Group Of Decision Makers Research Articles

We need to aim at the top: Factors associated with cybersecurity awareness of cyber and information security decision-makers.

Cyberattacks pose a significant business risk to organizations. Although there is ample literature focusing on why people pose a major risk to organizational cybersecurity and how to deal with it, there is surprisingly little we know about cyber and information security decision-makers who are essentially the people in charge of setting up and maintaining organizational cybersecurity. In this paper, we study cybersecurity awareness of cyber and information security decision-makers, and investigate factors associated with it. We conducted an online survey among Slovenian cyber and information security decision-makers (N = 283) to (1) determine whether their cybersecurity awareness is associated with adoption of antimalware solutions in their organizations, and (2) explore which organizational factors and personal characteristics are associated with their cybersecurity awareness. Our findings indicate that awareness of well-known threats and solutions seems to be quite low for individuals in decision-making roles. They also provide insights into which threats (e.g., distributed denial-of-service (DDoS) attacks, botnets, industrial espionage, and phishing) and solutions (e.g., security operation center (SOC), advanced antimalware solutions with endpoint detection and response (EDR)/extended detection and response (XDR) capabilities, organizational critical infrastructure access control, centralized device management, multi-factor authentication, centralized management of software updates, and remote data deletion on lost or stolen devices) are cyber and information security decision-makers the least aware of. We uncovered that awareness of certain threats and solutions is positively associated with either adoption of advanced antimalware solutions with EDR/XDR capabilities or adoption of SOC. Additionally, we identified significant organizational factors (organizational role type) and personal characteristics (gender, age, experience with information security and experience with information technology (IT)) related to cybersecurity awareness of cyber and information security decision-makers. Organization size and formal education were not significant. These results offer insights that can be leveraged in targeted cybersecurity training tailored to the needs of groups of cyber and information security decision-makers based on these key factors.

The Boundaries of Popular Control in Late Medieval English Towns

Abstract Scholarship on pre-modern popular politics often focuses on speech, identifying the ways in which people outside the elite could have a “voice” in government. Using examples from late medieval English towns, this article argues for the existence of a particular kind of popular politics that centered on seeing and hearing rather than speaking. This type of politics—labeled “popular control”—concerned the right of the urban political community at large to observe rituals of governance and to audit financial accounts. Through these acts of collective witnessing, lesser citizens and non-citizens exerted an indirect political power to restrict leaders’ freedom of action and to ensure that their performance of office abided by set rules. The unusually detailed Hall Rolls and Hall Books produced by the civic government of Lynn in 1412–13 and 1418–25 illustrate that “popular control,” far from being a vehicle for increasing the urban commons’ “voice” in municipal decision-making, often stood in opposition to principles of elected representation. After 1418, more people were being admitted to the inner sanctum of virtuous individuals deemed capable of offering rational counsel to mayors and jurats, but there were fewer opportunities for the wider public to witness performances of governance by this expanded group of decision-makers. The crux of debate in fifteenth-century English towns—and, perhaps, in the tumultuous world of late medieval Europe more generally—was often less about who should exercise political influence and more about how popular political power could be exercised most appropriately and effectively.

Understanding decision-makers and their needs: framing Global Burden of Animal Diseases offerings to enhance relevance and increase impact.

In a world characterised by data deserts and data swamps, translating evidence into actionable policies and practices is not easy. This article addresses this challenge through the lens of evidence emerging from the Global Burden of Animal Diseases (GBADs) initiative. It emphasises the need for an intentional approach that connects research information with the specific needs of decision-makers and identifies specific impact pathways associated with different groups of decision-makers. The GBADs programme aims to support animal health decisions, and the authors outline the diverse landscape of decision-makers in this field, encompassing the public and private sectors, livestock keepers, civil society and international development agencies. Key issues such as disease prioritisation and lobbying are also discussed. The authors propose an ‘evidence ecosystem'approach, one that understands data users and their interactions, for analysing the needs of decision-makers, and framing GBADs offerings according to these needs. Two case studies, a recently concluded global case study of disease prioritisation decision-making and an ongoing policy analysis and needs assessment for GBADs in Indonesia, are presented to demonstrate how evidence ecosystem analysis and audience segmentation could be used to tailor GBADs information offerings for different decision-making groups. The article concludes by recommending that GBADs'future applications prioritise information offerings, adapt them to decision-makers'needs and consider how different segments of decision-makers will utilise the information to achieve real-world impacts.

E-health literacy in stroke patients: Latent profile analysis and influencing factors.

This study sought to explore latent categories of electronic health (e-health) literacy among stroke patients and analyse its influencing factors. A cross-sectional, descriptive exploratory design with the STROBE reporting checklist was applied. Between July and October 2020, 558 stroke participants from three tertiary care hospitals in Henan Province, China, were recruited using a convenience sampling method. A general information questionnaire and the Electronic Health Literacy Scale were used to collect their socio-demographic information and e-health literacy. Latent profile analysis was used to analyse latent categories of e-health literacy in stroke patients. Multiple logistic regression was used to analyse factors influencing latent categories of e-health literacy in stroke patients. Three latent categories of e-health literacy existed, including the low e-health literacy group, the low application-high decision-making group and the high literacy-low decision-making group. Multiple logistic regression showed that education level, presence of comorbidities, willingness to interact with people with mental illness, health information sources, frequency of Internet access, frequency of health information inquiry and willingness to receive remote care were predictors of the participants' latent categories of e-health literacy. Three latent categories of e-health literacy in stroke patients exist, and each latent category's characteristics should be considered while developing health education programmes. It is imperative that healthcare providers understand the requirement of creating tailored and efficient health education programmes for various categories of stroke patients to enhance their e-health literacy. It is imperative to improve Chinese stroke patients' overall e-health literacy. We categorized stroke patients' e-health literacy using advanced LPA. These findings hold implications for healthcare approaches, contributing to the enhancement of stroke patients' e-health literacy, enabling them to apply the acquired e-health information to manage and solve their own health issues. No patient or public contribution.

Commentary-A Military Health Care Ethics Framework.

Ethical practice within military health care is a significant topic of professional and academic debate. The term "military health care ethics" enfranchises the entire health care team. Military health care professionals are subject to tension between their duties as military personnel, and their ethical duties as health care professionals, so-called "Dual Loyalty." Some military health care practitioners have suffered moral injury because of the psychological stress associated with ethical challenges on military operations. It is important to define military health care ethics and also to consider how it should be taught. The essence of ethical practice is ethical decision-making. It has become self-evident from our experience of teaching military health care ethics that a simple and agreed framework for analyzing an ethical problem is required. This paper describes the development of the King's Military Healthcare Ethics Framework in support of a military health care ethics policy on behalf of the NATO Military Healthcare Working Group. There is logic to using a stepped approach to analyze an ethical problem in military health care. These steps are: "Identify" the problem, "Analyze" the problem including consideration of perspectives, "Fuse" the analysis, and "Decide". Step 1-Identify-is intended to orientate the decision-making group, and to articulate the problem specifically and clearly in order to determine the exact ethical issue and the secondary issues that arise. Step 2-Analyse-considers the problem from 4 perspectives: patient, clinical, legal, and societal/military. These reflect the breadth of perspectives that impact on health care practice within a military context. Step 3-Fuse-is the culminating step. The conclusions from the analysis of perspectives should be summarized and key references cited. This will determine the exact decision(s) to be made. Step 4-Decide-clearly articulates the decision made and provides the record of the key reasons for making that decision. This may include areas of enduring uncertainly and any planned review of the decision. The King's Military Healthcare Ethics Analytical Framework has been evaluated for content validity through iterative discussion at 4 meetings of the NATO MHCWG and a specific workshop on military health care ethics over 2022/2023. It is included within the draft NATO Standardization Agreement on Military Healthcare Ethics.

A Hybrid method of SWARA and ARAS for ranking of supplier: A case study at PT.Adi Satria Abadi (PT.ASA)

The development of a suggested model for rating suppliers is the goal of this research. In this study, suppliers are rated and ranked using Additive Ratio Assessment (ARAS) and Stepwise Weight Assessment Ratio Analysis (SWARA). The suggested approach incorporates both objective and subjective criteria while applying Delphi to a subset of the criteria. In order to test the proposed model in a leather company for actual use, a case study is provided. The model is able to capture all objective and arbitrary criteria in the dynamics of the group of decision-makers when rating suppliers. To help in decision-making, this proposed model includes criteria selection. Because the results of the ranking of suppliers will depend on how accurately the criteria are chosen. The suggested approach produces a workable resolution because it is not sensitive to changes in the parameters

Impact of Microfinance Initiatives on Poverty Alleviation in Bangladesh

Purpose: The aim of the study was to analyze the impact of microfinance initiatives on poverty alleviation in Bangladesh. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Microfinance in Bangladesh has boosted incomes, improved housing and food security, and empowered women economically, fostering entrepreneurship and decision-making. It has also enhanced social cohesion and community development through economic participation. Despite challenges, microfinance remains crucial for poverty reduction in Bangladesh. Unique Contribution to Theory, Practice and Policy: Social capital theory, agency theory & capability approach may be used to anchor future studies on analyze the impact of microfinance initiatives on poverty alleviation in Bangladesh. Foster community engagement and social cohesion within microfinance groups through participatory decision-making processes, group activities, and capacity-building initiatives. Incorporate social capital building objectives into microfinance program design and evaluation criteria, incentivizing MFIs to prioritize community empowerment and social capital formation.

Predictive models for delay in medical decision-making among older patients with acute ischemic stroke: a comparative study using logistic regression analysis and lightGBM algorithm.

To explore the factors affecting delayed medical decision-making in older patients with acute ischemic stroke (AIS) using logistic regression analysis and the Light Gradient Boosting Machine (LightGBM) algorithm, and compare the two predictive models. A cross-sectional study was conducted among 309 older patients aged ≥ 60 who underwent AIS. Demographic characteristics, stroke onset characteristics, previous stroke knowledge level, health literacy, and social network were recorded. These data were separately inputted into logistic regression analysis and the LightGBM algorithm to build the predictive models for delay in medical decision-making among older patients with AIS. Five parameters of Accuracy, Recall, F1 Score, AUC and Precision were compared between the two models. The medical decision-making delay rate in older patients with AIS was 74.76%. The factors affecting medical decision-making delay, identified through logistic regression and LightGBM algorithm, were as follows: stroke severity, stroke recognition, previous stroke knowledge, health literacy, social network (common factors), mode of onset (logistic regression model only), and reaction from others (LightGBM algorithm only). The LightGBM model demonstrated the more superior performance, achieving the higher AUC of 0.909. This study used advanced LightGBM algorithm to enable early identification of delay in medical decision-making groups in the older patients with AIS. The identified influencing factors can provide critical insights for the development of early prevention and intervention strategies to reduce delay in medical decisions-making among older patients with AIS and promote patients' health. The LightGBM algorithm is the optimal model for predicting the delay in medical decision-making among older patients with AIS.

EquiCity game: a mathematical serious game for participatory design of spatial configurations

We propose a mathematical framework for developing social-choice games that are designed to mediate decision-making processes for city planning, urban area redevelopment, and architectural configuration of urban housing complexes. The proposed framework features a digital serious gaming approach for participatory design to support transparency and inclusion in the process of decision-making and ensure an equitable balance of sustainable development goals in spatial design outcomes. The mathematical process consists of a Markovian design machine for balancing the design decisions of actors, a massing configurator equipped with fuzzy logic and multi-criteria decision analysis, algebraic graph-theoretical accessibility evaluators, and automated solar-climatic evaluators using geospatial computational geometry. We demonstrate the effectiveness of the framework by implementing a multi-player online game that facilitates a participatory decision-making workshop for forming multi-functional building complexes by providing a generative configurator equipped with automated appraisal/scoring mechanisms for revealing the aggregate impact of alternatives. The EquiCity game empowers a group of decision-makers to reach a fair consensual spatial design by mathematically simulating many rounds of reasonable trade-offs between their decisions, with different levels of interest or control over various types of investments. The novelty of the framework is in its capability to encompass decision-making about the most idiosyncratic aspects of a site related to its heritage status and cultural significance to the most generic aspects such as balancing access to sunlight for the site while respecting ‘the right to sunlight’ of the neighbours of the site, ensuring coherence of the entire configuration with regards to a network of desired closeness ratings, the satisfaction of a programme of requirements, and intricately balancing individual development goals in conjunction with communal goals and environmental design codes.

Crop insurance, factor allocation, and farmers’ income: evidence from Chinese pear farmers

Crop insurance, as a crucial tool for agricultural risk management, holds significant importance in increasing farmers’ income. This study analyzed the intrinsic relationship and mechanism between crop insurance, factor allocation, and pear farmers’ income. Using field survey data from 1,337 pear farmers in Xixian and Weixian counties in China, we employed OLS regression models and mediation effect models to empirically investigate the direct and indirect impacts of crop insurance on pear farmers’ income. Additionally, we examined the moderating role of agricultural cooperatives and group heterogeneity. The research findings revealed the following: (1) Although crop insurance increases agricultural expenses, it mitigates income losses due to disasters, ultimately leading to a net increase in pear farmers’ income. (2) Crop insurance enhances agricultural labor and machinery inputs, and encourages pear farmers to adopt green production techniques, thereby boosting their income. (3) The beneficial impact of crop insurance on pear farmers’ income is even more pronounced when farmers are members of cooperatives. (4) Heterogeneity analysis showed that for pear farmers who make individual decisions and have smaller land areas, crop insurance can increase their income, while its impact on farmers who make group decisions or have larger land areas is not significant. In conclusion, this study proposes to promote the development of crop insurance, deepen factor market-oriented reforms, support and guide the development of cooperatives, and pay attention to the heterogeneity among different groups of farmers.

The Effect of Individual Traits on Emerging Roles in Synchronous Computer-Mediated Groups

This study examines group dynamics in a virtual decision-making context through the lens of role theory and speech act theory, furthering previous research on the roles that emerge in such settings. Specifically, this research uses communication transcripts and text analysis to complete two main research objectives. First, we extend prior research by exploring how individual traits of group members (specifically, personality, cognitive ability, and social sensitivity) are related to emerging roles in computer-mediated communication. Personal characteristics such as agreeableness, social sensitivity, and motivation were significant predictors of role emergence in online decision-making groups. Agreeableness predicted the emergence of the listener role, social sensitivity predicted the emergence of the manager role, and motivation predicted the emergence of the sharer role. Second, we answer the call for more replication research and further validate the results from previous research by measuring roles assumed by individuals working synchronously online; we highlight the findings that are confirmed across previous research and our current study.

Ways to increase the validity of group decision

The modern step of evolution of administrative activities is characterized the growing trend of growing group decision-making. A group does have an opportunity to process more information, correct each other’s mistakes, use one another’s habits, knowledge and competences. However, this does not mean that the more we make group decisions the better. Nevertheless, it’s better if we don’t use this method if it is not necessary. The necessity is determined by how sudden and unexpected is the situation, whether or not is the information enough to make a right decision. Make a decision with a group does have it’s disadvantages. One of those is considered to be the phenomenal of “group thinking”, Among the many ways to overcome this, we consider the most important to be the provision of diversity of members of the decision-making group and the encouragement of organizational learning, which will help to develop different ideas, will grow the wish of group members to lead the environment they work in. Key words: leading decision, group thinking, effectiveness of the meeting, organizational learning, choosing stuff.

Characterization The Factors Influencing Construction Productivity Using Index System and D-S Evidence Theory

It is a very importance, both theoretically and practically, to create an indicator system to evaluate the factors affecting construction productivity. This paper uses the expert consultation opinion, the questionnaire survey technique, and the documentary research methods to analyze the and prioritizing influencing factors on construction productivity and evaluate it from the aspects of construction, management, special circumstances, and building the evaluation index system of those factors. Based on the principle of Dempster-Schaffer evidence theory to make group decisions by constructing a comprehensive judgment matrix (to effectively gather the opinions of experts and solve the problem of conflicting opinions, then determine the weights of the indicators through the analytical hierarchy process,. In the end, an index system was obtained to evaluate the factors affecting construction productivity in Iraqi projects, including three first-level indicators/indicators, seven secondary indicators, and 56 third-level indicators, which provides theoretical guidance for project departments in order to study these factors. And work towards developing a system to effectively increase project productivity.

Stochastic multi-criteria decision-making for scheduling of wind–photovoltaic–hydropower systems

Abstract The decision-making process of wind–photovoltaic–hydropower systems involves knowledge from many fields. Influenced by the knowledge level of the decision-maker and the attribute information of the scheme set, there exists a certain uncertainty in the indicator weights. In view of this, this paper proposes a stochastic multi-criteria decision-making framework for scheduling of wind–photovoltaic–hydropower systems, which overcomes the difficulty of uncertainty in indicator weights or even completely unknown information about indicator weights at the time of decision-making. The Stochastic Multi-criteria Acceptability Analysis (SMAA) theory and the VIKOR model are introduced, and the proposed SMAA–VIKOR model makes the indicator weight space explicit. The study shows that the proposed SMAA–VIKOR model can overcome the obstacle of decision-makers’ lack of information on indicator weights. The ranking acceptability indicators calculated by the model show a more obvious trend of advantages and disadvantages, which gives full confidence to the decision-making group to formulate a plan to be implemented. It breaks through the bottleneck of group decision-making, which is difficult to make effective decisions due to the condition of incomplete information, and enriches the library of stochastic multi-criteria decision-making methods for the scientific formulation of scheduling schemes of wind–photovoltaic–hydropower systems under uncertainty conditions.

Health Disparities Among Family Decision-Makers in China: An Ordered Probit Analysis of the China Family Panel Studies.

The family decision-makers serve as the backbone of the family, and their health status warrants consideration. This study aims to explore how the health status of this group of people, namely the family decision-making group, is affected, and to delve into the mechanisms of influence based on this. The goal is to provide reliable evidence and strategies for the health management of the family decision-makers group, contributing to the achievement of the "Healthy China 2030" Planning Outline. Drawing on data from the China Family Panel Studies (CFPS), this study utilizes an Ordered Probit Model to analyze and compare the health status of family decision-makers and non-decision-makers. The findings indicate that decision-makers tend to experience poorer health outcomes than other family members, with increased pressure related to decision-making identified as a significant contributor to their declining health. Heterogeneity analysis reveals that the negative effect is less pronounced in households with higher net worth but more pronounced in those with more significant housing, education, and medical spending pressures. Moreover, this study analysis highlights that enhancing individual or family socioeconomic status can alleviate the adverse health effects experienced by family decision-makers. The study reveals the presence of certain health adverse effects among family decision-makers. The implications drawn from this research hold significance for the health management of this demographic, underscoring the necessity for tailored interventions aimed at addressing the distinctive challenges confronted by this group.

Analysis of Critical Success Factors of Logistics 4.0 using D-number based Pythagorean Fuzzy DEMATEL method

Logistics 4.0 is a concept related to Industry 4.0, encompassing skills and notions of supply chain organization, integrating logistics with advanced technology in order to satisfy consumer demand for customized goods and services. Industry 4.0 is transforming businesses and supply chains through advanced technologies like analytics, big data, Internet of things, and cyber-physical systems, enhancing warehousing, manufacturing, and logistics. Logistics 4.0 can be regulated by properly analyzing specific Critical Success Factors using a Multi-Criteria Decision Making model in uncertain or ambiguous circumstances. Hence, it is necessary to explore the CSFs while bringing logistics 4.0 into action. These CSFs are interlinked, and this interlinkage is examined through the D-number-based Pythagorean fuzzy Decision Making Trial and Evaluation Laboratory method, which is suitable for group decision-making in incomplete and uncertain data. The proposed research paradigm incorporates the abilities of Trapezoidal Pythagorean Fuzzy Numbers for dealing with fuzziness and D-Numbers for getting an improved and further precise decision from a heterogeneous group of decision-makers using their linguistic choices. Additionally, it is adaptive and versatile in managing the intrinsic uncertainty brought on by ambiguous and subjective information.

Training Preservice Teachers to Make Data-Based Decisions: A Comparison of Two Interventions

Data-based decision-making, which involves evaluating students’ progress and making instructional decisions, is an integral competency for preservice teachers. Several studies have found that visual aids, such as decision-making models, may be an effective way to train preservice teachers to make instructional decisions. The purpose of this study was to investigate the effects of a decision-making model, with and without supplemental online instruction, on preservice teachers’ accuracy in identifying data patterns and making data-based decisions. Results showed that participants in both the decision-making model only and online training plus decision-making model groups had greater accuracy compared with participants who received no training. However, there were no significant differences between the two treatment groups, suggesting that the decision-making model may stand alone as an effective intervention to train preservice teachers to identify a data-based decision. Implications for research and practice are discussed.

To report or not report? How attitudes, values, and knowledge play a role in mandated reporting

ABSTRACT In 2021, 600,000 U.S. children were victims of maltreatment. Decisions to report suspicions of child maltreatment can be influenced by one’s attitudes, beliefs, and knowledge. This qualitative study explores the lived experiences of 15 social workers navigating decisions to report or not report suspicions of child maltreatment. Findings indicate the influence attitudes, beliefs, and knowledge have in the decision-making process. Three distinct decision-making group processes were identified, varying primarily in beliefs and knowledge, those who “always err on the side of caution,” those who believe “suspicion is a gray area” and those who consider “imminent danger as a factor.”

Complex linear Diophantine fuzzy sets and their applications in multi-attribute decision making

This study utilizes the concept complex linear Diophantine fuzzy set (CLDFS) which is an advanced framework for handling ambiguity in the presence of periodicity for decision-making. Unlike existing techniques, CLDFS offers a larger solution space, incorporating reference parameters α and β. Two real-life scenarios – bridge design selection and AI system choice – are examined to showcase CLDFS’s impact on practical applications. The study presents multi-attribute decision-making (MADM) and multi-attribute group decision-making (MAGDM) algorithms with visualizations, applied to warehouse distributor selection and faculty candidate evaluation. The comparative analysis highlights CLDFS’s advantages over other methods

BHARAT: A simple and effective multi-criteria decision-making method that does not need fuzzy logic, Part-1: Multi-attribute decision-making applications in the industrial environment

A simple and effective multi-criteria decision-making methodology named as “Best Holistic Adaptable Ranking of Attributes Technique (BHARAT)” is proposed that can be used in single- as well as group decision-making scenarios of the industrial environment. The attributes data for various alternatives can be quantitative or qualitative (i.e., expressed in linguistic terms). This paper proposes to transform the qualitative attributes into quantitative attributes by means of simple linear scales rather than complex fuzzy scales. The proposed BHARAT method normalizes the data with reference to the “best” alternative corresponding to an attribute and the normalization procedure is repeated for all the attributes to get the normalized data. A group of decision-makers or a decision-maker assigns ranks to the attributes according to how important they are deemed to be, and these ranks are then transformed into the proper weights. The total scores of the alternatives are calculated by multiplying the weights of the attributes by the corresponding normalized data of the attributes for different alternatives. Four industrial case studies are presented to illustrate the potential of the suggested BHARAT method. The first case study deals with the problem of an automated warehouse selection for a large industrial plant involving a single decision-maker, 13 attributes, and 4 alternative warehouses; the second case study deals with the problem of sustainable maintenance service provider selection for a large petrochemical plant involving fuzzy group decision-making with 5 decision-makers, 9 attributes, and 4 alternative maintenance service providers; the third case study deals with the problem of alternative strategy selection for implementation of a make-to-order system for passenger car manufacturers involving 6 factors, 18 sub-factors, and 3 alternative strategies; and the fourth case study deals with the problem of process parameters selection in a sustainable high speed turning operation involving 4 attributes and 9 alternative sets of experimental conditions. The results of the proposed decision-making method and its second version are compared with the other popular decision-making methods. The proposed method and its another version are proved simple, effective, powerful, flexible, easy to apply, do not require the use of fuzzy logic, offer logical and consistent procedures to assign weights to the attributes, and are applicable to different decision-making scenarios of the industries. Part-1 of this paper describes the applications of the BHARAT method to multi-attribute decision-making problems and Part-2 describes the evaluation of Pareto solutions using the BHARAT method in multiple objective decision-making problems.