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This study aims to progress scholarly understanding of the staycation phenomenon by examining customer segments and documenting local customers’ attribute preferences.

A stated choice experiment is used to examine customer preferences for staycation package attributes. Latent class discrete choice modeling is deployed to classify customers into market segments based on their preferences. The profile of each segment is enhanced by documenting customer characteristics and consumption styles.

Six prominent market segments are identified using a combination of sociodemographics, consumption styles and staycation attribute preferences. The findings draw on consumer experiences during the COVID-19 pandemic to generate theoretical insights into preferred staycation packages. Empirically, the estimation results from the research framework and choice experimental method demonstrate that staycation market segments exhibit distinct preference structures.

Practitioners and policymakers can incorporate the findings of this study in designing and/or assessing staycation packages. This can ensure differentiated products for defined segments that resonate within local communities through positive word of mouth, thus offering prospective spillovers to visiting friends and relatives.

This is a pioneering study on preference heterogeneity from the customer perspective, with a focus on staycation markets. The findings can encourage and assist hotel sector leaders to capitalize on local market developments to achieve a more resilient hospitality business model.

The purpose of this study is to identify the process of virtual influencer stickiness in the age of influencer marketing, which has received little attention in the literature. This is essential because the research creates a theoretical model of follower loyalty/stickiness to virtual influencer techniques from the standpoint of influencer marketing, which has a substantial effect on the evolution of the global marketing world.

In 2022, 302 people who currently follow an Instafamous virtual influencer took part in an Instagram self-administered online survey.

The findings show that both expertise and trustworthiness have a positive and significant influence on parasocial interaction, which in turn has a significant influence on virtual engagement and stickiness.

This research will specifically assist international readers in understanding how to harness and increase the efficiency and efficacy of interactive marketing strategies and methods to engage and retain followers of Instafamous virtual influencer. Moreover, the findings will be beneficial to opinion leaders, brand managers, company investors, entrepreneurs and service designers.

1. The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

2. This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

3. In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

4. This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The present work aimed to present the perception of Tunisian professionals towards companies engaged in social responsibility practices and describe the tax evasion strategies of socially responsible Tunisian companies following the coronavirus disease 2019 (COVID-19) pandemic (COVID-19) shock.

A survey was sent to 119 Tunisian tax administration auditors. Data analysis methods principal component analysis (PCA) and regression analysis were used. The data were collected through a questionnaire after the general containment of Tunisia from September 2020 to February 2021. These quantitative data were analysed using processing software (STATA).

Professionals of the tax authorities, particularly those in charge of the audit mission, aim for corporate profitability from the perspective of stakeholders that seek to integrate ethics and social responsibility into companies and consider employee morale a top priority. The results show that highly ethical and socially responsible professionals are far from practising aggressive strategies. Thus, an auditor from the tax administration is far from engaging in social responsibility to justify fraudulent acts. During the COVID-19 period, the role of these professionals was to prevent and detect fraud in the tax sector to fight corruption and investigate taxes based on sound regulations.

The results are consistent with optimal taxation theory, which postulates that a tax system should be chosen to maximise a social welfare function subject to a set of constraints. Professionals seek to make taxation much simpler for taxpayers by providing advice and consultation to manage tax obligations. The minimisation of tax or the play of tax values requires expertise in the field to respect legal constraints. Therefore, these professionals play a crucial role in tax collection, as the professionals' advice and suggestions can influence taxpayers' decision-making.

In recent years, academic researchers, policy makers and the public have become increasingly interested in corporate tax evasion behaviour. At the same time, companies are under increasing pressure to integrate CSR into the companies' decision-making processes, which has led to increased academic interest in CSR. Opportunistic tax minimisation reduces state resources and funds needed for government programmes to improve the social welfare of the entire community. This study represents an overriding concern not only for legal and tax authorities and companies, but also for shareholders and stakeholders.

The authors' study contributes to the existing literature by determining the state of play on corporate social responsibility (CSR) practices amongst Tunisian tax authorities' professionals. In Tunisia, an executive of the tax authorities in charge of the verification mission is required to verify the proper application of the accounting and tax legislation in force, follow up on tax control operations on declared taxes and validate the sincerity of the accounts. This study focussed on the tax evasion of companies engaged in social responsibility practices according to the judgements of Tunisian tax authorities' auditors during the global COVID-19 pandemic.

This paper aims to determine the impact of perceived virtuality on team dynamics and outcomes by adopting the Input-Mediators-Outcome (IMO) framework. Further, it also investigates the mediating role of team processes and emergent states.

The authors collected survey data from 315 individuals working in virtual teams (VTs) in the information technology sector in India using both offline and online questionnaires. They performed the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The authors investigated two sets of hypotheses – both direct and indirect (or mediation interactions). Results show that psychological empowerment and conflict management are significant in managing VTs. Also, perceived virtuality impacts team outcomes, i.e. perceived team performance, team satisfaction and subjective well-being.

The interplay between the behavioural team process (conflict management) and the emergent state (psychological empowerment) was examined. The study also helps broaden our understanding of the various psychological variables associated with teamwork in the context of VTs.

Findings from this study will aid in assessing the consequences of virtual teamwork at both individual and organisational levels, such as guiding the design and sustainability of VT arrangements, achieving higher productivity in VTs, and designing effective and interactive solutions in the virtual space.

The study examined the interplay between behavioural team processes (such as conflict management) and emergent states (such as psychological empowerment). The study also theorises and empirically tests the relationships between perceived virtuality and team outcomes (i.e. both affective and effectiveness). It may serve as a guide to understanding team dynamics in VTs better.

This exploratory study attempts to enhance the current understanding of the research and practice of VTs within a developing economy.

With the empirical evidence on the purchase behaviour of tinned tomatoes, food labelling and the safety consciousness of consumers in Ghana were examined.

Primary data were obtained from 130 consumers. Descriptive statistics, factor analysis and multinomial probit analysis were applied.

Consumers use tinned tomatoes for cooking because of its easy accessibility in nearby shops, guaranteed constant supply, attractive package, it being affordable/cheaper, its better colour, advertisement/promotion, and longer shelf life. There is a low level of food safety consciousness among consumers since only one-fifth read labels on tinned tomatoes very often, and one-fifth do not read labels at all. Consumers frequently check on tinned tomatoes' most essential information: brand/type, manufacturing and expiry dates, and weight/volume. Age, residential status, contact information, nutritional benefits and affordability influence the choice of retail brand of tinned tomatoes. The health label consumer segment and conventional label consumer segment were identified, with the majority being the former.

The sample size used for the study could be improved in terms of number and geographical coverage. This is because the study was limited to only one main urbanised area in Ghana. Therefore, it will be worthwhile for a further study to be conducted by comparing urban and rural consumers in Ghana and other countries within Africa, to either validate or reveal a different trajectory of consumer behaviour relevant to marketing, policy and practice.

Tomato paste (tinned tomatoes) is consumed in almost all homes in Africa, but there are food scare concerns about tinned tomatoes due to reported cases of adulteration with unhealthy materials such as starch and food colour, leading to negative health implications on consumers. This makes the reading of tinned tomato labels very crucial. Thus, it is of policy relevance to investigate consumers' reading behaviour of label information on tinned tomatoes in Ghana. However, previous studies on food labelling focussed on food and nutrition labelling and implications of food labelling on consumers' purchase behaviour, with most of them outside Africa.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

There is limited research examining the relationship between social media and green food purchasing behaviour. In the current study, we examine the factors that affect consumers’ green food purchasing behaviour in Türkiye.

Data collected from the participants by survey method were analysed using Smart PLS 4.0 with IBM SPSS 26 and PLS to run SEM.

Our findings have revealed that from all the structural elements in the theory of planned behaviour (TPB), only attitude and perceived behavioural control contribute to consumers’ green food purchasing behaviour, while subjective norms do not contribute to consumers’ green food purchasing behaviour. Additionally, it was found that social media usage (SMU) and digital marketing interactions (DMI) have a positive and significant effect on green food purchasing behaviour. More information, experiences, opinions and recommendations on green foods in social media channels can encourage consumers to buy more green food.

This study first evaluates the applicability of the TPB model in explaining green food purchasing behaviour. This study is extended with two new factors included in the original framework of the TPB model, namely, SMU and DMI.

The purpose is to use co-citation analysis of servant leadership (SL) research to investigate the evolution of the field, its subfields, gaps and opportunities for future research in a systematic manner.

A document co-citation technique and three clustering algorithms (latent semantic index (LSI), the log-likelihood ratio (LLR) and the mutual information (MI) index) were employed to analyse 24,030 references from 549 articles spanning a period of 50 years.

Cluster analyses reveal that SL research consists of eight distinct subfields: (1) conceptualisation and measurement of SL; (2) SL and related theories; (3) methodological foundations and empirical expansion of SL research; (4) individual-level cognitive effects of SL and related theories; (5) “Warmth effects” of leadership behaviour; (6) antecedents of effective leadership; (7) SL, marketing, sales management and ethics and (8) SL, job design and work engagement. Important gaps and opportunities for future research are identified.

The analyses do not show a complete picture of research on SL. Interesting works used by subgroups of SL researchers may not have enough citations to be included in the results. Moreover, bibliometric analyses do not explain the impact of books, journals and articles on the practice of SL. The authors welcome future analyses of the most influential sources of SL practice. The authors expect that managerial and practice-oriented books and journals, such as the International Journal of Servant Leadership and the Servant Leadership Theory and Practice, would play a central role in such analyses.

The discussions of the nature of SL, its effects and antecedents are useful to leaders who want to develop a SL style or assist others in developing it. For researchers and doctoral students, the cluster analyses of co-citations give an overview of the subfields of SL research and reveal important knowledge gaps in the literature.

SL has several favourable effects on the motivation and psychological well-being of followers. Also, followers tend to adopt a willingness to serve.

Previous research has categorised SL research into three broad categories or phases. The cluster analyses of the co-citations reported here reveal a meaningful structure of eight distinct subfields. Knowledge gaps within the subfields represent novel opportunities for future research on SL. The authors also suggest a new subfield of SL research: pedagogical approaches to the motivation and development of SL skills.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

The tech savvy generation Z consumers constitute a significant market of online shopping. Understanding their shopping behavior is thus a pressing need to expand the e-commerce business. Under this backdrop, the study aims to predict the online shopping behavior of generation Z customers in Bangladesh.

This study used the theory of consumption values (TCV) along with shopping enjoyment to understand the online shopping behavior of generation Z. A structured set of questionnaire was used to gather the responses on a five point Likert scale. A total of 411 valid responses were considered after discarding incomplete responses. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) approach with the help of smart PLS 4.0 software.

The statistical findings reveal that functional value is the most significant determinant of online shopping behavior among generation Z followed by social value, conditional value and epistemic value. The study also reveals that relationship between emotional value and online shopping behavior and relationship between conditional value and online shopping behavior is moderated by shopping enjoyment.

The paper contributes to the consumer behavior literature as the findings provide a comprehensive model from values perspectives to understand online shopping behavior among Gen Z customers in a developing country like Bangladesh. The findings of this study offer important insights to the marketers also since it reveals the values consumers consider while shopping online. The findings might help practitioners develop their online strategies to expand the business.