Time Inconsistency Research Articles

Absolutism and Misguided Policies: Muhammadiyah and NU's Criticism against Government's Handling of COVID-19A

This study examines the role of Islamic Civil Society Organizations (ICSOs), specifically Muhammadiyah and Nahdlatul Ulama (NU), in addressing COVID-19 in Indonesia. In contrast to previous works, it focuses on their constructive criticism against the Indonesian government, which has undergone political absolutism leading to misguided policies in addressing COVID-19 Pandemics. Drawing on theoretical frameworks from Civil Society Organizations, this study shows that the two ICSOs constructively criticized the state for its inadequate, inconsistent, and contradictory policies on handling Covid 19 pandemics caused by political absolutism in the parliament. The results enriched the debate on Islamic Civil Society theories, shedding light on their voluntary and inclusive nature and their intricate relationship with government.

Reasoning on property graphs with graph generating dependencies

Data dependencies are a key concept in data management and have been researched in data integration, data quality and query optimization. With the increasing use of graph-structured data in diverse applications, there is also an increasing interest in the study of graph data dependencies. In this scenario, different classes of graph data dependencies have been proposed in the literature. In this work, we study the class of Graph Generating Dependencies (GGDs). Graph Generating Dependencies (GGDs) informally express constraints between two (possibly different) graph patterns which enforce relationships on both graph's data (via property value constraints) and its structure (via topological constraints). While most of previously proposed classes of graph data dependencies focus on generalizing equality-generating dependencies for graph data, Graph Generating Dependencies (GGDs) can express tuple- and equality-generating dependencies on property graphs, both of which find broad application in graph data management. Given this new class of dependency, in this paper, we discuss the reasoning behind GGDs on Property Graphs. We propose algorithms to solve three main reasoning problems: the satisfiability, implication, and validation problems for GGDs and analyze their complexity. By studying these problems, we can understand the expressiveness and the limitations of GGDs in practical applications. To demonstrate the practical use of GGDs, we propose an algorithm that finds inconsistencies in data through validation of GGDs. Our experiments show that even though the validation of GGDs has high computational complexity, GGDs can be used to find data inconsistencies in a feasible execution time on both synthetic and real-world data.

WTO체제하의 중국 신재생 에너지 자동차 보조금 정책에 관한 연구

Purpose - The purpose of this study is to derive improvement measures for China's renewable energy vehicle subsidy policy under the WTO system. The parts of the new and renewable energy vehicle subsidy system enacted by China that are inconsistent with the WTO subsidy agreement are identified, and policy improvement measures are suggested. Design/Methodology/Approach - This study conducted existing literature studies and case analysis to derive improvement measures for China's renewable energy vehicle subsidy policy under the WTO system. First, the existing literature research analyzed previous studies on the renewable energy vehicle subsidy policy. Second, the case analysis identified the inconsistency of China's renewable energy vehicle subsidy policy with the WTO subsidy agreement based on the results determined in WTO-related dispute cases. Findings - Since it is stipulated that only renewable energy vehicle producers are eligible for subsidies under China's renewable energy vehicle subsidy policy, renewable energy vehicle subsidies establish the specificity specified in the WTO subsidy agreement. Local governments established factories locally and provided subsidies only to renewable energy companies using on-site facilities, which is a prohibited subsidy under the WTO subsidy agreement. Research Implications - First, prohibited subsidies must be removed by expanding the subject of subsidies or changing the payment method. Second, the central government should strengthen the supervisory capabilities of local governments. Third, it is necessary to encourage and expand the introduction of personal capital in the field of renewable energy infrastructure. Fourth, various support measures in addition to the subsidy policy should be added to reduce the suspicion of prohibited subsidies in other countries and promote industrial development.

Optimal Contracts for Time-Inconsistent Consumers with Heterogeneous Beliefs

In many markets (e.g., cell phones, video games), firms offer menus of contracts that include some tariffs charging per-use prices above marginal cost and others below marginal cost. We term this puzzling phenomenon as two-sided deviations from marginal cost pricing and present a potential explanation based on two well-recognized consumer characteristics. The first one is that consumers’ actual consumptions may depart systematically from their initial plans (i.e., time-inconsistent preferences). In addition, consumers can be either sophisticated or naive in their beliefs about their time inconsistency (i.e., heterogenous beliefs). We characterize properties of the optimal contracts for a firm to screen the time-inconsistent consumers with heterogeneous beliefs. We articulate the conditions under which the optimal menu may account for two-sided deviations from marginal cost pricing. We also show that, contrary to intuition, a higher degree of time inconsistency may reduce firm profit and increase social welfare. Meanwhile, reducing consumer naivete may harm the society. Moreover, we confirm that our main results are robust to the presence of time-consistent consumers. This paper was accepted by Dmitri Kuksov, marketing. Funding: This work was supported by the Hunan Provincial Natural Science Foundation of China [Grant 2022JJ40102]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.02653 .

Knowledge Graph Construction and Digital Twin Modeling Integrating Multi-modal Data

Supply chain analytics is focusing more and more attention on industrial logistics. Optimal allocation of assets is severely restricted by the timing inconsistency and geographical instability of industrial logistics assets brought by unpredictability and variability. Unnecessarily lengthy drive distances and lengthy delays are caused by the incapacity to acquire and utilize industrial logistics asset spatial-and-temporal (ST) qualities rationally, which affects the processes' potential to operate sustainably. Thus, for efficient usage of resources in industrial logistics, a novel machine learning (ML)-assisted knowledge graph (ML-KG) design is provided in this work. For evaluating the multi-modal data produced by widely deployed IoT devices, a novel customizable diversified kernelized support vector machine (CDK-SVM) approach is also suggested. After establishing the suggested ML-KG framework for ST integrity in the representation of the digital twin version, links are carried out and reasoning is performed using job data related to industrial logistics. The graph mechanism effectively distributes the industrial logistics resources. Lastly, the outcome proves that the suggested process is successful in the distribution of industrial logistics assets.

LVI-Fusion: A Robust Lidar-Visual-Inertial SLAM Scheme

With the development of simultaneous positioning and mapping technology in the field of automatic driving, the current simultaneous localization and mapping scheme is no longer limited to a single sensor and is developing in the direction of multi-sensor fusion to enhance the robustness and accuracy. In this study, a localization and mapping scheme named LVI-fusion based on multi-sensor fusion of camera, lidar and IMU is proposed. Different sensors have different data acquisition frequencies. To solve the problem of time inconsistency in heterogeneous sensor data tight coupling, the time alignment module is used to align the time stamp between the lidar, camera and IMU. The image segmentation algorithm is used to segment the dynamic target of the image and extract the static key points. At the same time, the optical flow tracking based on the static key points are carried out and a robust feature point depth recovery model is proposed to realize the robust estimation of feature point depth. Finally, lidar constraint factor, IMU pre-integral constraint factor and visual constraint factor together construct the error equation that is processed with a sliding window-based optimization module. Experimental results show that the proposed algorithm has competitive accuracy and robustness.

Entangled in complexity: An ethnographic study of organizational adaptability and safe care transitions for patients with complex care needs.

The aim of this study was to visualize vulnerabilities and explore the dynamics of inter-professional collaboration and organizational adaptability in the context of care transitions for patients with complex care needs. An ethnographic design using multiple convergent data collection techniques. Data collection involved document review, participant observations and interviews with healthcare and social care professionals (HSCPs). Narrative analysis was employed to construct two illustrative patient scenarios, which were then examined using the Functional Resonance Analysis Method (FRAM). Thematic analysis was subsequently applied to synthesize the findings. Inconsistencies in timing and precision during care transitions pose risks for patients with complex care needs as they force healthcare systems to prioritize structural constraints over individualized care, especially during unforeseen events outside regular hours. Such systemic inflexibility can compromise patient safety, increase the workload for HSCPs and strain resources. Organizational adaptability is crucial to managing the inherent variability of patient needs. Our proposed 'safe care transition pathway' addresses these issues, providing proactive strategies such as sharing knowledge and increasing patient participation, and strengthening the capacity of professionals to meet dynamic care needs, promoting safer care transitions. To promote patient safety in care transitions, strategies must go beyond inter-professional collaboration, incorporating adaptability and flexible resource planning. The implementation of standardized safe care transition pathways, coupled with the active participation of patients and families, is crucial. These measures aim to create a resilient, person-centred approach that may effectively manage the complexities in care transitions. The recommendations of this study span the spectrum from policy-level changes aimed at strategic resource allocation and fostering inter-professional collaboration to practical measures like effective communication, information technology integration, patient participation and family involvement. Together, the recommendations offer a holistic approach to enhance care transitions and, ultimately, patient outcomes. Findings are reported per the Consolidated Criteria for Reporting Qualitative research (COREQ). No patient or public contribution.

Understanding the Impact of Visual and Kinematic Information on the Perception of Physicality Errors

Errors that arise due to a mismatch in the dynamics of a person’s motion and the visualized movements of their avatar in virtual reality are termed ‘physicality errors’ to distinguish them from simple physical errors, such as footskate. Physicality errors involve plausible motions, but with dynamic inconsistencies. Even with perfect tracking and ideal virtual worlds, such errors are inevitable in virtual reality whenever a person adopts an avatar that does not match their own proportions or lifts a virtual object that appears heavier than the movement of their hand. This study investigates people’s sensitivity to physicality errors in order to understand when they are likely to be noticeable and need to be mitigated. It uses a simple, well-understood exercise of a dumbbell lift to explore the impact of motion kinematics and varied sources of visual information, including changing body size, changing the size of manipulated objects, and displaying muscular strain. Results suggest that kinematic (motion) information has a dominant impact on perception of effort, but visual information, particularly the visual size of the lifted object, has a strong impact on perceived weight. This can lead to perceptual mismatches which reduce perceived naturalness. Small errors may not be noticeable, but large errors reduce naturalness. Further results are discussed, which inform the requirements for animation algorithms.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations.

The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerningwhich diseases and policy decisions they will be helpful for.

INTERTEMPORAL CONSUMPTION WITH ANTICIPATING, REMEMBERING, AND EXPERIENCING SELVES

AbstractWe study intertemporal choice through a novel and flexible framework that accounts for savoring of future consumption and memories of past consumption. The model uses standard intertemporal budget constraints but enriches preference structures with utility from anticipation, remembering, and experience. We also present an internal commitment mechanism that ensures dynamic consistency. We provide a revealed preference characterization of this model and apply it to quarterly consumption data from Spanish households. Utility from anticipation is important—and time inconsistency not strictly needed—to rationalize consumption patterns in the data.

EXPLORING HOW ELEMENTARY SCHOOL PRINCIPALS USE SCHOOL-BASED MANAGEMENT TO LEAD ADAPTIVELY

The literature review explores School-Based Management (SBM) in education, highlighting its potential benefits and significant challenges. Mandated by Republic Act 9155, SBM aims to empower school leaders with greater authority and accountability for improving learning outcomes. However, several formidable obstacles hinder effective SBM implementation. Schools often grapple with resource constraints, including limited financial, material, and human resources, which impede their full engagement in SBM initiatives. Moreover, insufficient training and capacity-building efforts for stakeholders hinder their ability to navigate decentralized decision-making processes effectively. Weak mechanisms for monitoring and evaluating SBM initiatives further hamper accountability and oversight. Stakeholder resistance to change poses a significant barrier to the adoption of SBM practices, while inconsistent policies and practices lead to fragmented implementation, undermining its coherence and effectiveness. Additionally, insufficient community engagement diminishes the participatory nature of SBM, hindering alignment with local needs and priorities. Despite these challenges, SBM remains a valuable mechanism for driving educational improvement. Addressing these barriers requires concerted efforts to strengthen support systems, enhance capacity-building initiatives, foster collaboration, and promote equity and inclusion. Continued research, policy advocacy, and concerted action are essential for sustaining SBM initiatives and fostering holistic educational development. By leveraging insights from this review, stakeholders can navigate the complexities of SBM implementation and work towards enhancing student outcomes and fostering inclusive and responsive educational systems.

Procrastination and intertemporal consumption: A three-period extension of the CAPM with irrational agents

In this paper, we investigate the capital asset pricing model (CAPM) derived from a three-period general equilibrium model incorporating time-inconsistent preferences. We define and consider two types of agents, i.e. they can be either sophisticated or naive. Sophisticated agents take into account their potentially changing future preferences when making a decision. Naive agents, on the other hand, do not anticipate this issue and their related self-control problems when they plan the consumption path.We demonstrate that the derivation of the CAPM equation can be achieved even if the agents in the financial economy have time-inconsistent preferences.

Sustainable Development and Renewable Energy Policy: A Review of Global Trends and Success Stories

As the world grapples with the pressing challenges of climate change and environmental degradation, the imperative for sustainable development and the adoption of renewable energy policies has become increasingly apparent. This comprehensive review explores the global landscape of sustainable development and renewable energy policies, shedding light on emerging trends and success stories that offer valuable insights for policymakers, researchers, and practitioners. The paper begins by examining the evolving international discourse surrounding sustainable development, emphasizing the crucial role of renewable energy in mitigating the adverse effects of climate change. It delves into the key principles and frameworks that guide global efforts towards sustainable development, highlighting the interconnectedness of economic, social, and environmental dimensions. The review identifies and analyzes the diverse approaches and strategies employed by countries worldwide to integrate renewable energy into their policy frameworks. Case studies from various regions showcase successful initiatives, emphasizing the impact of well-designed policies on fostering a transition to cleaner and more sustainable energy systems. Examples of effective policy instruments, such as feed-in tariffs, renewable energy targets, and innovative financing mechanisms, are explored to provide a nuanced understanding of the factors contributing to success. Furthermore, the review critically assesses the challenges and barriers hindering the widespread adoption of renewable energy policies, including policy inconsistencies, technological constraints, and socio-economic factors. Insights gained from the analysis offer valuable lessons for refining existing policies and developing new strategies to accelerate the global shift towards sustainable and renewable energy solutions. This review serves as a comprehensive resource for policymakers, researchers, and stakeholders, offering a nuanced understanding of the current global trends in sustainable development and renewable energy policies. By drawing upon success stories and identifying key challenges, it provides a roadmap for fostering effective and scalable solutions to address the urgent need for a sustainable energy future.

The complex web of land use planning, legislation and urban mobility in Maseru, Lesotho

Applying an exploratory case study design, the study analyses urban mobility along the Main North 1 Road. We argue that urban mobility in Maseru, Lesotho is compromised by a complex web of issues including inconsistent urban transport policies, inadequate road infrastructure, and land use activities along some roads. Data were collected from primary and secondary sources, including key informant interviews, direct observations, and a review of policy documents on urban mobility. We show that urban mobility along the Main North 1 Road is jeopardised by outdated land use planning schemes and legislation that are out of sync with local realities as they support vehicular movement while neglecting pedestrians’ needs, compromising their safety. The state of the infrastructure also contributes to urban mobility inefficiencies. The study concludes that the urban mobility system needs to be understood holistically to identify leverage points critical for interventions and planning for sustainable urban mobility.

Towards a public sustainable finance paradigm for the green transition

AbstractSustainable finance is often discussed as a solution to the climate crisis, but its impacts are limited and its discourse focuses on mobilising private investments through public de-risking, without considering direct government action. We argue that this is due to an implicit reference to mainstream economic theory assuming that an active state leads to time inconsistency problems and crowding-out effects. However, these assumptions have been sufficiently refuted as public investments may actually crowd-in private capital. We therefore propose a paradigm shift towards what we call Public Sustainable Finance, aimed at empowering the role of the state in the green transition on the discursive, policy, and political economy levels. Studying the case of Germany, we show how Public Sustainable Finance can be introduced despite tight fiscal regimes. To this end, we propose that the Climate- and Transformation Fund be given its own borrowing powers. By borrowing an average of 23 billion euros annually from 2024 to 2030, the existing financing gap that has been exacerbated following the November 2023 constitutional court ruling can be closed, enabling a more rapid and effective green transition.

A fuzzy description logic based IoT framework: Formal verification and end user programming.

The Internet of Things (IoT) has become one of the most popular technologies in recent years. Advances in computing capabilities, hardware accessibility, and wireless connectivity make possible communication between people, processes, and devices for all kinds of applications and industries. However, the deployment of this technology is confined almost entirely to tech companies, leaving end users with only access to specific functionalities. This paper presents a framework that allows users with no technical knowledge to build their own IoT applications according to their needs. To this end, a framework consisting of two building blocks is presented. A friendly interface block lets users tell the system what to do using simple operating rules such as "if the temperature is cold, turn on the heater." On the other hand, a fuzzy logic reasoner block built by experts translates the ambiguity of human language to specific actions to the actuators, such as "call the police." The proposed system can also detect and inform the user if the inserted rules have inconsistencies in real time. Moreover, a formal model is introduced, based on fuzzy description logic, for the consistency of IoT systems. Finally, this paper presents various experiments using a fuzzy logic reasoner to show the viability of the proposed framework using a smart-home IoT security system as an example.

The Impact of Integrated Patient Education on Short-Term Revisit Rates in Healthcare Settings: A Quality Improvement Project.

Patient education plays a critical role in healthcare, influencing outcomes and resource utilization. However, effectively integrating patient education into clinical practice remains challenging due to time constraints and inconsistencies in information delivery. Enhancements in Electronic Health Records (EHR) offer potential solutions by facilitating customized, quality education delivery. This study investigates the impact of an EHR-enhanced patient education intervention on short-term revisit rates to healthcare facilities. A quasi-experimental, pre-test/post-test design without a control group was employed at the International Medical Center in Riffa, Bahrain. The intervention consisted of modifications to the EHR system to support patient education, along with staff training on effective education delivery. Patient revisit rates within seven days post-consultation were compared before and after the intervention using chi-square tests and logistic regression, adjusting for potential confounders. A total of 1,239 patients participated in the study, which was divided into two groups: 754 patients in the pre-intervention group and 485 patients in the post-intervention group. A significant change was observed in the patient revisit rates: in the pre-intervention group, 53.32% of patients (402 out of 754) returned within seven days, compared to 41.44% of patients (201 out of 485) in the post-intervention group, with a p-value < 0.01. Enhancements to EHR systems, combined with comprehensive staff education on patient education, can lead to significant reductions in short-term patient revisits. This underscores the importance of integrating technological and educational interventions in healthcare settings to improve patient outcomes and efficiency.

Influence of Cultural Factors and Regulatory Policies on Uptake of Life Assurance Products in Kenya

Life assurance products have been used over the years as both an instrument of protection and a tool for investment. Cultural factors feature prominently among the factors that influence the uptake of Life assurance. This study sought to establish the influence of cultural factors on the uptake of Life assurance products in Kenya, moderated by Regulatory policies. The study was anchored on the Human Life Value Theory. The independent variables in the study were the Cultural factors, the dependent variable was the uptake of Life Assurance products, and the moderating variable was regulatory policies. The study employed a Descriptive survey research design and was quantitative in nature. The sample size of the study was 537 respondents calculated using the Taro Yamane (1970) formula from a study population of 6376 Public Primary school teachers in Kisumu County. The study used primary data, which was collected using a closed-ended questionnaire. The data was analyzed using descriptive statistics, correlation, and regression. The findings indicated that there is a significant relationship between Cultural factors and Life Assurance product uptake among policyholders in Kisumu County, where Cultural factors alone could explain 30.1 percent of the variance in the uptake of Life Assurance products. Equally, there is a strong relationship between Cultural factors, regulatory policies, and uptake of Life Assurance products. The study resolved inconsistencies in theory, policy, and practice, thereby bolstering the argument that insurance companies should consider Cultural factors that increase the use of life assurance products.

Journalistic Construction of Reporting on Covid-19 in Online Media

The Covid-19 pandemic is a global outbreak that has significantly changed people's social lives. The complexity of this issue has caused the coverage of Covid-19 to be dominant with negative news. Negative news can produce various psychological disorders that make readers avoid the news. The news media thus has a significant role in bridging society's adaptation to new patterns of life during the pandemic and adaptation to inconsistent government policies in dealing with the Covid-19 pandemic. Therefore, it is important for the news media to be able to bridge government policies with the psychological conditions of people affected by the pandemic. In this research study, constructive journalism can be one solution to overcome this problem. Through constructive journalism, the journalist's job is not only to focus on negative things but also on solutions and positive sides when covering news. Quantitative content analysis was used in this research by applying six elements of constructive journalism to 7 covid-19 articles published by CNN.com in 2020-2022. The research results show that news articles about Covid-19 on CNN.com are not constructive. All elements of constructive journalism found in these articles are below 50%. The element with the highest percentage found was The Rosling (47%) The lowest element found in covid-19 articles on CNN.com was the co-creation element at 9%.

EU delegations as intermediaries of perceptions of the EU: A view from the MENA region

ABSTRACT The European Commission in its 2015 study on the perceptions of the EU acknowledged that mutual perceptions held by actors in the international arena affect their expectations about the other’s behaviour and hereby guide the interpretation of the other’s actions. Knowledge of how and what image of the MENA countries and of the EU is conveyed by country delegations is important for understanding whether the information that influences EU foreign policy-making is representative, and of whom. EU delegations are an acknowledged source of knowledge that feed into EU policymaking, and proposals have even been made for strengthening their role. Based on interviews with heads of delegations/Ambassadors in 2021, four interlinked categories of concerns affecting the perceptions of the EU are identified: historical legacy; knowledge about and expectations towards the Union; competing values and aims; and the EU’s internal policy inconsistencies. The findings in the interviews are contextualized through an analysis of previous research on the perceptions of the EU. Further, the article discusses the role of delegations in EU policy-making and invites to take a critical view of Ambassadors´ ‘perceptions of the perceptions of the EU’.