Experience plays a vital role in the decision-making (DM) process. In this paper simulation, modeling, and analysis of past experience over DM has been done using the Iowa gambling task (IGT). The Human DM process is very complex and difficult to model through computational methods because it is a subjective type of process and varies person-to-person. Therefore, this study is an attempt to simulate a DM model similar to the human DM process. For this collection of real data was done and was provided as input to the developed eight Reinforcement Learning (RL) models. The result shows that the performance of the model based on Prospect Utility (PU) learned with Decay Reinforcement Rule (DRI) and Trial Dependency Choice (TDC) is better as compared to other models. It is observed from the analysis of data and also validated that simulation and models output that the experienced group performs better than inexperienced.

As a country surrounded by the ocean, Indonesia is categorized as a country that has marine potential. The fishermen communities’ economy depends on ocean. However, the fishermen communities live below the poverty line and their average income is less than regional minimum wage. In conjunction with the issue, this study seeks to investigate the factors affecting the income of fishermen communities and right decision to fishermen in covering with welfare insurance in Cirebon, Indonesia. The quantitative study is designed using cross-sectional approach. The data collected by applying random sampling with open-ended questions and interview. A total of 100 fishermen’s have participated in this study. The study used some factors in measuring the fishermen community income, namely coastal environment condition, fish catching technology and location, operational capital, climate (season) condition, fishermen’s age, fishermen’s education, and fishing experience. The data are analyzed using the multinomial logistic regression model by assisting the statistical software, i.e., SPSS-23. The results show that coastal environment condition, fish catching technology and location, operational capital, climate (season) condition, fishermen’s age, fishermen’s education, and fishing experience have significant effects on fishermen income. Interestingly, the factor of coastal environment condition and climate (season) condition have significant negative effects on fishermen income. In conclusion, this study identified that two important factors reduced the welfare level of fishermen (via income). Also, in line with that things, the right decision which can provide to support and assist the fishermen community was by providing the welfare insurance. It is purposely to give them the protection from various risks faced by fishermen.

This paper presents an empirical investigation on the perceptions of individual investors about the impact of accounting disclosures on their decision makings on the stock exchange market. The study uses some quantitative methods with survey questionnaires sent to investors participating in the Vietnam stock market. By using SPSS 22, the research develops a research model with 11 accounting information groups (factors) which are measured by 82 items. The results indicate that the income information significantly affected investors’ decisions on buying, selling and holding securities while the information on assets, the accounting principles and policies had little impact on individuals’ investment decisions. The voluntary disclosures, however, show more effects than mandatory disclosures on the investors' decision making.

This article examines the nexus between Big data governance, dynamic capability and decision-making. Survey data was garnered from firms in Jordan and fuzzy sets (fsQCA) approach was applied. Fuzzy set configural modeling revealed two causal models for high decision-making effectiveness conditions. First, Big data governance, number of employees and firm age are necessary for higher levels of effective decision-making. Second, dynamic capability, number of employees and firm age are necessary for higher levels of effective decision-making. Insights for practitioners in an emerging economy and possible areas of future research are highlighted.

Company activities can yield both favorable and adverse outcomes. Among the detrimental effects are various environmental crises stemming from companies' failure to responsibly manage and uphold ethical business practices within their operational environment. This study aims to scrutinize the impact of artificial intelligence and social media on augmenting public administration decision-making and its repercussions on corporate social responsibility within enterprises situated in Sidoarjo, East Java Province, Indonesia. The sample comprises 130 respondents representing companies actively engaged in corporate social responsibility endeavors. Employing purposive sampling technique, data collected from surveys were subjected to Structural Equation Modeling-Partial Least Squares (SEM-PLS) analysis. The research outcomes and data analysis reveal that artificial intelligence significantly and directly influences corporate decision-making as well as public administration of social responsibility. Likewise, the utilization of social media by both corporations and government exhibits a direct and positive correlation with corporate decision-making and corporate social responsibility. Public administration decision-making also demonstrates a direct and significant impact on corporate social responsibility within companies in Sidoarjo, East Java Province, Indonesia. Moreover, public administration decision-making partially mediates the effects of artificial intelligence utilization and social media utilization on public administration of social responsibility within companies in Sidoarjo, East Java Province, Indonesia.

This study examines the robust relationships between Roblox's business model, collaborative learning, participation in the decision-making process, and cooperative literacy within the Indonesian Roblox community. All hypotheses were substantiated, emphasizing the significance of understanding the business model, promoting collaborative learning, and encouraging active involvement in decision-making activities for fostering cooperative literacy among players. The research employed an exploratory research design with a quantitative approach. Sampling bias and self-reported data are acknowledged limitations, along with the cross-sectional design's inability to establish causality. To address these constraints, future research should employ longitudinal methods, diverse data collection approaches, and intervention studies. Cross-cultural research comparing the Indonesian Roblox community with other cultural contexts is also encouraged. Practical recommendations include integrating features that support collaborative learning and decision-making participation within the Roblox platform. Collaboration between educational institutions and Roblox to use the platform as an educational tool is suggested, offering students a unique opportunity to develop cooperative literacy skills. These findings offer valuable insights into cooperative literacy and community engagement within the Roblox ecosystem, providing a roadmap for its development. This research contributes to the platform's growth and success in Indonesia, making it a more cooperative and informed community.

Fuzzy Analytical Network Process (F-ANP) method is able to consider the complex relationships among different levels of decisions, transactions, and feedbacks of criteria and alternatives to calculate the weights of the elements. The large number of pair-wise comparisons in F-ANP and also difficulties in understanding the way of comparisons for the expert, have reduced the efficiency and practicality of this method. In this paper, in order to eliminate the above-mentioned problems, it has been tried to provide an approach using the Fuzzy Best-Worst method, called F-BWANP. The proposed method, requires less comparison data and leads to more consistent comparisons, which means that more reliable results can be obtained, while making it much easier for responding by experts. Finally, in order to describe the proposed method and evaluate its capability, a numerical example is provided.

Nowadays, weekend travel is gradually gaining people's attention due to societal impacts, with the desire to improve health, relax, rest, and entertain after days of exhausting work. Therefore, the development of weekend travel is a strategy of interest to managers and leaders, leading to intense competition among destinations. Although it has been long established worldwide, weekend travel in Vietnam has only recently gained popularity, primarily among young people. Therefore, researching the factors influencing the decision to choose weekend travel destinations is significant in developing strategies for this type of tourism. The research results show that the choice of weekend travel destinations by Ho Chi Minh City tourists is driven by various internal and external factors. Among them, internal motivations, income, convenience in the trip, the image of the destination, etc., are factors rated highly by tourists. There are significant differences in some internal and external factors according to age groups. Model testing and research hypotheses indicate that 66.4% of destination choices are influenced by the proposed factors in the model. Among them, the destination image has the most significant impact, followed by income, internal motivations, and distance. The remaining factors in the model have low or no impact on the satisfaction and commitment to return to weekend travel destinations for Ho Chi Minh City tourists.

Strategic management in a port system is complex since the Port Community has to coordinate actions and generate synergy among all the private actors that integrate the export and import logistics chains, trade associations and trade unions. Based on the opinion of the port experts and the analytical network process (ANP), the research identifies the relevant criteria for strategic, business and operational decision-making in the Port Community, in the technological and risk contexts. With the criteria found and considering the strategic alignment that is required, management indicators are constructed. Based on a generic model, a new strategic conceptual model (PORTGD) of ANP for decision management is designed for the Port Community, a cause and effect analysis is carried out and a sensitization study is performed on the nodes. The discussion of the results and conclusions highlights the importance of technological investment, control of port security and good practices for the port system investigated.

In recent times, there have been developments in the maritime industry that underscore the need to optimise operations to yield maximum productivity. Apart from this, stakeholders in this industry have also advocated improvements in seaport operations' critical areas. However, there is no known study in which the relationship between performance criteria and seaport operation measures is investigated. This study proposes a framework for selecting operation measures for the maritime industry. It uses stakeholders' expectations for operational criteria and fuzzy logic to design the framework. Nine criteria were considered in the framework, while Fuzzy VIKOR (VIsekriterijumska optimizacija I KOmpromisno Resenje) and fuzzy Shannon entropy were incorporated into it. The framework's applicability was tested using information that was obtained from Tin can port, Lagos, Nigeria. During this process, hinterland traffic diversion (A1), congestion pricing (A2), off-dock container yards (A3), Fast rail shuttles (A4), expanded rail connections (A5) were considered as alternatives for seaport operational measures. When the developed framework was used to analyse the collected information from Tin Can port, Lagos, Nigeria, the fuzzy VIKOR index ranked the alternatives as A1 » A2 » A3 » A5 » A4. Therefore, this study's insights show that mathematical models can be used to make informed seaports decisions.