This study focuses on the inhibitors of the Digital Payment Platform (DPP) that prevent the user from adopting the payment platform. The objective of the study is to find out the most important criteria (inhibitors) that influence the user decision regarding the DPP adoption and also find out the most influential DPP apps that have greater inhibitors. We have used Multi-criteria Decision Making (MCDM) techniques such as the Best-worst Method (BWM), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Sensitivity Analysis to assess the reliability of inhibitors present in Digital Payment Platforms (DPPs). The finding of this study shows that privacy concerns are one of the most important inhibitors which become a barrier in the adoption of DPPs. While we used the TOPSIS method to analyze the alternative apps, which showed that Instagram Pay is the platform where the user faces the highest inhibitors which refrain the user from adopting it. Contrary to it, sensitivity analysis with five criteria with five DPPs revealed that WhatsApp Pay is one of the platforms which has the most consistent impact of inhibitor and hence users avoid using this app. The implication of the study highlights the critical area of adoption and focuses on the payment app which has greater inhibitors. We have to reduce the inhibitors from the respective apps for the wider adoption of DPPs.

Purpose – This study aims to explore the factors influencing the adoption of social media payment platforms (SMPPs) and examines the interrelationships among these factors. Design/methodology/approach – A systematic literature review identified 31 key adoption factors. Using social network analysis (SNA), we mapped and analyzed the interrelationships among these factors. Additionally, we used the Delphi technique to validate and assess their impact. Findings – The study reveals that perceived usefulness emerges as the most critical factor driving the adoption of SMPPs. Moreover, the SNA highlights significant interdependencies among factors, providing deeper insights into the ecosystem of SMPP adoption. Research limitations/implications – The findings offer practical guidance for users and socially innovative companies in decision-making related to SMPP adoption. Additionally, the study identifies avenues for future research, particularly in leveraging network-based methodologies for service management research. Originality/value – This study is the first to apply SNA tools in the context of SMPPs, offering a novel methodological perspective and advancing the understanding of adoption dynamics in this emerging field.

In the digital age, investing in e-gold is increasing in popularity. This study’s objective is to assess the moderating role of dispositional innovativeness between fintech adoption and the intention to invest in e-gold, as well as to understand investors’ behavioral intentions. This study uses the theory of planned behavior model to analyze the data. We prepared a structured questionnaire to collect data from Maharashtra, a state in India, and used PLS-SEM for analytical purposes. We also used focus group interviews to validate the findings from PLS-SEM. Our evidence shows that attitude, subjective norms, and perceived behavioral control significantly impact fintech adoption and the intention to invest in e-gold. This study also confirmed that dispositional innovativeness moderates the relationship between fintech adoption and the intention to invest in e-gold. This study implies that policymakers can redesign the regulation of digital assets to promote transparency, security, and faith in the fintech platform by recognizing the interest rate in e-gold.

This study examines how YouTube influencers can help shape equity decisions. We used a structured questionnaire with 26 questions to collect data using a purposive sample and the KMO and Bartlett tests to test the adequacy of the sample. Additionally, we used the Cronbach Alpha test to check the reliability of the questionnaire and principal component analysis to identify the factors related to YouTube influencers and their influence on equity investors. Our findings reveal a relationship between YouTube channel influencers and the financial decisions of equity investors. These factors influence credibility, influencer engagement, influencer trustworthiness, influencer investment fit, influencer’s YouTube channel promotion, and influencer-driven equity insights. This study could help investors make better decisions after learning pertinent information regarding equities. Investors can improve their investment strategies by identifying trustworthy and valuable influencer content by having a better understanding of these elements. This study provides novel insights into how digital content creators can shape equity investment decisions. However, a limitation of our study is that our findings do not show causality, only correlations between YouTube influencers and equity investments.

This study investigates one of the Social Media Payment Platform (SMPP) known as WhatsApp Pay's awareness among users in Uttar Pradesh, India. Data was collected via a survey from 449 respondents, then analyzed using SPSS. Results indicate a moderate level of WhatsApp Pay awareness, influenced by security features, user context, and Pay insight and Pay Connect insights. The study suggests increased government promotion and regulation to enhance global awareness. Future research should broaden the scope and sample size for greater generalizability.

Tax evasion and financial crime significantly impact international economies by distorting corporate governance, reducing government revenues, and increasing wealth inequality. Tax evasion is characterized by illegal activities such hiding of funds offshore, income understatement and the hiding of funds offshore, while financial fraud consists of intentional financial misrepresentation for organizational or individual benefit. The present study explores the main causes of tax evasion and financial fraud, grouping them into economic, psychological, organizational, regulatory, and technological causes. Heavy taxation, economic turmoil, and exorbitant compliance costs encourage businesses and individuals to hide taxes. Greed, moral disengagement, and peer pressure due to psychological characteristics further drive fraudulent actions. Loopholes in regulation, inadequate corporate governance, and technological evolution, such as cryptocurrency abuse, encourage financial wrongdoings. Past research significantly addresses economic and regulatory factors while usually neglecting psychological and technological determinants, especially in the case of emerging economies. To overcome this gap, in this study, the Analytic Hierarchy Process (AHP) has been used to quantify the importance of various factors influencing tax evasion behavior. A structured electronic survey of 15 participants with response categories in five essential dimensions was conducted. The outcome is to strengthen tax policy, enforcement powers, and international coordination to counteract financial fraud and tax evasion.

This study explores risk perceptions in cryptocurrency investments among Indian investors. It employs a multistage random sampling survey of 228 investors. Four key factors influence this perception: conceptual clarity, investment education, awareness of investment options, and fear-induced psychological factors. The overall risk perception of crypto investors is high. Based on our findings, we suggest that the Indian government should organize an awareness campaign to create awareness and educate investors about cryptocurrency. Policymakers and investment managers should focus on transforming high-risk investors into lower-risk investors through education and support, fostering a more favorable investment environment.

Purpose – This paper aims to gain insight into the current understanding of the need to belong and how its significance evolves over time, while also suggesting future research directions based on a comprehensive content analysis. Design/methodology/approach – This study employs a systematic literature review (SLR) and content analysis approach to explore the domain related to need to belong (NTB) until the year 2024. Following a methodologically structured approach, this research employed the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. Further, the study synthesized 80 pertinent academic articles and organized them into a review framework using 4 W’s framework – What, Where, How and Why along with the Theory, Context, Characteristics, and Methodology (TCCM) framework. Findings – This SLR synthesizes the findings from a diverse array of studies. Various perspectives on defining, evaluating and fostering a sense of belonging have obstructed the much-needed advancement in this urgent and significant subject. The present study delineated the four primary themes and the corresponding four subthemes that emerged from the systematic clustering of scholarly articles within the literature review. Originality/value – To the authors’ knowledge, this research presents one of the initial SLRs focused on the concept of NTB that is grounded in a framework and outlines an agenda for future research.

Lately, social media companies worldwide have introduced payment features on their social media platforms. This has given social media users the option to make payments to their near and dear ones without changing the platform while engaged in chatting. The adoption of Social Media Payment Platforms (SMPP) varies across user groups and is influenced by socio-demographic characteristics, convenience, and perceived risk. Understanding these factors is essential for enhancing user engagement and trust, thereby addressing the gaps in current SMPP adoption research. The purpose of this study is to ascertain the behavioural intention and perception level of users toward Social Media Payment Platforms (SMPP) adoption and to identify the factors which motivate and inhibit from using social payment apps. To understand the intention of the users to behave and adopt SMPP, we conducted in-depth structured interviews. Qualitative analysis was used to analyse the data, using pre-defined categories (deductive) and code emerging from the respondent discussions (inductively) to identify the relevant influencing factors. Through data analysis, we identified three key themes that categorised user behaviour: socio-demographic, convivence and vulnerability to risks, which is further divided into several sub-themes such as age, gender, education, occupation under socio-demographic, while perceived usefulness (PU) and perceived ease of use (PEOU) comes under the theme of convivence and lastly, under Vulnerability of risk includes privacy, security and platform features. The findings of the study can be validated and explored in future research, which will provide a clear understanding of identifying factors that influence SMPP adoption and behaviour intention.

This study focuses on the inhibitors of the digital payment platform that prevent the user from adopting the payment platform. The study's objective is to find out the most important criteria (inhibitors) that influence the user decision regarding the digital platform adoption. We have used one of the Multicriteria Decision Making (MCDM) techniques namely the Best-Worst Method (BWM) for this analysis. The findings of this study show that privacy concerns are most significant inhibitors that have become the barrier to the adoption of digital payment platforms. The implication of the study highlights the critical area of adoption and focuses on the payment app which has greater inhibitors. We have to reduce the inhibitors from the respective apps for the wider adoption of digital payment platforms.

The digital payment market is growing at unprecedented rates in India. This can be attributed to the introduction of the Unified Payment Interface (UPI). It has completely disrupted the digital payment space by effectively increasing the user base of digital payments multiple times in India. However, any market innovation's success or failure is heavily influenced by how consumers perceive it. Therefore, the study aims to know the perception of UPI users by using the sentiment analysis technique. The data on consumer behaviour was scraped from the latest Google Play Store reviews using Python scripts. After the data pre-processing, Exploratory Data Analysis and Word Cloud Analysis were done. Interesting findings from the analysis were found concerning the top three payment apps: GPay, Paytm, and PhonePe. The research also presents a few managerial implications which could be applied for better customer experience. The goal of these payment apps should be to convert negative customer reviews into positive ones.