Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.
This study adopts a discursive and analytical perspective to explore how technological advances are reconfiguring the dynamics of the global labour market, with special attention to the phenomenon of microwork. Microwork, characterised by short, fragmented tasks carried out through digital platforms and geographically distributed, has seen exponential growth, particularly in nations with lower economic development. This type of work shows a growing distinction between tasks of a complex and creative nature and those of a repetitive and monotonous nature that do not require advanced skills to perform. This differentiation can intensify wage disparities between developed and developing countries, as well as contribute to the precariousness of work in activities considered less complex and valued. The article highlights the emergence of unstable and poorly paid jobs that do not require specific qualifications and discusses their impact on social security systems in countries where labour regulations are insufficient. Using a theoretical-methodological approach, the research examines the role of artificial intelligence in the rise of micro-labour and its socio-economic implications. It concludes that despite the flexibility and short-term earning opportunities offered by microwork, it poses considerable challenges in terms of income security, workers’ rights, and social protection, emphasising the need for regulatory measures to mitigate its adverse effects on vulnerable communities.
In the rapidly evolving landscape of China’s pharmaceutical industry, this study investigates how pharmaceutical enterprises can achieve profitable sales innovation amid the process of digital transformation. Grounded in the Affordance theory, it posits that the positive impact of digital transformation on sales innovation is driven by the affordance afforded by digital technology and ubiquity. The research focuses on A-share pharmaceutical companies in China, utilizing data from 2012 to 2022 and employing multiple regression analysis to examine the influence of digital transformation on corporate sales innovation. The results demonstrate a significant positive effect of digital transformation on sales innovation. The study further categorizes digital transformation into technological affordance and ubiquity affordance, separately validating their roles in promoting sales innovation. Moreover, by considering synergistic effects, the research unveils the intricate relationship between digital transformation and corporate innovation performance. The findings provide a fresh perspective on understanding how digital technology propels sales innovation and offer concrete guidance for the digital transformation practices in the pharmaceutical industry.
This study examines conditions that impact PPP delivery success or failure in the roadways sector in India using Qualitative Comparative Analysis. QCA is well-suited for problems where multiple factors combine to create pathways leading to an outcome. Past investigations have compared PPP and non-PPP project delivery performance, but this study examines performance within PPPs by uncovering a set of conditions that combine to influence the success or failure road PPP project delivery in India. Based on data from 21 cases, pathways explaining project delivery success or failure were identified. Specifically, PPPs with high concessionaire equity investment and low regional industrial activity led to project delivery success. Projects with lower concessionaire equity investment and low reliance on toll revenue and with either: (a) high project technical complexity or (b) high regional industrial activity, led to project delivery failure. The pathways identified did not have coverage values that they were extremely strong. Coverage strength was hindered by lack of access to information on additional conditions that could be configurationally important. Further, certain characteristics of the Indian market limit generalization. Identification of combinations of conditions leading to PPP project delivery success or failure improves knowledge of the impacts of structure and characteristics of these complex arrangements. This study is one of the first to use fuzzy QCA to understand project delivery success/failure in road PPP projects. Moreover, this study takes into account factors specific to a sector and delivery mode to explain project delivery performance.
Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.
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