Why Is It Hard to Fight Herding?

Abstract

The ubiquity of information, in part a consequence of the fast growth of Internet technologies, provides individuals with previously unknown opportunities to acquire and share information about new technology products. We witness numerous situations where potential adopters observe the decisions (but not the reasoning) of others and imitate their adoption behaviors. This implies that herd behavior can lead to en mass adoption. However, individuals possessing different characteristics exhibit different degrees of herd behavior. The characteristics of a given technology must also fit with the requirements of the task(s) that a technology adopter wants to fulfill. It is important to understand these phenomena in the herding context because they can influence a technology's staying power. We examine how several different user and technology characteristics interact with the antecedents of herd behavior, observed popularity of prior adoption and perceived uncertainty, to predict one's individual propensity for imitation in technology adoption. We test our research model via an online experiment with 260 respondents. One key finding is that while prior research has not found uncertainty to have the expected effect on propensity to imitate, it does in fact have a significant effect when various individual difference and technology moderators are taken into account.

Influence Factors on Consumers’ Instant Cross-buying under Supermarkets’ Cross-border Integration: From the Perspective of the Elaboration Likelihood Model

“…Herd mentality is measured by three items adapted from Darban and Polites (2020). The items used include “When many people buy in a cross-border integrated supermarket, it will prompt me to want to buy products in different formats,” “When friends and others are recommending, it will prompt me to want to buy products of different formats,” and “When there is a lot of related social media and advertising, it will prompt me to want to buy products in different formats.”…”

“…Faced with the unfamiliar, consumers tend to refer to the buying opinions of other people before making a decision in order to both eliminate incomplete information and reduce the uncertainty of choice as well as reduce the effort of searching for information (Chen et al, 2021; He et al, 2021). Darban and Polites (2020) empirically researched users’ adoption of new technologies and found that their herd mentality had a significant impact on their first use intentions. Shen et al (2016) found that when consumers and online reviewers have similar educational backgrounds and attitudes, they tend not to pay too much attention to product information, but rather imitate their purchasing decisions and adopt their reviews.…”

The establishment of transactive memory system in distributed agile teams engaged in AI-related knowledge work

“…Mattke et al (2020) presented that social media platforms can lead to herding behavior. In the context of AI, it is very important to consider herding behavior among group members, as it will affect the acceptance and persistence of the AI task (Darban and Polites, 2020). Herding behavior is a manifestation of herd mentality, which may require mutual learning and knowledge transfer among members (Li et al , 2014).…”

“…Although individuals with different characteristics will exhibit varying degrees of conformity (Darban and Polites, 2020), conformity will weaken team diversity to some extent. Intellectual diversity facilitates the establishment of TMS by increasing the professionalism and diversity of team members (Lewis and Herndon, 2011).…”

Detecting deception in computer-mediated communication: the role of popularity information across media types

“…While prior studies have shed light on the influence of herd behavior in the IS context in different ways, the influence of different types of PI and how they are presented to users is yet to be distinguished and analyzed (e.g. Darban and Polites, 2020; Sun, 2013; Vedadi and Warkentin, 2020).…”