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As avatars are increasingly becoming popular, both scholars and businesses are acknowledging the vast potential that avatars hold for the future. Despite this growing interest in avatars, no review articles have attempted to provide a comprehensive overview of avatar literature and its implications for consumers. The present review addresses this gap using the combination of descriptive analysis (for corpus performance), bibliometric analysis (for corpus performance and emerging themes), and thematic analysis (for emerging themes and implications as well as future research opportunities). We conducted a review of 47 Scopus-indexed articles from 34 journals between year 2006 and 2023. By examining the corpus performance of avatar literature, the emerging themes, and future research opportunities, this review offers scholars a comprehensive overview of the subject matter.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

Property developers identify the vital role of social media brand engagement (SMBE) in sustaining their businesses in competitive marketplaces, but it remains underexplored. This paper examines how SMBE mediates the effects of firm-generated content (FGC) and user-generated content (UGC) on brand trust, considering the moderating effects of social media influencer endorsement (SMIE) and self-image congruence (SIC) for luxury residential properties (LRPs).

Around 516 high-income homebuyers in Vietnam who shared information about LRP on social media were targeted to test the research model empirically. The primary data collected from paper-based surveys were analysed using SPSS 26 and AMOS 24.

Results indicate that FGC and UGC positively impact SMBE and consequently significantly affect brand trust. Further, results confirm the moderating roles of SMIE and SIC in the effects of FGC and UGC on SMBE.

Data and sample size were limited to meet the generalisation from different nations and cross cultures.

The authors' findings suggest that marketers should apply the authors' integrated SMBE model to strengthen brand–consumer interactions and increase their sales revenue.

This study is the first in its application of the uses and gratifications theory and self-congruence theory to investigate how SMBE mediates the relationship between FGC and brand trust as well as between UGC and brand trust. Noticeably, this study makes a novel contribution as the first to quantitatively explore the moderating effects of SMIE and SIC in the authors' research model.

This paper aims to introduce International Digital Collaborative Autoethnographical Psychobiography (IDCAP).

This paper describes how IDCAP was developed to answer research questions about what it takes and what it means to recover from mental illness. During its development, IDCAP combined the diverse and intersectional experiences, knowledge and interests of an Anglo-Swedish research team with what could be found in different publications concerning the experiences and the mental illnesses of the musicians Syd Barrett, Peter Green and Brian Wilson.

IDCAP combines features of autoethnography and psychobiography to offer a novel qualitative research method.

Whilst IDCAP was created to focus on recovery from mental illness and musicians, it can be applied to other areas of research. It shares the same limitations as autoethnography and psychobiography, although some of the features of IDCAP may go some way to mitigate against these.

IDCAP is a novel research method that is offered to other researchers to develop and enhance further through application.

IDCAP is a collaborative research method that encourages the involvement of a wide range of researchers from different countries and cultures. It can be used to give voice to marginalised groups and to counter discrimination and prejudice. Recovery from mental illness is a topic of great personal and social value.

IDCAP is a novel research method that, to the best of the authors’ knowledge, has not been explicitly used before.

Self-initiated international placements by students have been largely ignored in the literature on outward mobility in higher education. The support given to self-initiated international placement students, if any, has received even less attention. This study aims to address this lacuna.

Drawing on insights from global mobility literature, we conducted a survey of UK university students who engaged in self-initiated international placements to various countries such as France, China, Brazil and Ghana. Data were analysed using descriptive statistics and thematic content analysis.

Findings reveal that these “voluntary” placements can improve language fluency, increase self-confidence, renew stress management abilities and enhance cross-cultural competencies and intercultural sensitivity. The study problematises the lack of support given to these students particularly in terms of career development.

Our paper is one of the first to bring this under-studied population to the attention of career guidance scholars. We propose that scholarly attention should be directed toward the agency of self-initiated international placement students and that targeted career guidance must be provided through more inclusive career services.

The purpose of this study is to develop a molecular imprinting electrochemical sensor for the specific detection of the anticancer drug amsacrine. The sensor used a composite of bacterial cellulose (BC) and silver nanoparticles (AgNPs) as a platform for the immobilization of a molecularly imprinted polymer (MIP) film. The main objective was to enhance the electrochemical properties of the sensor and achieve a high level of selectivity and sensitivity toward amsacrine molecules in complex biological samples.

The composite of BC-AgNPs was synthesized and characterized using FTIR, XRD and SEM techniques. The MIP film was molecularly imprinted to selectively bind amsacrine molecules. Electrochemical characterization, including cyclic voltammetry and electrochemical impedance spectroscopy, was performed to evaluate the modified electrode’s conductivity and electron transfer compared to the bare glassy carbon electrode (GCE). Differential pulse voltammetry was used for quantitative detection of amsacrine in the concentration range of 30–110 µM.

The developed molecular imprinting electrochemical sensor demonstrated significant improvements in conductivity and electron transfer compared to the bare GCE. The sensor exhibited a linear response to amsacrine concentrations between 30 and 110 µM, with a low limit of detection of 1.51 µM. The electrochemical response of the sensor showed remarkable changes before and after amsacrine binding, indicating the successful imprinting of amsacrine in the MIP film. The sensor displayed excellent selectivity for amsacrine in the presence of interfering substances, and it exhibited good stability and reproducibility.

This study presents a novel molecular imprinting electrochemical sensor design using a composite of BC and AgNPs as a platform for MIP film immobilization. The incorporation of BC-AgNPs improved the sensor’s electrochemical properties, leading to enhanced sensitivity and selectivity for amsacrine detection. The successful imprinting of amsacrine in the MIP film contributes to the sensor's specificity. The sensor's ability to detect amsacrine in a concentration range relevant to anticancer therapy and its excellent performance in complex sample matrices add significant value to the field of electrochemical sensing for pharmaceutical analysis.

The purpose of the article is to shed light on how COVID-19 affects employee involvement in environmental responsibility and innovative performance in the banking industry, and whether employee engagement mediates the relationship between the variables. Thus, this study tries to understand bank employees’ perspectives in relation to the variables.

The study was collected during Time lag (1) and Time lag (2) from 156 to 216 bank employees, respectively. The study applied two types of analysis, to comprehend the impact of COVID-19 on employees, descriptive analysis and the partial least squares (PLS) are used.

The study's findings focused mainly on the influence of COVID-19 in Jordanian banks on employee innovative performance (EIP) due to pandemic, in addition to its effect on environmental responsibility engagement (ERE). The findings indicated a positive significant relationship between the variables. Meanwhile, employee engagement (EE) mediated the effect between the exogenous and endogenous variables.

The current research provide light on the value of employees' innovative performance and banks' commitment to environmental responsibility for those working in the banking industry, particularly during a pandemic. The findings have significant ramifications for the banking industry and in raising employee engagement.

The relationship between industrial policy and exploratory innovation is imperfect.

The authors use Chinese high-tech enterprise identification policy (HTEP) as a natural experimental group to test policy impacts, spillover effects and mechanisms of action.

First, HTEP promotes exploratory innovation. In addition, HTEP has a greater impact on non-exploratory innovation. Second, HTEP has spillover effects in two phases: HTEP (2008) and the 2016 policy reform. HTEP affects exploratory innovation in nearby non-high-tech firms, and the policy effect decreases monotonically with increasing distance from the treatment group. Third, HTEP affects innovation capacity through financing constraints, technical personnel flow and knowledge flow, which explains not only policy effects but also spillover effects. Fourth, the analysis of policy heterogeneity shows that the 2016 policy reforms reinforce the positive effect of HTEP (2008). By deducting the effects of other policies, the HTEP effect is found to be less volatile. In terms of the continuity of policy identification, continuous uninterrupted identification has a crucial impact on the improvement of firms’ innovation capacity compared to repeated certification and certification expiration. Finally, HTEP has a crowding-out effect in state-owned enterprises and large firms’ innovation.

This paper contributes to the existing literature in several ways. First, the authors enrich the literature on industrial policy through exploratory innovation research. While previous studies have focused on R&D investment and patents (Dai and Wang, 2019), exploratory innovation helps firms break away from the inherent knowledge mindset and achieve sustainable innovation. Second, few studies have explored the characteristics of industrial policies. In this paper, the authors subdivide the sample into repeated certification, continuous certification and certification expiration according to high-tech enterprise identification. In addition, the authors compare the differences in policy implementation effects between the 2016 policy reform and the 2008 policy to provide new directions for business managers and policy makers. Third, innovation factors guided by industrial policies may cluster in specific regions, which in turn manifest externalities. This is when the policy spillover effect is worth considering. This paper fills a gap in the industrial policy literature by examining the spillover effects. Finally, this paper also explores the mechanisms of policy effects from three perspectives: financing constraints, technician mobility and knowledge mobility, which can affect not only the innovation of beneficiary firms directly but also indirectly the innovation of neighboring non-beneficiary firms.

This paper aims to reduce waste management and generate wealth by investigating the novelty of combining chicken feather fiber and bamboo particles to produce hybrid biocomposites. This is part of responsible production and sustainability techniques for sustainable development goals. This study aims to broaden animal and plant fiber utilization in the sustainable production of epoxy resins for engineering applications.

This research used two reinforcing materials [chicken feather fiber (CFF) and bamboo particles (BP)] to reinforce epoxy resin. The BPs were kept constant at 6 Wt.%, while the CFF was varied within 3–15 Wt.% in the composites to make CFF-BP polymer-reinforced composite (CFF-BP PRC). The mechanical experiment showed a 21% reduction in densities, making the CFF-BP PRC an excellent choice for lightweight applications.

It was discovered that fabricated composites with 10 mm CFF length had improved properties compared with the 15 mm CFF length and pristine samples, which confirmed that short fibers are better at enhancing randomly dispersed fibers in the epoxy matrix. However, the ballistic properties of both samples matched. There is a 40% increase in tensile strength and a 54% increase in flexural strength of the CFF-BP PRC compared to the pristine sample.

According to the literature review, to the best of the authors’ knowledge, this is a novel study of chicken fiber and bamboo particles in reinforcing epoxy composite.

Considering the ongoing discourse on diversity, equity and inclusion, brands aim to develop marketing campaigns that demonstrate respect for all individuals. Despite these intentions, many advertisements still provoke strong negative reactions from consumers due to brand transgressions in social media marketing campaigns that violate these values. The purpose of this paper is to analyze the repercussions that such social media marketing campaigns have on brands, categorizing these campaigns as brand transgressions in social media advertising.

This research uses a mixed-method design that includes semi-structured interviews (Study 1), a content analysis (Study 2) and an online experiment (Study 3).

This paper clarifies the elements that qualify as brand transgressions in advertising within the diversity, equity and inclusion discourse. The negative electronic word-of-mouth (e-WOM) associated with brand transgressions in advertising comprises negative emotions (e.g. anger, contempt, disgust and hate) and behavioural intentions to penalize the brand (e.g. negative word-of-mouth, brand avoidance and protest behaviours). The negative e-WOM stemming from these transgressions amplifies the adverse consequences for consumer–brand relationships by negatively influencing other consumers through sympathy towards the offended parties.

This paper offers brand managers guidelines for preventing and managing negative consumer reactions towards brands based on their responses to marketing campaigns that contradict the principles of diversity, equity and inclusion.

This paper contributes to the literature on brand transgressions related to diversity, equity and inclusion values by exploring their impact on consumer–brand relationships and highlighting the pivotal role of sympathy in perpetuating negative consequences.