The Indonesian creative economy has been on the rise since 2015 when it has started being measured and prioritized by the government. Its contribution towards the Indonesian GDP has risen significantly as well. A small part of that creative sector is the video game industry and market. The video game global market will be worth USD 200 Billion in 2023. Indonesia currently is ranked 16th in terms of market size. Although having an enormous market opportunity, local video game producers only contribute 1%. Growth opportunities exist, however local game studios are facing the difficulty of recruiting quality game developers. Higher education institutions need to produce graduates having the knowledge, competences, and skills relevant for their work. This study is done to identify and prioritize attributes for the design of a university level program in game development that ensures employability in the sector. A qualitative thematic analysis is done in identifying the important factors for an academic program, followed by an analytical hierarchical process in determining the factors. Result of the study shows that a curriculum with internships in game studios, ensuring students are knowledgeable on the business models & video game market, having practitioners teach in the program, and creating a community of practice in the university is essential in producing quality graduates.

This study aims to determine an accurate forecasting model, especially an error rate of around 0, and to examine how the automatic rejection system reacts to stock price as a result of the pandemic. The statistical clustering method is used for the dataset in form of daily observations, while the sample covers the period of cases before and after COVID-19 pandemic from 02 January 2019 to 20 June 2020 at the Trinitan Minerals and Metal Company. Furthermore, the data used in the estimation are the opening and closing price of returns, which are later processed using SAS analysis tools. It is shown that the most appropriate decision-making processes are those proven to be most effective. Therefore, predicting future events based on a suitable time series model will help policymakers and strategists make decisions and develop appropriate strategic plans regarding the stock market. Meanwhile, 98% of the ARIMA (1,1,1) is a forecasting model which can be applied to predict stock prices. The new approach of this study is an integrated autoregressive moving average used as an attempt to accurately predict stock prices during a pandemic.

Tourist village program is one development priority program for rural development. Despite numerous opportunities to develop tourist villages such as the availability of natural resources and high demand for tourist villages recently, some challenges are still faced to develop tourist villages, especially in a developing country such as Indonesia. Governance problems, infrastructure, and effective partnership are among other factors that remain challenging in developing tourist villages. This study attempts to identify factors that determine the state of tourist villages in Indonesia and determine the appropriate strategies for better tourist village development. Using the case of tourist villages in Kedung Ombo, Central Java, a water based attractive tourist village, this study uses both machine learning and multicriteria approaches by means of Promethee in order to address the objective of the study. This study shows that government support, application of information technology, infrastructure, local participation, partnership, and attractive variations, are among the determinant factors that affect tourist village development. The study also reveals that the appropriate strategies for tourist village development include, improving infrastructure, institutional strengthening, and capacity building. This study could be used to assist local national as well as sub-national governments to effectively manage tourist villages in Indonesia.

The purpose of this study is to analyse the simultaneous spatial relationship between economic growth and e-commerce as well as the spillover effect between the two variables in East Java at the beginning of the Covid-19 pandemic in 2020. To answer the research objectives, spatial simultaneous modeling is used with the Spatial Autoregressive Generalized Spatial Three Model. Stage Least Square (SAR-GS3SLS) using rook contiguity. Based on the results of the SAR-GS3SLS, it can be concluded that at the beginning of the Covid-19 pandemic in 2020 in East Java, economic growth and e-commerce were simultaneously spatially interconnected. Variables that affect East Java's economic growth are e-commerce activities, the number of villages that have Base Transceiver Stations (BTS) and the spatial lag of economic growth (ρ1) while the open unemployment rate (TPT) and the Gini ratio have no significant effect on growth. economy. Variables that affect e-commerce are economic growth, internet banking users, percentage of population who have cellphones, number of millennials, number of villages that have ATMs and spatial lag of e-commerce (ρ2) while the number of villages with 4G/LTE signals has no effect on e-commerce. commerce. Regencies/cities that provide the highest spillover of economic growth and e-commerce in East Java are Malang, Mojokerto and Madiun Regencies. The three districts were able to provide a positive net spillover.

Strategy is a way to be able to find effective and efficient ways to achieve goals. There are three important strategies carried out by companies, namely strategic planning, strategic role, and strategic maneuvering. The interesting thing is that relatively not much research has been conducted regarding the measurement of financial performance which is studied from the perspective of corporate strategy that influences financial performance. This is also supported by technological developments that affect companies, so companies must have the right strategy so that the company's financial performance can improve. This study examines the effect of strategic planning, strategic roles, and strategic maneuvers on financial performance. This study uses resource-based view theory as a study in testing the influence model of strategic planning, strategic role, and strategic maneuvering on financial performance. The study is conducted in Indonesia with a sample consisting of owners, directors and managers who use big data analytics in the companies they run. The sampling technique used is convenient sampling. The analysis technique used in this study is multiple linear regression analysis with the independent variables namely strategic planning, strategic role, and strategic maneuvering and the dependent variable namely financial performance. The results of this study indicate that strategic planning had no significant effect on financial performance, but strategic role had a significant effect on financial performance. Furthermore, strategic maneuvering has a significant effect on financial performance.

This study investigates the intricate relationships between macroeconomic infrastructure, supply chain smoothness, national competitiveness, and economic growth within the BRICS nations—Brazil, Russia, India, China, and South Africa. This study adopts a quantitative approach with cross-sectional data to examine the interrelationships. The research confirms that macroeconomic infrastructure significantly influences supply chain smoothness and a country's economic growth, underscoring the pivotal role of infrastructure development in enhancing supply chain efficiency and fostering economic expansion. However, rejecting hypotheses regarding the direct impact of supply chain smoothness and national competitiveness on economic growth highlights economic growth dynamics' complex and multifaceted nature within the BRICS context. This study emphasizes the need for nuanced, context-specific strategies to address each BRICS nation's unique challenges and opportunities. Theoretical implications call for a more comprehensive theoretical framework considering the contextual factors influencing economic growth within BRICS countries. Practical implications highlight the importance of strategic infrastructure investments and comprehensive policy approaches that extend beyond isolated factors. Despite its contributions, this study has limitations, including simplifying complex economic relationships and needing more country-specific analyses. Future research should explore broader variables, non-linear relationships, and country-specific nuances to understand economic growth in the BRICS group better.

This research examined the relationships between Organizational Commitment, Organizational Citizenship Behavior (OCB), the Supply Chain, and Green Hospital practices in a healthcare setting. A cross-sectional study was conducted using self-reported data from healthcare employees. Structural equation modeling was employed to analyze the relationships and mediation effects. The study confirmed that Organizational Commitment positively impacts the Supply Chain and Green Hospital practices. Similarly, Organizational Citizenship Behavior significantly influences the Supply Chain and Green Hospital initiatives. The Supply Chain was found to have a positive impact on Green Hospital practices and served as a mediator in the relationships between Organizational Commitment and Green Hospital and Organizational Citizenship Behavior and Green Hospital. The research provides valuable insights for healthcare organizations seeking to enhance their sustainability efforts. Fostering Organizational Commitment and Organizational Citizenship Behavior among employees can contribute to more efficient supply chain operations and environmentally responsible practices. The study underscores the crucial role of supply chain management in translating commitment and proactive behaviors into tangible sustainability initiatives. The research is context-specific, and using self-reported data and a cross-sectional design may limit generalizability. Future studies should explore these relationships in diverse settings and consider longitudinal or mixed-method approaches.

Fuel availability is essential in supporting the sustainable economic growth of a country. The manufacturing industry, transportation activities, and shipping products between regions are the primary sectors that require a sustainable fuel supply. The fuel station contributes to distributing and delivering fuel in serving the demand for the fuel. This study investigates supplier competency's role in supporting fuel station business performance through supplier integration, vendor-managed inventory, and supply chain collaboration. The research surveyed 71 fuel stations in Timor Leste using a questionnaire designed with a five-point Likert scale. The questionnaires are distributed to supervisors or higher positions at fuel stations by distributing questionnaires by direct delivery and also through Google Forms for areas far away in downtown Timor Leste. Data from respondents were analyzed using smartPLS software version 4.0. The results found that supplier competency positively impacts supplier integration, vendor-managed inventory, and supply chain collaboration. Moreover, supplier integration positively impacts vendor-managed inventory, supply chain collaboration, and business performance. Vendor-managed inventory fuel station sites can have an impact on improving supply chain collaboration and business performance. In addition, supply chain collaboration between vendors and fuel stations in Timor Leste enables continuous business performance improvement. This research paves the way for supervisors, managers, and fuel station top management to collaborate with suppliers in maintaining inventory levels and forecasting the supply and demand for fuel procurement requirements. Finally, this research contributes to the theory of inventory optimization and supply chain performance.

Adopting MIGO Bio P 2000 Z in soybean cultivation in Indonesia has yielded significant advancements in sustainable agriculture. This innovative technology has demonstrated substantial potential in enhancing agricultural productivity. Environmental impacts of using MIGO Bio P 2000 Z include reduced reliance on chemical fertilizers, improved soil quality, positive contributions to greenhouse gas emissions reduction, and support for biodiversity conservation. Economically, implementing MIGO Bio P 2000 Z has increased soybean production, reduced fertilizer costs, higher incomes for soybean farmers, export opportunities, and investments in agricultural technology. While the primary focus is on economic impact, reducing chemical fertilizer use also benefits the environment by preventing pollution and soil degradation. Further, integrating MIGO Bio P 2000 Z into the soybean supply chain has bolstered supply sustainability, decreased dependency on soybean imports, and improved food security. Its positive effects include enhanced agricultural productivity, reduced environmental impact, and support for the well-being of farmers. Collaborative efforts, including government support, training, diversified markets, and strict monitoring, are essential for optimizing the technology's potential. Adopting MIGO Bio P 2000 Z in Indonesian soybean cultivation offers a sustainable and environmentally friendly approach to bolstering economic growth, food security, and the agricultural sector. In addressing challenges and enhancing the benefits, investing in training, market diversification, and regulations is vital while supporting farmers, especially small-scale ones. This holistic approach will secure Indonesia's soybean supply chain and strengthen the nation's agricultural resilience.

This study attempts to investigate the effects of Islamic events on both Islamic and conventional stock markets and analyze which market reacts more pronouncedly to these events. From 2012 to 2022, the research used daily stock return data from eight nations: Kuwait, India, Nigeria, Malaysia, Pakistan, Qatar, Saudi Arabia, and the United Arab Emirates. The study examines how Islamic holidays such as Ashura, Eid Meelad ul Nabi, Eid ul Azha, and Ramadan affect both Islamic and Western stock markets. The researchers use the Generalized Autoregressive Conditional Heteroscedastic (GARCH) model to analyze the data. The results of this analysis show that Islamic events in India, Nigeria, Malaysia, Pakistan, and Qatar have a strong and favorable link with Islamic stock returns. However, it was discovered that there is a little correlation between Islamic events and Islamic stock returns in the remaining three nations. The study also reveals a strong and favorable correlation between Islamic events and conventional stock performance in all countries. By offering a comparative analysis of the effect of Islamic events on Islamic stock markets and mainstream stock markets, these findings add to the body of current material. Every religion has its own set of rituals that its adherents observe, and these rituals frequently have an impact on different economic and non-economic activities. This study sheds light on the precise connection between these events and stock market performance by examining the impact of Islamic occasions on both Islamic and conventional stock markets.