This study employs a transfer matrix, dynamic degree, stability index, and the PLUS model to analyze the spatiotemporal changes in forest land and their driving factors in Yibin City from 2000 to 2022. The results reveal the following: (1) The land use in Yibin City is predominantly characterized by cultivated land and forest land (accounting for over 95% of the total area). The area of cultivated land initially increased and then decreased, while forest land continued to decline and construction land expanded significantly. The rate of forest land loss has slowed (with the dynamic degree decreasing from −0.62% to −0.04%), and ecosystem stability has improved (the F-value increased from 2.27 to 2.9). The conversion of cultivated land to forest land is the primary driver of forest recovery, whereas the conversion of forest land to cultivated land is the main cause of reduction; (2) cultivated land is concentrated in the central and northeastern regions, while forest land is distributed in the western and southern mountainous areas. Construction land is predominantly located in urban areas and along transportation routes. Areas of forest land reduction are mainly found in the central and southern regions with rapid economic development, while areas of forest land increase are concentrated in high-altitude zones or key ecological protection areas. Stable forest land is distributed in the western and southern ecological conservation zones; (3) changes in forest land are primarily influenced by annual precipitation, elevation, and distance to rivers. Road accessibility and GDP have significant impacts, while slope, annual average temperature, and population density exert moderate influences. Distance to railways, aspect, and soil type have relatively minor effects. The findings of this study provide a scientific basis for the sustainable management of forest resources and ecological conservation in Yibin City.
The purpose of this study is to explore factors influencing the blockchain adoption in agricultural supply chains, to make a particular focus on how security and privacy considerations, policy support, and management support impact the blockchain adoption intention. it further investigates perceived usefulness as a mediating variable that potentially amplifies the effects of these factors on blockchain adoption intention, and sets perceived cost as a moderating variable to test its influence on the strength and direction of the relationship between perceived usefulness and adoption intention. through embedding the cost-benefit theory into the integrated tam-toe framework and utilizing the partial least squares structural equation modeling (PLS-SEM) method, this study identifies the pivotal factors that drive or impede blockchain adoption in the agricultural supply chains, which fills the gap of the relatively insufficient research on the blockchain adoption in agriculture field. the results further provide empirical evidence and strategic insights that can guide practical implementations, to equip stakeholders or practitioners with the necessary knowledge to navigate the complexities of integrating cutting-edge technologies into traditional agricultural operations, thereby promoting more efficient, transparent, and resilient agricultural supply chains.
This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.
The global shortage of nurses has resulted in the demand for their services across different jurisdictions causing migration from developing to developed regions. This study aimed to review the literature on drivers of nurses’ migration intentions from source countries and offer future research directions. A search strategy was applied to ScienceDirect, Web of Science, and Scopus academic databases to find literature. The search was limited to peer-reviewed, empirical studies published in English from 2013–2023 resulting in 841 papers. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a systematic review of 35 studies after thorough inclusion and exclusion criteria. In addition, the VOSviewer software was utilized to map network visualization of keywords, geographic and author cooperation for bibliometric understanding. The findings revealed various socio-economic, organizational, and national factors driving nurses’ migration intentions. However, limited studies have been conducted on family income, organizational culture, leadership style, infrastructure development, social benefits, emergency service delivery, specialized training, and bilateral agreements as potential drivers for informing nurses’ migration intentions. Moreover, a few studies were examined from a theoretical perspective, mainly the push and pull theory of migration. This paper contributes to the health human resources literature and shows the need for future studies to consider the gaps identified in the management and policy direction of nurse labor migration.
In today's changing world of work, Strategic Human Resource Management (SHRM)) still focuses on making workers more productive. This study systematically examines the mediating function of incentives both monetary and non-monetary between antecedent characteristics (e.g., leadership, organizational culture) and employee productivity using a systematic literature review (SLR) of papers published from 2010 to 2024. The review adheres to PRISMA principles and integrates 18 peer-reviewed studies chosen through a stringent screening and quality evaluation process from Scopus and Google Scholar. The results show that the success of incentives depends a lot on things like the ideals of the business, the style of leadership, and the demographics of the workforce. Thematic analysis, informed by the Ability-Motivation-Opportunity (AMO) theory and Strategic Human Resource Management (SHRM) frameworks, delineates four principal processes by which incentives affect productivity: goal alignment, perceived equity, motivational pathways, and cultural congruence. The research emphasizes the necessity of customizing incentive systems to specific organizational contexts and offers practical guidance for HR professionals. Recognizing limitations and publishing bias, suggestions for future incentive system design are presented.
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