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نتیجه جستجو - اقدامات جمعی آنلاین

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Why tourists engage in online collective actions in times of crisis: Exploring the role of group relative deprivation
چرا گردشگران در مواقع بحرانی به اقدامات جمعی آنلاین می پردازند: بررسی نقش محرومیت نسبی گروه-2020
Social media platforms empower tourists to engage in secondary crisis communication and even take collective action against destinations. Such online actions result in challenges for tourism destinations related to crisis management and image restoration, especially for human-induced tourism crises caused internally by managerial or institutional faults. Based on the theory of relative deprivation and examining the reputation crisis of Snow Town as a case, this study aims to understand the cognitive, emotional, and behavioral mechanisms of tourists’ secondary crisis communications. The results show that group relative deprivation perceived by tourists can elicit their group-based anger and distrust toward the destination and can also lead to online collective action and offline behavioral intentions (here, negative travel intention). Additionally, the results show a reverse influence of aim-oriented and behavior-oriented online collective actions on travel intentions and that aimoriented actions positively mediate anger and travel intentions. This study provides new insights into how a personal incident evolves to become a tourism crisis during social-media communications and discusses managerial implications for crisis management and post-crisis marketing.
Keywords: Group relative deprivation | Group-based anger | Destination trust | Collective online actions | Secondary crisis communication | Crisis management
مقاله انگلیسی
2 Big data prediction of durations for online collective actions based on peak’s timing
پیش بینی داده های بزرگ زمانی برای اقدامات جمعی آنلاین بر اساس زمان قله-2018
Peak Model states that each collective action has a life circle, which contains four periods of ‘‘prepare’’, ‘‘outbreak’’, ‘‘peak’’, and ‘‘vanish’’; and the peak determines the max energy and the whole process. The peak model’s re-simulation indicates that there seems to be a stable ratio between the peak’s timing (TP) and the total span (T) or duration of collective actions, which needs further validations through empirical data of collective actions. Therefore, the daily big data of online collective actions is applied to validate the model; and the key is to check the ratio between peak’s timing and the total span. The big data is obtained from online data recording & mining of websites. It is verified by the empirical big data that there is a stable ratio between TP and T; furthermore, it seems to be normally distributed. This rule holds for both the general cases and the sub-types of collective actions. Given the distribution of the ratio, estimated probability density function can be obtained, and therefore the span can be predicted via the peak’s timing. Under the scenario of big data, the instant span (how long the collective action lasts or when it ends) will be monitored and predicted in real-time. With denser data (Big Data), the estimation of the ratio’s distribution gets more robust, and the prediction of collective actions’ spans or durations will be more accurate.
Keywords: Big data ، Prediction ، Peak’s timing ، Ratio ، Span ، Collective actions
مقاله انگلیسی
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بازدید امروز: 3680 :::::::: بازدید دیروز: 3097 :::::::: بازدید کل: 37947 :::::::: افراد آنلاین: 39