Articles de revues sur le sujet « Digital Transformation. Technological Innovation. Logistics Optimization »

The rapid expansion of e-commerce and the growing demand for faster delivery have significantly reshaped the role of warehouse logistics in modern business. Traditional warehouse management methods are no longer sufficient to handle the rising volume of goods, underscoring the urgent need for innovative technological solutions. This study focuses on the evolution of smart warehousing—from basic barcoding systems to sophisticated technologies involving robotics, drones, and artificial intelligence. A noticeable gap remains in the academic literature between theoretical research on warehouse optimization and its practical applications. While many publications emphasize technical advancements, they often overlook the economic and social implications of automation. Moreover, there is a lack of interdisciplinary research that bridges technological innovation with the transformation of business models and the evolution of labor relations. This article analyzes key technological trajectories and demonstrates how the integration of digital twins, predictive analytics, and autonomous robotics not only enhances operational performance but also fundamentally redefines warehouse management practices. The insights presented are relevant for logistics company executives, technology developers, infrastructure investors, and supply chain management researchers.

The integration of Artificial Intelligence (AI) in supply chain management has emerged as a transformative strategy to enhance efficiency, resilience, and adaptability in complex global logistics networks. This proposes a comprehensive model for AI integration in supply chain optimization, drawing comparative insights from the United States and Nigeria two economies with contrasting technological infrastructures, regulatory frameworks, and economic dynamics. The model emphasizes a multi-tiered approach incorporating predictive analytics, real-time decision-making, and intelligent automation. In the U.S., AI adoption is characterized by advanced infrastructure, data availability, and investment in digital transformation, enabling real-time inventory management, demand forecasting, and autonomous logistics. Conversely, Nigeria presents a context of infrastructural challenges and data limitations, yet exhibits increasing potential for AI-driven solutions through mobile technology, cloud computing, and emerging policy support. The proposed model comprises four core pillars: (1) AI-readiness assessment focusing on digital infrastructure and data maturity; (2) phased AI adoption strategy tailored to sector-specific needs; (3) stakeholder collaboration for technological transfer and capacity building; and (4) policy alignment to foster ethical AI use and cross-border interoperability. Through comparative analysis, the model identifies key enablers and barriers within each country, highlighting opportunities for technology leapfrogging in Nigeria and continuous innovation in the U.S. This argues that while the scale and mode of AI integration may differ, the strategic alignment of technology, talent, and governance is essential for effective supply chain optimization in both regions. This research contributes to the discourse on inclusive AI deployment by illustrating how adaptable frameworks can bridge technological disparities and drive supply chain resilience. Ultimately, it underscores the importance of localized strategies within a global model, fostering both economic growth and digital equity. The findings serve as a guide for policymakers, industry leaders, and technology developers seeking to harmonize AI integration across diverse socio-economic contexts.

The article explores the concept of a Port-Integrated Autonomous Network (PIAN) as a systemic model of the digital transformation of seaports in the context of innovative technologies. The PIAN combines autonomous port operations, distributed artificial intelligence, global blockchain document management, predictive analytics tools, and sustainable ecosystems. The article presents several mathematical models - phase implementation (PRM), stakeholder collaboration (SCM), and continuous innovation (CIM) - that allow for the optimization of efficiency, reduction of risks, and consideration of communication costs. The author identifies key technological components of smart ports, including autonomous equipment, digital platforms, sensor infrastructure, predictive maintenance, and intelligent traffic management systems. Special attention is paid to the legal aspects of implementation, particularly challenges in cybersecurity and regulatory compliance (GDPR, etc.). Based on the analytical model, a roadmap for the gradual introduction of technologies in ports with different readiness levels is proposed, allowing PIAN to be adapted to the specifics of local conditions. The article forms a theoretical and methodological basis for port administrations and logistics operators seeking to improve port infrastructure’s efficiency, flexibility, and sustainability in the maritime industry’s digital transformation context.

This article explores the influence of artificial intelligence on enhancing management efficiency in the oil and gas industry. The authors analyze the impact of artificial intelligence (AI) on improving efficiency in the oil and gas sector, including the optimization of exploration, extraction, logistics, and environmental safety; market size; long-term trends in application areas, etc., highlighting key technological solutions. These include data analysis automation, risk prediction, and integration of IoT platforms. Based on the conducted research, it is proposed to expand the use of artificial intelligence to enhance the efficiency of the oil and gas industry through the implementation of hybrid machine learning algorithms, strengthening inter-industry collaboration, and developing digital security standards. Special attention is given to the role of AI in reducing carbon footprint and adapting to global climate initiatives. Machine learning methods, big data analysis, and case studies of leading companies (Schlumberger, ExxonMobil, SIBUR) were utilized. Statistical models were applied to assess the reduction of production costs (by up to 40%) and increase the accuracy of geophysical exploration. Data were obtained from industry reports, patent databases, and software solutions. AI is used to digitize production records and automatically analyze geological data based on deep neural networks, which allows for identifying problems and optimizing key oil exploration processes. Intelligent market demand analysis through data collection and visualization enhances supply chain efficiency. Modern commercial solutions drive the digital transformation of the industry and innovation. The research findings are applicable for optimizing exploration, extraction, and logistics. Unlike existing works, the focus is on the specifics of emerging markets. Despite current challenges (costs, data quality), the implementation of AI will enable: Strengthening well logging data collection; Implementing intelligent geophysical exploration; Automating fault diagnosis. A key direction is the creation of an innovative research center to accelerate digital transformation and the implementation of innovations.

The article examines the key aspects of the innovative transformation of operational systems of construction enterprise stakeholders in the context of the digitalization of the economy. Principles and approaches to the formation of adaptive operational models that enable enterprises to function effectively under conditions of rapid technological changes are identified. Strategic directions for integrating digital technologies into production, management, and logistics processes and their impact on the competitiveness of construction enterprises are outlined. Special attention is given to the ecosystem approach to transformation, which is based on the integration of innovations, digital platforms, and inter-organizational cooperation. The focus is placed on digital technologies such as Building Information Modeling (BIM), Enterprise Resource Planning (ERP) systems, the Internet of Things (IoT), and process automation, which contribute to creating competitive advantages and ensure the synergistic effect of stakeholder interaction. The impact of these technologies on resource management optimization, cost reduction, and accuracy improvement in construction project execution is analyzed. The article emphasizes the need to develop integrative management models that address both technological and organizational aspects. Construction enterprise stakeholders, facing the challenges of the digital economy, require the implementation of innovative mechanisms for collaboration among participants in the construction process. The ecosystem approach discussed in the article proposes creating a unified digital space that ensures effective communication, real-time data exchange, and improved transparency in managerial decision-making. The structural role of strategic goal-setting is considered as a key component of successful transformation, enabling the prioritization of objectives, the creation of roadmaps for digitalization, and the adaptation of business processes to modern requirements. The significance of innovative culture and the development of staff competencies is highlighted to ensure the resilience of transformational changes. The conclusions of the article emphasize the importance of a systematic approach to modernizing operational systems of construction enterprise stakeholders in the context of the digitalization of the economy. The proposed concept serves as a foundation for implementing long-term innovative solutions aimed at enhancing the efficiency, flexibility, and resilience of enterprises in a dynamic environment.

ABSTRAKDalam era globalisasi yang semakin berkembang, inovasi teknologi memainkan peran krusial dalam meningkatkan efisiensi dan efektivitas sistem logistik internasional. Transformasi digital, seperti penerapan Internet of Things (IoT), Artificial Intelligence (AI), Blockchain, dan Big Data, telah memungkinkan optimalisasi rantai pasok, peningkatan kecepatan distribusi, serta pengurangan biaya operasional. Penelitian ini bertujuan untuk mengeksplorasi peran orientasi pasar, responsivitas, inovasi, intelijen pemasaran, dan kepuasan pelanggan dalam industri logistik internasional. Metode penelitian menggunakan pendekatan kuantitatif melalui penyebaran kuesioner yang selanjutnya di analisis menggunakan software PLS-SEM. Temuan menunjukkan hubungan signifikan antara orientasi pasar dan inovasi, menekankan pentingnya memanfaatkan wawasan pasar untuk mengembangkan solusi yang kompetitif. Responsivitas juga memainkan peran penting dalam meningkatkan kepuasan pelanggan dengan cara memenuhi kebutuhan pelanggan secara efektif. Namun, penelitian ini mengidentifikasi bahwa inovasi tidak selalu memediasi hubungan antara responsivitas dan kepuasan pelanggan, yang menunjukkan dampak yang lebih bernuansa dan bergantung pada konteks. Temuan ini menekankan perlunya perusahaan untuk mengadopsi strategi terintegrasi yang menggabungkan inovasi, responsivitas, dan pendekatan yang berfokus pada pelanggan untuk mencapai keberhasilan yang berkelanjutan di sektor logistik yang kompetitif.ABSTRACTIn the era of growing globalization, technological innovation plays a crucial role in improving the efficiency and effectiveness of international logistics systems. Digital transformations, such as the implementation of the Internet of Things (IoT), Artificial Intelligence (AI), Blockchain, and Big Data, have enabled supply chain optimization, increased distribution speed, and reduced operational costs. This study explores the role of market orientation, responsiveness, innovation, marketing intelligence, and customer satisfaction in the international logistics industry. The research method uses a quantitative approach through distributing questionnaires which are then analyzed using PLS-SEM software. The findings reveal a significant relationship between market orientation and innovation, emphasizing the importance of leveraging market insights to develop competitive solutions. Responsiveness also plays a vital role in enhancing customer satisfaction by addressing customer needs effectively. However, the study identifies that innovation does not always mediate the relationship between responsiveness and customer satisfaction, indicating a nuanced and context-dependent impact. These findings underline companies' need to adopt integrated strategies combining innovation, responsiveness, and customer-centric approaches to achieve sustainable success in the competitive logistics sector.

Integrating artificial intelligence (AI) in supply chain optimization represents a transformative paradigm shift in modern business operations, fundamentally reshaping how organizations manage their supply chain networks. This comprehensive article synthesizes findings from extensive studies across manufacturing and logistics sectors, demonstrating that organizations implementing structured AI adoption frameworks achieve significantly higher returns on investment than traditional approaches. Through analysis of global enterprises over recent years, this article reveals that companies following systematic implementation methodologies experience substantial improvements in operational efficiency and decision-making accuracy. This article presents a detailed framework encompassing five critical dimensions: maturity assessment, data strategy development, pilot project implementation, enterprise-wide integration, and future considerations. Organizations implementing comprehensive data strategies demonstrate marked improvements in prediction accuracy and considerable reduction in process inefficiencies, while those adopting phased pilot implementations achieve notably faster full-scale deployment rates. This article further indicates that enterprises establishing robust governance frameworks experience fewer integration challenges and better stakeholder alignment. Integrating IoT technologies with AI frameworks significantly improves supply chain visibility and enhances real-time decision-making capabilities. This article provides actionable insights for organizations embarking on AI transformation initiatives, emphasizing the importance of a balanced approach between technological innovation and practical implementation considerations while focusing on sustainable and ethical practices. The analysis contributes to theoretical understanding and practical implementation of AI in supply chain management, offering a structured pathway from initial assessment through enterprise-wide deployment and continuous improvement.

В статье исследуются ключевые аспекты стратегического управления в эпоху цифровой трансформации. Проведен последовательный анализ эволюционного развития стратегического менеджмента: от традиционных методик к современным гибким моделям, опирающимся на применение искусственного интеллекта, аналитику больших данных, блокчейн-технологии, интернет вещей и концепцию открытых инноваций. Существенное внимание уделено трансформации организационных структур и управленческих процессов, а также воздействию цифровых технологий на разработку и воплощение стратегических решений. Рассмотрены потенциальные риски цифровизации, среди которых выделяются усиление киберугроз и недостаточность цифровых компетенций персонала. В качестве успешного примера цифровой трансформации приводится опыт компании Spotify, даются рекомендации по внедрению искусственного интеллекта, технологий дополненной и виртуальной реальности, а также сети 5G для увеличения пользовательской вовлеченности и обеспечения устойчивого роста. Представлен экономический анализ предложений по дальнейшему развитию цифровых технологий, расчеты подтверждают высокую инвестиционную привлекательность проекта. Статья акцентирует необходимость комплексного подхода к стратегическому управлению в условиях интенсивных технологических изменений современной бизнес-среды. This article discusses the main development areas of X5 Retail Group, in particular in the field of technological innovations in the management and quality control of goods and services. This work is written to demonstrate the economic and social effect of quality control technologies, as well as innovations in the management of the company’s services. Particular attention is paid to digital solutions that improve the efficiency of the administrative system: automation of business processes, the implementation of analytics systems based on big data and artificial intelligence, as well as digital platforms for quality management. The key practices of X5 Retail Group in the field of digitalization are analyzed, including logistics optimization, assortment management and quality control at all stages of the supply chain. It is shown how the introduction of modern technologies helps to reduce costs, increase process transparency and improve customer experience. Specific examples demonstrate the cost-effectiveness of digital solutions, their impact on operations and the long-term competitiveness of the company. As a result of the study, it was revealed that our own resource in the form of artificial intelligence not only increases the efficiency of employees, but also minimizes costs and the number of incidents in the quality control process. The study will be useful for retail chain managers, digital transformation specialists and anyone interested in using innovative technologies to improve management efficiency in retail.

The oil and gas sector, a cornerstone of the global energy supply, is poised at the brink of a technological renaissance as it embraces Artificial Intelligence (AI). This paradigm shift is driven by the industry's imperative to enhance efficiency, bolster safety, and notably, optimize costs amidst volatile market conditions and escalating operational complexities. This paper presents an in-depth exploration of the multifaceted applications of AI technologies in streamlining cost management across various phases of oil and gas projects—from exploration to distribution. At the heart of this exploration is the elucidation of AI's transformative role in predictive analytics, automation, and decision support systems. By harnessing the power of machine learning algorithms, the industry can predict equipment failures, optimize maintenance schedules, and ensure uninterrupted production, thereby significantly reducing downtime costs. Furthermore, AI-driven data analytics enable the identification of patterns and insights from vast datasets, leading to more informed and cost-effective decision-making. The paper also delves into the integration of AI in operational domains such as drilling optimization, where AI algorithms analyze geological data to determine optimal drilling locations and parameters, thus minimizing the risk of costly non-productive time. Similarly, in the realm of supply chain management, AI facilitates dynamic routing and inventory control, curtailing logistical expenses. Highlighting case studies and empirical data, the paper underscores the tangible benefits realized by early adopters of AI in the industry, showcasing a potential reduction in operational costs and an increase in efficiency that often surpasses traditional methodologies. This detailed examination not only charts a course for future AI-driven endeavors in the oil and gas sector but also serves as a clarion call for stakeholders to navigate the intricacies of digital transformation strategically. In conclusion, the paper posits that the integration of AI stands as a beacon of innovation, promising not only cost optimization but also a sustainable and resilient future for the oil and gas industry. The findings herein aim to galvanize industry leaders, policymakers, and technologists to foster a collaborative ecosystem where AI can flourish, driving the industry towards a new horizon of operational excellence.

The world has entered an era of digital economy, and China’s logistics industry is accelerating its digital transformation to promote the upgrading of industrial structure, enhance safety and efficiency, improve service quality, optimize user experience, and ultimately drive intelligent transformation. Furthermore, in response to the current state of digital logistics, this paper proposes optimization and innovation policies such as strengthening the training of logistics innovation technical personnel, enhancing the economic infrastructure of digital logistics, and promoting deep integration between the digital economy and logistics industr -to enrich logistic theory under the digital economy and promote high-quality development of contemporary logistics industry.

The U.S. startup ecosystem is a highly competitive one and for that reason project management (PM) strategies have to be dovetailed with digital marketing analytics to propel business growth. In this study, the influence of structured PM methodologies like Agile, Scrum, Waterfall and Hybrid on digital marketing analytics for startup success in marketing efficiency, customer engagement and business scalability will be examined. The design choice was a quantitative one with survey data from 200 professionals at US based startups (founders, project managers, digital marketing managers, data analysts among others). The findings show that startups utilizing structured PM frameworks achieve much greater digital marketing performance. The results of regression analysis revealed that digital analytics use (β = 0.55, p < 0.001) was the strongest influencer of marketing effectiveness and the adoption of omnichannel (β = 0.45, p = 0.001) was the key predictor of sustained startup growth. Logistic regression analysis shows that startups implementing PM strategies have 2.15 times a higher chance to reach marketing success. The study reveals some key challenges of less entrenched adoption of PM frameworks such as a budget constraint, lack of skilled personnel and resistance to digital transformation that still prevent the full-scale adoption of PM frameworks in marketing strategy execution. The findings of the study are of critical importance to U.S. startups in the areas of data driven decision-making, real-time marketing analytics and PM methodologies to gain marketing ROI, customer retention and competitive advantage. The conclusion of this research is that utilizing project management principles in coordination with digital marketing analytics will lead to long term business sustainability in U.S. startup landscape. 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<b>Research Background and Purpose</b>: In an era of digital transformation, logistics companies must adapt to technological advancements to maintain competitiveness. This study examines the impact of digital transformation on logistics capabilities, with a specific focus on the mediating role of innovation orientation. While prior research has explored the direct effects of digital transformation, studies investigating the mechanisms behind this relationship remain limited. Addressing this gap, the study aims to provide empirical insights for academia and industry. <b>Design/Methodology/Approach:</b> The research employs a quantitative methodology based on Industry 4.0 principles. Data were collected from 401 participants using a judgmental sampling method from businesses affiliated with the Istanbul Chamber of Commerce (Türkiye) transportation and logistics services committee. The analysis was conducted using SPSS 23.0 and SPSS PROCESS Macro 4.3 (Model 4) with the bootstrap technique to examine mediation effects. <b>Findings:</b> The results indicate that digital transformation significantly enhances logistics capabilities. It positively influences sub-dimensions such as logistics service differentiation and logistics innovation. Moreover, innovation orientation partially mediates this relationship, suggesting that companies with a stronger innovation focus benefit more from digitalization. <b>Value Added and Limitations</b>: This study contributes to the literature by offering theoretical and methodological insights into the interplay between digital transformation, logistics capabilities, and innovation orientation. The findings provide practical recommendations for logistics companies in formulating digital transformation strategies. However, the study is limited to data from Istanbul Chamber of Commerce-affiliated businesses, which may affect generalizability. Future research could expand these findings by including a broader range of sectors and employing alternative research methodologies.

This study investigates the high-quality development of Chinese logistics SMEs by analyzing the effects of digital technology adoption, organizational resilience, utilization innovation, and exploratory innovation. It explores how digital transformation improves operational efficiency and adaptability, while assessing the mediating role of utilization innovation in connecting technology adoption and resilience to enterprise success. Additionally, the study examines the moderating effect of exploratory innovation on these relationships. A survey of 340 logistics professionals and SMEs within China's supply chain sector was conducted, with hypotheses tested using SPSS and SmartPLS-4. The results reveal that digital technology adoption and organizational resilience significantly contribute to enterprise development, with utilization innovation playing a pivotal mediating role. Furthermore, exploratory innovation moderates the relationship between digital adoption and innovation, highlighting the importance of adaptability in dynamic markets. This study presents a comprehensive framework integrating digital adoption, resilience, and innovation, offering valuable insights into how SMEs can address the challenges of digital transformation. Policymakers and industry stakeholders are encouraged to implement supportive policies, financial incentives, and technological investments to enhance the competitiveness of SMEs.

This study explores the high-quality development of Chinese logistics small and medium enterprises (SMEs) by examining the impact of digital technology adoption, organizational resilience, exploratory innovation, and environmental uncertainty. The research investigates how digital transformation enhances operational efficiency, adaptability, and competitiveness while assessing the mediating role of exploratory innovation in linking technology adoption and resilience to enterprise success. Additionally, the study evaluates the moderating effect of environmental uncertainty on these relationships. A survey was conducted among 340 logistics professionals and SMEs operating within China's supply chain sector, focusing on their digital transformation efforts, resilience strategies, and innovation-driven business models. The hypotheses were tested using descriptive analysis in SPSS and structural equation modeling (SEM) in SmartPLS-4. The findings indicate that digital technology adoption and organizational resilience significantly enhance high-quality enterprise development, with exploratory innovation playing a crucial mediating role. Moreover, environmental uncertainty moderates the relationship between digital adoption and innovation, highlighting the need for adaptability in dynamic markets. This study contributes to the existing literature by integrating digital adoption, resilience, and innovation within a unified framework, particularly in the context of Chinese logistics SMEs. The results emphasize the importance of reducing digital adoption barriers, strengthening organizational resilience, and leveraging innovation to enhance long-term sustainability. Policymakers and industry stakeholders are encouraged to implement supportive trade policies, financial incentives, and technological investments to optimize the performance of Chinese logistics SMEs in an increasingly competitive environment.

Based on the panel data of 29 provinces and cities in China from 2013 to 2020, the mediating effect model and the moderating effect model are used to empirically analyze the transmission role of technological innovation and industrial structure optimization in the digital economy influencing the green transformation of manufacturing industry, and the moderating role of environmental regulation in the digital economy promoting the green transformation of the manufacturing industry. The results of the empirical study show that the digital economy promotes the green transformation of the manufacturing industry through technological innovation and industrial structure optimization. On the other hand, the intensity of environmental regulation has a significant negative moderating effect on the green transformation of the manufacturing industry promoted by the digital economy.

The logistics industry, as a cornerstone of global trade, is undergoing significant transformation through the integration of digital technologies. However, persistent challenges such as supply chain inefficiencies, high operational costs, and environmental concerns necessitate strategic optimization approaches. This study explores the synergistic application of digital tools and mathematical techniques, such as linear programming and predictive modeling, to optimize logistics operations. Using a Systematic Literature Review (SLR) approach, the research synthesizes findings from peer-reviewed journals and industry case studies. Key findings highlight how technologies like IoT, blockchain, and AI enhance supply chain transparency, decision-making, and sustainability. Practical implications emphasize scalable optimization frameworks and stakeholder collaboration to address adoption barriers and foster innovation. This study provides actionable insights for policymakers and industry leaders to align logistics practices with global sustainability goals, ensuring resilience and efficiency in an evolving market landscape.

The purpose of this research is to study the provision of logistics services in the context of Industry 4.0 and analyze the level of application of modern technologies in the field of transport and logistics based on an assessment of the relationship between technological readiness, the development of innovation and the efficiency of logistics in Kazakhstan. Based on data from the World Bank and the World Economic Forum on the Logistics Performance Index (LPI) and Global Competitiveness (GCI), a correlation analysis was made between the indicators of technological readiness, innovation and the Logistics Performance sub-indices. Also, based on the data of a sample study by the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan on the use of ICT, the main trends in the development of digital technologies in the field of transport and warehousing in the country have been identified. Correlation analysis showed that in Kazakhstan the level of technological readiness has a strong relationship with the development of logistics efficiency parameters: customs, tracking of cargo transportation, quality of service and competence, quality of infrastructure, adherence to delivery times. It should be noted that the development of logistics is not associated with the innovative development of the country, this is due to the low level of innovation in the country. The study of statistical data in Kazakhstan revealed a low level of digital transformation of the transport and logistics sector: there is a passive use of digital technologies at transport and warehousing enterprises, a low level of investment in digitalization, the need for personnel in the field of ICT in logistics.

The digital economy era presents new opportunities for supply chain finance to ease financial pressures on businesses and foster digital technological innovation by integrating capital, information, and logistics. Despite this, businesses encounter significant innovation costs and challenges during digital transformation, making traditional financing methods insufficient. Supply chain finance offers an innovative solution by merging the financial, informational, and logistic flows of the supply chain's upstream and downstream, leveraging digital technology to refine credit assessments and risk management. This paper examines the influence of supply chain finance on the digital technological innovation levels of businesses and the mechanisms behind it, using data from Chinese listed companies from 2009 to 2023. The findings reveal that supply chain finance substantially boosts digital innovation by enhancing financing avenues, fostering information exchange, and empowering technology; company size positively moderates the link between supply chain finance and digital innovation. Heterogeneity analysis indicates that while supply chain finance has a more pronounced effect on state-owned enterprises, non-state-owned firms also gain benefits. The study's conclusions offer a theoretical foundation for refining financial resource allocation and enhancing supply chain finance policies, as well as strategic guidance for businesses to advance their digital transformation practices.

The digital economy has become an important path for the transformation and upgrading of industrial structure. Technological innovation, as the primary driving force for development, is a key entry point in analyzing this issue. This paper conducts empirical analysis based on Panel data of 31 provinces in China from 2011-2021, and constructs Mesomeric effect and moderating effect models. Research has found that the development of the digital economy has a significant promoting effect on the rationalization of industrial structure; The digital economy can promote the improvement of technological innovation level; From a national perspective, the level of technological innovation reflects the masking effect in the process of promoting industrial structure rationalization in the digital economy, and this conclusion is still valid after robustness testing.Based on this, we need to strengthen the construction of digital infrastructure, rely on the digital economy to stimulate independent innovation and technological transformation level, and promote the upgrading of industrial structure.

The digital economy has become an important path for the transformation and upgrading of industrial structure. Technological innovation, as the primary driving force for development, is a key entry point in analyzing this issue. This paper conducts empirical analysis based on Panel data of 31 provinces in China from 2011-2021, and constructs Mesomeric effect and moderating effect models. Research has found that the development of the digital economy has a significant promoting effect on the rationalization of industrial structure; The digital economy can promote the improvement of technological innovation level; From a national perspective, the level of technological innovation reflects the masking effect in the process of promoting industrial structure rationalization in the digital economy, and this conclusion is still valid after robustness testing.Based on this, we need to strengthen the construction of digital infrastructure, rely on the digital economy to stimulate independent innovation and technological transformation level, and promote the upgrading of industrial structure.

Manufacturing enterprises are confronted with the historic opportunity and challenge of balancing green transformation with economic development to achieve the goal of carbon neutrality. Some advanced companies are increasingly pursuing green development and innovation by expanding and optimizing the use of digital technology. In this study, we employ Chinese listed manufacturing companies from 2013–2019 as the research sample and examine the mechanism by which corporate digital optimization affects green technological innovation, as well as the mediating role of green R&D collaboration between the two. We also introduce external environmental orientation as a moderating variable. The results of fixed-effect Poisson model analysis are as follows. First, a positive correlation between digital optimization and green R&D collaboration indicates that scaling up digital optimization promotes green R&D collaboration. Second, we observe an inverted U-shaped relationship between green R&D collaboration and green technological innovation. Third, green R&D collaboration acts as a mediating factor between digital optimization and green technological innovation, and external environmental orientation moderates the relationship between digital optimization and green R&D collaboration. Fourth, the threshold effect results indicate that the optimal value of digital optimization projects is 10.167, with too many or too few projects impairing the effect of digital optimization on green technological innovation. All of the above results passed the robustness test.

The synergistic application of human-AI integration and sound-vibration technology is profoundly reshaping the digital transformation landscape and technological innovation in Chinese enterprises. In this research, with technological innovation as the mediating variable, how human-AI integration and sound-vibration technology jointly optimize enterprise digital transformation was investigated. A human-AI collaborative model incorporating sound-vibration technology is constructed and validated using confirmatory factor analysis (CFA) and partial least squares structural equation modeling (PLS-SEM), revealing its dual role in accelerating digital transformation and driving technological innovation. Data from the power sector of Chinese technology enterprises is analyzed, with 262 observations collected via a structured questionnaire and examined using structural equation modeling. The findings demonstrate that human-AI integration significantly enhances organizational capabilities through complex data processing, sound-vibration signal analysis, and decision optimization, while the application of sound-vibration technology further improves the efficiency of equipment monitoring and predictive maintenance, thereby supporting digital transformation. Technological innovation plays a critical mediating role, with its contributions to operational efficiency and emerging business models empirically validated. The research not only enriches the theoretical framework of human-AI integration and sound-vibration technology in digital transformation but also provides actionable strategic recommendations for enterprises and decision-makers to achieve continuous innovation and competitive advantages in the era of intelligent and digital transformation.

Digitalization is a key trend in the development of the Russian economy. The construction industry is certainly involved in the processes of digital transformation, which is reflected in a number of targeting documents of the state level. However, it should be noted that the main attention is paid to the digitalization of the main production processes directly. At the same time, auxiliary processes are ignored. As a result of the study, it was concluded that the digital transformation should include the processes of marketing, logistics, attracting and post -sales interaction with clients, infrastructure, managing human resources, supply and technological development.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. These research results provide important support to further promote the intelligent development of the logistics industry.

The purpose of this study is to establish the degree of digitalization of the transport and logistics industry, to determine its state in the Central Asian region. Based on the purpose of the work, the authors set the task to analyze the degree of implementation and use of modern technologies in transport logistics. In addition, the article deals with the problem of competitiveness of the transport and logistics industry of Kazakhstan and other Central Asian countries. In particular, through the use of statistical data and indices of international organizations, the issue of the effectiveness of logistics services in the market of the region is addressed. As a result of the study, the relationship between technological readiness, innovation development and logistics efficiency in Kazakhstan is assessed. The authors have identified the main problems and development prospects that can contribute to an increase in the volume of movement of goods and income growth.

The purpose of writing the article is to study the main provisions and prerequisites for the formation of digital technologies for the logistics systems, the evolution of digitalization processes. The evolution of digital technologies development – from the third industrial revolution (1969) and up to the present day is considered. The development of digital technologies has also influenced the evolution of logistics and supply chain conceptions. The history of the establishing of logistics as a science, the formation of supply chains and the acquisition by the logistics system of the status of «necessary» at the enterprise began in the 1950s and continues to this day. The evolution of logistics and supply chain conceptions is considered. Over time, under the influence of transformation processes, definitions of such concepts as «logistics system», «digital technology», «digital transformation» and many others are formed, implemented and improved, some of these are discussed in the presented article. Based on the analysis of existing formulations, a definition of the essence of the concept of «digital technology for a logistics system» is proposed as such that was not previously considered by scholars. Digital technologies for the logistics systems are information digital technologies, namely: software, robots, devices that perform automated functions of collecting, storing, processing and transmitting information, the introduction of which into the logistics system for managing orders, vehicles, stocks, warehouse resources optimizes the entire process of monitoring activities, helps to reduce fuel and maintenance costs, meet customer needs, increase profits and make business more efficient. The emergence and development of digital technologies for logistics systems is closely connected with the digitalization of all globalization processes. Technological innovation and customer needs for innovative technologies and services are increasingly changing the industry. This transformation significantly affects the direction in which enterprises will move in accordance with new challenges. IT standards are being introduced into industrial automation, devices are becoming more miniature and more functional. Today, the transformation processes of the logistics system are taking on newer forms, so further research on their implementation and development appears very important and relevant.

The paper describes the features of planning in-house technological, transport and logistics processes of a resource-extracting complex. The factors influencing the transport capacity of production processes and their situational analysis are given. The directions of optimization of related interrelated processes based on digital transformation of characteristic indicators and their step-by-step iteration are proposed

The scientific article refl ects the main results of a comprehensive researching of the process of transformation of business systems and international logistics technologies under the influence of digitalization trends, primarily artificial intelligence, in the context of the widespread introduction of Industry 4.0 conceptual approaches into economic, production and distribution cycles.In the context of the globalization of the economy and the rapid development of technology, key changes in the processes of managing integrated supply chains under the influence of digital technologies and intelligent systems are considered. The aspects discussed in this article, ranging from digital tools in warehouse management to the use of blockchain and artificial intelligence in international logistics, highlight the importance of innovation in this area. Modern technologies such as warehouse management systems, robotic technologies, blockchain and artificial intelligence show potential for improving the efficiency of logistics processes and optimizing costs.The scientific significance of this study lies in understanding these technological changes and their impact on international logistics structures. The emphasis in the work is on identifying the main trends affecting the efficiency and sustainability of logistics systems in the context of digitalization at the present stage of scientific and technological progress and informatization of society. In conditions of constant competition, the timely introduction of new technologies is one of the critical factors for the successful positioning of a company in the market.

Developed countries are actively implementing the digital transformation of the real economy with the transition to an information management system with rational integration of data into a single structured space with new opportunities for obtaining information support for decision-making. Integration mechanisms of technologies for the formation of optimal crop rotations and logistics technologies, reflecting in recent years two of the main principles of the digital economy of countries, are discussed. Science-based crop rotations determine the technological processes in agriculture and must be informationally and algorithmically integrated. However, their effective application requires the creation of optimization models associated with optimizing digital logistics technologies that combine all factors of crop rotation formation. The relevance of logistics optimization is determined by the need to reduce the huge costs for it in Russia (about 20% of the country’s GDP). The article presents a mathematical model for the formation of optimal crop rotations, which makes it possible to georeferencing the obtained promising crop rotations, considering logistics.

This study examines how DTDC, a leading logistics and courier company, has utilized web tracking tools to implement digital transformation strategies. The paper explores the integration of management strategies with cutting-edge digital tools to enhance operational efficiency, customer satisfaction, and decision-making. By analysing the role of web tracking systems, this paper sheds light on their impact on organizational agility, data-driven culture, and market competitiveness. The evaluation of digital transformers with web tracking practices are crucial due to the city's role as a major commercial hub in India, characterized by high volume shipping demands and complex logistics networks. Web tracking strategies in this region are imperative for maintaining timely delivery schedules, optimizing inventory turnover, and minimizing operational costs. This study delves into the various aspects of chi square tools examining how strategies such as layout optimization, technological integration, workforce management, and supply chain coordination contribute to enhancing organizational efficiency. Keywords: Digital Transformation, Web Tracking Tools, Management Strategies, DTDC Logistics, Operational Efficiency, Customer Experience, Data Analytics.

Industrial transformation (IT) is the inevitable course for the sustainable development of resource-based cities, while digital inclusive finance (DIF) provides essential capital elements for industrial transformation. Based on the panel data of 115 resource-based cities in China from 2011 to 2019, this paper discusses the influence mechanism of digital inclusive finance on industrial transformation from the perspectives of the optimization of industrial structure (OIS) and the rationalization of industrial structure (RIS). The empirical results show that digital inclusive finance has a positive effect on both the optimization of industrial structure and the rationalization of industrial structure. Digital inclusive finance influences industrial transformation through residents’ income and technological innovation. In addition, in the analysis of income gap and innovation gap, low-income regions have a better effect on the industrial transformation of industrial structure optimization, while high-income regions have a better effect in manufacturing upgrading, thus resulting in a more significant effect of industrial transformation on the rationalization of industrial structure. Obviously, the development of high-innovation regions has relative advantages with more channels for industrial transformation, which have significant effect of industrial transformation. Therefore, it is necessary to provide differentiated reform on the basis of unified development reform.

Introduction. In modern conditions of development of the world economy, the digital economy is one of the most relevant and important factors in ensuring economic growth. The digital transformation of the economy is a primary direction of innovative development of socio-economic systems, and therefore a tool for creating long-term competitive advantages of the transport and logistics system. The article examines the issue of economic problems associated with obtaining an integrated assessment of the level of competitiveness of the transport and logistics system. The purpose of the article is to analyze the impact of the digitalization of the economy on the competitiveness of the transport and logistics system and to create a model for obtaining an integrated evaluation of its competitiveness based on factors that reflect the specifics of the services provided by the system in the conditions of the digital transformation of the economy. Research methods. The digital transformation of the transport and logistics system is carried out based on the implementation of digitalization at all levels of business processes of economic structures: from the optimization of the logistics of physical flows and the optimization of data exchange to customer service. To assess the level of competitiveness of the transport and logistics system, it is proposed to calculate the competitiveness index by group of services in the process of transporting material flow. The model for calculating the integrated indicator of the competitiveness of the transport and logistics system is described, which is a three-stage multifactor model. Results. The economic evaluation of the digital transformation of the development of logistics services in railway transport allows for specifying the specifics of service services and clarifying the possibilities of using logistics methods of service response in carrying out cargo transportation. This makes it necessary to clarify the place and role of service support of cargo flow in the transport and logistics system and points to bottlenecks that must be overcome in the future to increase the level of competitiveness not only of the system but also of the country as a whole. Conclusions. The development of the digital transformation of the transport and logistics system consists of solving various socio-economic and technological tasks, which include the emergence of new products and new markets; reduction of costs for conducting business activities; and increasing productivity and efficiency of logistics and transport processes. As a result is increased competition in the transport and logistics system.

In the era of rapid technological advancements and global economic transformation, the emergence of “new productivity” has become a critical driver of industrial upgrading. New productivity, characterized by the integration of digitalization, intelligence, and sustainability, represents an advanced stage of productivity development. Technological innovation serves as the core force behind this transformation, reshaping traditional industries and fostering the emergence of new industrial systems. This paper explores the pathways and mechanisms through which technological innovation drives industrial upgrading from the perspective of new productivity. By analyzing theoretical foundations and real-world cases, it identifies key factors such as digital transformation, intelligent manufacturing, and sustainable practices. The study also examines the interactions between technological innovation, industrial structure optimization, and value chain enhancement, providing insights into policy-making and strategic development for realizing high-quality industrial growth.

This study offers a narrative literature review on transportation mode integration in logistics distribution, focusing on the interplay between infrastructure development, digital technologies, and collaborative logistics platforms in enhancing multimodal systems. Drawing from databases like Scopus, Web of Science, and Google Scholar, the review highlights how infrastructure serves as the foundation for logistics flow, digital tools facilitate real-time coordination and route optimization, and collaborative platforms support stakeholder alignment, especially in urban settings. Despite advancements, regional disparities in infrastructure, digital capacity, and policy enforcement hinder logistics efficiency. Empirical evidence shows that AI-supported multimodal logistics can reduce delivery times by up to 25% and transportation costs by 18% in dense urban areas. While developed countries leverage innovation and strong frameworks, developing regions struggle with technological access and policy inconsistencies. Sustainability is a recurring theme, with digital tools contributing to emissions tracking and carbon reduction. The study calls for integrated policies, infrastructure investment, and scalable digital solutions, particularly for underserved regions. Key recommendations include strengthening collaborative networks, enhancing digital skills, and implementing region-specific strategies. This review contributes to the global dialogue on sustainable logistics and outlines future research directions to address persistent gaps in multimodal logistics integration.

The formation of integrated logistics is the economic mainstream today, which can be characterized by rationality, striving for balance, as well as the predominance of “predatory” instincts for the development of economic agents. At the same time, it is has the features of hedonism and subjectivity, and besides, the evolutionary nature of its influence on the socio-economic system is not fully reflected. Today, the trend of its development is formed with the help of socio-technological drivers of the digital economy and information and communication technologies. So, logistics can be useful in the field of rational choice of optimization, which allows not to break away from the realities in theory. Moreover, digital logistics is already able to offer an achievable vision of the future arrangement in the field of management of flow processes in the modern information space, as well as to determine the optimal paths of evolutionary development.

The article analyzes the features of Kenya’s economy transformation characterized not so much by the industrial sector development, but the growth of the service sphere associated with the introduction of digital technologies, which determines the creation of new direct and indirect jobs and professions. Kenya has created one of the largest and fastest growing technological ecosystems in Africa. It was due to several factors, such as the emergence of Internet service providers in the early 1990s, the network building for mutual traffic exchange in the early 2000s, the launch of the M-Pesa mobile payment platform in 2007, the laying of submarine cables in 2009 and the formation of a technology cluster in Nairobi. E-business is becoming more widespread in the country, including financial technologies, banking, e-commerce, logistics services, the usage of digital automated technologies for industry, agriculture, healthcare, and education. Digital innovation is driving productivity gains in key sectors of the economy. The creation of adequate ICT infrastructure and access to Fiber Optic Broadband infrastructure for all the citizens, including low-income population, are the base for Kenya’s digital transformation. It is a key enabler in delivering Kenya’s Vision 2030 flagship project. The expanding of mobile broadband technologies 3G/4G/5G is vital for socio-economic growth. Some new technologies, which oriented at the conditions of developing countries, are used for increasing digital integration: BRCK that assures consistent internet access even in the very remote areas and new technology of wireless internet on the base of light beam. The very important problem is the creation of qualified specialists for digital economy.

Digital transformation is rapidly evolving digital standardization, driven by technological advancements and societal needs. SMART standards, developed using a structured approach encompassing machine readability, self-execution, and optimization, help machines and humans interact, accelerating the integration and utilization of digital technologies. Online Standard Development (OSD) provides agile support for standard development, enabling swift adaptation to technological changes.
 This study examines the current status of digital standardization by major organizations, such as KATS, IEC, and CEN/CENELEC, and investigates essential elements to improve the effectiveness and accessibility of digital standards. The findings emphasize the importance of collaborative standard development involving all stakeholders, alongside technological advancements, to create an environment where digital standards can be widely applied and efficiently utilized.

This study conducts a comprehensive bibliometric analysis to explore the evolving relationship between intellectual capital and Industry 4.0 within the logistics sector. The research identifies trends, key contributors, and thematic developments in this interdisciplinary field using data from two leading scientific databases, Web of Science and Scopus. The primary objective is to understand the critical areas of intellectual capital—human, structural, and relational—and their application in Logistics 4.0, driven by technological innovations such as cyber-physical systems and digital transformation. The methodology employs established bibliometric techniques, including co-occurrence and thematic mapping, to evaluate research questions addressing publication trends, country contributions, source relevance, and author influence. Data from 2001–2024 for Web of Science and Scopus datasets reveal key insights: consistent publication growth, leading contributions by countries like China and the USA, and the emergence of themes such as sustainability, innovation, and digital transformation. Comparative analysis highlights differences in keyword trends and collaborative networks between databases, with Scopus displaying a notable time lag in topic evolution. Findings emphasise the pivotal role of intellectual capital in driving logistics innovation, underscoring its integration with Industry 4.0 technologies. Limitations include potential database biases and a data lag for 2024. This study is a foundational reference for scholars and practitioners who leverage intellectual capital for competitive advantage in the digitised logistics era.

Digital transformation in manufacturing enterprises requires more than technological implementation—it demands a systematic reimagining of business processes, organizational culture, and strategic objectives. A well-structured roadmap begins with clearly defined transformation objectives focused on operational efficiency, cost optimization, product innovation, customer experience, and supply chain resilience. Before implementation, organizations must conduct thorough capability assessments across technology infrastructure, software landscapes, data architecture, digital literacy, leadership alignment, and cultural readiness. Successful transformations follow a phased approach: foundation building establishes connectivity and governance frameworks; process enhancement leverages analytics and digital twins; and intelligent operations deploy AI-driven solutions for predictive maintenance and autonomous scheduling. Measuring transformation success requires comprehensive frameworks spanning operational metrics, financial indicators, and innovation measures to ensure continuous improvement and value creation.

Digital new quality productive forces has emerged as a pivotal force in driving the contemporary economic transformation and upgrading.This study integrates Schumpeter’s theory of innovation with Romer’s theory of endogenous growth to systematically explore the impacts of digital infrastructure development, industrial digital transformation, and the integration of digital and real economies on high-quality economic growth.It highlights the pivotal role of digital new quality productive forces in enhancing total factor productivity(TFP),optimizing industrial structures, and promoting sustainable growth.The findings reveal that digital new quality productive forces not only significantly boosts economic efficiency through enhanced TFP and an innovation-driven approach but also provides essential empirical support for policymakers during the digital transformation process. Moreover,by promoting technological innovation and talent development, it facilitates continuous optimization and upgrading of industrial structures,thereby laying a solid foundation for achieving high-quality and sustainable economic growth.

The article analyzes the impact of financial services digitalization on traditional industries. Innovative tools, including artificial intelligence, algorithmic lending, and digital payment platforms, are examined. Their role in business process transformation, operational efficiency improvement, and the development of new economic models is determined. The influence of digital financial solutions on insurance, healthcare, industry, energy, logistics, and transportation is investigated. The advantages and limitations of digital technology adoption in these industries are identified. The system analysis methods used in the study allow for identifying the interconnections between digital finance and industry-specific innovations. A comparative analysis of case studies on the implementation of digital financial instruments demonstrates that financial services digitalization serves as a catalyst for innovation in the economy. It reduces transaction costs, increases deal transparency, and accelerates the technological development of traditional industries.

Amid the digital transformation of the logistics industry, smart logistics algorithms have emerged as a crucial technology to enhance efficiency and reduce costs. This paper reviews the evolution of traditional logistics technologies and highlights the pivotal roles played by advancements such as the Internet of Things, big data analytics, artificial intelligence, and automation in driving logistics innovation. It delves into the application of intelligent logistics algorithms across areas like path optimization, intelligent scheduling, data mining and prediction, and smart warehousing. To address the challenge of inconsistencies between training and testing objectives, the paper introduces DRL4Route, a deep reinforcement learning-based framework for path optimization, along with the DRL4Route-GAE model. Extensive offline experiments and online deployments validate that the model significantly outperforms existing optimal benchmark methods on real datasets, improving metrics like location deviation squared and top-three location prediction accuracy. These research findings provide essential support for advancing the intelligent development of the logistics industry.

Digital transformation in manufacturing environments has revolutionized traditional operational paradigms through the implementation of advanced enterprise resource planning systems. Manufacturing organizations have achieved substantial improvements in inventory management, production scheduling, and supply chain optimization through systematic integration of digital solutions. The transformation encompasses critical elements including materials management, production planning, warehouse operations, and logistics execution, resulting in enhanced operational efficiency and reduced costs. Change management strategies, including super user programs and gamification techniques, have played pivotal roles in ensuring successful implementation and sustained adoption. The integration of cutting-edge technologies such as blockchain, autonomous guided vehicles, and digital twins has further enhanced manufacturing capabilities. Organizations implementing these solutions have demonstrated marked improvements in supplier relationship management, warehouse efficiency, and production optimization. These implementations have yielded significant financial benefits through inventory reduction, productivity enhancement, and freight optimization, while establishing robust foundations for future innovation and competitive advantage.

The global logistics landscape is experiencing unprecedented transformation, driven by rapid technological advancements and increasing complexity of supply chain networks. Digital twin technology emerges as a revolutionary approach to supply chain management, offering comprehensive solutions for optimization and disruption mitigation. This comprehensive review examines the transformative potential of digital twin technologies in revolutionizing global logistics through systematic analysis of existing literature, implementation frameworks, and case studies. Our investigation reveals that digital twin implementation can potentially reduce operational costs by 30-40%, decrease supply chain disruption times by up to 60%, and improve overall supply chain resilience through advanced predictive modeling. The research synthesizes evidence from multiple domains, demonstrating digital twins' capacity to address critical challenges in contemporary supply chain management. By exploring emerging trends, implementation mechanisms, and critical challenges, this review provides a balanced perspective on the opportunities and limitations of digital twin technologies. The findings suggest that while digital twins present promising solutions for supply chain optimization, successful implementation requires careful consideration of technical infrastructure, data integration strategies, and organizational capabilities.