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Hypocrisy often observed in the social responsibility practices of commercial enterprises is more likely to occur in social enterprises. However, this issue has received little research attention. This study explores, from a consumer perspective, the formation of perceived hypocrisy and its impact on the cognitive legitimacy of social enterprises.

This research conducted two experiments, and data were collected from 515 subjects in China to test the proposed hypotheses.

Behavioral inconsistency in social enterprises leads to consumers' perceived hypocrisy. The higher the perceived hypocrisy towards social enterprises, the weaker their cognitive legitimacy of social enterprises. At a lower level of inconsistency, the perceived hypocrisy of social enterprises was lower than that of commercial enterprises. Egoistic attribution to prosocial behavior moderated the negative effect of perceived hypocrisy on cognitive legitimacy. The stronger the egoistic attribution, the greater is the negative effect of perceived hypocrisy on the cognitive legitimacy of social enterprises.

Social entrepreneurs should be acutely aware of the harmful effects of hypocrisy on social enterprises. Social enterprises should not exaggerate their propaganda or be consistent with their words and actions.

This study innovatively analyzes the damage to the cognitive legitimacy of social enterprises caused by the hypocrisy that tends to occur in commercial enterprises and argues from the consumer viewpoint. These findings enrich the perspective on exploring social enterprise legitimacy.

This paper aims to explore how a shared service centre (SSC) is mobilised in a power-dominant context of a Chinese state-owned enterprise (SOE). Specifically, it examines the mobilisation of SSC within this multi-divisional SOE, the role and dynamics of actors involved and the influence of changes in the integrated information system (IIS) during the mobilisation process.

The study follows a qualitative case study methodology. The authors draw on actor-network theory to examine the network and translation processes constructed in mobilising SSC in the chosen SOE. The data sources of this study were collected through semi-structured interviews, observations and documentary reviews.

The mobilisation of SSC is not a linear process but rather a “spiral” interplay through continuous interactions and compromises between human and non-human actors. Power gave the core actor as an orchestrator legitimacy and formality to reduce resistance and obstruction in translation for the mobilisation of SSC. The changes in IIS appear to facilitate the interaction between the heterogeneous actors.

This case study contributes towards understanding the mobilisation of SSC in a power-dominant context by highlighting the impact of changes in IIS and the details of the mobilisation of SSC in terms of the role played by both the individual actors and the technology.

This study provides a broader understanding of the interactions of the heterogeneous actors for mobilising SSC in a power-dominant context. More importantly, the study inspires future research into examining how SSC practices unfold and how the changes in IIS influence the mobilisation of SSC.

This study aims to clarify identity building and authenticity management in human brand research, focusing on inside operators managing corporate accounts on social media. Conventional human brand research analyzes online influencers, and there is a research gap in whether these previous findings apply to corporate accounts.

Using netnography and interview data, this study analyzes Japanese corporate accounts on Twitter.

A corporate account’s identity is constructed under the influence of not only the brand but also the actual inside operator, called naka-no-hito, and other accounts that interact on social media. Corporate accounts are able to exhibit humanistic passion through the inside operator’s personality and maintain a distance from commerciality – to manage their authenticity. These activities attract general and other corporate and media accounts, and interactions with them re-create promotion effects.

This study observed that corporate accounts’ authenticity is not a trade-off between passion and commercial transparency but a compatibility achieved by coordinating interests among actors, together with the presence of inside operators.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.

The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.

The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.

The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.

The purpose of this paper was to study the color change kinetics of lac dye in response to aldehydes, carbon dioxide and other food spoilage metabolites for its potential application in intelligent food packaging.

UV–Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A₅₂₈/A₄₈₈) with time using zero and first-order reaction kinetics. Lac dye-based indicator was prepared to validate the result of study for monitoring quality of strawberries.

Lac dye was orange-red in acidic medium and purple in alkaline medium. Color change of dye in response to benzaldehyde followed zero-order reaction kinetics, whereas for carbon dioxide first-order model was found best. No color change of dye solution was observed for alcohols, ketones and sulfur compounds. In the validation part, the color of the indicator label changed from purple to orange when the strawberries spoiled.

The study expands application area for lac dye as sensing reagent in intelligent food packaging for spoilage or ripeness detection of fruits and vegetables.

It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.

The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.

The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.

The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.

To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

Considering both the current opportunities of the Internet of things (IoT) and aviation, as well as the potential opportunities they may offer for the future, it is understood that they are among the important issues that need to be examined in the literature. This study aims to provide an idea by conducting bibliometric and visualization analyses of the current trends and development opportunities of IoT and aviation.

In this study, descriptive and bibliometric analyses within the framework of co-author, co-citation, bibliographic coupling, and keyword co-occurrence analysis were carried out for publications found to be published between 2007 and 2023 in the Web of Science (WoS) database related to IoT and aviation. VOSviewer (ver. 1.6.18) program and the Biblioshiny application were used to create bibliometric networks and provide visualization.

As a result of some descriptive and visualization analyses, the current trend of publications on IoT and aviation and future publication opportunities has been revealed. It has been understood that the subject of IoT and aviation is one of the subjects whose number of publications has increased in recent years and has not yet fully matured in terms of the number of publications and has the potential to make new publications.

In this study, bibliometric analysis of IoT and aviation, which could not be found examined before in the literature, and the creation of existing bibliometric networks by visualizing were carried out.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

The current study proposes a moderated mediation model to predict work-from-home engagement during an emergency such as the coronavirus disease 2019 (COVID-19) pandemic based on the integration of well-known concepts, including inclusive leadership, organizational support and perceived risk theory.

An online questionnaire on the Google Forms platform was designed and distributed to Vietnamese employees using a convenience sampling method. A total of 794 valid questionnaires were used for data analysis. Partial least squares structural equation modeling (PLS-SEM) was employed to test the proposed model and hypotheses. The instrument's validity and reliability were tested and ensured.

The study found that inclusive leadership has direct and indirect effects on work-from-home engagement through the separate and serial mediating roles of perceived organizational support and employee motivation. The present study also revealed that the effects of perceived organizational support and employee motivation on work-from-home engagement are strengthened by employee risk perception. Moreover, the study showed that perceived organizational support and employee motivation performed the lowest of the four elements that were considered, while the importance of these two factors was the highest.

These findings suggest that in an emergency such as COVID-19, contextual factors should be given more attention. Based on these findings, several theoretical and practical implications for human resource management are highlighted.

By integrating inclusive leadership, organizational support and perceived risk theory to explore employees' engagement in working from home during an emergency, the present study demonstrated that in addition to traditional factors, leadership and contextual factors should be considered for studies on working from home in an emergency such as the COVID-19 pandemic. The present study established that these factors might encourage employees' work-from-home engagement.