Social media adoption behaviour: Consumer innovativeness and participation intention

With the emergence of social media, the trends of selfies have become common across various social networking platforms as a distinctive way of self-presentation. It has aroused the interest of various scholars to comprehend the consumer adoption behaviour for social media. Thus, built on the innovation diffusion theory (IDT) and theory of planned behaviour (TPB) perspective, this paper developed a model to empirically test whether and how critical factors of consumer selfie-posting behavioural intention on social media affect behavioural intention and word-of-mouth to consequently enhancing their adoption behaviour towards social media to post selfies. The data were gathered from 353 young consumers who post their selfies clicked via smartphone on their social media accounts. The results revealed that consumer innovativeness and participation intention directly and indirectly affect consumer adoption behaviour for social media to post their selfies. Additionally, the study identified that among all critical factors, participation intention and perceived behaviour control have strongest influence on behavioural intention to post selfies followed by consumer innovativeness, attitude towards selfie-posting and subjective norms. The study contributes to the extension of TPB by adding participation intention and positive WOM, adoption of social media. This research validated the significant roles of consumer innovativeness, participation intention, positive WOM and intention to post selfies in predicting the adoption behaviour. Practitioners and marketers of social media sites can improve the usability and effectiveness of positive WOM and intention to post selfies to attract more young consumers.     

Non-linear dynamics of hot and cold cycles in Indian IPO markets: evidence from Markov regime-switching vector autoregressive model

The study aims to examine non-linear relationship between initial public offering (IPO) volume and average monthly initial returns for ‘hot’ and ‘cold’ issuing cycles in the Indian IPO markets using a two-state Markov regime-switching vector autoregressive model. The sample considers 557 IPOs during the period 2004–2014. The study establishes the presence of hot and cold states in Indian IPO markets. It finds bidirectional causality between IPO volume and initial returns for ‘hot’ issuing periods. The empirical findings suggest that the market possesses valuable information content in terms of the past issuing activity which has the potential to increase the predictability of future market behaviour.