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

Haoyan Lin, Jie Huang

The output regulation problem for unknown linear systems has been studied using state-based and output-based internal model approaches in the special case with no disturbances. This paper further investigates the output regulation problem for unknown linear systems using a data-driven output-based approach via value iteration. For this purpose, we first develop a novel output-feedback control law that does not explicitly rely on the observer gain to solve the output regulation problem. We then show that the data-driven approach for designing an output-feedback control law for the given plant can be reduced to the data-driven design of a state-feedback control law for a well-defined augmented auxiliary system. As a result, we develop a systematic data-driven approach to solve the output regulation problem for unknown linear systems via value iteration. Finally, we establish a relation between the data-driven state-feedback control law and the data-driven output-feedback control law in the LQR sense.

Yue Li, Lei Wang, Kaixuan Wang et al.

The rapid proliferation of autonomous AI agents is driving a shift toward agentic commerce, where agents are expected to autonomously invoke and pay for services. While blockchain-based payments offer a programmable foundation for such interactions, the recently proposed x402 standard fails to enforce end-to-end atomicity across service execution, payment, and result delivery. In this paper, we present A402, a trust-minimized payment architecture that securely binds cryptocurrency payments to service execution. A402 introduces Atomic Service Channels (ASCs), a new channel protocol that integrates service execution into payment channels, enabling real-time, high-frequency micropayments for agentic commerce. Within each ASC, A402 employs an atomic exchange protocol based on TEE-assisted adaptor signatures, ensuring that payments are finalized if and only if the requested service is correctly executed and the corresponding result is delivered. To further ensure privacy, A402 incorporates a TEE-based Liquidity Vault that privately manages the lifecycle of ASCs and aggregates their settlements into a single on-chain transaction, revealing only aggregated balances. We implement A402 and evaluate it against x402 with integrations on both Bitcoin and Ethereum. Our results show that A402 delivers orders-of-magnitude performance and on-chain cost improvements over x402 while providing trust-minimized security guarantees.

Yingrui Fan, Junbo Zhao

Data centers (DCs) are increasingly recognized as flexible loads that can support grid frequency regulation. Yet, most existing methods treat workload scheduling and regulation capacity bidding separately, overlooking how queueing dynamics and spatial-temporal dispatch decisions affect the ability to sustain real-time regulation. As a result, the committed regulation may become infeasible or short-lived. To address this issue, we propose a unified day-ahead co-optimization framework that jointly decides workload distribution across geographically distributed DCs and regulation capacity commitments. We construct a space-time network model to capture workload migration costs, latency requirements, and heterogeneous resource limits. To ensure that the committed regulation remains deliverable, we introduce chance constraints on instantaneous power flexibility based on interactive load forecasts, and apply Value-at-Risk queue-state constraints to maintain sustainable response under cumulative regulation signals. Case studies on a modified IEEE 68-bus system using real data center traces show that the proposed framework lowers system operating costs, enables more viable regulation capacity, and achieves better revenue-risk trade-offs compared to strategies that optimize scheduling and regulation independently.

Khursheed Salman, Paul Virendra Kumar, Kidwai Farhan Ahmad

The Delhi Metro’s (DM) public transportation share has been decreasing due to fare hikes and COVID-19 restrictions. To improve ridership, a study is being conducted to evaluate the DM’s performance and identify areas for improvement. The Magenta Line, is investigated through an on-board survey in July-August 2021 to collect primary data. The survey covers commuter perceptions of safety & security, financial & economic factors, infrastructure & comfort and functional & operational features. The Relative Importance Index approach is used to analyze the data and evaluate DM performance. An ANN model is also presented to determine the factors influencing the choice to travel on the DM, with the “metro fare per trip” being a key consideration. The study found that safety and security had the highest RII, followed by efficiency and viability, functional and operational features, infrastructure and comfort, and financial and economic factors. The metro fare had the lowest RII.

Hamidreza Heydari, Mohammadreza Talaee, Aynaz Naseri

High-speed railway tracks have expanded significantly across the world in recent years. The increase in train operating speeds imposes considerable aerodynamic forces on the track, which can lead to several technical issues—one of the most important being the ballast flight phenomenon. Among the key factors contributing to ballast flight are the geometric properties of the aggregates, particularly their effective area and particle size. Since there is still limited understanding regarding how geometric properties of the aggregates (e.g. effective area and particle size) impact ballast flight, the present study aims to investigate this issue using a series of wind tunnel tests. The wind tunnel provides a controlled environment to simulate aerodynamic conditions similar to those found in high-speed railways and to evaluate the influence of various parameters on ballast flight behavior. In this study, five different standard ballast gradations defined by the Iranian Standard No. 301 were tested. The findings showed that aggregates with a larger effective area tended to initiate flight at higher airspeeds. Furthermore, an increase in particle size was associated with a higher flight velocity. Among the tested gradations, the ballast with grade No. 4 exhibited the best resistance against ballast flight, indicating its potential as an optimal choice for high-speed railway tracks.

Ayman Bahjat Abdallah, Hamza Ahmad Almomani, Zu’bi M. F. Al-Zu’bi

<i>Background</i>: The present study investigates Industry 4.0’s (I4.0) impact on supply chain capabilities (SCCs), supply chain innovation (SCI), and supply chain performance (SCP). The influence of SCCs and SCI on SCP is also explored. Additionally, the mediating impacts of SCCs and SCI on the I4.0-SCP relationship are analyzed. <i>Methods</i>: The study’s population consisted of manufacturing companies located in Amman, Jordan. A purposive sample of 211 companies was selected. Self-administered questionnaires were completed by targeted managers in the participating companies. <i>Results</i>: The outcomes indicated that the total impact of I4.0 on SCP was significant and positive. I4.0 positively affected both SCCs and SCI. Additionally, SCCs and SCI were found to positively affect SCP. Finally, the results demonstrated a full mediating impact of SCCs and SCI on the I4.0-SCP relationship, with over two-thirds of the mediation impact attributed to SCCs. <i>Conclusions</i>: This research is among the earliest to examine I4.0’s impact on SCP. It also fills a research gap by exploring I4.0’s influence on both SCCs and SCI. To the best of our knowledge, the present study is the first to investigate the mediation effect of SCCs and SCI on the I4.0-SCP relationship, thus providing a valuable contribution to the existing literature.

Subei Mutailifu, Paolo Brandimarte, Aili Maimaiti

<i>Background</i>: We consider a variant of the traveling salesperson problem motivated by the case of a company delivering furniture. The problem is both dynamic, due to random arrivals of delivery requests, and multiperiod, due to flexibility in delivering items within a time window of a few days. A sequence of daily routes must be selected over time, and both volume and route duration constraints are relevant. Moreover, customers are irregularly distributed in clusters with high or low density. When receiving a request from a low-density cluster, we may consider the possibility of waiting for further requests from the same cluster, which involves a tradeoff between total traveled distance and service quality. <i>Methods</i>: We designed alternative decision policies based on approximate dynamic programming principles. We compared policy and cost function approximations, tuning their parameters by simulation-based optimization. <i>Results</i>: We compared the decision policies by realistic out-of-sample simulations. A simple trigger-based decision policy was able to achieve a good compromise among possibly conflicting objectives, without resorting to full-fledged multiobjective models. <i>Conclusions</i>: The insights into the relative strengths and weaknesses of the tested policies pave the way to practical extensions. Due to its computational efficiency, the trigger policy may be improved by base-policy rollout and integrated within a multi-vehicle routing architecture.

Hanqin Chen, Ye Lu, Huaqin Huang

Trade policy uncertainty has become a significant feature of today's global economy. While its impact on free trade is evident, its microeconomic effects remain open to debate. This study explores the influence of trade policy uncertainty on corporate ESG performance and its underlying mechanisms, using data from A-share listed companies in China from 2010 to 2020. The findings reveal that increased trade policy uncertainty significantly and robustly enhances corporate ESG performance. Heterogeneity analysis indicates that high-tech enterprises are better equipped to improve their ESG performance in response to trade policy uncertainty. Furthermore, strengthening internal controls and appointing CEOs with environmental backgrounds also help firms seize the opportunities arising from trade policy uncertainty. In terms of mechanisms, trade policy uncertainty intensifies industry competition, compelling firms to enhance their ESG performance to gain market share. Additionally, it stimulates green technological innovation, further optimizing ESG outcomes. Therefore, efforts should focus on improving the ESG standards system, establishing ESG incentive policies, increasing the transparency and predictability of trade policies, and promoting corporate green development to advance national sustainable development goals.

Ahmed Sabir, Rajesh Sharma

In this work, we investigate the correlation between gender and contextual biases, focusing on elements such as action verbs, object nouns, and particularly on occupations. We introduce a novel dataset, GenderLexicon, and a framework that can estimate contextual bias and its related gender bias. Our model can interpret the bias with a score and thus improve the explainability of gender bias. Also, our findings confirm the existence of gender biases beyond occupational stereotypes. To validate our approach and demonstrate its effectiveness, we conduct evaluations on five diverse datasets, including a Japanese dataset.

Christopher Clayton, Antonio Coppola

We examine whether and how granular, real-time predictive models should be integrated into central banks' macroprudential toolkit. First, we develop a tractable framework that formalizes the tradeoff regulators face when choosing between implementing models that forecast systemic risk accurately but have uncertain causal content and models with the opposite profile. We derive the regulator's optimal policy in a setting in which private portfolios react endogenously to the regulator's model choice and policy rule. We show that even purely predictive models can generate welfare gains for a regulator, and that predictive precision and knowledge of causal impacts of policy interventions are complementary. Second, we introduce a deep learning architecture tailored to financial holdings data--a graph transformer--and we discuss why it is optimally suited to this problem. The model learns vector embedding representations for both assets and investors by explicitly modeling the relational structure of holdings, and it attains state-of-the-art predictive accuracy in out-of-sample forecasting tasks including trade prediction.

Natalia Khan, Wei Deng Solvang, Hao Yu

<i>Background:</i> Spare parts warehousing in the oil and gas industry is essential for offshore production. With the introduction of Industry 4.0 and its subsequent technological tools, new functions are enabled in industrial logistics activities. Efficiency, visibility, optimization, and productivity are often mentioned as benefits of successful Industry 4.0 technology implementation in logistics activities. In this paper, the implementation of Industry 4.0 technologies such as the Industrial Internet of Things (IIoT) in spare parts warehousing in the oil and gas industry is studied. <i>Method:</i> 133 peer-reviewed journal publications indexed in Scopus and Web of Science are analyzed in a systematic literature review. The review is structured as frequency and content analysis. <i>Aim:</i> As there is limited research on this specific topic, the aim is for this paper to be a theoretical foundation that assists the industry with future solutions. <i>Results:</i> The list of benefits of implementation gathered from the literature is comprehensive. However, the list of challenges is particularly pertinent to the oil and gas industry and indicates a strong inclination towards limited and controlled implementation of some technologies. The safety demands of the industry mean there are many limitations to implementation currently. <i>Conclusions:</i> This paper reflects on the results, identifies research gaps, and gives proposals for future research.

Théo Durandard, Alexis Ghersengorin

We study the robust regulation of contracts in moral hazard problems. A firm offers a contract to incentivise a worker protected by limited liability. A regulator restricts the set of permissible contracts to (i) improve efficiency and (ii) protect the worker. The regulator faces uncertainty about both the worker's actions and the firm's production cost, and evaluates regulations based on their worst-case regret. The regret-minimising regulation mandates a minimum piece rate compensation for the worker. This rule simultaneously guarantees a fair share for the worker and preserves enough contractual flexibility to provide incentives.

Gianmarco Del Sarto, Marta Leocata, Giulia Livieri

We develop a model based on mean-field games of competitive firms producing similar goods according to a standard AK model with a depreciation rate of capital generating pollution as a byproduct. Our analysis focuses on the widely-used cap-and-trade pollution regulation. Under this regulation, firms have the flexibility to respond by implementing pollution abatement, reducing output, and participating in emission trading, while a regulator dynamically allocates emission allowances to each firm. The resulting mean-field game is of linear quadratic type and equivalent to a mean-field type control problem, i.e., it is a potential game. We find explicit solutions to this problem through the solutions to differential equations of Riccati type. Further, we investigate the carbon emission equilibrium price that satisfies the market clearing condition and find a specific form of FBSDE of McKean-Vlasov type with common noise. The solution to this equation provides an approximate equilibrium price. Additionally, we demonstrate that the degree of competition is vital in determining the economic consequences of pollution regulation.

Snežana Tadić, Mladen Krstić, Željko Stević et al.

<i>Background</i>: Possible solutions to overcome the many challenges of home delivery are collection and delivery points (CDPs). In addition to commercial facilities, the role of CDPs can also be played by users’ households, providing a crowd storage service. Key decisions regarding CDPs relate to their location, as well as the allocation of users to selected locations, so that the distance of users from CDPs is minimal. <i>Methods</i>: In this paper, the described problem is defined as a <i>p</i>-median problem and solved for the area of the city of Belgrade, using the heuristic “greedy” and the simulated annealing algorithm. <i>Results</i>: Fifty locations of CDPs were selected and the users allocated to them were distributed in over 950 zones. The individual distances between users and the nearest CDPs and the sum of these distances, multiplied by the number of requests, were obtained. An example of modification of the number of CDPs is presented as a way of obtaining solutions that correspond to different preferences of operators and/or users in terms of their distances from the CDPs. <i>Conclusions</i>: User households can be used as CDPs to achieve various benefits. Locating CDPs, i.e., selecting households, can be solved as a <i>p</i>-median problem, using a combination of heuristic and metaheuristic algorithms. In addition, by modifying the number of medians, the total and average distances between users and CDPs can be better managed. The main contributions of the paper are the establishment of users’ households as potential locations of CDPs, the establishment of a framework for analysis of impact of the number of CDPs on the sum and average distances from the customers, as well as the creation of a basis for upgrading and modifying the model for implementation in the business practice.

Bahram Alidaee, Haibo Wang, Lutfu S. Sua

<i>Background</i>: Last-mile delivery (LMD) is a challenging and costly supply chain process that involves direct customer interaction. In a recent study by the World Economic Forum, it was emphasized that last-mile logistics is an emerging research area. In particular, the European Commission Directorate General for Energy and Transport provides guidelines for abnormal road transport, such as heavy, bulky, and oversized (HBO) products. In the last few years, many research articles have been published on the topic of LMD. Several literature review studies from the perspective of different stakeholders have also been published. The delivery of HBO products is more challenging in many ways compared to parcel delivery. Although HBO products yield the most profitable sales, the LMD of HBOs is less studied compared to parcel deliveries. <i>Methods</i>: This research employed a descriptive review method to scan 195 published articles and reports related to LMD and HBOs. <i>Results</i>: Our results identified the challenges in the field and identified the need for separate approaches for different customer segments, such as rural and urban customers, as well as older and younger customers, when formulating delivery strategies. <i>Conclusions</i>: This paper highlights the research gap in this field by using a descriptive literature review methodology and presents academic contributions available so far, as well as challenges for further research.

Ailian Qiu, Yingchun Yu, John McCollough

Purpose – This thesis deeply studies the impact mechanism of digital service trade on the high-quality development of the manufacturing industry from the aspects of technological innovation and industrial structure. Design/methodology/approach – In this thesis, 40 countries from 2010 to 2020 were selected as samples, and the panel fixed-effect model and intermediary effect model were used to empirically analyze the impact path of digital service trade on the high-quality development of global manufacturing. Findings – Overall, digital service trade has a positive impact on the high-quality development of the global manufacturing industry. Through the analysis of the intermediary effect mechanism, it is found that digital service trade can further positively affect the high-quality development of the global manufacturing industry by promoting technological innovation and industrial structure upgrading. Research limitations/implications – Based on the empirical results, targeted countermeasures and suggestions are given in this paper. Practical implications – Through the test of national heterogeneity, it is found that in developing countries, digital service trade mainly acts on the high-quality development of the manufacturing industry by promoting industrial structure upgrading. Social implications – In developed countries, digital service trade mainly promotes the high-quality development of manufacturing through technological innovation; from the perspective of industry heterogeneity, the three service industries of information and communication technology (ICT), other business services and property have the intermediary effect of technological innovation and industrial structure. Originality/value – This manuscript suggests that trade in digital services should be promoted as a national trade priority.

Mathew Azarian, Hao Yu, Asmamaw Tadege Shiferaw et al.

<i>Background</i>: Systematic literature review (SLR) is increasingly utilized to maximize the element of rigor and minimize the individual bias of research synthesis. An analysis of the Web of Science (WoS) database indicates that 90% of the literature review studies using SLR have been published between 2012 and 2022. However, this progressive agenda is impaired by the lack of methodological consistency and rigorousness. To fill this gap, this paper aims at mapping the theoretical comprehension and practices of SLR and providing a stepwise approach to employing such a framework. <i>Methods</i>: A comprehensive narrative review is used in this paper to analyze the studies concerning the literature review typology and the structural assessment of the SLR. Furthermore, the methodological approach of the literature review studies that adopted the SLR and were published in the <i>Logistics</i> journal is assessed across a set of vital criteria associated with conducting an SLR. <i>Results</i>: There is a concrete link between the purpose of a review, i.e., to describe, test, extend, or critique, and the literature review type. There are 17 distinct literature review types, e.g., a narrative review, a bibliometric analysis, etc., which must be justified meticulously regardless of the SLR. The ambiguity in conceiving the SLR either as a toolkit or a review type, the lack of justification regarding the review purpose and type, and vague conceptual distinguishment between the bibliometric analysis, as a distinct review type, and the SLR framework, are only a few of the shortcomings observed in the analyzed papers. <i>Conclusions</i>: Given the significant role of SLR in elevating the element of rigor within the literature review studies, it is deemed essential to employ this framework by paying attention to two holistic factors: (1) theoretical distinction between the literature review purpose, the literature review type, and the SLR; (2) strict adherence to the SLR procedure with a high degree of accuracy and explicitness.

Akriti Verma, Shama Islam, Valeh Moghaddam et al.

Emotion regulation is the process of consciously altering one's affective state, that is the underlying emotional state such as happiness, confidence, guilt, anger etc. The ability to effectively regulate emotions is necessary for functioning efficiently in everyday life. Today, the pervasiveness of digital technology is being purposefully employed to modify our affective states, a process known as digital emotion regulation. Understanding digital emotion regulation can help support the rise of ethical technology design, development, and deployment. This article presents an overview of digital emotion regulation in social media applications, as well as a synthesis of recent research on emotion regulation interventions for social media. We share our findings from analysing state-of-the-art literature on how different social media applications are utilised at different stages in the process of emotion regulation.

Habeeb Solihu, Jackson Sekasi, Ray Kumar Pradip

Aside from providing services and infrastructure for the mobility of people and goods, sustainable transport is a cross-cutting accelerator that can fasttrack progress towards other crucial goals such as SDGs 1, 4, 5, and 13; as such, it is imperative in achieving the 2030 Agenda for Sustainable Development. This, therefore, serves as the impetus for this study. This study administered about two hundred and forty (240) questionnaires to railway transportation passengers and was analyzed to compare the performance of the Railway Stations along the North-South Axis of the Addis Ababa Light Rail Transit (AA-LRT). Six (6) out of seventeen (17) stations along this axis were considered for this study, not only because they comprise terminal stations but also, because they are situated in highly populated areas with high demand potential. The stations were categorized and the comparison was based on the passengers’ perspectives on the selected performance indicators. Also, because the data are dichotomous, Binary Logistic Regression Model was used to model a relationship equation between the dependent variable (level of performance) and the performance indicators (predictors). The selected stations were ranked according to their performances while conclusions and recommendations were suggested to further enhance their performance for customers’ satisfaction. Finally, adopting the methodology in this study for investigating the performance of railway stations elsewhere in the world is recommended.

Shih-Che Lo

<i>Background</i>: The logistics network design with cross-docking operations enables shipping service providers to integrate the physical flow of products between vendors and dealers in logistics management. The collective goal is to synchronize the goods in both pickup and delivery operations concurrently to reduce the handling cost, inventory cost, and operation cost generated. Therefore, the optimal vehicle routing plan is crucial to generate a truck routing schedule with minimal total cost, fulfilling the purchasing requirements and the distribution demand. Global warming and climate change are important topics due to increasing greenhouse gas emissions. Sustainable logistics management with optimized routes for trucks can assist in reducing greenhouse gas emissions and easing the effects of temperature increases on our living environment. <i>Methods</i>: A heuristic approach based on Particle Swarm Optimization, called ePSO, was proposed and implemented in this paper to solve the vehicle routing problems with cross-docking and carbon emissions reduction at the same time. <i>Results</i>: Performance comparisons were made with the Genetic Algorithm (GA) through the experiments of several vehicle routing problems with pickup and delivery benchmark problems to validate the performance of the ePSO procedure. <i>Conclusions</i>: Experimental results showed that the proposed ePSO approach was better than the GA for most cases by statistical hypothesis testing.