- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
When groups of consumers share information or express their opinions about products and services, their attitudes or behavior sometime align without centralized coordination, a phenomenon known as herding. Building on pattern-based explanations of herding from the cognitive science literature, we propose a framework to elucidate herding behavior based on three dimensions: the speed of contagion, i.e., the extent to which the behavior spreads in a given time, the number of individuals, i.e., the proportion of the whole population expressing the behavior, and the uniformity of direction, i.e., the extent to which the mass behavior is increasingly uniform with one variant becoming dominant. Based on these dimensions, we differentiate eight patterns of herding behavior from slowly diffusing, small and disparate groups through to rapidly spreading, massive herds expressing a convergent behavior. We explore these herding patterns in an online setting, measuring their prevalence using over four thousand streams of data from the online micro-blogging application, Twitter. We find that all eight patterns occur in the empirical data set although some patterns are rare, particularly those where a convergent behavior rapidly spreads through the population. Importantly, those occurrences that develop into the pattern we call “stampeding,” i.e., the rapid spread of a dominant opinion expressed by many people, generally follow a consistent development path. The proposed framework can help managers to identify such noteworthy herds in real time, and represents a first step in anticipating this form of group behavior.
In this paper, we take the first steps in forming a basic structured framework for distinguishing between different types of herding. Different cases of herding have different characteristics; some spread more quickly, some reach more people and in some a consensus emerges. Some of these characteristics may make one herd important for firms or governments whereas others require less attention. The first objective of this paper is to propose a framework, based on the pattern-based explanation of herding from the cognitive science literature, by which we can identify different patterns of mass behavior. We describe a conceptual framework whereby eight different patterns can be distinguished based on three dimensions: the number of individuals expressing a behavior, the speed of contagion with which the behavior spreads through a population, and whether there is a uniformity of direction to the behavior. The eight resulting herding patterns cover a wide variety of herding types from small, indistinct clusters through to rapid, large-scale and united crowds.