The digitalization of the construction industry is deemed a crucial element in Construction 4.0’s vision, attainable through the implementation of digital twinning. It is perceived as a virtual strategy to surmount the constraints linked with traditional construction projects, thereby augmenting their productivity and effectiveness. However, the neglect to investigate the causal relationship between implementation and construction project management performance has resulted from a lack of understanding and awareness regarding the consequences of digital twinning implementation, combined with a shortage of expertise among construction professionals. Consequently, this paper extensively explores the relationship between digital twinning implementation and construction project management performance. The Innovation Diffusion Theory (IDT) is employed to investigate this relationship, utilizing a quantitative research approach through document analysis and questionnaire surveys. Additionally, partial least squares structural equation modeling (PLS-SEM) with SmartPLS software is employed to deduce the relationship. The results underscore that digital twinning implementation significantly improves construction project management performance. Despite recognizing various challenges in digital twinning implementation, when regarded as moderating factors, these challenges do not significantly impact the established causal relationship. Therefore, this investigation aligns with the national push toward the digitalization of the construction sector, highlighting the positive impacts of digital twinning implementation on construction project management performance. Moreover, this study details the impacts of implementing digital twinning from the construction industry’s perspective, including positive and negative impacts. Afterwards, this paper addresses the existing research gap, providing a more precise understanding and awareness among construction industry participants, particularly in developing nations.

This research investigates how accountants in Thailand are adapting to changes driven by advances in digital technology, environmental issues, and professional accounting organizations. The study identifies key factors influencing these shifts and assesses their impact on the accounting field. A survey of accountants from large manufacturing firms in Thailand was conducted, examining internal, external, and personal factors affecting their roles and responsibilities. The study uses Structural Equation Modeling (SEM) to analyze data from 174 respondents, identifying leadership and digital technology readiness as internal factors; sustainability force, professional entity, and digital technology force as external factors; and competency skills and attitude as personal factors. The fit indices collectively suggest that the model has a good fit to the data, demonstrated by Comparative Fit Index (CFI) value (0.91), Tucker-Lewis Index (TLI) (0.891), Root Mean Squared Error of Approximation (RMSEA) (0.067), and chi-square/degree of freedom model (1.776). The combination of the indices supports the conclusion that the model is robust and well-aligned with the observed data, and importantly capturing the relationships between the constructs under the study. Results reveal a significant transformation in the professional identity of Thai accountants, primarily driven by their positive attitude towards changes. Notably, professional accounting bodies and educational institutions appear to hinder this evolution. The findings emphasize the need for professional organizations to realign their strategies to better support the evolving roles of accountants.

Considering increasing concerns about climate change and its implications for global agricultural competitiveness and food security, a small text has assessed the sensitivity of agriculture competitiveness employing a composite scale to the climate change impacts. The world’s food production and supply chains have been jeopardized strain as the world struggles to cope with the far-reaching consequences of climate change, which are worsened by a series of natural disasters, the Ukraine-Russia war, and the continuous fight against infectious diseases like COVID-19. Natural disasters and armed conflicts are overstretching people’s capabilities to acquire nutritive foods at economical/reasonable prices, risking local and global food security and agricultural market competitiveness. The study develops a framework for global agricultural competitiveness assessment by conducting a Delphi Expert survey. The framework has served as a global benchmark for assessing and comparing the national and international agriculture landscape. Its implementation will significantly contribute to the development of policies that promote inclusive and sustainable agricultural practices. Through this action, it guarantees to substantially enhance worldwide food security, thereby effectively tackling the urgent issues that impact communities across the globe.

Massive open online courses (MOOCs) are intentionally designed to be easily accessible to many learners, regardless of their academic level or age. MOOCs leverage internet-based technology, allowing anybody with an internet connection to have unrestricted access, regardless of their location or time limitations. MOOCs provide a versatile and easy opportunity for acquiring top-notch education, enabling anyone to learn at their preferred speed, free from limitations of time, cost, or geographical location. Given the advantages they offer, MOOCs are a valuable method for improving the quality and availability of education in Indonesia. Following the outbreak of the COVID-19 pandemic, colleges and institutions have implemented the establishment of digital campuses. One important characteristic of these digital campuses is that they prioritize processes but overlook data and lack standardized standards. The problems and fundamental causes include challenges related to the comprehensive information architecture. The main factor contributing to this challenge is the absence of uniform and well-defined information standards. The existing connectivity and data exchange mechanisms in several schools are poor, leading to substantial data discrepancy among various departments due to the limited content of the fundamental data utilized. Moreover, the absence of clear information about the reliable source of data exacerbates the problem. The main objectives of data governance are to improve data quality, eliminate data inconsistencies, promote extensive data sharing, utilize data aggregation for competitive benefits, supervise data modifications based on data usage patterns, and comply with internal and external regulations and agreed-upon data usage standards. The aim of this project is to create a data governance framework that is customized to the specific conditions in Indonesia, with a specific emphasis on MOOC providers. The researcher chose design science research (DSR) as the research paradigm as it can successfully tackle relevant issues linked to the topic by creating innovative artefacts about the data governance framework for MOOC providers in Indonesia. This research highlights the necessity and significance of implementing a data governance framework for MOOC providers in Indonesia, hence increasing their awareness of this requirement. The researchers incorporated components from the data management body of knowledge (DMBOK) into their data governance framework. This framework includes ten components related to data governance, which are further divided into sub-components within the MOOC providers’ framework.

Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.

The rising trend of tourists selecting agrotourism as a tourist destination has become an intriguing study issue. Seremban is a well-known tourist attraction that is popular among visitors. As a result, Seremban has been selected as the study site. However, river pollution may have an influence on Seremban’s natural environment and agrotourism potential. Furthermore, inadequate infrastructure, such as unauthorized parking, exacerbated the inhabitants’ problems. A growing number of young people leave Seremban to pursue employment or further education in other cities, with no desire to work as farmers. The labor scarcity has also made it difficult for farmers to grow their farms. Consequently, the study aims to examine how factors such as the natural environment, tourist infrastructure, perceived social advantages, and perceived barriers influence the attitudes of Seremban residents towards agrotourism, with a focus on its potential for driving economic growth. This study adopts quantitative research methods, employing descriptive and causal research designs. Primary data collection is conducted through questionnaires, supplemented by secondary data. Non-probability quota sampling is utilized due to the absence of a specific sampling frame, with a sample size of 385 respondents determined using G*Power software. Constructs are developed based on previous research, and the questionnaire comprises Likert-scale items to gauge attitudes and perceptions. A pilot study assesses the instrument’s reliability. Data analysis is performed using SPSS software, encompassing multiple linear regression and Pearson correlation analyses in addition to descriptive statistics. The findings provide valuable insights into the factors driving residents’ perceptions of agrotourism in Seremban, emphasizing the importance of the natural environment, tourism infrastructure, perceived social benefits, and perceived barriers in shaping attitudes. Additionally, the study highlights the resilience of residents’ positive attitudes toward agrotourism, despite potential challenges and barriers identified. Overall, these results offer implications for policymakers and stakeholders involved in tourism development in the region.