Destination image and city branding are accumulating a growing body of knowledge in urban studies and tourism literature. Although several visitor destination image models have been proposed, the most prevalent in Asia remains the comprehensive destination image model. This is the first research to test the applicability of this model beyond the United States and with international (rather than domestic) visitors. Jakarta is chosen as the geographical test area for this study, which incorporates structural equation modeling on a data sample of international leisure visitors in Jakarta. The findings indicate that the destination image model could be generalized beyond the US and applied to Jakarta. This study finds that tourism policymakers in Jakarta should focus on promoting the friendliness of local residents and improving the city’s cleanliness, as these are the two most positive and negative perceptions. Overall, this study showed that a unique destination image—a largely under-researched topic in place branding—is a variable that should be considered when formulating the overall place image of city destinations around the world.

This study explores the factors influencing the adoption of e-wallets in the Jakarta-Bogor-Depok-Tangerang-Bekasi (Jabodetabek) metropolitan region, Indonesia, among Generation Z and millennials. The research uses a quantitative approach and analyzes data from 136 participants using SEM-PLS. The study examines Perceived Usefulness, Ease of Use, Risk, Trust, Convenience, and Attitude toward the Service. The findings reveal that Perceived Ease of Use influences Usefulness rather than Attitude toward the Service. Perceived Risk influences Attitude toward the Service, and Trust is crucial. This research contributes significantly to the existing literature on e-wallets and digital payment technology in Indonesia, thus contributing to the growth of the country's digital economy. Providers should communicate transparently about security and improve accessibility to increase adoption rates.

This manuscript is a good topic, but the Introduction part must be added with facts about the real problems of liquidity of commercial banks in Ethiopia, using time series data since this research uses time series from 2011 to 2021. How about the COV...

The study on the role of religious moderation in food consumption practices as a strategy to maintain environmental balance highlights the unique synergy between Islamic and Confucian values within the local context of Pontianak, West Kalimantan, Indonesia. This article explores the moderate practices of Muslims and Confucians in Pontianak in valuing food to maintain environmental balance. More specifically, this article asks how Islamic and Confucian values of moderation are reflected and integrated into daily consumption practices to maintain environmental balance sustainably. Data was collected through in-depth interviews with informants representing Muslim and Confucian communities. The results show that both communities own environmentally friendly practices reflected in efforts to reduce food waste and control consumption. The concept of moderation and balance in Islam and Confucianism is the main foundation of this practice, as well as religious teachings, cultural norms, and ethical values. The findings suggest that environmental stewardship can be a point of convergence between religion and culture to maintain the sustainability of natural resources. These findings’ policy and conceptual implications can be used to promote awareness of environmental stewardship among Muslim and Confucian communities and develop inclusive sustainability strategies. Further studies can expand the scope and go deeper in understanding sustainable behavior in diverse cultural contexts.

Financial distress poses a serious threat to Indonesia’s property and real estate sector, requiring reliable prediction models to prevent bankruptcy and maintain economic stability. This study compares the predictive accuracy of four classical financial distress models (Altman Z-Score, Zmijewski X-Score, Springate S-Score, and Grover G-Score) using data from 30 IDX-listed firms (150 observations) from 2020 to 2024. A quantitative approach was applied through descriptive statistics, Kolmogorov-Smirnov normality tests, Kruskal-Wallis, and Mann-Whitney U tests, with cash flow patterns as the benchmark of financial distress. The results show significant differences among the models (p<0.001), confirming H1, with the Zmijewski X-Score achieving the highest accuracy (79%), followed by Altman (76%), Grover (72%), and Springate (29%). The Zmijewski model’s logistic regression approach and emphasis on leverage make it the most effective predictor for firms in volatile market conditions, supporting H2. These findings highlight that model performance depends on economic context, emphasizing the need for continuous validation in emerging markets. The Zmijewski X-Score offers practical value for investors, managers, and policymakers in strengthening financial resilience and early distress detection.