Search results

This study aims to propose a law enforcement strategy for investment fraud through comparative studies in the United States of America (USA), Canada and Indonesia, and to identify the factors that cause weak law enforcement on investment fraud with the object of a binary options case study in Indonesia.

This research is a type of legal research, namely, research based on legal materials (library-based). The legal materials used include primary legal materials and secondary legal materials. The approaches used are the statute approach, the case approach and the comparative approach. The data collection technique used in this research is a literature study. The analysis was carried out qualitatively by using an interactive model.

In 2022, the Indonesian Financial Services Authority (OJK) recorded that the total value of public losses because of investment fraud in Indonesia reached 117.4tn IDR. Weak law enforcement is the reason investment fraud thrives in society. Strategies that can be implemented to prevent investment fraud include early detection of new investment fraud modes through the whistleblower program, mutual legal assistance in criminal matters, criminal restitution and improvement of public financial literacy.

This study examines the problems of law enforcement against investment fraud with a case study of binary options in Indonesia. A law enforcement strategy is built on identifying issues and adopting law enforcement policies against investment fraud in Canada and the USA.

For individuals, the results of this research can be used as reading material to increase their understanding of investment fraud. For the government, the results of this study can be a reference in an effort to eradicate the rise of investment fraud cases more effectively and create a safe digital economic space for investors.

The results of this study are expected to be useful in providing recommendations for strategies to strengthen law enforcement against the problems of investment fraud cases so as to form a conducive investment climate in the sense of being safe, comfortable and profitable.

Legal frameworks to prevent investment fraud are rarely discussed. The rise in binary options cases that occur is an indication of weak law enforcement in the investment sector. Therefore, an in-depth study of law enforcement strategies to prevent investment fraud is needed, with comparative studies in the USA, Canada and Indonesia.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

The human service triad (i.e. the relationship between the customer, frontline employee (FLE) and managerial employee) experiences a range of well-being challenges when faced with the introduction of service robots. Despite growth in service robot scholarship, understanding of the well-being challenges affecting the human service triad remains fragmented. Hence, the purpose of this paper is to synthesise the literature and offer a research agenda aligned with the proposed Robotic-Human Service Trilemma. By taking a job performance approach (which considers the actions, behaviours and outcomes linked to organisational goals), the Robotic-Human Service Trilemma conceptualises three well-being challenges (intrusion, sideline and interchange). These challenges are realised via the realistic capabilities and constraints of service robot implementation.

This research relies on a systematic review of all disciplines concerning service robots. In total, 82 articles were analysed using thematic coding and led to the development of the Robotic-Human Service Trilemma and research agenda.

The analyses reveal the Robotic-Human Service Trilemma consists of three challenges: intrusion, sideline and indifference. The findings demonstrate that FLEs are required to counterbalance the constraints of service robots, leading to an uneven well-being burden within the human service triad. This paper suggests a research agenda for investigation of the challenges that underpin the Robotic-Human Service Trilemma.

Through the conceptualisation of the Robotic-Human Service Trilemma, this study is the first to explore how states of well-being equilibrium exist within the human service triad and how these states are challenged by service robots. The authors present a balanced centricity perspective to well-being that contrasts previous trade-off approaches and that enhances the body of service robot literature with a well-being lens.

As a new research interest, robots have surpassed human performance across several aspects. In this research, the authors wish to investigate whether robot adopters perform better than non-adopters in terms of export behavior, especially when distinguishing between different types of firms.

The authors try a new strategy to identify the extent of robot adoption by import data and compare the export trajectories of robot adopters and non-adopters by employing the propensity score matching-difference in difference (PSM-DID) method.

The authors find that robot adopters are more likely to enter export markets and improve subsequent export performance, as the gains from doing so can spread the reduction in variable production costs to a larger customer base abroad. But this rule does not always seem to work; for large-scale firms, robot adoption makes it easier to win export competition and increase market share, while small and medium-sized enterprises (SMEs) do not seem to enjoy any benefits from adoption. More importantly, robot adoption also leads to the fiercer market competition when improving the productivity of firms, which will threaten smaller non-adopters.

The findings provide new evidence for the scale bias of robotics and offer new insights into whether exporters or future exporters ought to adopt robots in production.

1. First, distinguishing from existing research, we explain the controversial results of previous work on robotics by providing evidence from export markets and using the concept of size bias, which helps to update the theoretical interpretation of robotics and provides new insights for current and future exporters to evaluate their robot adoption decisions.

2. Second, we extend previous research by further considering the potential robotics threats faced by non-adopters, especially we record that export gains of robot adopters are partially at the expense of smaller non-adopters, which provides new evidence for the rationale of SME protection policies and supplements robotics theory with new knowledge, such as the competitive game of firms related to robot adoption.

3. Third, to our knowledge, prior research tended to examine the economic effects of robotics through industry data provided by the IFR, this may lead to systematic bias due to the inability to distinguish the robot adoption intentions of different firms. In this respect, we try a new strategy through robot import data and further distinguish between robot adopters and non-adopters in the sample, which helps to mitigate the potential bias in the findings and provide a complement to the recently developed literature related to robotics.

4. Finally, as we pointed out earlier, robot adoption could be an interesting research work for the Chinese export market, which helps us to obtain some special findings, such as in assessing whether the benefits of robots are equally appropriate for economies that previously had an advantage in terms of labor.

First, distinguishing from existing research, we explain the controversial results of previous work on robotics by providing evidence from export markets and using the concept of size bias, which helps to update the theoretical interpretation of robotics and provides new insights for current and future exporters to evaluate their robot adoption decisions.

Second, we extend previous research by further considering the potential robotics threats faced by non-adopters, especially we record that export gains of robot adopters are partially at the expense of smaller non-adopters, which provides new evidence for the rationale of SME protection policies and supplements robotics theory with new knowledge, such as the competitive game of firms related to robot adoption.

Third, to our knowledge, prior research tended to examine the economic effects of robotics through industry data provided by the IFR, this may lead to systematic bias due to the inability to distinguish the robot adoption intentions of different firms. In this respect, we try a new strategy through robot import data and further distinguish between robot adopters and non-adopters in the sample, which helps to mitigate the potential bias in the findings and provide a complement to the recently developed literature related to robotics.

Finally, as we pointed out earlier, robot adoption could be an interesting research work for the Chinese export market, which helps us to obtain some special findings, such as in assessing whether the benefits of robots are equally appropriate for economies that previously had an advantage in terms of labor.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

This study aims to realize efficient, fast and safe robot search task, the belief criteria decision-making approach is proposed to solve the object search task with an uncertain location.

The study formulates the robot search task as a partially observable Markov decision process, uses the semantic information to evaluate the belief state and designs the belief criteria decision-making approach. A cost function considering a trade-off among belief state, path length and movement effort is modelled to select the next best location in path planning.

The semantic information is successfully modelled and propagated, which can represent the belief of finding object. The belief criteria decision-making (BCDM) approach is evaluated in both Gazebo simulation platform and physical experiments. Compared to greedy, uniform and random methods, the performance index of path length and execution time is superior by BCDM approach.

The prior knowledge of robot working environment, especially semantic information, can be used for path planning to achieve efficient task execution in path length and execution time. The modelling and updating of environment information can lead a promising research topic to realize a more intelligent decision-making method for object search task.

This paper focuses on understanding firm-level determinants of industrial robots' adoption and how these determinants result in heterogenous processes of robotisation across firms within the same sector. The paper presents results from in-depth case studies of final assemblers in the South African automotive sector.

The research has been conducted through multiple case studies with a focus on final assemblers. During the case studies, as well as before and after it, data coming from in-depth semi-structured interviews were triangulated with secondary data available from the international database on industrial robots' adoption and documents provided by firms and institutions.

This paper identifies three firm-level determinants of robotisation – i.e. modularity of the production process, flexibility in the use of technology and stability in product design. The results also showed that firms' robotisation depend on each of these determinants as well as their interdependence. The authors introduce a framework to study interdependence between these technology–organisational choices, which reveals heterogenous patterns of technology deployment and related managerial implications.

This research introduces a new framework on factors driving industrial robotisation – a key digital production technology – and offers empirical evidence of the heterogenous deployment of this technology. The authors identify two main manufacturing approaches to robotisation in the automotive sector: one in which the firm designs a robotised process around a certain product design – i.e. the German/American way and one in which the firm designs its product based on certain robotised processes – i.e. the Japanese way. These findings are valuable for both industry, operational research and the scientific community as they reveal heterogeneity on the “how” of robotisation and implications for manufacturing technology management.

The widespread usage of artificial intelligence (AI) is prompting a number of ethical issues, including those involving concerns for fairness, surveillance, transparency, neutrality and human rights. The purpose of this manuscript is to explore possibility of developing cognitive morality in AI systems.

This is explorative research. The manuscript investigates the likelihood of cognitive moral development in AI systems as well as potential pathways for such development. Concurrently, it proposes a novel idea for the characterization and development of ethically conscious and artificially intelligent robotic machines.

This manuscript explores the possibility of categorizing AI machines according to the level of cognitive morality they embody, and while doing so, it makes use of Lawrence Kohlberg's study related to cognitive moral development in humans. The manuscript further suggests that by providing appropriate inputs to AI machines in accordance with the proposed concept, humans may assist in the development of an ideal AI creature that would be morally more responsible and act as moral agents, capable of meeting the demands of morality.

This manuscript has some restrictions because it focuses exclusively on Kohlberg's perspective. This theory is not flawless. Carol Gilligan, one of Kohlberg's former doctoral students, said that Kohlberg's proposal was unfair and sexist because it didn't take into account the views and experiences of women. Even if one follows the law, they may still be engaging in immoral behaviour, as Kohlberg argues, because laws and social norms are not perfect. This study makes it easier for future research in the field to look at how the ideas of people like Joao Freire and Carl Rogers can be used in AI systems.

It is an original research that derives inspiration from the cognitive moral development theory of American Professor named Lawrence Kohlberg. The authors present a fresh way of thinking about how to classify AI systems, which should make it easier to give robots cognitive morality.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

This paper aims to explore and review the potential of robotic rehabilitation as a treatment approach for Alzheimer’s disease (AD) and its impact on the health and quality of life of AD patients.

The present discourse endeavors to provide a comprehensive overview of extant scholarly inquiries that have examined the salience of inhibitory mechanisms vis-à-vis robotic interventions and their impact on patients with AD. Specifically, this review aims to explicate the contemporary state of affairs in this realm by furnishing a detailed explication of ongoing research endeavors. With the objective of elucidating the significance of inhibitory processes in robotic therapies for individuals with AD, this analysis offers a critical appraisal of extant literature that probes the intersection of cognitive mechanisms and assistive technologies. Through a meticulous analysis of diverse scholarly contributions, this review advances a nuanced understanding of the intricate interplay between inhibitory processes and robotic interventions in the context of AD.

According to the review papers, it appears that implementing robot-assisted rehabilitation can serve as a pragmatic and effective solution for enhancing the well-being and overall quality of life of patients and families engaged with AD. Besides, this new feature in the robotic area is anticipated to have a critical role in the success of this innovative approach.

Due to the nascent nature of this cutting-edge technology and the constrained configuration of the mechanized entity in question, further protracted analysis is imperative to ascertain the advantages and drawbacks of robotic rehabilitation vis-à-vis individuals afflicted with Alzheimer’s ailment.

The potential for robots to serve as indispensable assets in the provision of care for individuals afflicted with AD is significant; however, their efficacy and appropriateness for utilization by caregivers of AD patients must be subjected to further rigorous scrutiny.

This paper reviews the current robotic method and compares the current state of the art for the AD patient.