Received: 13th Nov 2021 | Review: 6th Jan 2022 | Accepted: 12th Feb 2022
Volume 30, Issue-2, April 2022
Decision making is a critical challenge under disruptive conditions. Information flow as critical component to decision making may exacerbate or mitigate the impact of disruptive conditions. Such highly complex and unpredictable conditions produce a high demand for information. Extant literature was found to be critical of unidirectional and sender-oriented models in crisis communication which essentially blocks the feedback loop and paralyzes the crisis managers to roll-out responses. However, the pervasive social media has created new patterns of dynamic information exchange to empower the individuals to be engaged in a more evidence-based participatory form of crisis communication to frame decisions. This study used social media analytics to identify the decision clusters arising out of information exchange over social media under disruptive uncertainties. The Theory of Complexity by Edgar Morin was used as the epistemological foundation of the study. Crawled data was used from the Tourism Tribe Facebook fan page. Normalized degree and betweenness centrality measures were used to analyse the semantic networks. Tourism Tribe exhibited the highest degree centralities for both before and during the pandemic-driven disruptions. Four individuals (names changed for anonymity) were identified to be the most influential in decision making based on information shared. The causality between uncertainty and decision revealed a wide array of decision parameters – health precautions to alternative leisure engagement. The study provided practical implications for a number of stakeholders. The tourism service providers and product designers are likely to get deeper insights into the choice and priorities of the tourists confronting disruptive conditions and may re-strategise tourism offers. The alternative leisure and recreational platforms (OTT, gaming platforms etc.) may introduce new products and/or re-design their schemes.
Key words: disruption, social media, analytics, semantic networks, influential
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