This study examines the factors influencing e-government adoption in the Tangerang city government from 2010 to 2022. We gathered statistics from multiple sources to reduce joint source prejudice, resulting in a preliminary illustration of 1670 annotations from 333 regions or cities. These regions included major urban centers such as Jakarta, Surabaya, Bandung, Medan, Makassar, and Denpasar, as well as other significant municipalities across Indonesia. After removing anomalous values, we retained a final illustration of 1656 annotations. Results indicate that higher-quality digital infrastructure significantly boosts e-government adoption, underscoring the necessity for resilient digital platforms. Contrary to expectations, increased budget allocation for digital initiatives negatively correlates with adoption levels, suggesting the need for efficient spending policies. IT training for staff showed mixed results, highlighting the importance of identifying optimal training environments. The study also finds that policy adaptability and organizational complexity moderate the relationships between digital infrastructure, budget, IT training, and e-government adoption. These findings emphasize the importance of a holistic approach integrating technological, organizational, and policy aspects to enhance e-government implementation. The insights provided are valuable for policymakers and practitioners aiming to improve digital governance and service delivery. This study reveals the unexpected negative correlation between budget allocation and e-government adoption and introduces policy adaptability and organizational complexity as critical moderating factors, offering new insights for optimizing digital governance.

The objective of the research is twofold. The study examines the role of public finance in promoting sustainable development in SSA. Secondly, the study investigates the optimal level of public finance beyond which public finance crowds out investment and hinders sustainable development in SSA. The study adopts a battery of econometric techniques such as the traditional ordinary least square (OLS) estimation technique, Driscoll-Kraay covariance matrix estimator, and the dynamic panel threshold model. The study found that an increase in public debts lead to a decline in sustainable development. In contrast, the results show that increase in spending on health and education, and tax can engender sustainable development in SSA. Further, we uncover the optimal levels of public spending on health and education, and public debts that engenders sustainable development in SSA. One main implication of the findings is that governments across SSA needs to reduce public debts levels and increase public spending on health and education to within the threshold levels established in this study to aid sustainable development in SSA.

The accessibility of FinTech services is increasing, and their convenience is making them more popular than traditional banks, particularly among Generation Z. The objective of this research is to identify and compare the factors influencing the conscious use of FinTech services among Generation Z members, who are the most active participants in this field of financial technology. The questionnaire based purposive sample consisted of Generation Z students who demonstrated adequate financial literacy and utilized FinTech, and who were learning in a university environment in Hungary and Romania. A sample of 600 respondents was selected for analysis after cleaning the data online. The methodological approach entailed the utilization of covariance-based structural equation modeling (CB-SEM). The results indicate that social influence (β = 0.18), consumer attitude (β = 0.53) and facilitating conditions intention (β = 0.11) all have a significant effect on the behavior intention, explaining 49% of the variance. In the context of performance expectation, the effect of facilitating conditions intention is not significant (p = 0.491). The motivation of Generation Z towards fintech solutions is evident in their preference for speed and ease of use. However, in order to reinforce consumer expectations and transfer the necessary experience and attitudes, it may be beneficial for service providers to adopt a partially different strategy in different countries. Generation Z can thus serve as a crucial reference point for the even more discerning expectations of subsequent generations. The findings may inform the formulation of strategies for fintech service providers to better understand customer behavior.

Tourism is one of the important sectors that support Indonesia’s economic growth. The tourism sector itself plays a strategic role in increasing the country’s foreign exchange. However, during the Covid-19 pandemic, tourism became one of the most affected sectors. Electronic visa on arrival (e-VOA) is a form of digital transformation in immigration services offered by the Indonesian government to increase the number of tourist arrivals during the recovery of the national economy, especially in the tourism sector, after the Covid-19 pandemic. This study provides an in-depth insight into how e-VOA functions as a digital transformation tool in the immigration and tourism sectors. By exploring the impact of e-VOA implementation, this article contributes to the understanding of how digitalisation can improve the efficiency of administrative processes and support the recovery of the tourism sector in post-pandemic Bali. This study uses qualitative approaches and methods with descriptive analysis techniques to create an objective description of a situation through numbers or statistical data. The results of this study show that e-VOA services effectively contribute to an increase in the number of foreign tourists in Bali. It also has a positive impact on the economic growth of tourism-related businesses in Bali.

Despite many investigations concerning antecedents of organizational commitment in the workplace, very few studies so far have analyzed the direct or indirect impact of HR change leadership role on organizational commitment via HR attribution. Therefore, given the reciprocal principle of social exchange theory, attribution theory and signal theory, this study formulated hypotheses and a model to test the relationships between included variables by employing the mixed-method approach. In-depth interviews were initially conducted to develop questionnaires to collect quantitative data. Employing PLS-SEM to analyze the data collected from 1058 employees working in 24 sustainable enterprises in Vietnam, the findings show that the degree of adopting HR change leadership role was positive, directly affecting organizational commitment. Also, both well-being and performance HR attribution play partially mediated roles in the relationship. The findings suggest that the organizational commitment depends on not only how the degree of adopting HR change leadership role is executed, but also how employees perceive and interpret the underlying management intent of these practices. In a sustainable context, adopting HR change leadership role plays a critical role in shaping employees’ interpretations of sustainable HR practices and their subsequent attributions. Besides, employees’ belief on why are sustainable HRM practices implemented has an influence on the organizational commitment that in turn contributes to the overall sustainable performance.

The proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.