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The main goal of this paper is to present a synthetic multiple criteria group decision-making (MCGDM) methodology for assessing the enterprise digital maturity with linear Diophantine fuzzy (LDF) setting.

This paper utilizes the presented LDF generalized Dombi operator to aggregate assessment information of experts. The developed combined weight model through merging the rank sum (RS) model and symmetry point of criterion (SPC) method is used to ascertain the comprehensive importance of criterion. The evaluation based on distance from average solution (EDAS) approach based upon regret theory (RT) is presented to achieve the sorting of candidate enterprises.

Firstly, the proposed method has strong stability. Secondly, the proposed method takes into consideration the psychological behavior of experts during the decision-making process which further enhances the rationality of the decision results. Finally, the proposed method integrates expert and criterion weight determination models which provides a practical evaluation framework for assessing the digital maturity of enterprises. The research outcomes confirm that the proposed approach fails to resolve the decision problems with unknown weight information flexibly, but also reflect the psychological behavior of expert in decision process. The presented weight approach also provides a rational algorithm to ascertain the weight more accurate.

A composite LDF group decision-making approach is presented by aggregating the proposed generalized Dombi operator, combined weight model and the EDAS model, which make the outcome more reasonable. Sensitivity analysis and comparison study are conducted to reflect the superiority of the proposed approach.

As blockchain-based virtual worlds gain prominence within the emerging metaverse and Web3, numerous global companies and investors are buying purely virtual land to explore new business potentials and capitalize on digital assets. Given the similarities to physical real estate, this study examines the dynamics of the secondary market for virtual land and relates its returns to those of physical real estate.

Using transaction-level data from a prominent virtual land platform, the authors construct a virtual land market index based on repeat sales index methodology from traditional real estate studies. Wavelet coherence analysis is employed to examine the dynamic correlation between virtual land and various physical real estate market returns. The determinants of this correlation are estimated using stepwise regression analysis. A portfolio analysis explores the implications of adding virtual land to traditional asset portfolios.

The correlation between virtual and physical real estate market returns is generally low, reaching its lowest during the Covid-19 lockdowns from 2020 to 2022. It spikes during acute economic turmoil such as the initial Covid-19 outbreak or interest rate change announcements. The correlation is primarily driven by consumer and economic climate, the price of the virtual economy token and investor attention. Portfolio analysis indicates that virtual land can enhance risk-adjusted returns within a traditional portfolio, particularly when added to a commercial real estate portfolio.

This study examines a single virtual land market, despite it being the oldest and one of the largest. Given the rapidly evolving nature of virtual worlds, it is crucial to further test the results and include new virtual land platforms as they emerge.

The findings provide actionable insights on portfolio implications for investors seeking alternative real-estate-like assets in the digital space. Additionally, this study offers strategic guidance for entering the metaverse, including a comprehensive overview of established virtual presences.

With the advancing digitization of real estate markets, this study is the first to explore the correlation between market returns of virtual land in the metaverse and traditional physical real estate. The findings provide valuable empirical insights for investors, policymakers, entrepreneurs and companies interested in the intersection of digital and traditional property markets.

This study aims to explore the antecedent factors that directly and indirectly influence electronic word of mouth (eWoM) for social commerce (s-commerce) in two developing countries (e.g. Kuwait and the United Arab Emirates [UAE]) by extending social cognitive theory.

This study uses a previous robust model (Rouibah et al., 2021) as theoretical background to investigate and compares the antecedents (trust in Instagram, perceived risks) on eWoM for s-commerce through the mediation of three mediators (perceived enjoyment, perceived value and customer satisfaction) among two Arab countries. Data was collected from Kuwait (n = 1,132) and the UAE (n = 190). Different statistical analyses and structured equation modeling-based analysis of moment structure are used to test the robustness of the research model.

This study found customer satisfaction to be most important factor that mediates the effect independent factors on eWoM for s-commerce in both countries. Surprisingly, perceived enjoyment has no effect, and trust in Instagram and perceived risks are the most important factors that are considered imperative for customer satisfaction and positive feedback.

One limitation of this study is that the author does not focus on the difference between the effects of textual and graphical information on customers’ decisions and trust in buying merchandise. Another limitation is that this study focuses on Kuwait and the UAE. Other Gulf Cooperation Council countries are also growing exponentially, and mobile and internet penetration rates are booming; they could be a trigger for more studies on whether differences occur among all of them.

The first implication is that it is the first in its field to extend the effects of eWoM. To the best of the author’s knowledge, compared to the online research this study is unique because the authors examine six factors for eWoM in s-commerce using the Instagram platform as opposed to other platforms.

The third implication of this study is that the previous ones have applied eWoM to different subjects of e-commerce such as tourism and marketing but have concentrated less on s-commerce, where in-depth research is needed much more to explore factors and theories that explain human behavior.

Furthermore, most of these studies have focused on the intention to use (Dincer and Dincer, 2023; X. Hu, Chen, Davison, and Liu, 2022; Zhou et al., 2023). However, the attention in this research is on the actual use.

The main purpose of the present research is to explore the possible effectiveness of information and communication technology (ICT), infrastructure development, exchange rate and governance on inbound tourism demand using time series data in India.

The stationarity of the variables is checked by using the ADF, PP and KPSS unit root tests. The paper uses the Bayer-Hanck and auto-regressive distributed lag (ARDL) bounds testing approach to cointegration to examine the existence of long-run relationships; the error-correction mechanism for the short-run dynamics and the vector error correction method (VECM) to test the direction of causality.

The findings of the research indicate the presence of cointegration among the variables. Further, long-run results indicate infrastructure development, word-of-mouth and ICT have a positive and significant linkage with international tourist arrivals in India. However, ICT has a positive and significant effect on tourist arrivals in the short run as well. The VECM results indicate long-run unidirectional causality from infrastructure, ICT, governance and exchange rate to tourist arrivals.

This study implies that inbound tourism demand in India can be augmented by improving infrastructure, governance quality and ICT penetration. For an emerging country like India, this may have far-reaching implications for sustaining and improving tourism sector growth.

This paper is the first of its kind to empirically examine the impact of ICT, infrastructure and governance quality in India using modern econometric techniques. Inbound tourism demand research aids government and policymakers in developing effective public policies that would reposition India to gain from a highly competitive global tourism industry.

Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio features (speech rate and average spectral centroid) on user engagement behavior.

We conducted a field study on TikTok. To test our various hypotheses, we used regression analysis on 2,511 videos containing product promotion information posted by 60 sellers between January 1, 2020 and November 20, 2021.

For visual variables, the number of shots and pixel-level image complexity were found to have nonlinear (inverted U-shaped) relationships with user engagement behavior. The vertical video form was found to have a positive effect on comments and shares. In the case of audio variables, speech rate was found to have a significant positive effect on shares but not on likes and comments. The average spectral centroid was found to have significant negative influences on likes and comments.

This study provides specific suggestions for sellers who create short-form videos to improve user engagement behavior.

This study contributes to the literature on short-form video advertising by extending the potential drivers of user engagement behavior. Additionally, from a methodological perspective, it contributes to the literature by using computer vision and speech-processing techniques to analyze user behavior in a video-related context, effectively overcoming the limitations of the widely adopted survey method.

The purpose of this paper is to present a bibliometric overview of research published in takaful by identifying the most relevant research in this field and the newest trends according to the information in the Scopus database. Several classifications are made, including analyzing the most productive authors, the most influential journals, the collaboration between countries and the highly cited articles.

This paper collected data from Scopus databases from 1989 to 2023. The Bibliometrics, R-Studio, VOSviewer and Excel software were used to analyze the collected data. Bibliographic analysis was applied, consisting of co-authorship, cartographic, co-citation and coupling analyses.

This paper found that the publication and citation of takaful are increasing over time, contributing to significant progress in impact and visibility. Salman, Ghazali, Hassan and Mamat are the most productive authors. Malaysia is the most cited country, followed by the UK, while institutions from Malaysia are leading the publication of takaful literature. In terms of collaboration between countries, network collaboration was found between countries in Asia (Malaysia and Indonesia), Central Asia (Pakistan and Bangladesh), the Middle East (the United Arab Emirates and Bahrain), Europe (the UK) and North America (the USA).

This paper examines the evolution of takaful literature using bibliometric analysis. The findings and potential applications of this research could be very beneficial to scholars and researchers in creating more dynamic improvements in the scientific development of takaful.

This study aims to examine the relationship between metaverse usage motivations and metaverse behavioral intention through Self-Determination Theory.

This study analyzed a sample of 501 South Korean individuals aged 18 and older who had prior experience using the metaverse, using a moderated mediation model.

The results indicate a significant direct effect between metaverse usage motivation and tourist behavioral intention, with tourist satisfaction significantly mediating this relationship. In addition, the authenticity and flow of metaverse tourism also have significant moderating effects on the model.

These insights can inform targeted marketing strategies, guiding the future development of metaverse tourism and hospitality.

The growth of social media globally has led to brands adopting memes as a tool for communication. They have influenced digital culture, politics and marketing. This study aims to highlight the research gap in meme literature by profiling and science mapping.

This study has performed a bibliometric analysis of research papers on memes from the Scopus database. The authors profiled the literature and found the most relevant journal, author and document. Science mapping techniques such as thematic analysis, thematic evolution and co-citation of papers with content analysis were used.

Profiling of literature revealed that the most relevant journal, based on a number of papers and citations, is New Media and Society. The top researcher on memes is Shiffman L (seven papers), and the most cited author is Menczer F (717 citations). The paper titled “Towards A Unified Science of Cultural Evolution” has the highest number of citations (402). Thematic mapping revealed “Social Movements” and “Twitter” are the currently trending themes. The co-citation analysis clustered the literature into two. The first cluster elucidates the theoretical underpinnings of memes, while the second cluster explicates the various contexts in which memes are studied.

This study will be vital to researchers hoping to study internet memes by providing directions for future research. Furthermore, the insights from this study will enable social media managers to use memes effectively.

To the best of the authors’ knowledge, this study seems to be the first to use bibliometric analysis to profile and map meme literature. This study provides a new perspective for meme researchers to explore memes and suggests marketers implement novel meme-based strategies in their marketing communications.

Using bibliometrics, this study aims to explore the intellectual structure of social segregation research, key contributors, thematic areas and hotspot topics.

A bibliometric analysis was performed for more than 15,000 research papers listed in one of the famous, rich and widely used scientific databases: Web of Science (WoS). This review approach was used to identify social research hotspots on segregation, intellectual structure, borders and development trends. VOSviewer and Gephi software were employed for mapping and analysis.

The study indicates a marked increase in segregation research, particularly from a spatial/urban perspective. The study reveals the interrelationship between segregation and many other social concepts, such as social equality, cohesion, integration and inclusion. In conclusion, addressing the ramifications resulting from the multiple forms of segregation will help in implementing social policies and evaluating their impact on achieving inclusive social development in general and the 2030 agenda of Sustainable Development Goals (SDGs) in specific.

This study remains limited to the precision and thoroughness of the bibliographic data gained from WoS.

This study is valuable for readers to gain rich insights into the state of research on social segregation. It also provides ideas for future research that prospective authors and interested research and academic institutions can investigate.

This study aims to explore the extent to which Chinese multinational enterprises (MNEs) rely on supranational institution – the Belt and Road Initiative (BRI) – versus host country institutional quality to navigate their foreign location choice.

This study uses a conditional logit regression model using a sample of 1,302 greenfield investments by Chinese MNEs in 54 BRI participating countries during the period 2011–2018.

The results indicate that as a supranational institution, the BRI serves as a substitution mechanism to address the deficiencies in institutional quality in BRI participating countries, thereby attracting Chinese MNEs to invest in those countries. In addition, the BRI’s substitution effect on host country institutional quality is more pronounced for large MNEs, MNEs in the manufacturing industry and MNEs in inland regions.

This study expands the understanding of the BRI as a supranational institution for MNEs from emerging markets and reveals its substitution effect on the host country institutional quality. Furthermore, it highlights that MNEs with diverse characteristics gain varying degrees of benefits from the BRI.