Hasil untuk "Regulation of industry, trade, and commerce. Occupational law"

Mojdeh Morshedi, Vincent Hargaden, Nikolaos Papakostas et al.

<i>Background:</i> Digital technologies are increasingly integrated into circular supply chains (CSCs) to enhance resource efficiency and extend product lifecycles. However, the practical adoption of intelligent circular supply chains (iCSCs) remains underexplored. <i>Methods:</i> This study provides a comprehensive review of how digital technologies enable circular practices across industries. It systematically reviews 95 peer-reviewed articles from WoS and Scopus, identifying 107 real-world iCSC cases. The cases are categorized by (1) digital enablers including AI, Big Data, Blockchain, IoT, Digital Twin, Additive Manufacturing, Cloud Platforms, and Cyber-Physical Systems; (2) alignment with Circular Economy (CE); (3) sector-specific circular practices; and (4) mapping implementations to the EU Circular Economy Action Plan (CEAP). This study develops a conceptual model illustrating how digital technologies support data-driven decision-making, automation, and circular transitions. <i>Results:</i> The analysis shows IoT, Blockchain, and AI as the most frequently applied technologies, facilitating collaboration, traceability, sustainability, and cost efficiency. “Reduce” and “Recycle” dominate among CE strategies, while circular transition pathways such as sustainable design, waste prevention, and digital platforms link policy to practice. <i>Conclusions:</i> By integrating systematic evidence with a holistic framework, this work provides actionable insights, identifies key implementation gaps, and lays a foundation for advancing iCSCs in research and practice.

Shams El-Adawy, A. R. Piña, Benjamin M. Zwickl et al.

This report builds upon the Categorization of Roles in the Quantum Industry report by providing detailed profiles for 29 distinct roles across the quantum workforce. While the earlier report established a framework of four major role categories (hardware, software, bridging, and public facing and business) and their subcategories, the current report expands on this structural framework by characterizing what professionals in each role actually do, particularly by identifying the tasks, knowledge, skills, abilities (KSAs), and experience typically required for each role. Each role profile follows a standardized structure guided by the Occupational Information Network (O*NET) framework. By presenting a fine-grained view of day-to-day work and qualification expectations, this report serves as a practical resource for educators, students, industry professionals, and policymakers aiming to understand, educate, and support the evolving quantum workforce.

Alfonso Buteler

El artículo examina la influencia de las nuevas tecnologías en los procesos de innovación administrativa dentro del ámbito público, desde la óptica del nuevo institucionalismo. Se argumenta que la incorporación de tecnologías no solo transforma prácticas y rutinas organizacionales, sino que también interactúa con estructuras institucionales, normas y valores preexistentes. A través de una revisión conceptual y teórica, se muestra cómo las innovaciones tecnológicas pueden tanto reforzar como desafiar las instituciones establecidas, dependiendo del grado de flexibilidad del entorno institucional y de la capacidad adaptativa de las organizaciones. Asimismo, se destaca el papel de los actores, el aprendizaje organizacional y los marcos normativos en la configuración del cambio institucional impulsado por la tecnología en Argentina.

Grzegorz Dobrowolski

Zasada udostępniania lasów jest szczególną regulacją prawa polskiego, która pozwala każdemu na wstęp do lasu i zbieranie płodów runa leśnego. Rozwiązanie to trzeba ocenić pozytywnie. Stanowi ono znaczącą wartość w zakresie udostępniania zasobów środowiska. Wiele obowiązujących rozwiązań wymaga jednak szybkich i głębokich zmian prawa. Przepisy te bowiem pochodzą z czasów poprzedniego systemu politycznego i nie uwzględniają w należyty sposób prawa własności. Konieczne jest również wzmocnienie odpowiednich procedur.

Gustavo Ferreira de Souza Dutra, Emerson Gabardo

O trabalho objetiva analisar a figura dos smart contracts na perspectiva do princípio da obrigatoriedade dos contratos, de maneira que possa ser determinada uma potencial ressignificação do “pacta sunt servanda” diante deles. Assim, busca conceituar e categorizar a blockchain e os contratos inteligentes para um exame de seus efeitos diante do Direito e o modelo do contrato tradicional. Por conseguinte, é realizada uma breve contextualização histórica da força obrigatória dos contratos, apontando suas concepções na história, analisando-o no contexto do meio digital. Considerando-se essa análise, são sistematizadas suas aplicabilidades em nível global e, posteriormente, na realidade brasileira – de modo a apresentar as possíveis vantagens e desvantagens do instituto. Adota-se na pesquisa a metodologia referencial bibliográfica, utilizando artigos, livros e obras que se reportam ao tema, assim como a legislação brasileira. Diante da pesquisa, conclui-se que o smart contract é uma opção com capacidade de reduzir os custos de transação e alguns riscos inerentes às operações. No entanto, devido às limitações da lógica de programação, seria uma opção viável para contratos mais simples e nichos específicos. Ademais, pode ser vantajoso aos entes públicos, no âmbito de sua própria rede Blockchain e, ainda, em face à possível utilização da moeda digital.

Maciuk Kamil, Santos Celso Augusto Guimarães, Kulesza Lukasz et al.

The air pollution of our planet is rising, and the contribution of road transport to global pollution has a serious impact on this phenomenon. Previous papers have analysed and recommended measures to reduce road transport’s negative environmental impact and carbon footprint. However, some restrictions are impossible (or very costly) to meet, even in developed countries. Unfortunately, presenting the impact of transport on air pollution levels as a whole can only give a general picture. This paper provides a more detailed analysis and attempts to assess the impact of one of the most important elements shaping modern transport, that is, vehicle engine types. Thus, the main objective of the study is to analyse and evaluate the different types of engines in vehicles from the point of view of technical, environmental, and economic aspects in European countries and to verify whether Europe is ready to implement the European Green Deal. The results indicate significant technological developments must occur in electric vehicles to become environmentally better than combustion engine-based cars. Additionally, in the case of some developing countries, owning a means of transport is still perceived as a symbol of a certain status, which is why it is still an important material asset. Thus, in rich countries, material status and environmental awareness (e.g. choice of public transport) will help to achieve climate neutrality, while poorer countries (even developed ones) may have severe problems in meeting EU requirements. Overall, while answering some questions, this article also poses new ones. Decision-makers often face challenging aspects. This article is intended to give them a basic knowledge to pursue an environmental policy that is viable and feasible for all countries.

Leonel J. R. Nunes

<i>Background</i>: This study explores the use of Mixed-Integer Linear Programming (MILP) models to optimize the collection and transportation of vineyard pruning biomass, a crucial resource for sustainable energy and material production. Efficient biomass logistics play a key role in supporting circular bioeconomy principles by improving resource utilization and reducing operational costs. <i>Methods</i>: Two optimization approaches are evaluated: a base MILP model designed for scenarios with single processing points and an advanced model that incorporates intermediate processing steps to enhance logistical efficiency. The models were tested using synthetic datasets simulating vineyard regions to assess their performance. <i>Results</i>: The models demonstrated significant improvements, achieving cost reductions of up to 30% while enhancing operational efficiency and resource utilization. The study highlights the scalability and real-world applicability of the proposed models. <i>Conclusions</i>: The findings underscore the potential of MILP models in optimizing biomass supply chains and advancing circular bioeconomy goals. However, key limitations, such as computational complexity and adaptability to dynamic environments, are noted. Future research should focus on real-time data integration, dynamic updates, and multi-objective optimization to improve model robustness and applicability across diverse supply chain scenarios.

Mohammad Akefi Ghaziani , Moosa Akefi Ghaziani, Vahid Akefi Ghaziani

Today, the development of renewable energy is generally admitted as a solution to tackle global warming and climate change. However, without attracting substantial foreign investments, it will be nearly impossible to develop renewable energies, particularly in developing countries that do not have the required financial resources and technologies. Unsurprisingly, the promotion of foreign investments in all economic sectors is influenced by International Investment Agreements (IIAs). These instruments contain various substantive and procedural regulations that are individually and collectively responsible for protecting and promoting foreign investments. Among them is the Most Favoured Nation Treatment (MFN), a fundamental principle of international trade law. However, the exact status and efficacy of MFN in IIAs have been a controversial issue so far. Therefore, it is essential to analyse this standard and its possible contribution to promoting foreign investments in renewables. Drawing on qualitative research, this article attempts to answer the question, ‘What is the importance of MFN clauses for the promotion of foreign investments in the renewable energy sector, and how can their efficacy be enhanced?’. Since MFN has a multilateralising effect on the obligations provided in other IIAs signed by the host State, in the absence of provisions to the contrary, it may equip the foreign investors in the renewable energy sector with a broader set of protections and perhaps incentive provisions. However, many IIAs and investor-state tribunals have intermittently overlooked the significance of this standard.

Zijie Pan, Stepan Gordeev, Jiahui Zhao et al.

This paper presents a novel methodology for predicting international bilateral trade flows, emphasizing the growing importance of Preferential Trade Agreements (PTAs) in the global trade landscape. Acknowledging the limitations of traditional models like the Gravity Model of Trade, this study introduces a two-stage approach combining explainable machine learning and factorization models. The first stage employs SHAP Explainer for effective variable selection, identifying key provisions in PTAs, while the second stage utilizes Factorization Machine models to analyze the pairwise interaction effects of these provisions on trade flows. By analyzing comprehensive datasets, the paper demonstrates the efficacy of this approach. The findings not only enhance the predictive accuracy of trade flow models but also offer deeper insights into the complex dynamics of international trade, influenced by specific bilateral trade provisions.

Parisa Elahidoost, Daniel Mendez, Michael Unterkalmsteiner et al.

[Context and motivation]: Understanding and interpreting regulatory norms and inferring software requirements from them is a critical step towards regulatory compliance, a matter of significant importance in various industrial sectors. [Question/ problem]: However, interpreting regulations still largely depends on individual legal expertise and experience within the respective domain, with little to no systematic methodologies and supportive tools to guide this practice. In fact, research in this area is too often detached from practitioners' experiences, rendering the proposed solutions not transferable to industrial practice. As we argue, one reason is that we still lack a profound understanding of industry- and domain-specific practices and challenges. [Principal ideas/ results]: We aim to close this gap and provide such an investigation at the example of the banking and insurance domain. We conduct an industrial multi-case study as part of a long-term academia-industry collaboration with a medium-sized software development and renovation company. We explore contemporary industrial practices and challenges when inferring requirements from regulations to support more problem-driven research. Our study investigates the complexities of requirement engineering in regulatory contexts, pinpointing various issues and discussing them in detail. We highlight the gathered insights and the practical challenges encountered and suggest avenues for future research. [Contribution]: Our contribution is a comprehensive case study focused on the FinTech domain, offering a detailed understanding of the specific needs within this sector. We have identified key practices for managing regulatory requirements in software development, and have pinpointed several challenges. We conclude by offering a set of recommendations for future problem-driven research directions.

Ritwik Raj Saxena

Concerns associated with occupational health and safety (OHS) remain critical and often under-addressed aspects of workforce management. This is especially true for high-risk industries such as manufacturing, construction, and mining. Such industries dominate the economy of India which is a developing country with a vast informal sector. Regulatory frameworks have been strengthened over the decades, particularly with regards to bringing the unorganized sector within the purview of law. Traditional approaches to OHS have largely been reactive and rely on post-incident analysis (which is curative) rather than preventive intervention. This paper portrays the immense potential of predictive analytics in rejuvenating OHS practices in India. Intelligent predictive analytics is driven by approaches like machine learning and statistical modeling. Its data-driven nature serves to overcome the limitations of conventional OHS methods. Predictive analytics approaches to OHS in India draw on global case studies and generative applications of predictive analytics in OHS which are customized to Indian industrial contexts. This paper attempts to explore in what ways it exhibits the potential to address challenges such as fragmented data ecosystems, resource constraints, and the variability of workplace hazards. The paper presents actionable policy recommendations to create conditions conducive to the widespread implementation of predictive analytics, which must be advocated as a cornerstone of OHS strategy. In doing so, the paper aims to spark a collaborational dialogue among policymakers, industry leaders, and technologists. It urges a shift towards intelligent practices to safeguard the well-being of India's workforce.

Paulo Carvão

This article addresses the societal costs associated with the lack of regulation in Artificial Intelligence and proposes a framework combining innovation and regulation. Over fifty years of AI research, catalyzed by declining computing costs and the proliferation of data, have propelled AI into the mainstream, promising significant economic benefits. Yet, this rapid adoption underscores risks, from bias amplification and labor disruptions to existential threats posed by autonomous systems. The discourse is polarized between accelerationists, advocating for unfettered technological advancement, and doomers, calling for a slowdown to prevent dystopian outcomes. This piece advocates for a middle path that leverages technical innovation and smart regulation to maximize the benefits of AI while minimizing its risks, offering a pragmatic approach to the responsible progress of AI technology. Technical invention beyond the most capable foundation models is needed to contain catastrophic risks. Regulation is required to create incentives for this research while addressing current issues.

Luay Jum’a, Marwan Mansour

<i>Background:</i> This paper revolves around a meticulous exploration aimed at discerning the impact of total quality management (TQM) and service quality (SQ) practices upon the financial performance (FP) of firms within the container shipping industry. Our pursuit extends further, delving into the intricacies of SQ as a potential mediating factor in the TQM–FP relationship. This distinctive study investigated six TQM practices in conjunction with five SQ factors, analyzing their impact on firm FP. <i>Methods:</i> This study used a quantitative research approach. Data were collected through a structured questionnaire from logistics specialists and experts in the shipping field. <i>Results:</i> The findings were interesting and showed that two TQM practices—managerial leadership and employee involvement—have a significant positive effect on SQ levels, and one SQ dimension, namely responsiveness, has the biggest and most significant effect on the FP of container shipping companies. Furthermore, SQ mediates the relationship between TQM and FP. <i>Conclusions:</i> This study provides a theoretical contribution by developing a conceptual model that elucidates the correlation between TQM practices and the degree of SQ on the FP of container shipping firms. Moreover, this study provides managers with a tool for identifying, prioritizing, and improving key TQM and SQ practices that contribute significantly to financial success.

Rahmattolla Janmohammadi, Mojtaba Asgharian, nima nasrollahi

In some cases, to discover the facts, foreign arbitral tribunals need to obtain evidence from third parties located outside the arbitral tribunal's seat and in another country's territory. Sometimes due to the lack of general jurisdiction and authority, they have to use the judicial assistance of the national courts of foreign countries. In many advanced legal systems, including the American legal system, this authority is provided for the courts to assist the international arbitral tribunals in providing evidence to foreign arbitral tribunals to obtain evidence, including testimony and submission of documents, judicial assistance and acceptance of representation. The present study aims to answer these questions with a descriptive-analytical method, judicial assistance of national courts in acquiring evidence for foreign arbitration courts and accepting judicial representation based on which legal rules are possible. Moreover, based on international commercial arbitration law, do the national courts of Iran have the possibility of providing judicial assistance and accepting judicial representation in acquiring evidence from arbitration courts whose headquarters are outside the country's territorial territory? Since in most countries, the discourse of arbitration involves two distinct systems consisting of domestic and international arbitration, in this study, only the International Commercial Arbitration Law was approved in 1376, and the international arbitration rules of some countries have been discussed. The provisions of domestic arbitration, except for a cursory glance, are ignored in the second part so that the field of research stays in the international arbitration system

Dursun Balkan, Goknur Arzu Akyuz

<i>Background</i>: The logistics sector is the backbone of today’s global trade, and is vital for the continuity of goods and services. The sector is gaining increased importance as logistics operate under the extreme conditions the world is passing through (COVID-19, earthquakes, wars). <i>Methods</i>: A comparative study is offered for Turkey and the EU27 and EA19 countries utilizing Eurostat database time series data for logistics turnover, based on regression analysis with and without COVID-19-affected data. General trends are identified regarding the logistics turnover and average turnover by different transportation modes in Turkey. Linear, exponential, logarithmic and polynomial regressions are fitted to the dataset to find the best fit. Afterwards, forecasting is performed based on the polynomial equation, which is identified as the best fit. A similar approach is repeated for the EU27 and EA19 countries to put forward the trends and forecasts as well as a detailed comparative discussion among countries. <i>Results</i>: Our study reveals the dramatic effect of COVID-19 on the turnover of different logistics modes and the radical shift that Turkey experienced from land transportation towards air transportation. <i>Conclusions</i>: Our study provides forecasting and a comparative picture for the logistics sector, shows the growth trends with respect to different transportation modes and reveals the effects of the pandemic on the logistics sector for Turkey and the EU27 and EA19 countries.

Mehrnaz Bathaee, Hamed Nozari, Agnieszka Szmelter-Jarosz

<i>Background:</i> In this paper, a new closed-loop supply chain (CLSC) network model, including economic, social and environmental goals, is designed. This paper’s primary purpose is to meet customers’ uncertain demands in different scenarios where the new robust-fuzzy-probabilistic method has been used to estimate the exact demand. Furthermore, strategic and tactical decisions, such as vehicle routing, facility location and optimal flow allocation in the CLSC network, are considered, and features such as queuing system in product distribution and time window in product delivery are considered. <i>Methods</i>: To solve the problem, NSGA II and MOPSO have been used. <i>Results</i>: The results of solving numerical examples in larger sizes show that as the environmental effects decrease and the social effects increase, the design costs of the total supply chain network (SCN) increase. Moreover, the NSGA II is more efficient than the MOPSO in problem-solving and achieving comparison indicators. <i>Conclusions</i>: The results of sensitivity analysis show that with increasing network uncertainty rate, the total costs of the SCN, the amount of greenhouse gas emissions and the maximum vehicle traffic time increase.

Xiao-Yu Cao, Bing-Hong Li, Yang Wang et al.

E-commerce, a type of trading that occurs at a high frequency on the Internet, requires guaranteeing the integrity, authentication and non-repudiation of messages through long distance. As current e-commerce schemes are vulnerable to computational attacks, quantum cryptography, ensuring information-theoretic security against adversary's repudiation and forgery, provides a solution to this problem. However, quantum solutions generally have much lower performance compared to classical ones. Besides, when considering imperfect devices, the performance of quantum schemes exhibits a significant decline. Here, for the first time, we demonstrate the whole e-commerce process of involving the signing of a contract and payment among three parties by proposing a quantum e-commerce scheme, which shows resistance of attacks from imperfect devices. Results show that with a maximum attenuation of 25 dB among participants, our scheme can achieve a signature rate of 0.82 times per second for an agreement size of approximately 0.428 megabit. This proposed scheme presents a promising solution for providing information-theoretic security for e-commerce.

Alexander Iksanov, Valeriya Kotelnikova

In the Karlin infinite occupancy scheme, balls are thrown independently into an infinite array of boxes $1$, $2,\ldots$, with probability $p_k$ of hitting the box $k$. For $j,n\in\mathbb{N}$, denote by $\mathcal{K}^*_j(n)$ the number of boxes containing exactly $j$ balls provided that $n$ balls have been thrown. We call $\textit{small counts}$ the variables $\mathcal{K}^*_j(n)$, with $j$ fixed. Our main result is a law of the iterated logarithm (LIL) for the small counts as the number of balls thrown becomes large. Its proof exploits a Poissonization technique and is based on a new LIL for infinite sums of independent indicators $\sum_{k\geq 1}\Bbb{1}_{A_k(t)}$ as $t\to\infty$, where the family of events $(A_k(t))_{t\geq 0}$ is not necessarily monotone in $t$. The latter LIL is an extension of a LIL obtained recently by Buraczewski, Iksanov and Kotelnikova (2023+) in the situation that $(A_k(t))_{t\geq 0}$ forms a nondecreasing family of events.

Hana Trollman, Guillermo Garcia-Garcia, Sandeep Jagtap et al.

<i>Background</i>: This research aims to identify how blockchain technology could support the ecological embeddedness of the coffee supply chain. Ecological embeddedness is a subset of the circular economy (CE) that demands legitimacy through design changes to product, production and/or packaging for benefits to economic actors and the environment. This is in contrast with legitimacy as a public relations exercise. Blockchain is a digital transformation technology that is not fully conceptualized with respect to supply chain implementation and the related strategy formulation, particularly in the context of sustainability. Furthermore, the integration of consumers into the CE remains not well understood or researched, with the main focus of CE being the cycling of resources. <i>Methods</i>: This research employs a qualitative case study methodology of the first coffee business in the USA to use blockchain technology as an exemplar. Gap analysis is then applied to identify how blockchain could be used to advance from the current state to a more sustainable one. <i>Results</i>: Findings indicate that the implementation of blockchain is not ecologically embedded in the example studied. <i>Conclusions</i>: The extension of blockchain technology to consider the by-products of production and valorizable waste throughout the supply chain as assets would support ecologically embedded CE for coffee.

Chakat Chueadee, Preecha Kriengkorakot, Nuchsara Kriengkorakot

<i>Background:</i> This research aimed to establish a network linked to generation, for the transport route of tapioca starch products to a land port, serving as the logistics hub of Thailand’s Nakhon Ratchasima province. <i>Methods</i>: The adaptive large neighborhood search (ALNS) algorithm, combined with the differential evolution (DE) approach, was used for the problem analysis, and this method was named modified differential evolution adaptive large neighborhood search (MDEALNS) is a new method that includes six steps, which are (1) initialization, (2) mutation, (3) recombination, (4) updating with ALNS, (5) Selection and (6) repeat the (2) to (5) steps until the termination condition is met. The MDEALNS algorithm designed a logistics network linking the optimal route and a suitable open/close factory allocation with the lowest transport cost for tapioca starch. The operating supply chain of tapioca starch manufacturing in the case study. The proposed methods have been tested with datasets of the three groups of test instances and the case study consisted of 404 farms, 33 factories, and 1 land port. <i>Results:</i> The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS. <i>Conclusions:</i> The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS.