Aashish Garg, Muskan Sachdeva, Simarjeet Singh and Pooja Goel
This paper aims to cognizance consumers' intention to participate in collaborative consumption (CC). Also, the gender difference regarding the above is examined.
Abstract
Purpose
This paper aims to cognizance consumers' intention to participate in collaborative consumption (CC). Also, the gender difference regarding the above is examined.
Design/methodology/approach
To quantify the consumers’ intention to participate in CC cross-sectional survey method has been used. In total, 333 potential consumers selected through convenience sampling participated in the survey. The study used the capabilities of the structured equation modelling technique to validate the proposed research model.
Findings
Except for hedonic motives, all other drivers such as reputation, economic benefits, sustainable motives and trust have a significant influence on the intention to participate in CC. The effect of gender was found on the relationship between Trust and Intentions only.
Practical implications
This study can be used as a guiding path in the domain of CC for practitioners, marketers, startups and policymakers as the opinion of potential users has been reported. The results of the study highlight that the consumers’ interest in CC participation and social reputation are the most influential drivers of intention to participate in CC. Marketers should design their strategies in such a way that the individual should feel like a social hero rather than just a responsible consumer while participating in CC.
Originality/value
The present study contributes to the literature by examining the intention to participate in CC through the lens of self-determination theory (SDT), specifically in the Indian context. The authors have also extended the SDT by adding a trust factor that is best to their knowledge not integrated till now. The present study integrated cognitive, economic, psychological and relational aspects to understand CC behavior.
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Kirti Sood and Simarjeet Singh
The present study aims to systematically synthesize the academic and industrial literature on multi-central bank digital currencies (m-CBDCs) arrangements.
Abstract
Purpose
The present study aims to systematically synthesize the academic and industrial literature on multi-central bank digital currencies (m-CBDCs) arrangements.
Design/methodology/approach
The study adopted a unique multivocal literature review methodology that considers both white and grey literature. For white literature searches, the study relied on Scopus, Web of Science (WOS), and Google Scholar bibliometric databases; for grey literature searches, the study used the Google search engine.
Findings
The findings of the study illustrated that M-CBDC arrangements, through various design options, have the potential to revolutionize the contemporary international payment system. M-CBDC arrangements will lead to more integrated financial systems and promote economic growth. However, m-CBDC arrangements will also have serious macroeconomic implications, such as contagion and currency substitution risks.
Research limitations/implications
The present review is one of the earliest reviews of m-CBDC arrangements. In addition, the findings of the study offer valuable insights for both academicians and policymakers.
Originality/value
The study is also one of the pioneer studies in management studies that apply a multivocal literature review methodology.
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Simarjeet Singh, Nidhi Walia, Sivagandhi Saravanan, Preeti Jain, Avtar Singh and Jinesh jain
This study aims to recognize the current dynamics, prolific contributors and salient trends and propose future research directions in the area of alternative momentum investing.
Abstract
Purpose
This study aims to recognize the current dynamics, prolific contributors and salient trends and propose future research directions in the area of alternative momentum investing.
Design/methodology/approach
The study uses a blend of electronic database and forward reference searching to ensure the incorporation of all the significant studies. With the help of the Scopus database, the present study retrieves 122 research papers published from 1999 to 2020.
Findings
The results reveal that alternative momentum investing is an emerging area in the field of momentum investing. However, this area has witnessed an exponential growth in last ten years. The study also finds that North American, West European and East Asian countries dominate in total research publications. Through network citation analysis, the study identifies five major clusters: industrial momentum, earnings momentum, 52-week high momentum, time-series momentum and risk-managed momentum.
Research limitations/implications
The present review will serve as a guide for financial researchers who intend to work on alternative momentum approaches. The study proposes several unexplored research themes in alternative momentum investing on which future studies can focus.
Originality/value
The study embellishes the existing literature on momentum investing by contributing the first bibliometric review on alternative momentum approaches.
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Simarjeet Singh, Nidhi Walia, Stelios Bekiros, Arushi Gupta, Jigyasu Kumar and Amar Kumar Mishra
This research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market…
Abstract
Purpose
This research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market. Apart from this, the study also proposes a novel risk-managed time-series momentum approach.
Design/methodology/approach
The study considers the adjusted monthly closing prices of the stocks listed on the Bombay Stock Exchange from January 1996 to December 2020 to formulate long-short portfolios. Newey–West t statistics were used to test the significance of momentum returns. The present research has considered standard risk factors, i.e. market, size and value, to evaluate the risk-adjusted performance of time-series momentum portfolios.
Findings
The present research reports a substantial absolute momentum effect in the Indian equity market. However, absolute momentum strategies are exposed to occasional severe losses. The proposed time-series momentum approach not only yields 2.5 times higher return than the standard time-series momentum approach but also causes substantial enhancement in downside risks and higher-order moments.
Practical implications
The study's outcomes offer valuable insights for professional investors, capital market regulators and asset management companies.
Originality/value
This study is one of the pioneers attempting to test the time-series momentum effect in emerging economies. Besides, current research contributes to the escalating literature on risk-managed momentum by suggesting a novel revised time-series momentum approach.
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Pooja Goel, Sahil Raj, Aashish Garg, Simarjeet Singh and Sanjay Gupta
Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented”…
Abstract
Purpose
Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented” benefits, many questions are being raised late regarding the long-term sustainability of the open online teaching e-learning model. With high dropout rates in MOOCs courses, recent research has focused on the challenges limiting MOOCs’ growth. But most of the research is directed toward students’ perspectives, leaving the instructors’ perspective. One of the most important aspects of instructors’ perspective is the motivation for MOOCs' development and delivery.
Design/methodology/approach
The present study collected the data from 25 MOOC developers of Indian origin. To prioritize or rank the motivational factor behind developing a MOOC, a fuzzy-analytical hierarchical process (F-AHP) technique was applied to the data set. The primary motivational factors considered for the study were professional development, altruism, personal development, institutional development, intrigue, monetary benefits and peer influence.
Findings
The results showed that professional development and personal development are two prime motives that drive MOOCs development. Monetary benefits and peer influence were the least important factors among all the factors considered for the study.
Originality/value
Previous studies have identified and modeled the motivational factors that contribute toward developing MOOCs. However, there was little knowledge about the hierarchy among the motivating factors. The present study fills this gap by establishing the ranking of motivational factors responsible for MOOCs development.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0205.
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Jinesh Jain, Nidhi Walia, Manpreet Kaur and Simarjeet Singh
The advocates of behavioural finance have denounced the existing literature on investors’ rationality in the decision-making process and questioned the existence of efficient…
Abstract
Purpose
The advocates of behavioural finance have denounced the existing literature on investors’ rationality in the decision-making process and questioned the existence of efficient markets and rational investors. Although diversified research has been conducted in the area of behavioural finance, yet there is a need of further explorations into the field as the available knowledge base is confined to one or a few behavioural biases confronted by investors while making investment decisions. Hence, this study aims to develop a comprehensive, reliable and valid scale to measure the behavioural biases affecting investors’ decision-making process.
Design/methodology/approach
To develop a comprehensive, reliable and valid scale for measuring the behavioural biases affecting investors’ decision-making process, rigorous multi-stage scale development methodology has been followed. Stage one started with an extensive review of the literature followed by interviews from experienced stockbrokers to clarify construct and getting novel insights about dimensions of behavioural biases. In stage two, 52 items measuring the dimensions of behavioural biases were generated and got evaluated from panel of judges. Pilot testing was done in the third stage which gave a set of 39 items. Finally, in fourth stage, data were collected from 332 individual equity investors on a 7-point Likert scale using the snowball sampling technique.
Findings
The results of the study highlighted that behavioural biases is a multidimensional phenomenon that significantly affects investors’ decisions and has different dimensions, namely, Availability Bias, Representativeness Bias, Overconfidence Bias, Market Factors, Herding, Anchoring, Mental Accounting, Regret Aversion, Gamblers’ Fallacy and Loss Aversion. The present research has developed a comprehensive, reliable and valid scale for measuring behavioural biases affecting equity investors’ decision-making process.
Originality/value
Behavioural finance is an emerging area in the field of research particularly in the Indian context which needs further exploration. The present research concentrates on rendering an empirically tested scale to the researchers for measuring the behavioural biases and its impact on investor’s decision-making. Such an instrument can contribute to making progress in the area of behavioural finance and other research studies may also find it useful to achieve their goals.
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Sanjay Gupta, Anchal Arora, Simarjeet Singh and Jinesh Jain
In the present era, artificial intelligence (AI) is transforming and redefining the lifestyles of society through its applications, such as chatbots. Chatbot has shown tremendous…
Abstract
Purpose
In the present era, artificial intelligence (AI) is transforming and redefining the lifestyles of society through its applications, such as chatbots. Chatbot has shown tremendous growth and has been used in almost every field. The purpose of this study is to identify and prioritize the factors that influence millennial’s technology acceptance of chatbots.
Design/methodology/approach
For the present research, data were collected from 432 respondents (millennials) from Punjab. A fuzzy analytical hierarchy process was used to prioritize the factors influencing millennials’ technology acceptance of chatbots. The key factors considered for the study were information, entertainment, media appeal, social presence and perceived privacy risk
Findings
The findings of the study revealed media appeal as the top-ranked prioritized factor influencing millennial technology acceptance of chatbots. In contrast, perceived privacy risk appeared as the least important factor. Ranking of the global weights reveals that I3 and I2 are the two most important sub-criteria.
Research limitations/implications
Data were gathered from the millennial population of Punjab, and only a few factors that influence the technology acceptance of chatbots were considered for analysis which has been considered as a limitation of this study.
Practical implications
The findings of this study will provide valuable insights about consumer behaviour to the business firm, and it will help them to make competitive strategies accordingly.
Originality/value
Existing literature has investigated the factors influencing millennials’ technology acceptance of chatbots. At the same time, this study has used the multi-criteria decision-making technique to deliver valuable insights for marketers, practitioners and academicians about the drivers of millennials’ technology acceptance regarding chatbots which will add value to the prevailing knowledge base.
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Sanjay Gupta, Nidhi Walia, Simarjeet Singh and Swati Gupta
This comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the…
Abstract
Purpose
This comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the emerging themes associated with noise trading.
Design/methodology/approach
This study combines bibliometric and content analysis to review 350 publications from top-ranked journals published from 1986 to 2020.
Findings
The bibliometric and content analysis identified three major themes: the impact of noise traders on the functioning of the stock market, traits of noise traders and different proxies used to measure the impact of noise trading.
Research limitations/implications
This study undertakes research papers related to the field of finance, published in peer-reviewed journals and that too in the English language.
Practical implications
This study shall accommodate rational traders, portfolio consultants and other investors to gain deeper insights into the functioning of noise traders. This will further help them to formulate their trading/investment strategies accordingly.
Originality/value
The successful combination of the bibliometric and content analysis revealed major gaps in the literature and provided future research directions.