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The study investigates the influence of perceived security (PS) on behavioral intention (BI) via the trust attitude process and explores the moderating effects of gender. PS in mobile wallets enhances user trust (TR), attitude (ATT) and intention (INT). Using a multiple and serial mediation model, both TR and ATT were found to mediate the relationship between PS and BI.

Drawing on the stimulus-organism-response (S-O-R) theory, the proposed conceptual model comprises PS, TR, ATT and BI. An online survey was conducted with a cross-sectional sample of 744 mobile wallet users in India. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the hypothesized relationships and test the mediation effects.

Results show that the stimulus, PS, has a positive and significant influence on TR and ATT, which eventually has a positive influence on BI. The research model explains 64.4 percent of the variance in BI. Further, both TR and ATT independently and parallelly mediate the relationship PS and BI. Lastly, gender is found to moderate the relationship between TR and BI and ATT and BI.

The research showed the importance of PS, TR and ATT towards mobile wallet adoption INTs. Further, the findings support the idea that developing TR and ATT is essential for shaping INTs. This suggests that mobile wallet service providers should invest in methods that not just enhance user TR but also reinforce a positive ATT towards the platform. To demonstrate TR, mobile wallet providers must ensure the confidentiality and privacy of user data, keep customer interests in mind and fulfill commitments. Lastly, for strengthening customer TR, excellent customer support is extremely important.

While prior researchers have majorly used technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) models to explain adoption INTs, this study examines the relationship between PS, TR, ATT and BI through the lens of the SOR framework.

The main purpose of this paper is to explain the preferences of consumers for using online payment services. This paper applies a unified theory model named stimulus-organism-response (S-O-R) theory for exploration.

This is quantitative research based on the structural equation modelling method. The stimulus-organism-response (S-O-R) theory was applied, whereby the author conducted an online survey through a structured questionnaire with users of mobile payment services. These consumers are using online payments for online shopping purposes. The survey was conducted all over India. The sample size is 355.

The study found that utilitarian, hedonic value and salesperson behaviour impact consumers satisfaction and behaviour while using online payment services. The study found that there is a significant direct relationship between consumer satisfaction and consumer behaviour. This study examines how financial mobile services contribute to e-commerce implementation, especially in the context of India.

This study incorporates a variety of factors, including the behaviour of salespeople, which affect consumer happiness, satisfaction and behaviour intention. This study reveals a direct relationship between consumer satisfaction and behavioural intention. Accordingly, the use of mobile banking and digital financial services has a positive impact on customer satisfaction. This study suggested that awareness about e-commerce services and mobile financial services is an important aspect of consumers satisfaction. Effective e-commerce services and mobile financial services have a positive impact on consumer behaviour.

This is a comprehensive model used for online payment services and directly related to emerging economies like India. This study examines the consumer willingness of the digital market in relation to online payment services. This study contributes to the relevant literature by simultaneously examining the role of e-commerce platform characteristics and online consumer psychology in influencing behavioural intention. Numerous factors have been revealed by this investigation.

Building on associative priming, anthropomorphism and biophilia theories, this study aims to explain that a natural–organic (that shows a natural object) and an anthropomorphised natural–organic logo (that shows an anthropomorphised natural object) both act as primes and imbue specific product value perceptions, which subsequently influence willingness to pay a premium price when products have not been used by or are unfamiliar to consumers.

Two between-subjects experiments were conducted with different products (one with real, but unfamiliar to consumers brand and another with a fictitious brand). Structural equation modelling was used to test the hypotheses.

Experimental studies showed that natural–organic logos evoked stronger utilitarian (functional and economic) value perceptions, which triggered greater willingness to pay a premium price compared to anthropomorphised natural–organic logos. The effect of hedonic (emotional and novelty) values on willingness to pay a premium price was stronger when an anthropomorphised natural–organic logo was used.

This research offers novel theoretical contributions highlighting the importance of careful logo design to imbue desired value perceptions when products have not been consumed or trialled.

Anthropomorphised natural–organic and natural–organic logos can provide different benefits to brand managers and can be used strategically to form desired value perceptions before products are consumed. Brands that wish to enhance premium pricing via hedonic values should consider using an anthropomorphised natural–organic logo. Natural–organic logos may be more suitable for brands that want to emphasise superior utilitarian values.

To the best of the authors’ knowledge, this research provides the first empirical assessment of the differential effects of the two forms of natural–organic logos on value perceptions and willingness to pay premium price.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.