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

Pyeonghwa Kim, Taylor Lewandowski, Michael Dunn et al.

We focus on occupational diversity in platform-mediated work to advance conceptual and empirical insight into the occupationally embedded nature of platform labor. We pursue this focus in response to a prevailing tendency to treat platform workers as a homogeneous group, overlooking the unique demands, constraints, and practices rooted in specific professions. Such generalizations hinder both understanding of platform work and the development of sociotechnical systems that support differentiated occupational realities. To address this gap, we present a longitudinal analysis of 108 online freelancers spanning five occupational categories. We show that occupational context structures workers' capacity to interpret and navigate platformic management, shaping distinct experiences across four dimensions of platform work: self-presentation, flexibility, skilling, and platform work sustainability. To articulate how digital labor platforms' managerial control interacts with occupational embeddedness, we introduce the concept of platformic occupational stratification and discuss four mechanisms that explain its logic and implications for platform-mediated work. These insights contribute to CSCW by informing occupation-sensitive research and design approaches that directly engage with the specific opportunities and challenges rooted in workers' situated occupational agency in platform-mediated work.

Ezieddin Elmahjub, Junaid Qadir, Abdullah Mushtaq et al.

As millions of Muslims turn to LLMs like GPT, Claude, and DeepSeek for religious guidance, a critical question arises: Can these AI systems reliably reason about Islamic law? We introduce IslamicLegalBench, the first benchmark evaluating LLMs across seven schools of Islamic jurisprudence, with 718 instances covering 13 tasks of varying complexity. Evaluation of nine state-of-the-art models reveals major limitations: the best model achieves only 68% correctness with 21% hallucination, while several models fall below 35% correctness and exceed 55% hallucination. Few-shot prompting provides minimal gains, improving only 2 of 9 models by >1%. Moderate-complexity tasks requiring exact knowledge show the highest errors, whereas high-complexity tasks display apparent competence through semantic reasoning. False premise detection indicates risky sycophancy, with 6 of 9 models accepting misleading assumptions at rates above 40%. These results highlight that prompt-based methods cannot compensate for missing foundational knowledge. IslamicLegalBench offers the first systematic framework to evaluate Islamic legal reasoning in AI, revealing critical gaps in tools increasingly relied on for spiritual guidance.

Akram Rostamkhani, Milad Alizadeh Galdiani, Mohammadreza Rezazadeh et al.

The decision-making process of customers choosing a product or service is complex and dependent on many factors. These factors do not remain unchanged, and customers may change their behavior over time. This is important in markets with alternative products or services, and manufacturers and service providers should effectively monitor customers’ behavior and preferences so that they could be successful in the market. In the freight transportation industry, customers can choose between freight transportation modes. This study sought to identify factors influencing customers’ choices of transportation modes and contribute to transportation managers. Influential factors, e.g., time, safety, and distance, were extracted from the literature. The insignificant factors were excluded through expert views based on the Delphi method, prioritizing the remaining factors through the decision-making and trial evaluation laboratory (DEMATEL)-based analytic network process (DANP) and constructing the DEMATEL matrix of the criteria. It was found that cost, time, speed, safety, and health are the most important determinants of freight customers’ choices of land transportation modes.

Molk Oukili Garti, Jabir Arif, Fouad Jawab et al.

<i>Background</i>: The objective of this qualitative research was to explore the impact of certain predefined factors on the sustainability of supply chains in Industry 5.0. The sustainability of supply chains was assessed by considering six factors from the existing literature: circular logistics, Industry 5.0 technologies, intellectual level and learning, logistics innovation, sustainable supply chain practices, and the managerial strategy of the company. <i>Methods</i>: Semi-structured interviews were conducted based on an interview guide with 14 participants who serve as managers and executives in supply chain management in Morocco. The interviews were transcribed, followed by lexical and thematic analysis using QSR NVivo 15 software. <i>Results</i>: The results showed that all the factors studied play a major role in achieving sustainable supply chain management. The testimonies of all participants highlighted the crucial role that Industry 5.0 technologies play in achieving the sustainability of supply chains, while combining them with the other factors studied. Consequently, these results made it possible to validate and confirm the six factors previously identified from the existing literature, while retaining them for potential future quantitative studies. <i>Conclusions</i>: To meet the dimensions of sustainability, it is recommended to focus on the most impactful factors in maintaining a sustainable supply chain and on all the possible interactions between these factors. Indeed, this study represents, on the one hand, an invitation for supply chain managers to pay greater attention to factors related to sustainability, and on the other hand, an initial pathway for future research that may subsequently highlight the interactions between factors leading to sustainability. This could help propose applicable models for supply chain managers, enabling them to adopt more effective strategies and identify the most feasible combinations of factors to achieve sustainable logistics.

Anna Wilk

Artykuł porusza tematykę podmiotowości prawnej elementów środowiska, takich jak rzeki czy lasy. Koncepcję uznania ich za podmioty prawa lansuje tzw. ruch praw natury. Rozwiązanie to oznaczałoby, że chroniony element przyrody byłby traktowany jak podmiot mający własne, niezależne od człowieka prawo do istnienia oraz „przedstawiciela ustawowego”, np. komitet naukowy, a jego zasobom przysługiwałaby ochrona przed nadmierną eksploatacją. Autorka rozważa więc, jakich zmian w polskim systemie prawnym wymagałoby przyznanie tworom natury podmiotowości prawnej i czy byłoby to celowe.

Rosa Hilda Félix-Jácquez, Óscar Hernández-Uribe, Leonor Adriana Cárdenas-Robledo et al.

<i>Background</i>: Remanufacturing products for sustainability involves layout and production planning, tools and equipment, material arrangement and handling, inventory management, technology integration, and more. This study presents an empirical vision through a discrete event simulation (DES) model integrating lean manufacturing (LM) and supply chain (SC) strategies with industry 4.0 (I4.0) technologies, applied to a case in a railway company. <i>Methods</i>: The work presents scenarios following a methodology with an incremental approach to implement strategies of lean manufacturing (LM) and supply chain (SC) in the context of I4.0 and their effects represented in DES models with applicability in remanufacturing and production line management. Five simulation scenarios were analyzed according to strategies layered incrementally. <i>Results</i>: Behaviors and outcomes were compared across the scenarios considering the remanufactured engines, percentage of process time, human labor occupation, and the statistical analysis of the process capability. Scenario five achieved the objective of remanufacturing 40 engines in one year with a cycle time of 214.45 h. <i>Conclusions</i>: The purpose was to design an engine remanufacturing line incorporating LM and SC strategies via a DES model, highlighting the importance of their gradual adoption toward I4.0 implementation. The integration of previous strategies improves flexibility and productivity in manufacturing processes.

Elisa Vieira, Larissa Tomaz, José Leitão et al.

<i>Background</i>: Due to the highly competitive nature of the retail sector, companies need to improve their operational efficiency. This study focuses on the application of the concepts of Lean production in the process of replenishing products on the shelves of the shops of one of the largest food retail chains in Portugal. <i>Methods</i>: This study aims to apply a transition from a “push” to a “pull” approach, based on real-time consumption. During a 5-day test, the impacts of implementing Lean principles and ergonomic trolleys in the process were investigated. <i>Results</i>: The test led to improved efficiency in product replenishment by eliminating pallets and reducing unfavourable product handling from the initial process. The implementation of a replenishment system in this manner allowed a reduced labour requirements from 28.4 to 19.2 man-hours per day and, the elimination of unnecessary handling and increase of product availability were reflected in gains on operational time and in replenishment time. <i>Conclusions</i>: This study provides empirical evidence for the effectiveness of Lean pull systems in retail replenishment, demonstrating a 32% reduction in labour hours.

Rojin Vafaei, MohammadReza Gholamian, Marzieh Marzieh Sedaghat Seyed Abadi

The railway industry in Iran is one of the country's oldest transport sectors. Over recent decades, efforts have been made to improve its infrastructure, such as connecting major freight hubs to the national rail network, shifting freight transport from road to rail. However, despite its key role in the national logistics system, limited progress has been achieved in modernizing the rolling stock and implementing precise and mechanized loading/unloading operations. This has resulted in resource inefficiencies, loss of freight, and declining confidence among cargo owners in the railway system. Additionally, from an environmental standpoint, inadequate waste and wastewater treatment systems have raised concerns about long-term ecological impacts. Circular economy principles seek to balance economic growth with environmental sustainability by reintegrating recycled materials into production cycles and minimizing ecological degradation. In this study, a network Data Envelopment Analysis (NDEA) model incorporating a centralized structure and cooperative game theory is developed to assess the circular economy performance of railway maintenance companies. The proposed model comprises two interconnected subsystems: the production subsystem, which includes rolling stock washing and repair, and the treatment subsystem, responsible for processing the wastewater and industrial waste produced by the first subsystem. By applying a cooperative game approach, the model enables efficiency evaluation of both subsystems under a unified framework. The proposed methodology is applied to the performance evaluation of Iranian railway maintenance companies during the period 2020–2024 (1399–1403 in the Iranian calendar). The results help identify efficient and inefficient units, offering strategic insights to enhance overall system performance toward best-practice benchmarks.

Josip Tomo Licardo, Nikola Tankovic

Large Language Models (LLMs) offer state-of-the-art performance in natural language understanding and generation tasks. However, the deployment of leading commercial models for specialized tasks, such as e-commerce, is often hindered by high computational costs, latency, and operational expenses. This paper investigates the viability of smaller, open-weight models as a resource-efficient alternative. We present a methodology for optimizing a one-billion-parameter Llama 3.2 model for multilingual e-commerce intent recognition. The model was fine-tuned using Quantized Low-Rank Adaptation (QLoRA) on a synthetically generated dataset designed to mimic real-world user queries. Subsequently, we applied post-training quantization techniques, creating GPU-optimized (GPTQ) and CPU-optimized (GGUF) versions. Our results demonstrate that the specialized 1B model achieves 99% accuracy, matching the performance of the significantly larger GPT-4.1 model. A detailed performance analysis revealed critical, hardware-dependent trade-offs: while 4-bit GPTQ reduced VRAM usage by 41%, it paradoxically slowed inference by 82% on an older GPU architecture (NVIDIA T4) due to dequantization overhead. Conversely, GGUF formats on a CPU achieved a speedup of up to 18x in inference throughput and a reduction of over 90% in RAM consumption compared to the FP16 baseline. We conclude that small, properly optimized open-weight models are not just a viable but a more suitable alternative for domain-specific applications, offering state-of-the-art accuracy at a fraction of the computational cost.

Olga Kononykhina, Frauke Kreuter, Malte Schierholz

Occupational data play a vital role in research, official statistics, and policymaking, yet their collection and accurate classification remain a challenge. This study investigates the effects of occupational question wording on data variability and the performance of automatic coding tools. We conducted and replicated a split-ballot survey experiment in Germany using two common occupational question formats: one focusing on "job title" (Berufsbezeichnung) and another on "berufliche Tätigkeit" (loosely translated as occupation or occupational task). Our analysis reveals that automatic coding tools, such as CASCOT and OccuCoDe, exhibit sensitivity to the form and origin of the data. Specifically, these tools were more efficient when coding responses to the job title question format than the occupational task format, suggesting a potential way to improve the respective questions for many German surveys. In a subsequent "detailed tasks and duties" question, providing a guiding example prompted respondents to give longer answers without broadening the range of unique words they used. These findings highlight the importance of harmonising survey questions and and ensuring that automatic coding tools are robust to differences in question wording. Further research is needed to optimise question design and coding tools for greater accuracy and applicability in occupational data collection.

Sudhanshu Garg, Andrew Wang, Chaitanya Kulkarni et al.

We present the development and optimization of PayPal's Commerce Agent, powered by NEMO-4-PAYPAL, a multi-agent system designed to revolutionize agentic commerce on the PayPal platform. Through our strategic partnership with NVIDIA, we leveraged the NeMo Framework for LLM model fine-tuning to enhance agent performance. Specifically, we optimized the Search and Discovery agent by replacing our base model with a fine-tuned Nemotron small language model (SLM). We conducted comprehensive experiments using the llama3.1-nemotron-nano-8B-v1 architecture, training LoRA-based models through systematic hyperparameter sweeps across learning rates, optimizers (Adam, AdamW), cosine annealing schedules, and LoRA ranks. Our contributions include: (1) the first application of NVIDIA's NeMo Framework to commerce-specific agent optimization, (2) LLM powered fine-tuning strategy for retrieval-focused commerce tasks, (3) demonstration of significant improvements in latency and cost while maintaining agent quality, and (4) a scalable framework for multi-agent system optimization in production e-commerce environments. Our results demonstrate that the fine-tuned Nemotron SLM effectively resolves the key performance issue in the retrieval component, which represents over 50\% of total agent response time, while maintaining or enhancing overall system performance.

Mirre J P Simons, Marc Tatar

The evolutionary biology of aging is fundamental to understanding the mechanisms of aging and how to develop anti-aging treatments. Thus far most evolutionary theory concerns the genetics of aging with limited physiological integration. Here we present an intuitive evolutionary framework built on how physiology is regulated and how this regulation itself is then predicted to age. Life has evolved to secure reproduction and avoid system failure in early life, and it is the physiological regulation that evolves in response to those early life selection pressures that leads to the emergence of aging. Importantly, asymmetrical regulation of physiology will evolve as the Darwinian fitness costs of loss of regulation will not be symmetrical. When asymmetrical regulatory systems break during aging, they cause physiological function to drift towards the physiological range where costs of dysregulation are lowest, rendering aging directional. Our model explains many puzzling aspects of the biology of aging. These include why aging appears (but is not) programmed, why aging is gradual yet heterogeneous, why cellular and hormonal signaling are closely related to aging, the compensation law of mortality, why trade-offs between reproduction and aging remain elusive, why longer-lived organisms show more signs of aging during their natural lifespans, and why longer-lived organisms can be less responsive to treatments of aging that work well in short-lived organisms. We provide predictions of our theory that are empirically testable. By incorporating physiological regulation into evolutionary models of aging, we provide a novel perspective to guide empirical research in this still growing field.

Mohammad Hasan Taj Langerudi, Farzin Dehdar

Cryptocurrencies, as one of the most essential products of blockchain technology, have unique and sometimes new features such as distributedness, asymmetric cryptography, and consensus mechanism, and they have a specific mechanism. Despite the widespread acceptance of crypto-currencies in our country, there are significant challenges in advancing their use. According to our country's legal system based on jurisprudence, these challenges can be summarised in the two axes of "not being property" and "being unknown" of cryptocurrencies. In addition, the use of cryptocurrencies inside the country is also prohibited by the approval of the Council of Ministers. To prove that cryptocurrencies are property, on the one hand, the definitions of property from a jurisprudential and legal point of view were discussed. On the other hand, the nature of cryptocurrencies was examined from the point of view of various legal documents and conventions. It was explained that cryptocurrencies can be considered property from a jurisprudential and legal point of view. On the other hand, while explaining the concept of white papers, the criticism that the mechanism governing cryptocurrencies is unknown has been answered. Finally, citing legal evidence, it has been demonstrated that the decision of the Council of Ministers is not strong enough to invalidate the contract in which the currencies were used.

Alessia Giulianetti, Marco Gotelli, Anna Sciomachen

<i>Background</i>: We focus on the inland rail forwarding of import containers from a marine terminal. Specifically, we present a discrete-event simulation study related to container-loading operations by train, evaluating different train departure policies within a predetermined schedule based on the capacity of the rail network. The aim is threefold: manage more containers shipped by train, improve terminal operational efficiency, and increase the rail share. <i>Methods</i>: The proposed procedures take full advantage of the digitization and visualization of data currently present in the terminal with the aim of improving the performance indices of interest, thereby increasing the terminal‘s operational efficiency. We evaluate the medium- and long-term impact of alternative strategies on container dwell times and the possible increase in the number of containers shipped by train. <i>Results</i>: The computational tests are performed with data from a terminal in the port of Genoa (Italy). The results show the relationships between train departure management policies and train departure distributions. The number of departing trains, cancelled trains, and trains departing with load percentages below 70% is studied. Average loads per train and estimated delays are also analyzed. <i>Conclusions:</i> It is noted that the results, which can be obtained with data from any terminal, are of great importance for optimizing operational management, offering practical solutions to improve efficiency and reduce container downtime.

Jun Cui

This study investigates the influence of generative artificial intelligence (AI) on the brand construction of cross-border e-commerce companies in the manufacturing industry in Tianjin, China. We examine the direct effects of generative AI on productivity, the mediating role of productivity in the relationship between generative AI and brand building, and the moderating influence of cross-border e-commerce strategies by developing and testing a comprehensive model. Based on data collected from 210 manufacturing firms in Chinese Tianjin, the results show that generative AI significantly increases productivity, which positively affects branding. Moreover, cross-border e-commerce strategies were found to moderate the impact of generative AI on branding, underscoring the importance of these strategies for using AI technologies to compete successfully in the global marketplace. This study provides valuable theory, empiricism and practical contributions to understanding the role AI plays in manufacturing and electronic commerce. Besides, this study tests several hypotheses to quantify these impacts using a structured model that consists of independent, dependent, mediating and moderating variables. Information is collected through a comprehensive survey of manufacturers in Chinese Tianjin and analyzed to test our proposed model. This study was analyzed and summarized using quantitative analysis, regression and structural equations (PLS-SEM).

Zhiwei Fei, Songyang Zhang, Xiaoyu Shen et al.

While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise required in the legal field. In this paper, we introduce InternLM-Law, a specialized LLM tailored for addressing diverse legal queries related to Chinese laws, spanning from responding to standard legal questions (e.g., legal exercises in textbooks) to analyzing complex real-world legal situations. We meticulously construct a dataset in the Chinese legal domain, encompassing over 1 million queries, and implement a data filtering and processing pipeline to ensure its diversity and quality. Our training approach involves a novel two-stage process: initially fine-tuning LLMs on both legal-specific and general-purpose content to equip the models with broad knowledge, followed by exclusive fine-tuning on high-quality legal data to enhance structured output generation. InternLM-Law achieves the highest average performance on LawBench, outperforming state-of-the-art models, including GPT-4, on 13 out of 20 subtasks. We make InternLM-Law and our dataset publicly available to facilitate future research in applying LLMs within the legal domain.

Lázaro Florido-Benítez

<i>Background:</i> The purpose of this study is to provide an assessment of international airports and airlines, ‘IAAs’, and to organize and classify the literature on air transport to stage the importance of this topic and encourage future research in the projection of the aviation and tourism sectors. <i>Methods:</i> It is a bibliographic study, and this work focuses on IAA documents published in major international journals, conferences, and books from 2000 to 9 June 2021; this topic is scattered across various journals and has secondary data in many disciplines. <i>Results:</i> The findings suggest a new paradigm applied to the IAA topic and are classified in four first-order research streams: airports; airlines; connectivity; and competition. This study identifies new challenges and opportunities for researchers, airport and airline operators, and stakeholders to make better future decisions. <i>Conclusions:</i> There is no agreement on an explicit definition of the IAA concept that captures the true nature of this topic. For this reason, this article is innovative in the new IAA concept and in how it will possibly change the theoretical frameworks in future scientific research in the aviation and tourism sectors. This study has been needed to better understand the effectiveness, projection, and different business strategies to be adopted by researchers and organizations in the aviation and tourism future.

Seyed Mohsen Ghaemfard, Fatemeh Mohseni

Although "Information and Communications Technology" provides numerous and intact opportunities for development, it has some challenges and threats. The law seeks to support opportunities for prevention from and fighting with challenges and threats. Since realising the essence of any concept leads to analysing its legal effects, analysing cyberspace in light of conceptual framework first results in understanding this space and then understanding its legal effects. Considering vast and new loads of information and Communications Technology as the main question, finding the concept of cyberspace as an objective and untouchable space and its legal effects is the subject of this article. This study has been done in a descriptive-analytical way using library and internet sources. The findings of this research indicate that cyberspace law is both different and similar to physical world law. However, the principles and basis of legislation and the tools, conditions, and effects of conducting conduct in cyberspace differ from the physical world.

Zahra Hemmat, Mohammad Mehraeen, Rahmatolloah Fattahi

A constitution is the highest legal document of a country and serves as a guide for the establishment of other laws. The constitution defines the political principles, structure, hierarchy, position, and limits of the political power of a country's government. It determines and guarantees the rights of citizens. This study aimed at topic modeling of Iranian laws. As part of this research, 11760 laws were collected from the Dotic website. Then, topic modeling was conducted on the title and content of the regularizations using LDA. Data analysis with topic modeling led to the identification of 10 topics including Economic, Customs, Housing and Urban Development, Agriculture, Insurance, Legal and judicial, Cultural, Information Technology, Political, and Government. The largest topic, Economic, accounts for 29% of regulations, while the smallest are Political and Government, accounting for 2%. This research utilizes a topic modeling method in exploring law texts and identifying trends in regularizations from 2016-2023. In this study, it was found that regularizations constitute a significant percentage of law, most of which are related to economics and customs. Cultural regularizations have increased in 2023. It can be concluded any law enacted each year can reflect society's conditions and legislators' top concerns.

Hareer Fatima Ahmed, Amin Hosseinian-Far, Rasoul Khandan et al.

<i>Background</i>: Knowledge transfer has been an important aspect in supply chain systems; however, there are many factors that affect the impact of transfer effectiveness. In previous studies, less attention has been given to the process of knowledge transfer and therefore, this paper highlights the significance of the process of knowledge transfer in supply chain processes. Enhanced supply chain networks have better performance when knowledge sharing is present, and it is important to identify and eliminate any supply chain complexity to improve the supply chain processes. <i>Methods</i>: A systematic review on the literature has been conducted to critically identify and evaluate the factors of supply chain complexity which impact knowledge transfer. <i>Findings</i>: The findings highlight the key benefits of effective knowledge transfer in supply chain systems by identifying risks associated with supply chain networks. <i>Conclusion</i>: The balanced power of facilitating knowledge transfer in supply chain processes helps in supply chain partnerships and reduces the supply chain complexity. This paper has both theoretical and practical contributions as it adds to the literature by identifying the factors of supply chain complexity drivers which are impacting the knowledge transfer.