This study presents a simple yet informative bibliometric analysis of servant leadership literature, aiming to provide a basic overview of its scholarly landscape and identify general trends. We conducted this analysis in September 2023. We focused solely on the Scopus database to understand the current state of servant leadership research. Despite extensive search efforts, we found no similar bibliometric analyses within the servant leadership domain during our study period. Therefore, our focus is to present a brief and straightforward analysis of current research in this field based on identification trends over time, connection between co-occurrence of author keywords, most and less discussed keyword, and areas of high and low concentration. Our findings show an increase in scholarly publications, reflecting a growing acknowledgment of servant leadership’s relevance in management practices. Interconnected keywords and themes such as leadership, transformational leadership, job satisfaction, work engagement, authentic leadership, ethical leadership, organizational citizenship behavior, trust, and leadership development emerge prominently. Additionally, less-discussed keywords such as accountability, core self-evaluations, educational leadership, stewardship, customer orientation, and psychological well-being provide alternative perspectives on these research results. While acknowledging limitations inherent in our bibliometric research, such as potential publication bias and language restrictions, our study offers valuable insights for scholars and practitioners interested in this area.

Through Qualitative Comparative Analysis (QCA) on destination attractiveness characteristics at the country level, this study identifies attribute configurations in the pre- and post-pandemic period to analyze the changes and differences generated by an exogenous event (COVID-19). The results suggest that the destination attractiveness attributes work together, in multidimensional configurations, to increase leisure travel volume. We found an important change in pat-terns/configurations of attractiveness between the pre- and post-pandemic scenarios. Our findings suggest that the destination attributes may change in importance and valuation or disappear for some configurations. The conclusion has implications for the stakeholders related to the destination attractiveness development, showing possible patterns of tourism attributes to guide the action to improve the resilience in the tourism sector and recover these activities in a disaster scenario.

The research utilizes a comprehensive dataset from MENA-listed companies, capturing data from 2013 to 2022 to scrutinize the influence of capital structure (CapSt) level on corporate performance across 11 distinct countries. This study analyzed 6870 firm-year observations using a quantitative research method through static and dynamic panel data analysis. The primary analysis reveals a positive correlation between the CapSt ratio and company performance using fixed effects (FE) techniques. Hence, the preliminary results were re-examined and affirmed using a two-step system generalized method of moment (GMM) estimator to address potential endogeneity concerns. This finding aligns with most studies conducted in advanced countries, indicating a positive correlation between CapSt and corporate performance. Furthermore, it is also consistent with some research conducted in less-developed markets. This research argues that, in the MENA region, the advantages of debt, such as tax saving, may outweigh the potential financial distress cost. Furthermore, it offers insights into the monitoring role of CapSt in MENA-listed companies. We strengthen our research results by employing various methodologies and using alternative measures of accounting performance and controlling size, notably panel quantile regression analysis.

Academic integrity has been at the centre of the discussion of the adoption of Chat GPT by academics in their research. This study explored how academic integrity mitigates the desire to use ChatGPT in academic tasks by EFL Pre-service teachers, in consideration of the time factor, perceived peer influence, academic self-effectiveness, and self-esteem. The study utilized web-based questionnaires to elicit data from 300 EFL Pre-service teachers across educational fields drawn from different schools across the world. Analysis was conducted using relevant statistical measures to test the projected four hypotheses. The findings provide evidence in support of Hypothesis 1, with a statistically significant path coefficient (β) of 0.442, a t-value of 3.728, and a p-value of 0.000. The hypothesis acceptance implies that when academic integrity improves, the impact of the time-saving aspect of the use of ChatGPT Across educational fields study decreases. This suggests that EFL Pre-service teachers who have a firm dedication to academic honesty are less influenced by the tempting appeal of ChatGPT’s time-saving features, highlighting the ethical factors that influence their decision-making. The data also provide support for Hypothesis 2, indicating a substantial inverse relationship with a path coefficient (β) of 0.369, a t-value of 5.629, and a p-value of 0.001. These findings indicate that stronger adherence to academic integrity is linked to a diminished effect of colleagues on the choice to use ChatGPT in Academic tasks. The results suggest that a firm dedication to academic honesty serves as a protective barrier against exogenous pressures or influences from colleagues when it comes to embracing cutting-edge technology. However, in general, these findings revealed there was a negative association between academically related factors (e.g., time factor, sense of peer pressure, language study self-confidence, and academic language competence), as well as an attitude toward adoption of ChatGPT and commitment towards academic integrity.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

This study examines the crucial role of digital marketing in promoting sustainable tourism in the villages of Bali. It adopts a mixed methods approach, using qualitative and quantitative data collection and analysis. The qualitative data were obtained from semi-structured interviews with management teams who have experience in implementing digital marketing strategies for village tourism. The interviewees were selected using a purposive sampling technique. The quantitative data were gathered from questionnaires distributed to domestic tourists who visited the villages. The questionnaires measured the tourists’ perceptions of digital marketing as a tool for village tourism marketing. The study found that digital marketing plays a vital role in promoting tourism villages, as most tourists learned about the villages through online media. The study also identified five dimensions of digital marketing, namely website media, social media, search engines, email marketing, and online advertising, which have potential effects on the sustainability of tourism villages. The study conducted statistical tests to examine the effects of 20 indicators of digital marketing on village tourism marketing. The results showed that 16 indicators had a significant positive effect, while four indicators had no effect. These findings suggest that digital marketing is an effective way to market tourism villages and enhance their sustainability.

In the process of global economy, in the face of increasing business competition, it is more difficult than ever for brands to approach consumers and persuade them to consume. In the commercial environment, the competition between enterprises is essentially the competition of brands, and the competition of brands must first carry out the competition of brand image. Brand image carries the mission of information dissemination and value creation and plays an important role in business behavior. How to improve customer purchase intention by optimizing brand image and greatly promote the development of business through brand image is the purpose of this study. The construction and application of brand image not only covers all the characteristics of the brand, but also the focus of consumers’ attention when choosing brands and products. This paper comprehensively uses the systematic theories and methods of art design, marketing and consumer psychology and behavior as support, and adopts research methods such as literature data to explore and study the field of brand image. This study finds that customer perception of brand image directly affects customer purchase intention. At present, there are relatively few researches on how brand image can empower business. Through the study of “optimizing brand image to improve customer purchase intention”, this paper focuses on the direction of brand image empowering business, broadens the research breadth and depth in the field of brand image, and enrichis the research achievements in the field of brand image.

Recently, the government of Ethiopia has been engaged in modernizing the trans-regional Ethio-Djibouti railway infrastructure using the Belt and Road Initiative. This railway corridor has been serving as the main get way for the landlocked Ethiopia to the port. This article creates an insight about the implications of the Ethio-Djibouti railway corridor by exploring the question: what kinds of urban form and morphological changes evolved due to the railway corridor? To examine the impact of this railway corridor, the article employed stratified sampling and multiple criteria intermediate cities selection method. Accordingly, four (Bishoftu, Mojo, Adama, and Dire Dawa) intermediate cities were selected as case study. The article points out that the railway corridor conceived different kinds of linear urban centers around stations. The identified four intermediate cities attract industries and logistic centers. Those industries, logistic centers, and new railway stations often established at the periphery of intermediate cities resulted labour influx from rural and nearby small urban centers and urban expansion that caused a rural-urban continuum of ribbon settlement and strengthen trade gate way for the landlocked Ethiopia that caused trans-regional integration.