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The increasing incidence of fraudulent financial reporting by firms in recent years raises concerns about investors' confidence in capital markets. Academicians and industry practitioners adopt diverse risk management techniques to detect fraudulent reporting of financial statements. This paper aims to determine the effectiveness of the Beneish M-score and Altman Z-score models for the early detection of material misstatements at Comscore, Inc., a media analytics firm in the United States of America.

The financial statements of Comscore Inc. from 2012 to 2018 were analyzed with the primary objective of early fraud detection by employing the Beneish M-score and the Altman Z-score.

The study’s outcomes indicate that the Beneish M-score is less predictable in fraud detection compared to the Altman Z-score. The study results did not confirm the efficacy of the Beneish model in predicting fraudulent financial statements. The study concludes that the choice of forensic tool greatly influences fraud detection outcomes.

The research findings can guide the policy decision-making of investors, financial auditors, and forensic auditors as this study provides some evidence of the effectiveness of forensic tools in the detection of financial statement fraud in corporate entities.

This is the first study to apply these two widely used tools to the most recent big corporate scandal: Comscore, Inc.

The behavioural decision-making process of individuals highlights the importance of investors’ sentiment and their correlation with the real economy. This paper aims to contribute to the literature of behavioural finance by examining the influence of contextual factors on investment decision-making.

Using a questionnaire, a total of 445 valid responses were collected from March to May 2021 through online sources. The current study uses a technique of Fuzzy-analytical hierarchical process (AHP) to assign relative weights to various contextual factors influencing investment decision-making. Harman’s single factor test was used to check common method bias.

Results of the study reveal that accounting information, self-image/firm-image coincidence, and neutral information as the top-ranked factors in influencing investment decisions, whereas advocate recommendation and personal financial needs emerged as less important factors in influencing investment decisions.

The current study collects data from Indian stock market investors, which may limit the generalization of the study to India only. Moreover, this study is cross-sectional in nature, and there are numerous factors that are not part of the study but might significantly influence the investors’ decision-making process.

The research has implications for both academicians working in the area of behavioural finance and practitioners’ who are active in stock markets, more specifically dealing with retail investors and in the domain of personal finance. Also, the current study will accommodate different groups, i.e. policy makers, financial advisors, investors, investment professionals, etc. in carrying out their professional work.

The current study will provide a comprehensive overview of individual investor behaviour. To the best of the authors’ knowledge, the present study is one of its kind to use the Fuzzy-AHP technique for evaluating the relative ranks of contextual factors influencing investment decision-making.

The purpose of this study is to recognise the role of information and communication technology (ICT) tools in different sectors like Education, Health Care, Business, FMCG and Entertainment in the phase of social distancing. This study also attempts to provide a quantitative review of the scholarly literature on this topic.

A comprehensive literature evaluation was undertaken using a database encompassing 150 English-language papers with publication dates ranging from 2019 to 2021. The research profile and thematic analysis are presented through a comprehensive content analysis, resulting in four themes. The study reviews various research articles and reports related to social distancing and opens a discussion on the growing importance of ICT tools during this COVID-19 era.

ICT acts as a surviving tool for the economy by creating a virtual environment and helping people to stay socially connected during this pandemic. There is a lack of empirical evidence to support the facts so further research is required.

There are two drawbacks to the current study. Firstly, this study established a rigorous review methodology in which the researchers opted to exclude any grey literature, non-peer-reviewed articles, books, notes and book chapters from consideration. These sources could have had pertinent literature. Secondly, even after protocol’s rigour and numerous rounds of checks by a team of academicians and researchers, an anomaly may have sneaked into the evaluation.

The current study contributes to the growing literature on ICT tools particularly in this phase of social distancing. This paper highlights the need for future research in this area supported by different statistics.

From the last few decades, environmental issues have become a global concern. Consumption activities are given much attention in the marketing literature, whenever the question about protecting the environment arises. The responsibility of the consumer toward the environment is a major concern and the purpose of this study is to prioritize factors responsible for determining environmental responsibility among young consumers. This research will provide valuable insights to the marketers in targeting those particular areas which according to young consumers are highly ranked/prioritized for being environmentally responsible.

In this study, data were collected from 400 young consumers from Punjab and Chandigarh. Fuzzy analytical hierarchy process (F-AHP) was applied to prioritize or rank the factors on the basis of significance for being environmentally responsible. The primary factors considered for further analysis were knowledge and awareness, attitude, green consumer value, emotional affinity toward nature, willingness to act and environment-related past behavior.

Results of the study depicted knowledge and awareness as the highest-ranked and prioritized factor for young consumers to become environmentally responsible, while environment-related past behavior emerged as the least important factor for consumers' environmental responsibility.

Data were collected from the young consumers of Punjab and Chandigarh only and only a few factors of consumers' environmental responsibility were considered for further analysis which depicts the limitation of the study.

The research study is highly useful for the government and the business firms to target the highly prioritized factors of environmental responsibility which will promote green consumption practices and behavior among young consumers.

Previous researches have explored the factors of environmental responsibility and modeled their relationships. However, the present study has employed the multi-criteria decision-making technique to provide valuable insights for marketers, academicians and practitioners about the drivers of consumers' environmental responsibility which adds value to the existing knowledge base.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

The main objective of this study is to compare the service quality of two retail chains of hypermarkets, namely, Big Bazaar and Spencer's, using the trapezoidal fuzzy approach.

Customers from Big Bazaar and Spencer's of Andhra Pradesh, India, have been surveyed through a well-designed questionnaire. The study attempts to compare the service quality of two major retail giants (Spencer's and Big Bazaar) in Andhra Pradesh by using the trapezoidal fuzzy approach to prioritize the attributes of service quality of retail outlets.

The result of the study indicates that the expectations of Big Bazar customers are higher as compared to Spencer's. Further, the study reveals – that Spencer's need to improve in the dimension of tangibility while Big Bazar needs to focus more on responsiveness.

As the data taken for the study are primary in nature, chances of bias may arise on the part of respondents, which may affect the validity of results. Further, the study is confined to two retail stores in Andhra Pradesh, India only, which may not reflect the broader picture.

Retailers may provide more importance to two major service quality dimensions, i.e. tangibility and responsiveness while preparing for their service and marketing strategies.

As the study relates to the comparative analysis of service quality of Big Bazar and Spencer's, the findings will be of additional value to these specific retailers. Therefore, it is expected that this study will fill the gap in the literature by prioritizing the expectations and perceptions of customers of Big Bazar and Spencer's.

The primary objective of this study is to prioritize the main intentions behind investment in cryptocurrency, in spite of its volatile nature and no regulatory framework.

This research paper has worked on collective constructs of the unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM) and social support theory with an added construct of financial literacy. A fuzzy analytical framework has been applied to prioritize the intentions of investors.

The result indicates that “Social Influence (SI)” is the most influencing factor, while “Effort Expectancy (EE)” is the least influencing factor considered by investors. The subdimensions ranked in the top priority by investors are as follows: “I want to invest in cryptocurrencies because I have a good level of financial knowledge (FL1)”; “The people who are important to me will think that I should use cryptocurrencies (SI2)”; “I have the necessary resources to use cryptocurrencies (FC2).” The least importance is given to “It will be easy for me to become an expert in the use of cryptocurrencies (EE3).”

Few of the constructs of the UTAUT, the TAM and social support theory have been considered while prioritizing intentions. Different other intentions also prevail under different theories that need to be researched further.

Unlike previous studies, this research adds the archetype of social commerce, social support and utility theories to analyze and prioritize the behavioral perspective of using cryptocurrencies in digital transactions.

This paper fills the gap in the research study, along with assisting the regulators and cryptocurrency practitioners to widen their knowledge base and to recognize the prioritized intentions.

Organic food market has grown rapidly on a global level and so is the interest of customers. The present paper ranks the factors and sub-criteria which are taken into consideration while making organic purchase decisions resulting in understanding the behaviour of consumers.

The present paper considered a sample of 550 respondents in the area of Punjab. Fuzzy AHP technique was applied to understand the key factors and sub-criteria which play a major role in organic food purchase decisions. The paper is empirical and descriptive in nature. The factors considered for the study include price, consumer knowledge, trust, attitude, behavioural intentions, subjective norms, perceived personal relevance and perceived consumer effectiveness.

The three major influential factors include price, trust and attitude ranked in the same order of preference which majorly affects the purchase decisions and talking about sub-criteria the three major criteria to purchase organic food include: “Price plays a significant role in purchase decisions (P2)”, “Organic food keeps me fit and healthy (A1)” and “Organic food intake makes me feel energetic (A2)”.

The present paper is limited to the area of Punjab and majorly eight factors have been taken into consideration. Further research can be explored on broader geographical and cultural areas with new dimensions in criteria and sub-criteria.

The findings of this paper will surely help the marketers to understand the behavioural intentions and preferences of the customers. Accordingly, they will strategize the policies to convert organic food market into a niche market with a high growth rate.

The existing literature explored various key factors. However, the present study comes up with ranking to the factors according to their priority in purchase decisions. This will definitely help marketers, business houses, practitioners and academicians about the key factors which affect purchase decisions, and it will surely add incredible knowledge into the existing database.

Research in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context.

A fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study.

The findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria.

This survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market.

The study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large.

To the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.

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.

This study combines bibliometric and content analysis to review 350 publications from top-ranked journals published from 1986 to 2020.

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.

This study undertakes research papers related to the field of finance, published in peer-reviewed journals and that too in the English language.

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.

The successful combination of the bibliometric and content analysis revealed major gaps in the literature and provided future research directions.