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This study investigates how individuals' self-awareness (specifically, private and public self-awareness) and environment-awareness (perceived expertise, similarity and familiarity) shape herd behavior, encompassing discounting one’s information and imitating others. Drawing from latent state-trait theory, this research aims to discern the impact of these factors on purchase intention and behavior.

Longitudinal data from 231 users in Xiaohongshu, China’s leading social commerce platform, were collected to test the proposed model and hypotheses.

The findings from this study show that private self-awareness negatively influences discounting one’s own information and imitating others. Public self-awareness positively affects imitating others, while it does not affect discounting one’s own information. Perceived expertise diminishes discounting one’s own information but does not significantly affect imitating others. Perceived similarity and perceived familiarity are positively related to discounting one’s own information and imitating others. The results confirm different interaction effects between self-awareness and environment-awareness on herd behavior.

First, this contributes back to the latent state-trait theory by expanding the applicability of this theory to explain the phenomenon of herd behavior. Second, this study takes an important step toward theoretical advancement in the extant literature by qualifying that both self- and environment-awareness should be considered to trigger additional effects on herd behavior. Third, this study provides a more enlightened understanding of herd behavior by highlighting the significance of considering the interplay between self- and environment-awareness on herd behavior. Finally, this study also empirically confirms the validity of classifying self-awareness into private and public aspects.

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

This study aimed to determine whether the brand image of fast-food restaurants moderates the relationship between satisfaction and loyalty among Chilean customers.

The study was conducted using a structural equation modeling approach and involved a sample of 1,000 fast-food customers who were surveyed through nonprobabilistic sampling with a questionnaire consisting of 21 items. The instrument underwent validation by a panel of experts, and the results obtained were processed using the statistical software Smart PLS4. Convergent validity, discriminant validity and the structural model were tested to assess the acceptance or rejection of the proposed hypotheses.

The results of the research indicate that product quality, service quality and physical environment are crucial factors influencing customer satisfaction and shaping customer loyalty. However, it was found that brand image does not moderate the relationship between satisfaction and loyalty in fast-food consumption.

The present study contributes to the field of knowledge on fast-food consumption behavior and unveils findings that help fill knowledge gaps regarding the influence of restaurant brand image on the relationship between satisfaction and consumption loyalty. Thus, it demonstrates that, for certain customers, the brand becomes an irrelevant factor for their consumption loyalty as long as the restaurant offers product quality, excellent service and a pleasant physical environment.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

This paper aims to explore students’ intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh.

The present study uses convenience sampling techniques to collect data from the respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total of 413 responses to examine the study’s measurement and structural model.

The results explore that perceived ease of use (PEOU) negatively affects intention to adopt AI-powered chatbots (IA), whereas university students’ perceived usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) and electronic word-of-mouth (EWOM) have a positive and direct impact on their IA. The finding also reveals that students' IA positively and significantly affects their actual use of AI-based chatbot (AU). Precisely, out of the five constructs, the TSF has the strongest impact on students’ intentions to use chatbots.

Students who are not aware of the chatbot usage benefits might ignore these AI-powered language models. On the other hand, developers of chatbots may not be conscious of the crucial drawbacks of their product as per the perceptions of their multiple users. However, the findings transmit a clear message about advantages to users and drawbacks to developers. Therefore, the results will enhance the chatbots’ functionality and usage.

The findings of the study alert the teachers, students and policymakers of higher educational institutions to understand the positive outcomes and to accept AI-powered chatbots such as OpenAI’s ChatGPT. Outcomes also notify the AI-product developers to boost the chatbot’s quality in terms of timeliness, user-friendliness, accuracy and trustworthiness.

This study aims to investigate the relationship between digital financial inclusion and economic growth in specific Asian countries, emphasizing the exploration of how digital financial inclusion dynamics impact gross domestic per capita income.

The study creates a digital financial inclusion composite index (DFII) by incorporating essential metrics from the Global Findex report. Economic growth is measured using Gross Domestic Product per capita income in its natural logarithmic form (LnPCI), with three control variables– employment-to-population ratio; population growth and inflation. The analysis utilizes a fixed-effect dummy variable model to examine the relationship, considering unobserved country-specific heterogeneity. 30 Asian countries have been selected for the study for the periods 2014, 2017 and 2021 based on their availability, as outlined in Table 4.

The research revealed a robust positive correlation between the Digital Financial Inclusion Index (DFII) and logarithmic GDP per capita income (LnPCI), indicating higher per capita income with enhanced digital financial inclusion. Employment and population exhibited minimal influence, whereas inflation had a notable negative effect on per capita income. Population growth showed a limited impact. The model demonstrated a high explanatory power for the dependent variable (high R-squared), and the residuals displayed low autocorrelation (Durbin–Watson of 1.96).

This study adds to the existing literature by examining the intricate connection between digital financial inclusion (DFI) and economic growth in 30 Asian countries, employing a comprehensive composite index for analysis.

The circular economy business models (CEBMs) provide ways for firms operating in the construction industry to move from a linear to a circular approach. Thus, this study aims to explore CEBM research within the construction sector to show the focus area of studies, highlighting new areas that require attention.

This study adopted a bibliometric approach, using the Scopus database as the data source. The keywords used for paper extraction from the database were “circular economy business” OR “circular business” AND “model” OR “models” AND “construction industry” OR “building industry”. The VOSviewer software was then used to prepare a co-occurrence and co-authorship map based on the bibliographic data gathered.

The study’s findings reveal five research clusters in the construction industry. These clusters include circular construction intelligence, modular business modelling, eco-construction, sustainable construction economics and smart energy-efficient buildings. The two most cited scholars had two publications each, while the top journals are the Journal of Cleaner Production and Sustainable Production and Consumption. This study concludes that there is a need for research within the construction sector to focus on CEBMs’ archetypes and frameworks. This will enable a smooth transition from linear to circular business models in the sector.

The information was gathered from a single database, Scopus; hence, using other databases, including Web of Science, Google Scholar and Dimensions, might produce more articles for examination and, consequently, different findings on the subject under investigation.

These findings would assist researchers in considering the areas mentioned, which are yet to receive attention, and, by extension, enhance economic development while maintaining environmental sustainability.

This paper made a significant contribution to the body of knowledge by identifying scholars and platforms that have been instrumental in advancing CEBM research and highlighting new areas that require attention in the construction sector.

The decisions of contractors could impact the reduction of construction carbon footprint. These decisions are linked to the belief of contractors which equally affects how they behave while delivering projects. This study aims to investigate the behavioural tendencies of contractors that could lead to carbon minimisation during the execution of construction projects.

An industry survey was performed amongst 41 UK construction professionals. Spearman’s correlation and factor analysis were used to analyse the data.

The result of the Spearman’s correlation gave rise to 14 contractors’ carbon reduction behaviour (CCRB) variables and their factor analysis yielded two distinct factors, namely, contractors’ consummate carbon reduction behaviour and contractors’ pragmatic carbon reduction behaviour. The findings suggest that in the UK, contractors are willing to take voluntary practical steps to decrease the carbon footprint of construction projects.

This finding might be unexpected to construction stakeholders, especially construction clients who may believe that infusing strict carbon reduction obligations in contracts is sufficient in nudging contractors to lessen the carbon impact of projects.

The study attempted to quantitatively derive CCRB, thereby extending the breadth of knowledge in the construction carbon reduction domain.

Food delivery apps (FDAs) have rapidly developed due to mobile technologies, changes in modern consumption and increased online use during the COVID-19 pandemic. Despite this, the platforms are struggling to build a stable customer base and make a profit. This study combined tech-driven motivators in an information system success model (ISSM) and emotional attachment operated by affect transfer theory (ATT) to explain why people might continue to use an FDA.

An online quantitative cross-sectional survey was carried out via the Prolific platform. Data were collected from 416 FDA users and analyzed to test the hypotheses using the partial least squares based structural equation modeling.

The study found that system quality, information quality and emotional attachment directly influence the continued use of FDA. Moreover, the results suggest that perceived social interactivity and perceived playfulness are significant antecedents of emotional attachment.

The findings of this study enrich the current literature on continuance intention in online food delivery services by integrating the technology- and affective-based factors. The findings also provide various practical implications for app designers and marketers to foster an emotional bond with users, resulting in high retention rate.

The study proposes the integrated framework of ISSM and ATT for enhancing understanding of consumer behaviors in the post-adoption stage for FDA.

The purpose of this paper is to calculate the financial inclusion index and analyze its dynamics in developing countries.

The authors use the two-stage principal component analysis (PCA) method and consider financial technology innovations to improve the accuracy of the financial inclusion index.

The authors found a downward trend in the financial inclusion index in most developing countries over the study period. The authors also found that a high financial inclusion index is linked to high scores in the Doing Business and high business climate regulation ranking. In addition, the authors observed that the rates of low financial inclusion in developing countries are due to low utilization of and unequal access to financial services.

The analysis suggests that policymakers in developing countries could invest in digital infrastructure to extend access to financial services in remote areas. They could also encourage financial innovation, particularly in financial technologies, by adopting flexible regulatory frameworks. Promoting the financial inclusion of marginalized groups through targeted initiatives tailored to their needs is another solution. They could also encourage the use of financial services by raising awareness and educating populations through training programs. Finally, to improve the business climate, governments could simplify administrative procedures and promote transparency and legal stability.

Unlike previous studies, the use of the two-stage PCA method and the consideration of financial technology (Fintech) innovations such as mobile money in the determinants of the financial inclusion index improve the accuracy of the index.