Intervention In Decision-making Research Articles

Applying Design Thinking to Develop AI-Based Multi-Actor Decision-Support Systems: A Case Study on Human Capital Investments

Artificial intelligence, particularly machine learning, has revolutionized organizational decision-making processes by assuming many decision responsibilities traditionally allocated to humans. In this scenario, decision-support systems based on AI have gained considerable relevance, although the attitudes of managers toward intelligent agents are still unbalanced towards human intervention in decision-making. An additional level of complexity arises when the development of these systems occurs within the context of investments in human capital, such as startup funding or organizational development. In this field, decision-making becomes even more critical, since it implies the will, goals, and motivations of every human actor involved: the investors and those seeking investments. termed multi-actor decision-making, this process involves multiple individuals or groups of individuals who, starting from non-coincident objectives, must reach a mutual agreement and converge toward a common goal for the success of the investment. Considering these challenges, this study aims to apply the design thinking technique as a human-centered methodology to support the design of an AI-based multi-actor decision-support system, conceived by Mylia (The Adecco Group), in the field of organizational development. Additionally, the integration of strategic organizational counseling will be introduced to facilitate the modeling of internal DM processes within the provider organization, enabling the seamless flow of internal behaviors from the decision-support system’s conceptualization to its integration in the external market.

Differences in information processing between experienced investors and novices, and intervention in fund investment decision-making

Differences in information processing between experienced investors and novices, and intervention in fund investment decision-making

How robust are current narratives to deal with the urban energy-water-land nexus?

Current energy, water, and land (EWL) nexus research treats all resources equally, causing bias in complicated nexus studies. To make the analysis robust, we consider resource endowment and significance. Here, we provide a methodological framework where the urban industrial resource nexus strength is constructed and assign weights to resources according to policies, describing resource efficiency and representing it in ternary diagrams to assess the urban industrial nexus innovatively. Results showed that energy drives urban development under all weights, with energy resource efficiency exceeding 60%. From consumption-based accounting, energy continues to dominate most industries under physical weightings but emphasizes the significance of water and land. While, under economic weightings, land supplants energy's dominance in specific sectors. Setting weights helps understand resource interaction, establish synergy based on urban development objectives, and minimize robustness. Our findings provide quantitative evidence for assessing urban resource efficiency to highlight priority sectors for intervention in urban decision-making.

Changes and improvements in Industry 5.0: A strategic approach to overcome the challenges of Industry 4.0

Industry 4.0 has introduced new technological advances such as Additive Manufacturing (AM), Artificial Intelligence (AI), Augmented Reality (AR), Cyber–physical systems (CPS), Blockchain, Cybersecurity and many more. It is also helping organisations to take on challenges like demand fluctuations and market volatility. Industry 4.0 is also the interconnection of computers, materials, and AI with minimal human intervention in decision-making. Although Industry 4.0 has tremendous potential for industrial growth, it has many challenges, such as technical integration, human resource issue, supply chain issues and data security. These challenges are expected to be addressed in the future by Industry 5.0 Industry 5.0 introduced various new technologies such as Predictive maintenance, Hyper customisation in the Industry, Cyber–Physical Cognitive systems, and the introduction of Collaborative Robots. Industry 5.0, with its human-centric approach, helped overcome the various challenges of Industry 4.0. In Industry 4.0, the focus was on sustainability and production volume, whereas in Industry 5.0, the primary focus is on human centricity. This paper’s literature review has been done by considering the findings and results discussed in various latest literature. We have listed various technological developments in Industry 5.0 and the advancements to the technologies of Industry 4.0. Industry 5.0 has tackled various issues faced in Industry 4.0, such as data privacy and technical integration issues. Resilience is also one of the critical aspects of Industry 5.0, which contributed towards hyper individualisation and helped make individualised products with specific user needs. This study would provide a base for the researchers and industries to get acquainted with Industry 4.0 technologies, their challenges, the technological advances, and the ways Industry 5.0 overcame the challenges of Industry 4.0. This paper also lists the recent application of these technologies, which would provide an idea of how these technologies can be implemented. Further, the limitations of these studies have been listed, providing an opportunity for future research in this domain. This paper provides a structured review of the technologies of Industry 4.0, the challenges they faced and how they can be removed through the technological advancements of Industry 5.0.

Presentation of a Conceptual Model for Central Bank Supervision over Banks with a Grounded Theory Approach

Objective: The aim of this research was to present a conceptual model for Central Bank supervision over banks with a grounded theory approach. Method: In this study, the grounded theory research approach based on parametric methods is employed. The statistical population of this research comprises experts and professionals in the field of central banking, capable of providing valuable information to the researcher. Sampling in this research has been conducted purposively. For this purpose, the qualitative samples of this research consist of 15 experts and professionals knowledgeable in the field of central banking. Data analysis of this research has been performed following the procedures of Strauss and Corbin (2011) at the Central Bank. Findings: According to the findings of the current research, factors such as government ownership in banks and changes in bank ownership, the impact of general economic conditions, the role of governance and government in supervision, government intervention in decision-making and management of the banking system, and the necessity of consistency and unity of approach in supervision are influential as intervening conditions on the strategies of the supervisory model. Further, the readiness of managers and experts in the banking system to accept the model, creating economic and social conditions meaning stability in the economic situation based on macroeconomic variables, attention to the characteristics of the banking industry as intermediaries in allocating surplus resources of some economic sectors to others in need of financial resources, and defining a suitable position for the supervisory institution in terms of ensuring the independence of the supervisory body, and providing sufficient authority in supervision were contextual conditions. Then, strategies for the success of the supervisory model were presented, including the identification and assessment of major risks in the banking industry such as credit risk, liquidity risk, market risk, and operational risk, in terms of structure and risk management methods, related analyses, and their impact on the future outlook of each bank's activities. Conclusion: Strategic analyses regarding the distribution of granted loans, commitments, investments in affiliated companies, and the status of bank reserves, assets, and collaterals, and the presentation of precautionary plans during economic shocks or potential crises are among the strategies of each bank.

A Novel Machine Learning–Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform

Machine learning is a technique for analyzing data that aids the construction of mathematical models. Because of the growth of the Internet of Things (IoT) and wearable sensor devices, gesture interfaces are becoming a more natural and expedient human-machine interaction method. This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns. The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition. Potential applications of hand gesture recognition research span from online gaming to surgical robotics. The location of the hands, the alignment of the fingers, and the hand-to-body posture are the fundamental components of hierarchical emotions in gestures. Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition. Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition. In this scenario, it may be difficult to overcome segmentation uncertainty caused by accidental hand motions or trembling. When a user performs the same dynamic gesture, the hand shapes and speeds of each user, as well as those often generated by the same user, vary. A machine-learning-based Gesture Recognition Framework (ML-GRF) for recognizing the beginning and end of a gesture sequence in a continuous stream of data is suggested to solve the problem of distinguishing between meaningful dynamic gestures and scattered generation. We have recommended using a similarity matching-based gesture classification approach to reduce the overall computing cost associated with identifying actions, and we have shown how an efficient feature extraction method can be used to reduce the thousands of single gesture information to four binary digit gesture codes. The findings from the simulation support the accuracy, precision, gesture recognition, sensitivity, and efficiency rates. The Machine Learning-based Gesture Recognition Framework (ML-GRF) had an accuracy rate of 98.97%, a precision rate of 97.65%, a gesture recognition rate of 98.04%, a sensitivity rate of 96.99%, and an efficiency rate of 95.12%.

The Legitimacy of Artificial Intelligence in Judicial Decision Making

Since the birth of artificial intelligence, the discussion of the legitimacy of its application to judicial scenarios has never stopped. The domestic academic circles question the legality of artificial intelligence decision-making mainly embodies four aspects: the judge's subjectivity crisis, the power legitimacy crisis, the imputation difficulty crisis, and the damage to the justice realization crisis. Therefore, it is urgent to clarify the legal logic of artificial intelligence in judicial decision-making and clarify its decision-making limits. Therefore, this paper aims to prove the legality of intelligent judicial operation simultaneously from the four-dimensional perspectives of artificial intelligence's intervention in judicial decision-making, such as the judge's subjectivity, the legitimacy of power, the attribution of fault, and the realization of justice, with a view to the subject, power, responsibility, justice, four aspects of the governance of China's intelligent judiciary to make recommendations.

Do dividends signal safety? Evidence from China

Our paper examines whether dividends convey information about future cash-flow volatility in the Chinese stock markets. We observe that dividend changes are followed by cash-flow-volatility changes in the opposite direction. Taking advantage of the unique context of China, we show, in both the two-way sorting analysis and the regression analysis, that the strong relation between changes in dividend and cash-flow volatility is robust after controlling for potential confounders, including firm-level financial market frictions, macroeconomic and market conditions, and government intervention in firms' decision-making, and holds after we control for endogeneity concerns. Furthermore, we perform the theoretic mechanism tests of the relation and present supporting evidence on the signaling theory under the setting of asymmetric information, instead of the free cash flow theory based on the assumption of agency conflict. This study enriches our understanding of the source and nature of cash-flow information contained in dividends.

Robust Botnet DGA Detection: Blending XAI and OSINT for Cyber Threat Intelligence Sharing

We investigated 12 years DNS query logs of our campus network and identified phenomena of malicious botnet domain generation algorithm (DGA) traffic. DGA-based botnets are difficult to detect using cyber threat intelligence (CTI) systems based on blocklists. Artificial intelligence (AI)/machine learning (ML)-based CTI systems are required. This study (1) proposed a model to detect DGA-based traffic based on statistical features with datasets comprising 55 DGA families, (2) discussed how CTI can be expanded with computable CTI paradigm, and (3) described how to improve the explainability of the model outputs by blending explainable AI (XAI) and open-source intelligence (OSINT) for trust problems, an antidote for skepticism to the shared models and preventing automation bias. We define the XAI-OSINT blending as aggregations of OSINT for AI/ML model outcome validation. Experimental results show the effectiveness of our models (96.3% accuracy). Our random forest model provides better robustness against three state-of-the-art DGA adversarial attacks (CharBot, DeepDGA, MaskDGA) compared with character-based deep learning models (Endgame, CMU, NYU, MIT). We demonstrate the sharing mechanism and confirm that the XAI-OSINT blending improves trust for CTI sharing as evidence to validate our proposed computable CTI paradigm to assist security analysts in security operations centers using an automated, explainable OSINT approach (for second opinion). Therefore, the computable CTI reduces manual intervention in critical cybersecurity decision-making.

Analysis of Students’ Causal Reasoning in Physics Problem Solving

This research was aimed to describe the causal reasoning of students in physics problem-solving. The research subjects were students of Physics Education Study Program of Universitas Tadulako. The research respondents consisted of two students obtained through a selection test of respondents representing the categories of high ability. Data collection through thinking-aloud activity and it was followed by an interview. The thinking-aloud data were analyzed according to Pearl which illustrates how students use students’ causal reasoning in solving the problem. Based on data analysis it can be concluded that causal reasoning has an important role for students when solving the problem. The causal reasoning process conducted by the respondents through the collection of information from the problem; structural equalization of the problem elements with elements of events known by the respondents; reviewed information for the provision of intervention or manipulation in the appropriate decision-making; and made a conclusion by considering a paradox and conflicting of the data on the problem.

El interés del menor. Criterios de determinación y aplicación en casos concretos

This article analyses the criteria incorporated into the new art. 2 LOPJM with the purpose of facilitating the determination of the minor’s best interests. Firstly, it aims to provide some general guidelines that are applicable in cases where con?ict between these criteria arise. The article goes on to examine the impact that some of these criteria may have when the Admin- istration adopts a measure to protect a minor and then proceeds to study other criteria of higher incidence when the minor’s representative must make a decision regarding the minor, due to his lack of maturity. In particular, the modi?cation made by the laws of 2015 in Law 41/2002 on Patient Autonomy and LO 2/2010 on Sexual and Reproductive Health is analysed, because these amendments broaden paternal intervention in decision-making, while limiting, to some extent, the capacity of minors to decide for themselves.

Revisiting Minors’ Reproductive Autonomy Rights under South African Law: The Rights and Wrongs of the Choice on Termination of Pregnancy Act

This article examines the interface between children’s autonomy, parental responsibility and state intervention in reproductive decisions of a particular type, namely the termination of pregnancy. Children asserting their autonomy in reproductive decision-making often confront counterclaims of legitimate intervention by parents or guardians responsible for caring for the child. Locating the right balance between competing interests is very important because uninformed decisions, with or without the support of parents, often carry heavy consequences for the education, health and life of the pregnant child. More specifically, this article seeks to investigate the extent to which South African law protects and empowers sexually active adolescents to make decisions concerning the termination of pregnancy. This involves an analysis of the degree to which relevant legislation appropriately reconciles children’s reproductive autonomy rights–—particularly the right to terminate a pregnancy without parental consent or approval–—with parental responsibility and state intervention. Parental responsibility and state intervention embody children’s right to and need for protection (from the immaturity that characterises youth) when decisions to terminate pregnancies are made. Accordingly, this article focuses on whether or not the Choice on Termination of Pregnancy Act strikes an appropriate balance between children’s autonomy, parental responsibility and state intervention in reproductive decision-making.

Investigating the value of integrated operations planning: A case-based approach from automotive industry

During the last decade, many researchers have focused on joint consideration of various operations planning aspects like production scheduling, maintenance scheduling, inventory control, etc. Such joint considerations are becoming increasingly important from the point of view of current advancement in intelligent manufacturing, also known as Industry 4.0. Under the concept of Industry 4.0, advanced data analytics aim to remove human intervention in decision-making. Thus, the managerial level coordination of decisions taken independently by various departments will be out of trend. Therefore, developing an approach that optimises various operations planning decisions simultaneously is essential. Available literature on such joint considerations is more of the exploratory in nature and is limited to simplistic production environments. This necessitates the investigations of value of integrated operations planning for wide range of manufacturing scenarios. Present paper adopts a case-oriented approach to investigate the value of integrated operations planning. First, an integrated approach for simultaneously determining job sequencing, batch-sizing, inventory levels and preventive maintenance schedule is developed. The approach is tested in a complex production environment of an automotive plant and substantial economic improvement was realised. Second, a comprehensive evaluation is performed to study the robustness and implications of proposed approach for various production scenarios. Results of such pervasive performance investigations confirm the value of proposed approach over conventional approaches.

The effect of small-sided games with different levels of opposition on the tactical behaviour of young footballers with different levels of sport expertise.

To optimize players' tactical abilities, coaches need to design training sessions with representative learning tasks, such as, small-sided games. Moreover, it is necessary to adapt the complexity of the tasks to the skill level of the athletes to maximally improve their perceptual, visual and attentive abilities. The objective of this study was to analyze the effect of two teaching programs, each utilizing modified games with varied levels of opposition, on decision-making and action execution in young players with different levels of sports expertise. 19 football players (U12), separated into two ability groups (Average versus Low skill-level), participated in a series of training sessions that were spread over 4 phases: Pre-intervention 1, Intervention 1 (teaching program based on modified games with numerical superiority in attack), Pre-intervention 2 and Intervention 2 (teaching program based on modified games with numerical equality). Each intervention phase lasted 14 sessions. Decision-making and the execution of pass action during league matches over the same period were evaluated using the Game Performance Evaluation Tool (GPET). The Average skill-level group showed significant differences after the first intervention in decision-making and execution of the pass action (decision-making, p = .015; execution, p = .031), but not after the second intervention (decision-making, p = 1.000; execution, p = 1.000). For the Low skill-level group, significant differences were only observed in the execution of passing between the first and last phases (p = .014). These findings seem to indicate that for groups with an average level of expertise, training with numerical superiority in attack provides players with more time to make better decisions and to better execute actions. However, for lower-level groups programs may take longer to facilitate improvement. Nevertheless, numerical equality did not result in improvement for either group.

What gets left behind for future generations? Reproduction and the environment in Spey Bay, Scotland

What gets left behind for future generations? Reproduction and the environment in Spey Bay, Scotland

Executive Control of Administrative Action: 'Cabinet Appeals' and the CRTC

The statutory provisions that empower the federal Cabinet to review decisions of the Canadian Radio-television and Telecommunications Commission in telecommunications and broadcasting matters are frequently criticized because of the perception that Cabinet intervention in the regulatory process poses a threat to the independence of the regulator and the integrity of its process. Although reforms have been adopted to address concerns about the lack of procedural fairness in the Cabinet appeal process, these have not allayed more fundamental concerns about the legitimacy of Cabinet intervention. The author examines issues such as the frequency of Cabinet intervention in CRTC decision-making, how the pattern of interventions has evolved over time under successive governments, and the nature of the issues on which Cabinet has intervened to assist understanding of the degree of political intervention in CRTC decision-making and its implications. The author argues that the status quo, which relies heavily on ex post Cabinet review of individual CRTC decisions, is seriously flawed. He presents some specific suggestions for reform that involve limiting the range of issues on which Cabinet may intervene in telecommunications cases and adopting procedural safeguards, based on those that already apply in the issuing of Cabinet directions to the CRTC, that would apply to reviews of decisions in both telecommunications and broadcasting cases.

Government intervention and firm investment: Evidence from international micro-data

Building on the important study by Beck et al. (2005), we examine how government intervention in firms' decision-making is related to their investment and sales growth. Using the unique World Bank dataset (WBES) covering 6500 firms in 70 countries, we find strong evidence that the extent of government intervention in firms' investment, employment, sales, pricing, dividend, and merger and acquisition decisions is negatively related to their investment and sales growth, with the effect being more profound in foreign owned firms and less significant in state-owned firms. The empirical results are robust to a series of robustness tests and instrumental variable regressions.

Is Mandatory Neonatal Eye Prophylaxis Ethically Justified? A Case Study from Canada

This article examines whether a policy of mandatory neonatal eye prophylaxis is ethically justified within the Canadian context. An existing framework for public health ethics is used to examine criteria that would justify state intervention in parental decision-making authority in order to protect public health. The benefits, harms, and utility of mandatory neonatal eye prophylaxis are described. Established criteria for the infringement of basic individual liberties in the interests of public health, including effectiveness, proportionality, necessity, least infringement and public justification, are considered. The extent and limits of parental decision-making authority are then discussed, and conditions that warrant state intervention in parental decision-making based on the harm principle are reviewed. Ultimately, infringement of parental authority is not deemed to be necessary to protect public health or to protect the newborn in this case and existing circumstances do not meet any criteria that would justify such an infringement. Mandatory eye prophylaxis is found not to be ethically justified in the current Canadian context.

The function of kishomon in early medieval Japan : The roles of divine intervention and secular reason in legal decision-making

The function of kishomon in early medieval Japan : The roles of divine intervention and secular reason in legal decision-making

Public Law and The Executive

The contemporary public law jurisprudence of the High Court has transformed the basis of judicial review of executive action, removed traditional restraints on the scope of executive power, reinforced the separation of powers, and transformed the federal compact by identifying new constitutional limits on State institutions. The High Court has, over the last two decades, emphasised the constitutional dimension of a number of terms found in the Constitution by characterising them as “constitutional expressions”. These expressions have been imbued with substantive force by identifying a bundle of essential characteristics of each such expression, being characteristics that Parliament cannot alter. The impact of this new approach on executive power has been the emergence of a constitutional foundation for Commonwealth and State administrative law, a renewed focus on the constitutional foundation of executive authority, and the extension of the separation of powers doctrine to State institutions. This development is of profound significance for the entire range of interaction between the judiciary and executive government.