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The purpose of this paper is to measure the effectiveness of the hedging with futures currency contracts. Measuring the effectiveness of hedging has become mandatory for Indian companies as the new Indian accounting standards, Ind-AS, specify that the effectiveness of hedges taken by the companies should be evaluated using quantitative methods but leaves it to the company to choose a method of evaluation.

The paper compares three models for evaluating the effectiveness of hedge – ordinary least square (OLS), vector error correction model (VECM) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH) model. The OLS and VECM are the static models, whereas DCC-MGARCH is a dynamic model.

The overall results of the study show that dynamic model (DCC-MGARCH) is a better model for calculating the hedge effectiveness as it outperforms OLS and VECM models.

The new Indian accounting standards (Ind-AS) mandates the calculation of hedge effectiveness. The results of this study are useful for the treasurers in identifying appropriate method for evaluation of hedge effectiveness. Similarly, policymakers and auditors are benefitted as the study provides clarity on different methods of evaluation of hedging effectiveness.

Many previous studies have evaluated the efficiency of the Indian currency futures market, but with rising importance of hedging in the Indian companies, Reserve Bank of India’s initiatives and encouragement for the use of futures for hedging the currency risk and now the mandatory accounting requirement for measuring hedging effectiveness, it has become more relevant to evaluate the effectiveness of hedge. To the authors’ best knowledge, this is one of the first few papers which evaluate the effectiveness of the currency future hedging.

The objective of this paper is to understand the benefits and utility of massive open online courses (MOOCs) as perceived by the student, vis-à-vis internship and determine the factors that influence student motivation and distraction in adoption of MOOCs.

An empirical study is conducted through a survey; data are collected through a structured questionnaire. The technology acceptance model (TAM) is used as the base framework. For data analysis, Statistical Product and Service Solutions–Analysis of Moment Structures (SPSS–AMOS) 24.0 is used.

The impact of context-specific distinctive features of MOOCs and characteristics of students on user satisfaction are examined through perceived ease of use and perceived usefulness. In the study, it is found that positive social influence and better facilitating conditions improve perceived ease of use and perceived usefulness leading to a better user satisfaction. Self-regulation positively influences self-efficacy among students while pursuing MOOCs. Contrary to the past researches, it is found that in the pandemic environment self-efficacy is not impacting perceived ease of use, perceived usefulness and satisfaction.

The findings of this study will benefit MOOCs developers and Higher Education Institutes (HEIs) in deeper understanding the significant factors affecting MOOC usage in higher education.

The study is ingrained to find the causes which will lead to user satisfaction of MOOCs by post-graduation students of B-schools in India. This is an original research and primary data has been collected for decision-making.

The purpose of this study is to understand the antecedents of omni-channel shopping with reference to the intention to purchase fashion products by millennials and their perspective towards the omni-channel method of shopping.

The research is based on a quantitative research technique comprising of 302 respondents. A structured questionnaire has been adopted for the survey and to collect data from millennials from India. The questionnaire consisted of 27 constructs, which were measured using a five-point Likert’s scale. In the first step first-order confirmatory factor analysis is carried out, by using the software IBM AMOS-20. The initial model is generated for six constructs, and outcomes are used to analyse the model’s goodness of fit and construct validity. In the second step, the conceptual model is tested through path analysis using structural equation modelling.

The findings indicate that perceived usefulness (PU) significantly affects the continuance intention of usage towards omni-channels. Perceived ease of use does not significantly affect continuance intention of towards usage of omni-channels, and it does not seem to have a significant effect on PU. Cost effectiveness and customer engagement of omni-channel have a significant effect on the continuance intention of its use. Finally, continuance intention towards usage of omni-channel does significantly affects the actual use of omni-channel.

The research on omni-channel for purchasing fashion products is meagre and this particular study with the usage of Technology Acceptance Model including millennials is adding value towards the knowledge base of marketing. This research develops a theoretical framework building on the technology adoption model and empirically tested it.

The purpose of this paper is to understand the reason of attraction for the young professionals (who left their paid employment) to pursue social entrepreneurship (SE) education, to understand role played by SE education program on developing entrepreneurship knowledge and skills to create social impact and to explore the influence of SE education on their career choices and job-preferences.

This exploratory study uses qualitative methodology to collect data from 16 alumni of Master of Arts in Social Entrepreneurship (MASE) Program, Tata Institute of Social Sciences, Mumbai, India.

The findings indicate that the knowledge and skills learned through the MASE program played a significant role to create an entrepreneurial mindset and put such skills into action to create impact (as job creator/entrepreneur or job seeker/intrapreneur) as well any change in their career choice, job-preference and job-mobility. The findings force us to re-define “success of SE education”, as in both the cases, they are creating social impact using their entrepreneurship knowledge and skills. Career advancement and personal growth opportunities, and their willingness to create impact as decision makers act as strongest motivators to choose the program. Furthermore, the study also highlights the additional factors, which influence their decision of choosing/not choosing SE as career option.

The findings cannot be generalized. The qualitative data is analyzed inductively to arrive at the findings.

The findings are relevant for SE educators and also the policy makers. Promotion of SE education will not only create employment for others, but will also address several other social problems, and contribute to inclusive development of the country.

The uniqueness lies in understanding the motivations behind the decision of pursuing MASE program then followed by exploring the influence of SE education on their career choices and job-preferences.

There is lack of research on key governance issues (KGIs) to expedite the sustainability of corporate governance reforms in the Indian context. The purpose of this paper is to formulate a list of KGIs that would help in sustainability enhancement of corporate governance regime in India vis-à-vis other global counterparts.

First, governance issues have been identified after a thorough literature review and after taking opinion and suggestions of experts. Second, data have been collected through the questionnaire survey. Lastly, a model based on fuzzy set theory has been designed to identify the KGIs for the sustainability enhancement of corporate governance regime in the Indian context.

Five KGIs have been identified in this study based on fuzzy set theory, namely, ownership structure of the companies, code of best practices of corporate governance, regulatory framework including monitoring institutions of the country, untrue independence of independent directors in decision-making and judiciary system of the country.

The KGIs identified for the Indian economy in this study can be a useful reference for the regulators and policymakers to fill the present quality gap and devise measures to curb noncompliance and or implementation of laws on the ground level.

The KGIs identified for the Indian economy in this study can be a useful reference for the regulators and policymakers to fill the present quality gap and devise measures to curb noncompliance and/or implementation of laws on the ground level.

The novelty of this study stems from the fact that very few studies have assessed the perception of stakeholder’s about the current corporate regime in India. No study has identified KGIs.

The purpose of this paper is to study the lead-lag relationship between the futures and spot foreign exchange (FX) market in India to understand the price discovery mechanism and the relationship between these two markets.

The estimation of lead-lag relationship is realized in three steps. First unit root and stationarity tests (Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski-Phillips-Schmidt-Shin) are applied to check the stationarity of the data. Second, cointegration tests (Engle and Granger’s residual based approach and Johansen’s cointegration test) are applied to determine long run relationship between the markets. Third, error correction estimation is carried out by applying Vector Error Correction Model (VECM) to determine the leading market.

The study finds that there is a long run relationship between the futures and spot market where the futures market has emerged as the leading market for the four currencies studied in the paper.

Majorly, the studies on Indian FX market limit themselves to identifying the efficiency of the market and the studies which talk about the lead-lag relationship focus on the Indian stock market. This paper enhances the existing literature on Indian FX market by exploring the less explored subject of the lead-lag relationship between futures and spot FX market in India.

The purpose of this paper is to explore the tourists' perception of smart tourism with the application of virtual reality and design a framework of smart tourism with elements of VR for Indian Tourism especially in the periods of the pandemic COVID-19. The ever-evolving and unprecedented COVID 19 situation had posed extreme challenges for the travel and tourism industry. In such conditions, it is becoming increasingly necessary to rely on digital technologies, ICT and smart tourism. ICT has served as a catalyst for innovations in tourism.

This study investigates the impact of smart tourism and virtual reality technology on the perception of tourists towards travelling decisions during and post COVID-19 scenario. The respondents involved in the study were tourists travelling in India, the tourists come from different parts of India. A structured questionnaire has been administered to collect data from 224 travellers across India. The questionnaire consisted 22 constructs. The constructs in this section were measured using a five-point Likert scale ranging. In the first step, the first order Confirmatory Factor Analysis (CFA) is carried out, by using the software IBM AMOS-20. The initial model is generated ix constructs, and outcomes are used to analyse the model's goodness of fit and construct validity. In the second step, Structural Equation Modelling (SEM) is carried out to do the path analysis of the proposed model. The effect of relationships amongst the theoretical constructs is also analysed using SEM.

The findings imply that the application of smart tourism along with virtual reality forms a positive perception of tourists and provides a sustainable platform for tourism organizations in Indian tourism. Virtual reality-based tourism has emerged as alternate for the tourism industry during the times of Covid, which in long run can be seen as a substitute to traditional tourism. The increasing use of blue ocean concepts, to delivery high-value experience at low cost has complimented the tourism industry. The researchers have made a modest attempt by proposing a blended model of smart tourism with virtual reality as a blue ocean strategy and which would ultimately facilitate the sustainability of the Industry by creating multi-dimensional values of experience for tourists in India.

The researchers have made a modest attempt by proposing a blended model of smart tourism with virtual reality as a blue ocean strategy, which would ultimately facilitate the industry's sustainability by creating multi-dimensional values of experience for tourists in India.

This qualitative study designs a smart tourism system with the use of the recent advances in ICT and Virtual Reality (VR), as a bridging solution and the saviour of the tourism sector in India during COVID 19. The integration of ICT into the travel experience has resulted in the social phenomena of smart tourism. This has led to a rise in use of smart tourism tools among tourism service providers.

Corporate treasurers manage the currency risk of their organization by hedging through futures contracts. The purpose of this paper is to evaluate the effectiveness of hedging by US currency futures contracts by taking into account the efficiency of the currency market.

The static models for calculating hedge ratio are as popular as dynamic models. But the main disadvantage with the static models is that they do not consider important properties of time series like autocorrelation and heteroskedasticity of the residuals and also ignore the cointegration of the market variables which indicate short-run market disequilibrium. The present study, therefore, measures the hedging effectiveness in the US currency futures market using two dynamic models – constant conditional correlation multivariate generalized ARCH (CCC-MGARCH) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH).

The study finds that both the dynamic models used in the study provide similar results. The relative comparison of CCC-MGARCH and DCC-MGARCH models shows that CCC-MGARCH provides better hedging effectiveness result, and thus, should be preferred over the other model.

The findings of the study are important for the company treasurers since the new updated Indian accounting standards (Ind-AS), applicable from the financial year 2016–2017, make it mandatory for the companies to evaluate the effectiveness of hedges. These standards do not specify a quantitative method of evaluation but provide the flexibility to the companies in choosing an appropriate method which justifies their risk management objective. These results are also useful for the policy makers as they can specify and list the appropriate methods for evaluating the hedge effectiveness in the currency market.

Majorly, the studies on Indian financial market limit themselves to either examining the efficiency of that market or to evaluate the effectiveness of the hedges undertaken. Moreover, most of such works focus on the stock market or the commodity market in India. This is one of the first studies which bring together the concepts of efficiency of the market and effectiveness of the hedges in the Indian currency futures market.

This study aims to examine the impact of home–host country distance on the cross-border mergers and acquisitions performance.

The results of this study are based on a final sample of 483 completed cross-border deals involving BRICS nation acquirers and targets spread across a set of 27 nations. While controlling for prior experience, among other factors, the impact of nine institutional distance dimensions on deal performance is examined. Cumulative abnormal returns calculated over the select event windows are used as a measure of deal performance.

The results of this study validate the explanatory power of cross-country distance and exhibit that financial and cultural distance exert a negative influence on deal performance, whereas political and global connectedness distance positively impacts performance. Interestingly, geographic distance is not found to be related to performance outcomes.

The results of this study caution against possible aggregation of the cross-country distance measure and point towards the need to acknowledge and analyse the multi-dimensional nature of distance.

The results of this study are expected to aid managers in devising internationalisation strategies and target selection, maximising their performance and shareholder wealth.

This study contributes to the knowledge of internationalisation and cross-country distance. It presents as one of the first to investigate the impact of institutional distance on deal performance using a substantially large multi-country emerging market data set.

The study aims to evaluate and compare the mergers and acquisitions (M&As) performance utilising a sample of deals originating from Brazil, Russia, India, China and South Africa (BRICS). In addition to nation-wise performance analysis, a further sub-sample analysis is conducted based on the target location (domestic and cross-border), development status (developed and emerging) and the acquired ownership stakes (majority and minority).

The final sample of the study includes 7,105 deals announced between 2000 and 2019. M&A performance is proxied by the abnormal returns earned over the select event windows. Multiple parametric and non-parametric tests are employed for testing the robustness.

The results indicate significant performance differences across BRICS markets, with the highest and lowest abnormal returns reported for Chinese and Russian acquirers, respectively. The disaggregated analysis also affirms the performance differences for the select sub-samples.

The study highlights the need for acknowledging and expounding the differences in M&As across emerging markets. Further, the results of the study provide a possible explanation of the disagreement over the M&A performance results reported in the previous literature.

Acknowledging and understanding the potential performance differences based on location, ownership strategies and development status can aid executives in sharpening decision-making and also help general investors.

The study contributes by examining a comprehensive sample of deals across five major emerging economies, as against the majority of previous studies which have their results based on either single nation samples or have utilised only a sub-sample of domestic or foreign acquisitions.