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Although existing studies provide valuable insight into how destinations create stimuli that support meaningful experiences, perceptions of different experiencescapes in the tourism context remain to be explored. This research aims to explore the experiencescape stimuli of female digital nomads.

The study adopted a qualitative research method and was structured by combining multiple qualitative data collection tools with a triangulated approach to examining the experiencescape.

Based on the experiences of female digital nomads toward destinations, their perception of the experiencescape, which includes sensory, functional, social, natural and cultural stimuli, has been revealed. From the explanations regarding the metaphors, the female digital nomads in the research have positive perceptions about destination experiences and are satisfied with being digital nomads.

The fact that the research is the first to focus on digital nomadism and experiencescape and that it reveals the perspective of female digital nomads who share their experiences in virtual communities, which is a research topic that is little emphasized in the literature, is a contribution to the theoretical framework on the subject. The practical contribution is that it will guide studies to improve and re-plan experiences in line with the stimuli emphasized by the female digital nomads studied. The results can play a supporting role in developing the market for female digital nomads.

This research offers a new perspective on exploring female digital nomads' perceptions of the destination experiencescape.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.

This paper aims to explore the role of perceived organizational injustice (POI) leading to workplace conflict in determining organizational performance (OP) among healthcare employees. This paper also examines the serial mediating effects of moral disengagement (MD) and knowledge hiding (KH).

In all, 244 public and private hospital employees in Pakistan provided the data set.

According to partial least squares-structural equation modeling findings, the negative association between POI and OP was serially mediated by KH and MD. The recovery process underlying the linkage between POI and OP is tested and highlighted in this paper as a first step in unraveling it.

The findings highlight the significance of taking moral and KH models into account when attempting to understand the moral cognitive processes that employees go through when they see injustice. Organizations should guarantee the equitable distribution of incentives and resources, as distributive and procedural justices are concerned with organizations.

By directing actions meant to prevent MD and KH, the findings may potentially inspire new, more focused treatments to safeguard patient safety and avoid losses in the healthcare industry. One way to reduce unethical conduct and MD is to have people declare or agree to a code of ethics.

The purpose of this paper is to identify the differences between Hungarian family-owned businesses (FOBs) and non-family-owned businesses (NFOBs) concerning the elements of SME competitiveness and financial performance.

The research covers the Hungarian data set of the Global Competitiveness Project (GCP, www.sme-gcp.org) of 738 (data collection between 2018 and 2020) non-listed SMEs, of which 328 were FOBs. The study uses the comprehensive, multidimensional competitiveness measurement of the GCP built on the resource-based view (RBV) and the configuration theory. Financial performance was captured with two composite indicators: short-term and long-term financial performance (LTFP). The comparative analysis between FOBs and NFOBs was conducted using binary logistic regression.

The results show that FOBs are more prone to focusing on local niche markets with higher longevity and LTFP than NFOBs. However, FOBs have lower innovation intensity and less organised administrative procedures. The most contradicting finding is that the FOBs’ higher LTFP is accompanied by significantly lower competitiveness than in the case of NFOBs.

This study goes beyond other GCP studies by including composite financial performance measures among the variables examined. The combination of performance-causing (resources and capabilities) and performance-representing (financial performance) variables provides a better understanding of the non-listed SMEs in terms of family ownership. The results help academia to enrich the RBV-competitiveness, the non-listed SME management and finance literature, and policymakers to design business development and support schemes. They also show future entrepreneurs the impact of family ownership on entrepreneurial success.

Unstructured data such as images have defied usage in property valuation for a long time. Instead, structured data in tabular format are commonly employed to estimate property prices. This study attempts to quantify the shape of land lots and uses the resultant output as an input variable for subsequent land valuation models.

Imagery data containing land lot shapes are fed into a convolutional neural network, and the shape of land lots is classified into two categories, regular and irregular-shaped. Then, the intermediate output (regularity score) is utilized in four downstream models to estimate land prices: random forest, gradient boosting, support vector machine and regression models.

Quantification of the land lot shapes and their exploitation in valuation led to an improvement in the predictive accuracy for all subsequent models.

The study findings are expected to promote the adoption of elusive price determinants such as the shape of a land lot, appearance of a house and the landscape of a neighborhood in property appraisal practices.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

This study aims to investigate the ecological awareness of Chinese consumers towards fast fashion and examine the effect of social sustainability claims on green brand image and purchase intentions in China, considering China’s unique environmental policy landscape and its significant role in the global fast fashion industry. The study explores the role of altruistic values in promoting sustainability within the well-known fast fashion brand “H” and how they shape brand image, consumer satisfaction and brand equity.

The study collected data from 257 Chinese participants and used a serial mediation model through the PROCESS macro in SPSS to analyse the correlation between green brand image, created through sustainability claims and consumer purchase intentions. The model also assessed the intermediary effects of brand image, satisfaction and equity.

The findings of the research indicate a direct and positive relationship between green brand image and consumer purchase intentions, emphasising the need for clothing and textile industry marketers to strategically promote altruistic values in their sustainability efforts and highlighting the importance of ecological awareness in shaping consumer behaviour in the Chinese context. This approach enhances green satisfaction and green brand equity and ultimately leads to higher green purchase intentions.

This study provides significant insights into the effectiveness of incorporating social sustainability claims in advertising to improve a brand’s green image and influence consumer behaviour. It emphasises the importance of altruistic values in sustainability strategies, offering valuable guidelines for marketers in enhancing green satisfaction and brand equity, thereby boosting consumer purchase intentions in the context of green branding and sustainability advertising. Focussing specifically on the Chinese market, this research sheds light on the impact of ecological awareness among Chinese consumers within the fast-fashion industry. Given China’s substantial role in shaping global fast-fashion production and its evolving environmental policies, this focus adds significant depth to our understanding of sustainability claims’ influence within this crucial consumer base.

Many believe that any social media harms kids because of frequent use. This study aims to examine these assumptions. It proposes and tests a model that considers two alternative pathways – one negative and one positive – through which social media affects teens’ self-reported subjective well-being.

This research used Preacher and Hayes process modeling to conduct path analysis on data collected on 585 teenagers from across the USA.

Results showed that along a negative pathway, frequent social media use leads to greater risky social media engagement that ultimately diminishes adolescent’s sense of well-being. Also, and perhaps simultaneously, frequent social media use leads to socially-connected social media use that enhances adolescent’s sense of well-being.

The research recommends ways parents, policymakers and platforms can encourage teens to use social media to connect with friends while guiding them away from pathways exposing them to risky behaviors.

Findings show more social media use is not necessarily harmful, but more of some types is bad, while more of others is good.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

The main objective of our study is to shed light on how perceived enjoyment influences the intricate relationship between value cocreation and consumer satisfaction, with a specific focus on the realms of tourist services.

To achieve the objective outlined in this research, an information survey was carried out on 400 consumers of tourist services who have participated in virtual cocreation processes through digital platforms. As a data analysis technique, the dynamic structural equation modeling (DSEM) analyzes the causal relationships between the elements under study.

Our extensive analysis draws upon the data collected through a survey spanning from 2018 to 2023, encompassing 400 participants who actively engaged in value cocreation processes in both physical and virtual settings. Our investigation considers two competing models to elucidate the role of perceived enjoyment. Our findings, established through DSEM illuminates that perceived enjoyment predominantly functions as a mediator, exerting a more pronounced influence on the connection between value cocreation and consumer satisfaction. Contrary to a moderating role, perceived enjoyment emerges as a significant mediator in our study.

The most significant addition is recognizing virtual value cocreation behaviors in tourist sector activities over time, primarily because it indicates the likelihood of negative repercussions of its usage. Furthermore, it must be capable of designing surroundings according to the characteristics of customers in terms of immersion and technology usage, preventing a rise in stress situations that might result in more negative consequences than planned. Another important insight is that virtual value cocreation initiatives have detrimental long-term implications, particularly in tourism.