The advent of the Internet Plus era, digital technologies, and the digital economy has instigated profound transformations in the commercial landscape, particularly evident in the systematic reshaping of the Digital Business Ecosystem (DBE), encompassing innovations in business models, norms of commercial conduct, and the exploration of business value. This paper delves into the panoramic view of digital business operations of typical companies to uncover the fundamental structural framework of digital commerce. Through deductive reasoning and drawing upon the theoretical framework of natural niche, we construct a niche model for the digital business ecosystem, thereby achieving a bionic deconstruction of the digital business ecosystem. The significance of this research lies in offering a novel research perspective for enterprises, economic regulatory bodies, and scholars in the field of business management, proposing a systemic approach rooted in niche theory models to competition. This approach provides a fresh theoretical framework for enterprises to devise their own ecological and sustainable development strategies. The key findings are as follows: (1) Most business firms establish competitive advantages by constructing commercial cloud platforms that facilitate internal digital transformation and enable digital synergy with external economic entities; (2) Within the digital business ecosystem, enterprises extend their digital capabilities externally through four modalities: data development, data application, data services, and data manufacturing. Externally, six primary forces and roles shape the ecosystem: suppliers, governments, social institutions, consumers, as well as external and internal industry players; (3) The digital business niche is a multidimensional and hyper volumetric relationship positioning between enterprises and the digital business environment. The niche factors include six dimensions: market, personnel, resources, social relationships, technology, and institutions; (4) Given limited ecological factors, the non-exclusivity between static resource allocation and dynamic technological investments in digital enablement leads to the generalization of property rights boundaries and industrial values within the digital business ecosystem. Consequently, this fosters extensive business applications and diversified business models, thereby resulting in less competition and more cooperation, symbiosis, and complementarity within the digital business niche.

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.

Using multiple evaluation methods and systems give a comprehensive assessment. A computer-based multiple-choice assessment system was designed, implemented, posted online, and used to assess students as part of their final evaluation marks for a discipline. The online system of evaluation was intended to be used multiple times for evaluating the assimilation degree of a specific course at the end of the course. The data recorded for the period 2017–2023 with about 1400 distinct users were used to analyze the performance of the evaluation system. The system worked fine and a slight modification of it served well on remote evaluation during COVID-19 period. However, the upturn of mobile phone applications requires the creation of a system adapted to the new virtual reality.

This study investigates university students’ understanding of the mole concept and its implications for chemistry education, highlighting the critical role of mathematical education. A questionnaire was administered to 303 students from universities in Panama, Mexico, Cuba, Chile, and Spain. The results reveal that only 29.7% of participants recognize the mole as a fundamental unit, while 20.8% confuse the amount of substance with a non-existent “Chemical System.” Only 18.5% correctly identified the substance quantity symbol as “n” and 32.7% were aware that Wilhelm Ostwald introduced the term mole, indicating deficiencies in historical knowledge. The significance of these findings highlights major misconceptions and gaps in both conceptual understanding and historical knowledge, underscoring the urgent need for revised teaching strategies. Addressing these issues is crucial for bridging the gap between theoretical knowledge and practical application, thereby enhancing instructional methods and optimizing chemistry education to improve students’ comprehension of fundamental concepts.