Objective: To promote the development of China’s crop seed industry with high quality, guarantee food security and sustainable agricultural development, scientific design of the evaluation index system for high-quality development of the seed industry and conduct of metric analysis are the keys to promoting the revitalization of the seed industry and the construction of a strong agricultural country. Methods: This paper focused on the high-quality development of China’s crop seed industry as the main research object by combining previous research findings of studies based on the connotation of high-quality development of the crop seed industry and constructed the evaluation index system of high-quality development of China’s crop seed industry which covers five dimensions, namely, innovation-driven development, green and sustained development, coordinated and comprehensive development, opening-up and strengthened development, and share-and-promote development, The Entropy method, Dagum’s Gini coefficient, Kernel’s density estimation, and panel regression methods were used to comprehensively analyze the spatial and temporal evolution, regional differences, and driving factors of the level of high-quality development of the crop seed industry in 30 provinces (municipalities and autonomous regions) of China from 2011 to 2020. Conclusions: After systematic analysis, it was concluded that (1) the overall level of high-quality development in China’s crop seed industry has stabilized, and progress has been made. (2) The overall inter-regional differences among the four major regions showed a gradual upward trend, with the inter-regional differences serving as the primary source of the differences and the contribution rate of various inter-regional differences demonstrating an upward trend. (3) Innovation capacity, the cultural and educational level of rural residents, the development of rural infrastructure, national financial support, and market-oriented approach are important factors driving the high-quality development of the crop seed industry in Chinese provinces (districts and municipalities).

In response to the increasing global emphasis on sustainability and the specific challenges faced by small and medium-sized enterprises (SMEs) in China, this study explores the integration of green reverse logistics within these enterprises to enhance their sustainability and competitiveness. The aim of this study is to understand the relationship between reverse logistics, green logistics, and sustainable development. Data analysis was conducted utilizing a combination of descriptive statistics and correlation analysis. A survey of 311 participants examined SMEs’ performance in reverse logistics practices and their initiatives in green logistics and sustainable development. The empirical findings reveal significant progress in reverse logistics practices among SMEs, reducing environmental impact and improving resource efficiency. Moreover, a notable positive correlation was identified between reverse logistics promotion and advancements in green logistics and sustainable development. SMEs’ investment in reverse logistics is closely linked to their efforts in environmentally conscious and sustainable supply chain management. These insights benefit SMEs and supply chain practitioners and offer a valuable reference for future research and practical applications in this field.

The technological infrastructure is the basis for the successful implementation and operation of information systems in small and medium enterprises. The study aimed to demonstrate the impact of cybersecurity on entrepreneurship strategies in small and medium enterprises. Through technological infrastructure in Balqa Governorate. The study population consisted of small and medium enterprises in Balqa Governorate in Jordan. The study followed the descriptive analytical approach and relied on the questionnaire to collect data. The sample size was 360 individuals were randomly select. The Statistical Package for Social Sciences (SPSS) was use to analyze the data. The study reached a set of results, including that the management of small and medium enterprises is committed to continuous supervision and control of customer information. Dealing with reliable parties to ensure the confidentiality of information, following strict standards for disclosure and circulation of customer data and information based on legal texts. Maintaining the privacy of customers’ financial data, in addition to supporting the successes of individuals based on the personal efforts of employees, providing a suitable work environment for employees, sustaining excellence and achievement, and working to increase awareness among its employees of the importance of innovation and creativity in work. The study recommended that customer data confidentiality should be consider a top priority for small and medium enterprises. The data should be stored in more than one place at the same time, that project websites should follow a privacy policy, and that the customer’s identity should be verify before submitting his data and documents, by involving employees in small and medium enterprises in specialized courses and workshops to demonstrate the importance of data and information confidentiality.

The article presents an answer to the current challenge about needs to form methodological approaches to the digital transformation of existing industrial enterprises (EIE). The paper develops a hypothesis that it is advisable to carry out the digital transformation of EIE based on considering it as a complex technical system using model-based system engineering (MBSE). The practical methodology based on MBSE for EIE digital representation creation are presented. It is demonstrated how different system models of EIE is created from a set of entities of the MBSE approach: requirements—unctions—components and corresponding matrices of interconnections. Also the principles and composition of tasks for system architectures creation of EIE digital representation are developed. The practical application of proposed methodology is illustrated by the example of an existing gas distribution station.

New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.