Examination of relationships among serendipity, the environment, and individual differences

McCay‐Peet, Lori; Toms, Elaine G.; Kelloway, E. Kevin

doi:10.1016/j.ipm.2015.02.004

Cited by 63 publications

(71 citation statements)

References 28 publications

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“…Thus, the system has to apply trial-and-error-and wait-and-see-based behaviours to solve the new problem (Vanderhaegen and Caulier 2011). Serendipity is a conflict of goal that relates to unexpected discovery that demonstrates that the initial baseline is wrong (McCay-Peet et al 2015): what is obtained has nothing to do with what it was expected. Cognitive blindness such as perseveration or the tunnelling effect is a conflict of perception when human experts with high levels of knowledge do not hear alarms even though the latter are functioning correctly (Dehais et al 2012).…”

Section: Taxonomy Of Dissonancesmentioning

confidence: 99%

Can dissonance engineering improve risk analysis of human–machine systems?

Vanderhaegen

Carsten

2017

Cogn Tech Work

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The paper discusses dissonance engineering and its application to risk analysis of human-machine systems. Dissonance engineering relates to sciences and technologies relevant to dissonances, defined as conflicts between knowledge. The richness of the concept of dissonance is illustrated by a taxonomy that covers a variety of cognitive and organisational dissonances based on different conflict modes and baselines of their analysis. Knowledge control is discussed and related to strategies for accepting or rejecting dissonances. This acceptability process can be justified by a risk analysis of dissonances which takes into account their positive and negative impacts and several assessment criteria. A risk analysis method is presented and discussed along with practical examples of application. The paper then provides key points to motivate the development of risk analysis methods dedicated to dissonances in order to identify the balance between the positive and negative impacts and to improve the design and use of future human-machine system by reinforcing knowledge.

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Section: Taxonomy Of Dissonancesmentioning

confidence: 99%

Can dissonance engineering improve risk analysis of human–machine systems?

Vanderhaegen

Carsten

2017

Cogn Tech Work

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“…Serendipity is a positive experience relating to the use of social media, resulting from a dynamic, messy information space that is unpredictable and full of surprises. McCay-Peet et al [38] found that social media environments may be better at leading to the unexpected, a facet of serendipity, than websites, databases, and search engines. Serendipitous experiences are often social in nature, involving a transfer of knowledge or information between people [37], a function for which social media platforms are aptly designed (see uses and gratifications).…”

Section: Serendipitymentioning

confidence: 99%

A Model of Social Media Engagement: User Profiles, Gratifications, and Experiences

McCay‐Peet

Quan‐Haase

2016

Why Engagement Matters

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“…She characterised information encountering on social media by identifying six elements of user, motivation, context, information behaviour, information, and information need. More recently, McCay-Peet, Toms, and Kelloway [4] also surveyed 289 professionals, academics, and graduate students to understand whether digital environments have the potential to facilitate information encountering. They found that social media sites support information encountering more than traditional tools such as databases, search engines, or intranets by connecting people to other people with interesting ideas and information.…”

Section: Information Encounteringmentioning

confidence: 99%

“…This also covers mechanisms that enhance the visibility and availability of existing knowledge which then increases the participants' encountering more information. Several authors [12][13][14] also argued that information encountering is not only about finding unexpected information but also about making unexpected connection between different pieces of information, people, ideas, and resources. However, this was out of the focus of this study but could be a theme for future studies.…”

Section: Introductionmentioning

confidence: 99%

Information encountering on social media and tacit knowledge sharing

Panahi

Watson

Partridge

2015

Journal of Information Science

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The purpose of this paper is to investigate how social media may support information encountering (i.e., where individuals encounter useful and interesting information while seeking or browsing for some other information) and how this may lead to facilitation of tacit knowledge creation and sharing. The study employed a qualitative survey design that interviewed twenty-four physicians who were active users of social media to better understand the phenomenon of information encountering on social media. The data was analysed using the thematic analysis approach. The study found six main ways through which social media supports information encountering. Furthermore, drawing upon knowledge creation theories, the study concluded that information encountering on social media facilitates tacit knowledge creation and sharing among individuals. The study provides new directions for further empirical investigations to examine whether information encountering on social media actually leads to tacit knowledge creation and sharing. The findings of the study may also provide opportunities for users to adopt social media effectively or gain greater value from social media use.

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Examination of relationships among serendipity, the environment, and individual differences

Cited by 63 publications

References 28 publications

Can dissonance engineering improve risk analysis of human–machine systems?

Can dissonance engineering improve risk analysis of human–machine systems?

A Model of Social Media Engagement: User Profiles, Gratifications, and Experiences

Information encountering on social media and tacit knowledge sharing

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