline
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6.3 Favorites
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6.4 Repeats
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6.5 Replies
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6.6 Hashtags
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6.7 Group Memberships
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6.8 Examples
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6.9 Interpretations
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7 Analysis, Measurements and Scoring
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7.1 Definition of ‘Desired Behaviors’
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7.2 Hashtags
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7.3 Data Fields
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7.4 Scoring Components
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7.5 Sample Group Selection
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7.6 Influence Metric (INF)
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7.7 Utiliy Metric (UTI)
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7.8 Composite Incentive Score (CIS)
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7.9 Examples
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7.10 Scoring Results
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7.11 Examination of Correlations
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8 Summary
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8.1 Research Methods
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8.2 Summarization of Findings
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8.3 Critique
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8.4 Topics for Further Research
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9 Bibliography and References
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10 Appendix
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10.1 SQL Queries
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About the Author
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