Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

Technological innovation allows nations to produce sophisticated products more efficiently and at higher quality to increase exports. Countries that aim to produce and export sophisticated products can improve their economic complexity and lead to the country’s economic development. Hence, the study investigates the impact of technological innovation on economic complexity in South Africa. Technological innovation, exports, and manufactured products were used as variables to examine South Africa’s economic complexity index. The study employed the ARDL method to determine the relationship among the variables. The ARDL F-bounds test reflected the long-run cointegration among the selected variables. The study produced long-run positive estimates of technological innovation, exports, and manufactured products on economic complexity, however, manufactured products and exports were insignificant. Granger causality indicated unidirectional causality on economic complexity to manufactured products, exports to technological innovation, and a bi-directional causal effect from exports to economic complexity and technological innovation to economic complexity. The study recommends that South Africa focus on innovation, create more diversified and sophisticated products and processes, and promote more manufacturing firms, particularly Agri-processed products.

Regional cooperation stands as a key strategy to address intense economic competition and formidable local governance challenges. Successful regional collaborations are typically founded on the basis of institutional similarity, which also serves as the starting point for a multitude of related theoretical studies. Consequently, the regional cooperation within the context of institutional conflicts has been overlooked. This paper aims to explore the process of regional cooperation against the backdrop of conflicts, using the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study and analyzing it from the perspective of the sociology of knowledge. The article posits that conflicts can stimulate interactions among various actors, foster the generation of local knowledge, and propel specific cooperative practices. Moreover, local and central governments, grounded in local knowledge and universal managerial insights, continuously authenticate and propagate local innovations, establishing guiding policies and, consequently, producing rational knowledge. The accumulation of such knowledge has not only strengthened civilian cooperation but also facilitated broader collaborative efforts. The study reveals that despite the GBA’s remarkable achievements in cooperation, challenges persist: on the one hand, there are issues with the government’s process of rational knowledge production and the quality of knowledge itself; on the other hand, excessive governmental dominance may suppress the production and application of local knowledge. Therefore, refining the knowledge production mechanism is especially critical. The findings of this paper uncover the mechanisms of regional cooperation amidst institutional conflicts and deepen our understanding of regional collaboration and cross-border governance.

This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

The research aims to examine the determinants influencing the business commitment toward sustainable goals in Vietnam. To employ a quantitative research approach, we surveyed 208 business leaders in Vietnam to assess their perceptions and actions regarding sustainable goals. We explored the impact of internal enterprise characteristics and external facilitating factors on different dimensions of sustainable goals by using logistic regression models. This paper’s findings reveal that enterprise attributes, corporate leadership traits, and external factors significantly influence sustainable goal engagement. Notably, corporate leaders emerge as pivotal factors, particularly in their willingness to embrace risks and uncertainties. Moreover, this paper’s analysis identifies external factors with limited efficacy in fostering sustainable business operations. These insights hold significant implications for governmental institutions in Vietnam, offering valuable guidance for updating and refining policies.

Given the large amount of railway maintenance work in China, whereas the maintenance time window is continuously compressed, this paper proposes a novel network model-based maintenance planning and optimization method, transforming maintenance planning and optimization into an integer linear programming problem. Based on the dynamic inspection data of track geometry, the evaluation index of maintenance benefit and the model of the decay and recovery of the track geometry are constructed. The optimization objective is to maximize the railway network’s overall performance index, considering budget constraint, maximum length constraint, maximum number of maintenance activities within one single period constraint, and continuity constraint. Using this method, the track units are divided into several maintenance activities at one time. The combination of surrounding track units can be considered for each maintenance activity, and the specific location, measure, time, cost, and benefit can be determined. Finally, a 100 km high-speed railway network case study is conducted to verify the model’s effectiveness in complex optimization scenarios. The results show that this method can output an objective maintenance plan; the combination of unit track sections can be considered to expand the scope of maintenance, share the maintenance cost and improve efficiency; the spatial-temporal integrated maintenance planning and optimization can be achieved to obtain the optimal global solution.