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The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility.

The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis.

The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility.

This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.

The purpose of this paper is to explore the antecedents of the behavioral intention and adoption of mobile payment services like m-wallets and m-banking by users in India. This is done by examining the diffusion of mobile payment technology within an extended framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The study attempts to extend the UTAUT model further by introducing three more constructs, namely- perceived cost, perceived risk and demonetization effect and analyzes the impact of demonetization that happened in India from November 8, 2016 to December 30, 2016 on the mobile payment service adoption process. Demonetization event is a case in point to assess whether forced adoption breaks the normal diffusion process or lends support to the same in the long term.

A survey was conducted in order to gauge the intention behind the adoption of mobile payment modes by users in India. The questionnaire was administered online solely and 880 responses were received within a period of 20 days from February 3, 2017, to February 23, 2017, using Google Forms as a medium. Usable responses were 640. The study adopted partial least square based structural equation modeling (PLS-SEM) technique to analyze the relation between latent variables: performance expectation, effort expectation, social influence, facilitating conditions, perceived cost, perceived risk, demonetization effect, behavioral intention and usage. For this purpose, SmartPLS3.0 software was used to create path diagrams and calculate estimate the significance of factor loadings using the bootstrap technique.

The key results indicates that behavioral intention, demonetization and facilitating conditions have a positive and significant impact on the adoption of mobile payment services in India. Overall, Model 3, which was extended UTAUT model, was observed to be a better model in explaining the antecedents of behavioral intention and usage. In addition to UTAUT antecedents, perceived cost and perceived risk proved to have additional explanatory power as antecedents of behavioral intention. Age acts as a moderating variable consistently across three models, implying that younger users give more importance to effortless interface of mobile payment services and get more influenced by peers and society that shapes their intention to use mobile payment services.

It is first of its kind attempt to assess the role of Demonetization in examining the antecedents of behavioral intention and adoption of mobile payment services by users in India under an extended UTAUT model. This study comprehensively examined the impact of forced adoption of mobile payment services by users in India in a natural setting provided by demonetization event that took place in India by conducting a primary survey right itself in the month of February, 2017 to get first hand response from the Indian users.