This research investigates the determinants of digital transformation among Vietnamese logistics service providers (LSPs). Employing the Technological-Organizational-Environmental framework and Resource Fit theory, the study identifies key factors influencing this process across different three stages: digitization, digitalization, digital transformation. Data from in-depth interviews with industry experts and a survey of 390 LSPs were analyzed using covariance-based structural equation modeling (CB-SEM). The findings reveal that the factors influencing the digital transformation of Vietnamese LSPs evolve across different stages. In the initial phase, information technology infrastructure, financial resources, employee capabilities, external pressures, and support services are key determinants. As digitalization progresses, leadership emerges as a crucial factor alongside the existing ones. In the final stage, the impact of these factors persists, with leadership and employee capabilities becoming increasingly important.
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 proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.
The creation of points where law, politics and education policies take intersection is a very complex and dynamic environment determined by philosophical shifts, economic problems, and social dynamics. This study dissects various complicated challenges facing the process of the framing of educational policies and their implementation which have become rampant due to the rapid political transformations. The researched evaluation is applied via both qualitative and quantitative methods, including juridical research, case and best practices studies and surveys, with the descriptive nature of the research as the main tool. The heart of the essay is three main themes - the contention between the rigidity of the academic standards and the holistic growth of students, its possible effects when students are too identified with a test-centric approach as their knowledge is sacrificed for their test scores, and the inclusion of rights and protections for underrepresented populations even when faced with a government’s resistance. Similarly, the research examines the perils of creating legislation too quickly, especially, because of unexpected side effects and interpretation conflicts. Findings show profound demographic differentials over districts which implies the designing and implementation of policies need to be modified accordingly. Unless a certain policy brings the best outcomes in the learning process, then nobody should choose it even if it means disrupting student well-being and decreasing their involvement. It is also emblematic of how cross-party cooperation and stakeholders’ understanding are important aspects of fairly dealing with complicated policy environments.
This study employs logistic regression to investigate determinants influencing active living among elderly individuals, with “Active Living” (1 = Active, 0 = Inactive) as the dependent variable. Analysing data from 500 participants, findings reveal significant associations between active living and variables such as chronic conditions (OR = 0.29, p < 0.001), mental well-being (OR = 1.57, p < 0.001), social support (OR = 5.75, p < 0.001), access to parks/recreational facilities (OR = 2.59, p < 0.001), income levels (OR = 1.82, p = 0.003), cultural attitudes (OR = 2.72, p < 0.001), and self-efficacy (OR = 2.01, p < 0.001). These findings highlight the complex interplay of factors influencing active living among elderly populations. Recommendations include implementing targeted interventions to manage chronic conditions, enhance mental well-being, strengthen social networks, improve access to recreational spaces, provide economic support for fitness activities, promote positive cultural attitudes towards aging, and empower older adults through self-efficacy programs. Such interventions are crucial for promoting healthier aging and fostering sustained engagement in physical activity among older adults.
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