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Loading the work on social capital theory, we have tried to check the influence of social currency (SC) on social media usage (SMU) and its subsequent impact on the brand experience (BE). The study attempted to ascertain the mediation of loyalty (LT) between the SC and SMU as well as the moderation of perceived ease of use (PEU) in the SMU and BE relationship.

The data were collected from 384 respondents employing snowball sampling technique by administering a questionnaire on seven-point Likert scale. The respondents were the active internet users, who devote the significant part of their daily routine to social media activities. Structural equation modelling was used to study the path of the considered variables.

The result of the study strengthened the findings of earlier studies on SC dimensions. This study elaborated about the positive impact of SC on SMU, SC on LT, LT on SMU, SMU on BE. The study also found the mediating effect of LT in the SC and BE relationship. The study did not identify a moderating role of PEU in the SMU and BE relationship.

By taking into account SC, SMU, LT, PEU and BE, the study adds the knowledge to the social capital theory.

This study aids marketers in adjusting social media strategies for the effective use of SC aimed to deliver enhanced BE. Additionally, it demonstrates the value of customer LT in the context of SC and SMU by customers.

This study is among the few research on the SC of the Indian user and its impact on SMU and BE. Checking the mediation of LT and the moderation of PEU in the SC context makes this study novel and different from any study conducted earlier.

This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.

Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.

The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.

Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.

The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.

Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.

The pandemic has severely affected sharing economy businesses specially ride-hailing services due to high levels of human-touch points. This research investigates the impact of COVID-19 infodemic, identification, and emotional support on intention to use ride-hailing. The authors further examine the moderating effects of internalization, compliance, social currency and informational support in the proposed conceptual model.

The data were collected from 412 respondents from Delhi in India, and hypothesized relationships were tested using hierarchical regression.

The results indicate that COVID-19 infodemic has a negative association with intention to use ride-hailing. Identification and emotional support show a positive association with intention to use ride-hailing. The results also support internalization and compliance as moderators between infodemic, identification and intention to use ride-hailing. Further, social currency and information support moderate the relationship between emotional support and intention to use.

This is the first research, which adds to the expanding literature on ride-hailing, especially during the post-pandemic period of “new normal”.

The study's objective is to examine the consumers' intention to buy counterfeit brand shoes. A conceptual model is developed to test the risk-taking and word-of-mouth (WOM) as a moderator in the relationship between status consumption, brand image, and consumer intention to buy counterfeit shoes.

Based on the theory of reasoned action (TRA) and signaling theory (ST), this research was conducted in the Indian National Capital Region. Using a structured instrument, the data was collected from 240 respondents. After checking the psychometric properties of the survey instrument using the Lisrel package of structural equation modeling, Hayes's PROCESS macros were used for testing the hypotheses.

The findings from the study indicate that (1) status consumption and brand image are positively associated with purchase intention of counterfeit brand shoes, and (2) risk-taking moderates the relationship between (1) status consumption and purchase intention, and (2) brand image and purchase intension, (3) significant three-way interaction between WOM, risk-taking and status consumption on purchase intention, and (4) significant three-way interaction between brand image, WOM, and risk-taking on purchase intention of counterfeit brand shoes.

As with any survey research, this study has common method variance as a potential problem. However, through the latent variable method and Harman's single-factor analysis, the common method variance was checked. The study has several implications for managers, e-marketers, and consumers.

The study has several implications for marketers selling counterfeit products and managers intending to protect their branded products.

A conceptual model showing two-way and three-way interactions between status consumption, risk-taking, and WOM influencing the consumer purchase intention of counterfeit products was discussed. This is the first of its kind in India to explore such relationships.

Dynamism has been the key to the success and popularity of social media, and users always try to adapt to the available new changes. Continuous growth in the access and reach of social media in the past decade has enabled the users to make a calculative assessment of their social media usage. Social currency is a phenomenon that helps the customer in their evaluation of social media usage. However, this concept is still in its infancy phase, and there have been hitherto no studies to understand the influence of social currency dimensions on Indian users. This paper aims to study the dimensions of social currency for a better insight into social media usage of Indian customers.

Data were collected from 384 respondents from the biggest residential university in Varanasi through a structured questionnaire using the snowball sampling technique. Responses were taken on a seven-point Likert scale. Responses were analyzed by the factor analysis method using the maximum likelihood estimation model.

The result of this study empirically demonstrated that six dimensions, i.e. conversation, information, utility, affiliation, advocacy and identity, constitute the social currency of the user while browsing social media sites. It was also found that among the factors described above, advocacy emerged as the most influential dimension of social currency for Indian users, followed by identity and affiliation.

The findings have various managerial implications for the firms that want to have a significant social media presence. These findings can help marketers to design a tailored social media campaign for Indian users in an efficient manner by successfully incorporating the aforesaid social currency dimensions in their strategy.

This study also reflects the societal impact of the dimensions of social currency on Indian users, as any change in the usage of social media can have a long-lasting effect on the mood of the people. The influence of the social currency dimension differs significantly in the context of Indian users compared to the existing literature, as they give more value to the behavioural aspect of the social currency (advocacy, identity and affiliation), strengthening the sense of belongings among the members.

This paper highlights, for the first time, the level of influence social currency dimensions have on Indian users, as there have been hitherto no studies to understand the influence of social currency dimensions on Indian users. Another significant contribution of this research is the empirical validation of the social currency determinants. Thus, this study may contribute to the social media strategy of the firm for Indian users by incorporating the social currency dimension, as discussed in the study.

The present study tries to examine the relationship between financial inclusion and environmental quality as proxied by carbon emissions in India covering the period from 2008 to 2018.

A financial inclusion index has been composed using principal component analysis (PCA) based on three dimensions: access, penetration and usage. After testing for stationarity of the data, the authors adopted the autoregressive distributive lag model (ARDL) methodology.

The study found that financial inclusion and growth lead to increased carbon emissions in India and the government must resort to greener policies, whereas empirical results support that globalization reduced the pollutants emissions in both the long term and short period in India.

Based on the results, several policy prescriptions are rendered for policymakers: (1) need to move toward greener energy policies and (2) enhance the awareness of green financing instruments such as green bonds in India. Therefore, policymakers should be more proactive in accepting green and sustainable financial alternatives.

The present study contributes to the scant literature on the financial inclusion–emission nexus in India. This study considers three inclusion parameters that are not present in previous studies.

This study examines the impact of interpersonal conflict on workplace aggression. Moreover, the moderating role in the association between interpersonal conflict and workplace aggression has been examined.

The research is grounded on the cognitive appraisal theory, which posits that interpersonal conflict contributes to aggression in the workplace. A sample of n = 250 employees from the steel industry in India was selected in two waves. The authors utilized Hayes' PROCESS macro v4.1 for path analysis.

The research reveals that interpersonal conflict is positively and significantly related to workplace aggression. Moreover, organizational climate is negatively associated with workplace aggression. The moderation analysis has revealed that organizational climate negatively moderates the relationship between interpersonal conflict and workplace aggression.

This study suggests that recognizing the significance of the organizational climate, companies can proactively curtail the progression of disputes into hostile behaviors. Nurturing a positive workplace climate becomes paramount, as it acts as a buffer against conflict escalation. Educating both staff and managers about the diverse forms of aggression and implementing appropriate protocols to address such behaviors are crucial steps toward fostering a positive climate.

This study provides new insights into the existing literature on workplace aggression, interpersonal conflict and organizational climate for future research.

The current study gives a quantitative analysis DT literature over the past ten years in domain of management and business where the field has witnessed a proliferation in studies. The study's primary areas of concentration were analyzing historical trends and identifying prospective future research opportunities in the field. Due of the way, it approaches innovation and problem-solving, design thinking has garnered a lot of interest from both academics and practitioners. Promoters and detractors, however, tend to have quite different perspectives on the program's core qualities, practicality and results.

The study adopts a bibliometric approach to a systematic literature review, where the analyses and visualizations are carried out using R Studio (Biblioshiny package) and VosViewer software. The study was conducted on 518 documents extracted from the Scopus database. To identify past research trends in the field, performance analysis based on productivity and/or impact of the research constituents was carried out to understand the intellectual structure of the field.

The study's findings indicated that few areas have received the most attention, which are presented as seven themes. While the emerging themes in the field include areas such as service design, service innovation, customer experience, innovation management, project management and 21st-century skills.

The studies are going deeper by breaking down concepts or processes and analyzing one aspect at a time, codesign and prototyping are such subareas within the realm of service or new product design and development.

This study is the first of its kind where a literature review has been conducted covering design thinking in the area of business management and accounting.

The present study tries to explore the various fund attributes that influence the mutual fund performance. Further, study examined the effect of mutual fund attributes namely, Net Asset Value (NAV), Portfolio turnover ratio (PTR), fund size (AUM), expense ratio (ExpR) and fund age (Age) on mutual fund's performance using gross return and risk-adjusted performance measures.

The study evaluated balanced panel data (short panel) comprising 81 Indian equity mutual fund schemes for the period of 2013–2019. The study estimated relationship between fund attributes (Net asset value, Portfolio turnover ratio, Fund age, fund size and Expense ratio) and fund performance (using gross return and risk-adjusted performance measures), through panel data regression using fixed-effects model as suggested by Hausman specification test on transformed data (due to high multicollinearity), with cluster-robust estimators due to the presence of heteroskedasticity in the model.

The findings of the study suggested that using gross return as fund performance measure, PTR, NAV, AUM, Age exhibit significant relationship with the fund performance whereas using risk-adjusted performance measures (Treynor ratio and Jensen alpha) NAV and ExpR significantly influences the fund performance. Identification of the significant relationship between fund characteristics and fund performance offers valuable insights to the investors and fund managers for rationally managing their portfolio with the ultimate objective of the wealth maximization.

The study considered only 81 equity mutual fund schemes. Some of the data were not available at the time of the study due to the policy of the company. The present study contributes significantly in examining the expected association between fund attributes and fund performance in the context of Indian mutual fund industry where this relationship were explored less.

The findings of the present study will help the investors to take the rational investment decision with the ultimate objective of maximum return with minimal risk. The findings also offer significant germane to the stakeholders in making rational decision-making process.

There is dearth of study concerning the relationship between mutual fund characteristics and fund performance with respect to Indian mutual fund industry. Therefore, study provides valuable insights to the area of the portfolio selection and management with respect to Indian mutual funds.

We have proposed and implemented AgentMatcher, an architecture for match‐making in e‐Business applications. It uses arc‐labeled and arc‐weighted trees to match buyers and sellers via our novel similarity algorithm. This paper adapts the architecture for match‐making between learners and learning objects (LOs). It uses the Canadian Learning Object Metadata (CanLOM) repository of the eduSource e‐Learning project. Through AgentMatcher’s new indexing component, known as Learning Object Metadata Generator (LOMGen), metadata is extracted from HTML LOs for use in CanLOM. LOMGen semi‐automatically generates the LO metadata by combining a word frequency count and dictionary lookup. A subset of these metadata terms can be selected from a query interface, which permits adjustment of weights that express user preferences. Web‐based pre‐filtering is then performed over the CanLOM metadata kept in a relational database. Using an XSLT (Extensible Stylesheet Language Transformations) translator, the pre‐filtered result is transformed into an XML representation, called Weighted Object‐Oriented (WOO) RuleML (Rule Markup Language). This is compared to the WOO RuleML representation obtained from the query interface by AgentMatcher’s core Similarity Engine. The final result is presented as a ranked LO list with a user‐specified threshold.