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

Sarah Small, Yana Rodgers, Teresa Perry

This paper examines changes in occupational crowding of immigrant women in frontline industries in the United States during the onset of COVID-19, and we contextualize their experiences against the backdrop of broader race-based and gender-based occupational crowding. Building on the occupational crowding hypothesis, which suggests that marginalized workers are crowded in a small number of occupations to prop up wages of socially-privileged workers, we hypothesize that immigrant, Black, and Hispanic workers were shunted into frontline work to prop up the health of others during the pandemic. Our analysis of American Community Survey microdata indicates that immigrant workers, particularly immigrant women, were increasingly crowded in frontline work during the onset of the pandemic. We also find that US-born Black and Hispanic workers disproportionately faced COVID-19 exposure in their work, but were not increasingly crowded into frontline occupations following the onset of the pandemic. The paper also provides a rationale for considering the occupational crowding hypothesis along the dimensions of both wages and occupational health.

Heather J. Alexander, Jonathan A. Simon, Frédéric Pinard

The law draws a sharp distinction between objects and persons, and between two kinds of persons, the ''fictional'' kind (i.e. corporations), and the ''non-fictional'' kind (individual or ''natural'' persons). This paper will assess whether we maximize overall long-term legal coherence by (A) maintaining an object classification for all future AI systems, (B) creating fictional legal persons associated with suitably advanced, individuated AI systems (giving these fictional legal persons derogable rights and duties associated with certified groups of existing persons, potentially including free speech, contract rights, and standing to sue ''on behalf of'' the AI system), or (C) recognizing non-fictional legal personhood through legal identity for suitably advanced, individuated AI systems (recognizing them as entities meriting legal standing with non-derogable rights which for the human case include life, due process, habeas corpus, freedom from slavery, and freedom of conscience). We will clarify the meaning and implications of each option along the way, considering liability, copyright, family law, fundamental rights, civil rights, citizenship, and AI safety regulation. We will tentatively find that the non-fictional personhood approach may be best from a coherence perspective, for at least some advanced AI systems. An object approach may prove untenable for sufficiently humanoid advanced systems, though we suggest that it is adequate for currently existing systems as of 2025. While fictional personhood would resolve some coherence issues for future systems, it would create others and provide solutions that are neither durable nor fit for purpose. Finally, our review will suggest that ''hybrid'' approaches are likely to fail and lead to further incoherence: the choice between object, fictional person and non-fictional person is unavoidable.

Frederik Zuiderveen Borgesius

Our society can benefit immensely from algorithmic decision-making and similar types of artificial intelligence. But algorithmic decision-making can also have discriminatory effects. This paper examines that problem, using online price differentiation as an example of algorithmic decision-making. With online price differentiation, a company charges different people different prices for identical products, based on information the company has about those people. The main question in this paper is: to what extent can non-discrimination law protect people against online price differentiation? The paper shows that online price differentiation and algorithmic decision-making could lead to indirect discrimination, for instance harming people with a certain ethnicity. Indirect discrimination occurs when a practice is neutral at first glance, but ends up discriminating against people with a protected characteristic, such as ethnicity. In principle, non-discrimination law prohibits indirect discrimination. The paper also shows, however, that non-discrimination law has flaws when applied to algorithmic decision-making. For instance, algorithmic discrimination can remain hidden: people may not realise that they are being discriminated against. And many types of unfair - some might say discriminatory - algorithmic decisions are outside the scope of current non-discrimination law.

Toqa Amoush, Luay Jum’a

<i>Background</i>: The retail sector in Jordan is adopting Industry 4.0 (I4.0) technologies to enhance efficiency and sustainability. Nevertheless, there is a lack of empirical evidence to inform retail managers regarding the impact of I4.0 adoption on environmental, economic, and social sustainability, particularly in dynamic contexts. Therefore, this study aims to investigate the impact of Industry 4.0 on the three types of sustainable performance, with the moderating effect of environmental dynamism. <i>Methods</i>: This quantitative study collected data using a cross-sectional survey of 100 retail professionals from large companies that was analyzed using structural equation modeling (SEM) to test the hypotheses. <i>Results</i>: I4.0 practices improved retail environmental, economic, and social sustainability. Additionally, environmental dynamism moderated the relationship between I4.0 and environmental sustainability, suggesting that dynamic environments may reduce the effectiveness of I4.0 technologies in driving environmental performance. Economic and social sustainability had no significant moderating effects. <i>Conclusions</i>: This study examines the sustainability benefits of I4.0 adoption in an unexplored developing economy. It emphasizes the strategic importance of digital transformation for retail sustainability and provides practical recommendations for dynamic markets. The findings support I4.0 technologies role in sustainable growth and lay the groundwork for digital transformation research in emerging markets.

Osayuwamen Omoruyi, Albert Antwi, Alfred Mwanza et al.

<i>Introduction</i>: This study explores the impact of logistics information technology (LIT) on supply chain relationships and distribution performance in small and medium-sized enterprises (SMEs) using South Africa as a case study. Although digital supply chain solutions are increasingly important, there is limited evidence of SME efficiency in emerging markets using LIT. <i>Methods</i>: This study utilises a survey of 313 SMEs from four South African provinces. Bayesian structural equation modelling (Bayesian SEM) was then used to examine LIT’s effects on distribution performances in terms of timeliness, product availability, and condition. <i>Results</i>: The results show that the adoption of LIT strengthens buyer–seller networks (β = 0.524, CI = [0.434, 0.613]) and improves distribution by enhancing both timeliness performance (β = 0.237, CI = [0.098, 0.372]) and product condition performance (β = 0.175, CI = [0.042, 0.259], β = 0.222, <i>p</i> < 0.001). However, it does not directly enhance product availability performance (β = 0.085, CI = [−0.030, 0.199]), signifying that LIT adoption by itself fails to improve product availability. The results also demonstrate that SME network relationships mediate the connection between LIT adoption and distribution performance metrics. <i>Discussion</i>: This study’s findings contribute to the literature and offer valuable information and guidance to policymakers as they underscore the importance for SMEs to invest in LIT integration and compatibility, as well as inventory optimisation and improved supplier communication to minimise transit time variation. Policymakers should support SMEs’ digital transformation through interventions including funding and training for LIT adoption. This study confirms the essential role of LIT in SME supply chains and illustrates that technology-facilitated relationships enhance distribution performance, which enhances SME competitiveness.

Marta Rinaldi, Mario Caterino, Stefano Riemma et al.

<i>Background</i>: Emergency scenarios present unprecedented challenges for supply chains worldwide, particularly in the management and distribution of critical supplies, where timely delivery and maintaining integrity are crucial. <i>Methods:</i> This article explores an innovative approach to enhance the emergency management of supply chains using blockchain technology and simulation-based modelling. The proposed methodology aims to tackle issues such as transparency, efficiency, and security, which are vital for managing logistics during crises. A case study involving a vaccine rollout is used to demonstrate how blockchain can optimise supply chain operations, reduce bottlenecks, and ensure better traceability and accountability throughout the process. The case study is specifically developed based on the distribution of COVID-19 vaccines in Italy. <i>Results:</i> The integration of blockchain technology not only enhances data integrity and security but also facilitates real-time monitoring and decision-making. <i>Conslusions:</i> The findings suggest that the proposed blockchain-based model can significantly improve supply chain resilience in emergency situations compared to traditional methods, thereby offering valuable insights for policymakers and supply chain managers facing future crises.

Nazanin Abbaspoor ekder, Ahmad Ramezani, Mohammad amin Maleki

The current study aims to design and validate the model of damage caused by cryptocurrency-related crimes in Iranian law with the aim of helping legal institutions to identify these damages and fix them. In order to analyze the problem, qualitative research strategy and thematic analysis were used. The research data were collected by means of semi - standard interviews with 12 experts in the field of corruption and related crimes who were selected using theoretical sampling method and it was rebuilt by applying the theme analysis method of the network type of the analyzed themes and the conceptual model of network measurement. The findings of the qualitative research showed that the design and validation of the model of damages and crimes related to cryptocurrencies in Iran law with the three overarching themes: 1- Legal, executive and legal damages related to the field of cryptocurrencies 2- Existence of various risks (activity, exchange rate, laws and regulations, etc.) in the field of cryptocurrencies 3- The threats related to the increase in cryptocurrency crimes have reached theoretical saturation. In addition, in order to validate the themes and the rebuilt model two credit assessment methods, the communication method and the audit method and also in order to test the reliability, two methods of reproducibility and transferability or generalizability have been used.1. Introduction Artificial intelligence, on the one hand, has somehow penetrated into various layers of bio-social life, and there is hardly any field that does not need to determine relations with artificial intelligence. On the other hand, the ever-increasing expansion and growth of artificial intelligence also entails the variety of its forms and effects. Every day, we see the penetration of artificial intelligence in a certain field: one day we talk about the Internet of Things, the next day the field of robotics undergoes major changes with the introduction of artificial intelligence, or in the field of medicine, artificial intelligence offers robotic surgeons. Therefore, it is necessary to get familiar with artificial intelligence and examine its role in each specific field. One of these special forms of artificial intelligence is chatbots. Today, chatbots and their various types have become a hot topic in technology circles and even a central topic of concern for users and ordinary people; In such a way that big companies in the field of technology are worried about falling behind other competitors in this field; This has caused us to see a new chatbot every day, or an updated sample of existing chatbots: From the Microsoft company, which surprised the users of the technology world by supporting and even expanding the chatbot ChatGPT, to the Google company, which was worried about falling behind the competitor, which forced it to design and release its own special chatbot. But it can be said that the most controversial and famous chatbot is ChatGPT, which produces text and audio works by talking and interacting with humans. This chatbot is considered a dialogue-oriented chatbot. The widespread use of chatbots has brought them into the interactions of normal users and has caused questions about possible risks and such issues. On the other side of the story, the knowledge of law is a field that has not been immune to the influence of artificial intelligence. This influence can be seen in different parts of this field, including drafting bills, providing legal advice, checking the chances of winning each case, helping judges to adapt the laws to the subject of the dispute, etc. But in addition to that, since the knowledge of the law is responsible for regulating the social relationships of "persons", it has the duty to discuss these emerging phenomena, determine their position, and make the result of human interaction with chatbots predictable. Therefore, first, it should be determined how the legal system looks at chatbots? Does it consider them as a person and impose the effects of personality on their relationships? Or not, it has another look at these forms of artificial intelligence. Secondly, the use of chatbots by users can involve risks, as a result of which there is a possibility of causing losses to users; Disclosure of information, moral damages caused by ethnic, racial, and gender insults, or even secondary actions caused by false information received from these chatbots and... How will these risks be compensated and how will civil liability be established? Thirdly, what happens to the works produced by these chatbots? These works may be in the form of written text, or audio or visual works. Does the intellectual property system have a place to support these works? Or even willing to support them? This article seeks to answer the aforementioned questions. In fact, firstly, the questions raised are scrutinized and analyzed; The necessity of these issues is examined; The different parts of the questions and the requirements for answering each one are explained; And finally, these questions are answered with legal analysis, and in parts of legal-economic analysis. The motivation of writing this article is actually the void of legal analysis in the field of artificial intelligence and especially chatbots and their role in social and legal relations. The emerging and newness of the issue of chatbots has caused that, despite its prevalence and extent, the doctrine and jurists to pay less attention to this issue. Scientific poverty and research results challenge the legal system in dealing with new issues. On the other hand, the lack of relevant and clear legal texts also makes the analysis difficult. The judicial procedure also, unlike facing such issues, does less to create basic rules and provide pathbreaking analyses in this field. Although the analysis presented in this article, and the motivation expressed, is based on the legal system of Iran, but the lack of establishment of a single procedure in international legal issues and other countries has also led to the legal rules presented and the solutions proposed in this article. comparative studies have an effective role in the final conclusions of each discussion of this article. 2. Methodology In terms of research method, this article is a kind of descriptive-analytical article. Since in this article, the place of artificial intelligence and chatbots in the world of law is described and explained and part of its essence is answered, this article is considered descriptive research. On the other hand, in this article, it is not enough to describe and interpret what is in the subject of chatbots, and in addition to describing the concepts around this phenomenon, it is necessary to analyze and review the issues and provide solutions in cases that face a gap in legal analysis, is also paid. On the other hand, due to the fact that many legal questions remain unanswered regarding artificial intelligence and chatbots in particular, this research is considered an applied research, which ultimately provides solutions and answers appropriate to Iran's legal system and appropriate to the ruling legal rules. Also, the dominant method in collecting information and data in this research is the library method, and by referring to the library and analyzing the content of books, domestic and foreign articles, and the opinions of judicial authorities, this article has been written. Of course, interacting with ChatGPT itself and other chatbots has also been an effective way to answer some legal ambiguities. The stated methods were appropriate to the research topic and research questions. These questions can be summarized in "What is the position of ChatGPT and the legal system's view of them", "Legal problems and challenges arising from human interaction with them (civil responsibility and intellectual property)". 3. Results and Discussion This article, which is an analysis of some legal aspects of chatbots, deals with three main axes: chatbots and personal law/chatbots and civil liability/and chatbots and intellectual property. In addition to these four axes, the natureof chatbots has also been investigated as a bridge to enter the main discussion. -The concept of chatbot: It is necessary to address this discussion in order to define the topic under study completely, clearly, and unambiguously, so that the audience knows exactly what is to be researched. Finally, a chatbot is considered a manifestation of artificial intelligence that has the ability to communicate with a human user, and ChatGPT is introduced as one of its most well-known examples. -Chatbots and personal law: Answering the question of whether the legal system, especially in Iran, can consider chatbots as having personality or not, requires addressing deeper issues in this field. But in the end, despite the movement of countries towards the acceptance of "relative personality" for autonomous artificial intelligence, chatbots having personality, even if relatively, face a negative response, especially in Iran's legal system. -Chatbots and civil liability rights: The possible damages caused by chatbots to users and, as the case may be, to other persons, forces the legal system to think about the issue of assigning responsibility, the type of assigned responsibility, and the solution for compensation. The answer to the article to these questions is the non-responsibility of the chatbot itself, and the responsibility of its supporting company regarding the assignment of responsibility, and the establishment of a graduated liability system regarding the type of responsibility and, accordingly, the method of compensation. -Chatbots and intellectual property rights: after the production and supply of written or even visual works by chatbots, the position of these works in the intellectual property system must be determined both in terms of the principle of protection or lack of it, and in terms of ownership attribution. In the field of moral rights, in order to link this category of rights with human issues, supporting the mentioned works seems to be ruled out. But in the case of material rights, this protection can be considered and the work attributed to the creator or a special protection system designed for such works. Entering these works into the public domain is also another way, which of course comes with criticism. 4. Conclusions and Future Research Chatbots are a new form of artificial intelligence that is available to the public today to talk and exchange opinions with people. The ability of chatbots to create intellectual property and violate the rights of others is one of the issues that make their legal study necessary. Considering the discussed issues, it can be concluded that the output of chatbots activity in the current situation belongs to the owner (supporting company or manufacturer/owner) who is involved in the production of the work. In terms of civil liability, it can be attributed to him, considering the benefit that the producing company gets from providing the service. However, the growing independence of these chatbots separates them from the original creators. For this reason, it becomes difficult to attribute the works and contents and subsequent responsibility to the creators/users. Therefore, the explanation of theories based on personality belonging to artificial intelligence, including chatbots or relative personality, is on the agenda of legal researchers of modern technologies. In this direction, it is suggested to analyze the legal situation according to the capabilities of chatbots. Of course, productive artificial intelligence, which chatbots are associated with to some extent, can have the highest level of personality and competence, and other intelligences are reduced to the level of tools. Legal changes following the Dabus case can depict a new future in the use of artificial intelligence and put productive intelligence in a new position. The lack of legal text in the field of artificial intelligence and especially chatbots, considering their role in economic and social interactions, makes it clear the need to approve the law and its draft in this field, which can adopt a way for the status of these technologies in the form of a single article to do. At least the most important legal issues that arise with the introduction of these artificial intelligences into social interactions, such as personal law, ownership, responsibility, and contracts, should take on a legal color according to the legal literature in this field and according to the opinions and analyses presented. create and modify as needed. On the other hand, this literature the law helps the judicial procedure in dealing with these new issues to resolve its confusion, and it can even cause the Iranian government to propose the ratification of international conventions on the subject of artificial intelligence and prepare the drafts according to the aforementioned analyzes and results. There are many gaps in the field of chatbots and legal research about them. From the research that can be done in the future in this field, we can refer to "Investigation of the impact of chatbots on procedural issues", "Criminal dimensions of chatbots", "Investigation of chatbots.

A. J. Bequet, C. Jallais, J. Quick et al.

Stress impacts driving-related cognitive functions like attention and decision-making, and may arise in automated vehicles due to non-driving tasks. Unobtrusive relaxation techniques are needed to regulate stress without distracting from driving. Tactile wearables have shown efficacy in stress regulation through respiratory guidance, but individual variations may affect their efficacy. This study assessed slow-breathing tactile guidance under different stress levels on 85 participants. Physiological, behavioral and subjective data were collected. The influence of individual variations (e.g., driving habits and behavior, personality) using logistic regression analysis was explored. Participants could follow the guidance and adjust breathing while driving, but subjective efficacy depended on individual variations linked to different efficiency in using the technique, in relation with its attentional cost. An influence of factors linked to the evaluation of context criticality was also found. The results suggest that considering individual and contextual variations is crucial in designing and using such techniques in demanding driving contexts. In this line some design recommendations and insights for further studies are provided.

Anjali Gupta, Shreyans J. Nagori, Abhijnan Chakraborty et al.

Social commerce platforms are emerging businesses where producers sell products through re-sellers who advertise the products to other customers in their social network. Due to the increasing popularity of this business model, thousands of small producers and re-sellers are starting to depend on these platforms for their livelihood; thus, it is important to provide fair earning opportunities to them. The enormous product space in such platforms prohibits manual search, and motivates the need for recommendation algorithms to effectively allocate product exposure and, consequently, earning opportunities. In this work, we focus on the fairness of such allocations in social commerce platforms and formulate the problem of assigning products to re-sellers as a fair division problem with indivisible items under two-sided cardinality constraints, wherein each product must be given to at least a certain number of re-sellers and each re-seller must get a certain number of products. Our work systematically explores various well-studied benchmarks of fairness -- including Nash social welfare, envy-freeness up to one item (EF1), and equitability up to one item (EQ1) -- from both theoretical and experimental perspectives. We find that the existential and computational guarantees of these concepts known from the unconstrained setting do not extend to our constrained model. To address this limitation, we develop a mixed-integer linear program and other scalable heuristics that provide near-optimal approximation of Nash social welfare in simulated and real social commerce datasets. Overall, our work takes the first step towards achieving provable fairness alongside reasonable revenue guarantees on social commerce platforms.

Klaus M. Miller, Julia Schmitt, Bernd Skiera

Privacy regulations often necessitate a balance between safeguarding consumer privacy and preventing economic losses for firms that utilize consumer data. However, little empirical evidence exists on how such laws affect firm performance. This study aims to fill that gap by quantifying the impact of the European Union's General Data Protection Regulation (GDPR) on online usage behavior over time. We analyzed data from 6,286 websites across 24 industries, covering 10 months before and 18 months after the GDPR's enactment in 2018. Employing a generalized synthetic control estimator, we isolated the short- and long-term effects of the GDPR on user behavior. Our results show that the GDPR negatively affected online usage per website on average; specifically, weekly visits decreased by 4.88% in the first 3 months and 10.02% after 18 months post-enactment. At the 18-month mark, these declines translated into average revenue losses of about USD 7 million for e-commerce websites and nearly USD 2.5 million for ad-based websites. Nonetheless, the GDPR's impact varied across website size, industry, and user origin, with some large websites and industries benefiting from the regulation. Notably, the largest 10% of websites pre-GDPR suffered less, suggesting that the GDPR has increased market concentration.

Chenhao Fang, Xiaohan Li, Zezhong Fan et al.

Product attribute value extraction is a pivotal component in Natural Language Processing (NLP) and the contemporary e-commerce industry. The provision of precise product attribute values is fundamental in ensuring high-quality recommendations and enhancing customer satisfaction. The recently emerging Large Language Models (LLMs) have demonstrated state-of-the-art performance in numerous attribute extraction tasks, without the need for domain-specific training data. Nevertheless, varying strengths and weaknesses are exhibited by different LLMs due to the diversity in data, architectures, and hyperparameters. This variation makes them complementary to each other, with no single LLM dominating all others. Considering the diverse strengths and weaknesses of LLMs, it becomes necessary to develop an ensemble method that leverages their complementary potentials. In this paper, we propose a novel algorithm called LLM-ensemble to ensemble different LLMs' outputs for attribute value extraction. We iteratively learn the weights for different LLMs to aggregate the labels with weights to predict the final attribute value. Not only can our proposed method be proven theoretically optimal, but it also ensures efficient computation, fast convergence, and safe deployment. We have also conducted extensive experiments with various state-of-the-art LLMs, including Llama2-13B, Llama2-70B, PaLM-2, GPT-3.5, and GPT-4, on Walmart's internal data. Our offline metrics demonstrate that the LLM-ensemble method outperforms all the state-of-the-art single LLMs on Walmart's internal dataset. This method has been launched in several production models, leading to improved Gross Merchandise Volume (GMV), Click-Through Rate (CTR), Conversion Rate (CVR), and Add-to-Cart Rate (ATC).

Mahdi Saqi, Seyed MohammadHadi Raji, Mohsen rezay sadrabadi

During the past years, cyberspace has become of the main issues of governments, and cryptocurrencies has been recognized as a sensitive area in need of policy in all countries of the world .This article, looking for: "What should be the pattern of regulating the virtual space, especially the phenomenon of cryptocurrencies in Iran, considering the legal status of the Supreme Council of Cyberspace and the comparative experience of China?" In this regard, by using library resources, the relationship between governance and regulation of virtual space has been described first, and then the concept of governance and regulation of cryptocurrencies have been discussed. In the following, we will compare the structure, duties and actions of China in the regulation of cyberspace, especially cryptocurrencies, with the actions of Iran, because the institution and structure of the regulation of cyberspace in China and Iran have similarities, including the fact that both of them use a supra-governmental structure to regulate cyberspace. The results show that firstly, the legal position of the Iran's Cyberspace Supreme Council in specialized issues of cyberspace such as cryptocurrencies, which have different dimensions, should be as a regulator of the regulators . Secondly, the multi-dimensionality of the issue of cryptocurrencies and the interference of different areas of money, finance, energy, industry and trade doubles the need for a national coordination headquarters, which has not been given serious attention so far.

Thomas K. Dasaklis, Evangelia Kopanaki, Panos T. Chountalas et al.

<i>Background</i>: The electronic Freight Transport Information (eFTI) regulation is critical in modernizing freight transport (FT) within the European Union by establishing a framework for the electronic exchange of information. Despite its importance, there is a notable gap in the literature regarding the practical implementation challenges, especially from an empirical perspective. <i>Methods</i>: To address this gap, our study utilized a grounded theory approach, conducting interviews with a diverse group of logistics experts from Greece. The selection of experts was strategic to ensure a comprehensive range of knowledge and expertise, including insights at the policy level as well as practical experiences. <i>Results</i>: Our findings highlight several significant challenges in the implementation of eFTI, including the digital skill gap among the workforce, issues with system interoperability, and diverse capacities and resources of companies of different sizes. Economic factors, regulatory frameworks and the necessity for targeted training and leadership support were also identified as crucial for the digital transition. <i>Conclusions</i>: The study shows that uniform eFTI implementation may not work for all organizations, highlighting the necessity for customized strategies that address specific challenges in the FT chain. Our research deepens the understanding of these issues, providing actionable insights for successful eFTI adoption.

Paul D. Larson, Robert V. Parsons, Deepika Kalluri

<i>Background</i>: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions reductions are constrained by technological and commercial realities. BEVs and FCEVs are expensive. Further, BEVs depend on existing electricity grids and FCEVs rely on steam–methane reforming (SMR) or electrolysis using existing grids to produce hydrogen. <i>Methods</i>: This study assembles publicly available data from reputable sources to estimate breakeven vehicle purchase prices under various conditions to match conventional (diesel) truck prices. It also estimates GHG emissions reductions. <i>Results</i>: BEVs face numerous obstacles, including (1) limited range; (2) heavy batteries and reduced cargo capacity; (3) long recharging time; and (4) uncertain hours-of-service (HOS) implications. On the other hand, FCEVs face two primary obstacles: (1) cost and availability of hydrogen and (2) cost of fuel cells. <i>Conclusions</i>: In estimating emissions reductions and economic feasibility of BEVs and FCEVs versus diesel trucks, the primary contributions of this study involve its consideration of vehicle prices, carbon taxes, and electricity grid capacity constraints and demand fees. As electricity grids reduce their emissions intensity, grid congestion and capacity constraints, opportunities arise for BEVs. On the other hand, rising electricity demand fees benefit FCEVs, with SMR-produced hydrogen a logical starting point. Further, carbon taxation appears to be less important than other factors in the transition to zero-emission trucking.

Étienne Fournier, Dorilys Kilgus, Aurélie Landry et al.

Since cobots (collaborative robots) are increasingly being introduced in industrial environments, being aware of their potential positive and negative impacts on human collaborators is essential. This study guides occupational health workers by identifying the potential gains (reduced perceived time demand, number of gestures and number of errors) and concerns (the cobot takes a long time to perceive its environment, which eads to an increased completion time) associated with working with cobots. In our study, the collaboration between human and cobot during an assembly task did not negatively impact perceived cognitive load, increased completion time (but decreased perceived time demand), and decreased the number of gestures performed by participants and the number of errors made. Thus, performing the task in collaboration with a cobot improved the user's experience and performance, except for completion time, which increased. This study opens up avenues to investigate how to improve cobots to ensure the usability of the human-machine system at work.

Candida M. Greco, Andrea Tagarelli

Transformer-based language models (TLMs) have widely been recognized to be a cutting-edge technology for the successful development of deep-learning-based solutions to problems and applications that require natural language processing and understanding. Like for other textual domains, TLMs have indeed pushed the state-of-the-art of AI approaches for many tasks of interest in the legal domain. Despite the first Transformer model being proposed about six years ago, there has been a rapid progress of this technology at an unprecedented rate, whereby BERT and related models represent a major reference, also in the legal domain. This article provides the first systematic overview of TLM-based methods for AI-driven problems and tasks in the legal sphere. A major goal is to highlight research advances in this field so as to understand, on the one hand, how the Transformers have contributed to the success of AI in supporting legal processes, and on the other hand, what are the current limitations and opportunities for further research development.

Dirk Lauinger, François Vuille, Daniel Kuhn

Low-carbon societies will need to store vast amounts of electricity to balance intermittent generation from wind and solar energy, for example, through frequency regulation. Here, we derive an analytical solution to the decision-making problem of storage operators who sell frequency regulation power to grid operators and trade electricity on day-ahead markets. Mathematically, we treat future frequency deviation trajectories as functional uncertainties in a receding horizon robust optimization problem. We constrain the expected terminal state-of-charge to be equal to some target to allow storage operators to make good decisions not only for the present but also the future. Thanks to this constraint, the amount of electricity traded on day-ahead markets is an implicit function of the regulation power sold to grid operators. The implicit function quantifies the amount of power that needs to be purchased to cover the expected energy loss that results from providing frequency regulation. We show how the marginal cost associated with the expected energy loss decreases with roundtrip efficiency and increases with frequency deviation dispersion. We find that the profits from frequency regulation over the lifetime of energy-constrained storage devices are roughly inversely proportional to the length of time for which regulation power must be committed.

Pardis Behbood , Hojjat Mobayen

owadays, cyber games are a profitable business with wide economic dimensions, including the property rights of gamers, i.e., “Accounts” and “Points”. Since the producers of cyber games are in a superior position to the gamers, by including terms in terms of Service, they usually limit their responsibility for protecting users’ accounts and points, providing support for the games, and reserving the right to terminate the game. For these reasons, the property rights of gamers are always in a precarious position. In Iranian law, due to the absence of specific laws, we can use the rule of “No-Loss” to protect users’ rights in two ways. On the one hand, according to the rule of “abuse of rights”, the producers have no right to damage the property rights of gamers to cause harm or make unconventional decisions in exercising the right. On the other hand, it is possible to deduce from the rule of "No-Loss" the compensation for the damage caused to the property rights of gamers, which cannot be compensated based on other rules of civil liability.

Jae-Whak Roh

Purpose – This study analyzed Korea's relations table through network analysis. In particular, among the centralities, eigenvector centrality, PageRank centrality and degree were used. The author studied which network characteristics affected the value-added rate. Design/methodology/approach – A network analysis method was used. Findings – It is the inward relationship that affects the value-added ratio of Korea's industries and the outward relationship has less influence. In particular, the inward relationship not only acts as a cost but also has an effect on the rate of added value recently. Research limitations/implications – Since the three years of 2010, 2015 and 2019 are the target, the data are somewhat insufficient to generalize. Practical implications – As for the value-added ratio of an industry, input is more important than output (sales). Therefore, where the input is received is very important. Social implications – It is possible to increase the understanding of the determinants of the value-added rate of Korean industries. Originality/value – (1) It was clarified which side is inward or outward in determining the industry in Korea. (2) The relationship between PageRank, eigenvector centrality and degree was analyzed in Korean cases. (3) Input is a cost and acts to increase added value.

Grzegorz Dobrowolski