Independent Decision Makers Research Articles

Impact of SHGs on social, economic and political women empowerment: a case study of Ghaziabad District, India

In India, the Self-Help Groups (SHGs) are playing a commendable role in poverty alleviation by reaching out to the poor rural women which forms the major percentage of their membership. These groups are determined to eradicate poverty from the country as these are truly active at the grass root level. An effort has been made to survey 388 respondents from four blocks of Ghaziabad district to find the impact of SHGs on the rural women at three unique levels namely social, economical and political. The study at hand reveals that women have become more authoritative socially and cost-effectively yet there is still the scope of upgrading with respect to Political empowerment. The members of SHGs in have become more confident and independent decision makers to a considerable extent.

From Individual Farms to Agriholdings: Methodological Implications. An Explorative Regional Case Study in East Germany

Agricultural economics and policy planning make use of—and rely on—agricultural statistics. Individual agricultural firms, as they are represented in statistical systems, are usually treated as independent economic decision-makers. Our paper investigates the impacts of agriholding structures on statistical and economic parameters. Therefore, the paper will draw on the empirical evidence generated in a local case study in seven communities in northeast Germany. It is argued that cross-regional investors systematically “assemble” agriholdings based on their overall business strategy. If large holding structures exist, then the individual business perspective may create a flawed representation of farm structures.

Supply Chain Risk Governance: Towards a Conceptual Multi-Level Framework

The coronavirus pandemic (COVID-19) is currently putting high pressure on most countries’ critical infrastructures (not only health care), creating huge uncertainties in supply and demand, and disrupting global supply chains. The global crisis will demonstrate the extent to which different parties (countries, public authorities, private companies etc.) can work together and take holistic decisions in such situations. A core question in supply chain management asks how independent decision-makers at many levels can work together and how this joint work can be governed. Supply chain risk management (SCRM), however, has focused mostly on how focal private companies apply SCRM processes to identify, analyse and mitigate risk related to upstream and downstream flows in their supply networks. At the same time, interorganisational collaboration to handle diverse risks is always needed. A risk that hits one organisation often affects other, interconnected organisations. This study aims to develop the term supply chain risk governance with an associated conceptual framework that embraces various types of supply chains and actors. In a cross-disciplinary literature study, we dissect, compare and combine risk governance with interorganisational aspects of SCRM and find that the mechanisms suggested in the risk governance literature coincide with many of those in SCRM. We suggest a combination of these to govern risk processes at an inter-organisational level, regardless of the type of organisation included in the supply chain. This would be suitable for critical infrastructures that often contain a mixture of private and public actors. The scope of the literature employed is limited, and some articles have played a larger role in the framework development. The paper explores new territory through this cross-disciplinary study, extends existing multi-level frameworks with inter-organisational governance mechanisms and proposes new governance mechanisms to the field. This study could support the understanding of how critical infrastructures in our society are governed so as to increase their resilience to both smaller and larger disruptions. (Less)

Bi-objective optimization problems with two decision makers: refining Pareto-optimal front for equilibrium solution

The Pareto-optimality concept in multi-objective optimization theory is different from the Nash equilibrium concept in noncooperative game theory. When the objective holders are independent decision makers, i.e., human entities or organizations, any solution on the Pareto-optimal front is not necessarily an equilibrium point, hence not a valid solution. The solution has to be a Pareto-optimal-equilibrium (POE) point. In this paper, we convert a bi-objective optimization problem into a two-player game problem by introducing “induced games,” and we propose a new refinement method to find a POE point. We prove that at least one such POE point exists for a class of linear bi-objective optimization problems, and we develop an algorithm to find it. We discuss that the innovative approach considered in this paper is of real future interest to some industrial and social applications. One such example is also presented.

Factors Influencing Women’s Perceptions of Shared Decision Making During Prenatal Care [13G

INTRODUCTION: Shared decision-making is central to providing patient-centered care and is associated with increased patient satisfaction, decreased healthcare costs and improved health outcomes. Women from different socio-economic, racial, and ethnic backgrounds may differ in their perceptions about the medical community and engagement in care. We sought to determine how patients perceived prenatal shared decision-making in an inner-city hospital serving a predominantly black population. METHODS: In an IRB-approved observational cross-sectional study at two different inner-city prenatal clinics, English-speaking women between 28 and 42 weeks’ gestation completed a survey assessing shared decision-making. Maternal demographics and preferences towards prenatal education resources were collected. Our primary outcome was a participant’s independence or dependence on a provider to make decisions about their care. Secondary outcomes included patient and provider perceptions of choices. Pearson Chi Square was used for analysis. RESULTS: Surveys were collected from 150 gravidas. Black women were more likely to be independent decision makers in their care in comparison to whites (25 [30.1%; of black women] vs 4 (8.9%; of white women [P=.015]). No other factors demonstrated significance. Seven participants (4.6%) had not considered they had choices in their care. All of these participants were enrolled in government assistance programs (P=.007). No differences were seen in the likelihood of providers discussing options for care with participants (P>.05 for all variables). CONCLUSION: Maternal race and socio-economic factors may significantly influence patients’ perceptions of shared decision-making. Results from this research will help guide the development of an educational tool to provide adaptive discussions to improve the quality of patient-centered care.

The Exposure to Animated Movies and Constructing Adolescents’ Perception towards Gender Role

This study aims to know the Egyptian adolescents’ perception towards gender roles; coinciding with the evolution of the female lead animated movies. Being affected by the third and the fourth wave of feminism in American society and its effect on Egyptian adolescents; since animated movies are mainly American produced. The study found that Egyptian adolescents perceive the female role in the society to be independent decision-maker and has her own rights, reassuring that women hold much more work-load than men and her biggest enemy and fighter is the society itself, not her capabilities, while animation movies from 2012 till 2018 hold more muscular personality traits and behavioral traits than feminine ones.

Medical Cases Adjudicated by the Transportation Appeal Tribunal of Canada: 2000-2018.

INTRODUCTION: In Canada, aviators and seafarers are required to be medically fit by international and domestic standards to be issued a medical certificate by Transport Canada (TC). In the event of denial or restriction, individuals have the right to a review by an independent decision-maker with medical expertise/training in marine and/or aviation medicine. This paper presents the results of cases submitted to the Transportation Appeal Tribunal of Canada over 19 yr.METHODS: The Tribunal's repository of medical records was searched and 112 adjudicated cases were reviewed.RESULTS: Since 2000, 55 (49%) cases were in the aviation sector and, since 2010, 57 (51%) cases were in the marine sector. The mean age of applicants was 49 and 54 yr for seafarers and pilots, respectively. Mental illness, cardiovascular disease, visual, and neurological disease were the most common reasons for a medical certificate restriction/denial. The Tribunal upheld the refusal to issue or renew a medical certificate in 89 (79%) cases and 23 (21%) cases were referred back to TC.CONCLUSIONS: Mental illness is the most frequent diagnosis that precipitates a request. The international literature is sparse on the number, causes, and results of the appeal process. Our findings and the application of the medical standards in Canada are generally comparable with those of the United Kingdom. It was not possible to make more than indirect comparisons to those of the United States.Brooks C, MacDonald C. Medical cases adjudicated by the Transportation Appeal Tribunal of Canada: 2000-2018. Aerosp Med Hum Perform. 2020; 91(2):79-85.

Who Are Robo-Advisor Users?

The purpose of this study is to explore the demand for robo-advising services by analyzing the participants’ behavioral characteristics and investment patterns. With the 2015 Financial Industry Regulatory Authority Investor data, we found that robo-advisor users were younger investors with high risk tolerance, whose self-assessment of financial knowledge is comparatively higher than their actual knowledge, and were independent decision-makers. By controlling for those behavioral attributes of robo-advisor users, we also found that robo-advisor users were reluctant to invest in individual stocks, while they showed the largest preference for investing in pooled investment products such as Exchange Traded Funds. Implications of this study’s findings can be beneficial to financial planning practitioners, academics, and regulators.

Optimization and coordination of decentralized supply chains with vertical cross-shareholding

We consider a decentralized supply chain in which an upstream firm sells a product to a downstream firm, who faces a random demand. The upstream firm and the downstream firm are linked by vertical cross-shareholding, which enables one firm to share the other firm’s profit. The two firms are both independent decision makers, and seek to maximize their own profits (i.e., profits after dividends). We investigate two distinct supply chains: push supply chain and pull supply chain. We first derive the optimal wholesale price and production quantity decisions of the two firms, and show that the impacts of vertical cross-shareholding on efficiencies of the push and pull supply chains are very different. We then study supply chain coordination. We find that to achieve a win-win coordination, one firm may need to operate at a loss first, and then get revenue by sharing its partner’s profit. We propose schemes to coordinate supply chains. The proposed schemes each contains three parameters. We show that the proposed schemes can coordinate supply chains with vertical cross-shareholding, and result in a win-win situation.

Toward the Special Computer Law of Targeting: 'Fully Autonomous' Weapons Systems and the Proportionality Test

One of the implications of “fully autonomous” weapons systems (AWS) as an independent decision-maker in the targeting process is that a human-centered paradigm should never be taken for granted. Indeed, they could allow a LOAC debate immune from that paradigm all the more because the underlying “principle of human dignity” has failed to offer convincing reasons for its propriety in international legal discourse. Furthermore, the history of LOAC tells us that the existing human-centered approach to the proportionality test—the commander-centric approach—is, albeit strongly supported and developed by states and international criminal jurisprudence, particularly since the end of the World War II, nothing more than a product of the time. So long as fully AWS exhibit the potential for better contribution to the LOAC goals to protect the victims of armed conflict than human soldiers, one could thus seek an alternative computer-centered approach to the law of targeting—a subset of LOAC—tailored to the defining characteristics of fully AWS in a manner to maximize their potential as well as to make the law more responsive to the needs of ever-changing battlespaces. With this in mind, this chapter aims to relativize the absoluteness of the existing human-centered approach to the proportionality test—which is not to deny the role of humans in the overall regulations of fully AWS whatsoever—and then, away from that approach, to propose an alternative one dedicated to fully AWS for their better regulation in response to the demands of changing times.

An Information Analysis of Iterative Algorithms for Network Utility Maximization and Strategic Games

A variety of resource allocation problems on networked systems, for example, those in cyber-physical systems or Internet-of-things applications, require distributed solution methods. Modern distributed algorithms usually require bandwidth-limited digital communication between the system and its users, who are often modeled as independent decision makers with individual preferences. This paper presents a quantitative information flow and knowledge gain analysis of decentralized iterative algorithms with bounded trajectories in the context of convex network utility maximization problems and strategic games with a unique Nash equilibrium solution. First, a novel generic framework is introduced to quantify knowledge gain in network resource allocation problems using entropy by taking into account priors in the solution space. Second, a general result is presented on the interplay between quantization of information and distributed algorithm performance both for linear and sublinear convergence. Third, information flow in distributed algorithms is studied and a lower bound is derived on the total amount of information exchanged for convergence under uniform quantization. The well-known primal-dual decomposition algorithm is used as an example to illustrate the results. Finally, convergence guarantees for distributed algorithms with estimation are investigated. This paper establishes specific links between information concepts and iterative algorithms in addition to building a foundation for integrating learning schemes into distributed optimization.

A supply chain network equilibrium model with a smoothing newton solution scheme

ABSTRACTConsidering that a supply chain comprises several independent decision makers, a supply chain network equilibrium model that consists of manufacturers, retailers and consumers is developed. After analysing the optimal conditions of various decision makers in the model, the equilibrium condition is established as an equivalent, finite-dimensional variational inequality formulation and is solved by a smoothing Newton method. The global and quadratic convergence of the method is established. The numerical results show the rapid convergence of the method. Additionally, the rapid convergence of the smoothing Newton method is beneficial when solving a complicated network model in the real world.

Computing base-stock levels for a two-stage supply chain with uncertain supply

We consider independent decision makers in a two-stage supply chain subject to uncertainty in upstream supply, and we use a recently published computational algorithm to generate independent, single-stage (ISS) base-stock inventory solutions for each stage in the system. These solutions are computed by employing straightforward, linear functions to estimate the parameters that must be set to seed the single-stage computational algorithm. Those linear functions are derived from the system-optimal solutions, which are found by solving a Markov chain model of the two-stage system. We demonstrate that the ISS solutions are often quite close to the system-optimal solution, and moreover, we develop a fast, descent-based search to quickly find the system-optimal solutions starting from the ISS solutions. We use our solution algorithm to generate optimal solutions to 1100 randomly-generated problem instances, allowing us to explore the behavior of the two-stage inventory system under various cost, demand uncertainty, and supply uncertainty conditions. We find that the downstream stocking levels are strongly influenced by the properties of the downstream demand, while the upstream stocking level is very strongly influenced by the holding costs and supply uncertainty, and only marginally by the retailer penalty cost. Moreover, the system responds to changes in the cost and uncertainty environment mostly by shifting the burden of holding cost either upstream or downstream, leaving the downstream penalty cost relative stable across the large set of problem instances we study.

A column generation based distributed scheduling algorithm for multi-mode resource constrained project scheduling problem

This study develops a column generation-based distributed scheduling algorithm for multi-mode resource constrained project scheduling problem. The proposed distributed algorithm shares less information among independent decision makers compared with the traditional integrated approach. In this problem, many independent processors, which can produce different types of products, coordinate with a resource manager (or third-party logistic), who provides different types of vehicles to deliver products to the customers. The problem is decomposed into two parts: production planning for individual processors and vehicle scheduling for the resource manager. A total of 1200 instances are randomly generated to verify the effectiveness of the proposed distributed algorithm. Results of computational experiments verify that the proposed distributed algorithm has good solution quality and calculation efficiency compared with the integrated approach, i.e., CPLEX, hybrid Benders Decomposition, and Lagrangian Relaxation. Lastly, a general framework for the distributed algorithm is proposed to solve a generalized problem.

Can a regional-level forest management policy achieve sustainable forest management?

While deliberating a regional level forest management policy, one should note the probable existence of plural and independent decision-makers in the target region and the possibility that they may not fully understand or obey the intent of the regional policy. To achieve sustainable forest management, the relationships between the policy and the decisions of individual decision-makers with respect to forestry activities (for example, thinning or clear-cutting) need to be considered. The objective of this study is to determine the extent to which zoning, as a regional forest management method that affects individual management activities, influences future forest resources. A Bayesian belief network (BBN) model was used to model relationships between zoning and individual forestry activities. Through the construction of the BBN model with factors (nodes) such as zoning types, forestry activities, and forest stand conditions, a conditional probability table (CPT) was obtained. This CPT shows the degree of possibility of harvest for each forest stand. Individual forestry activities were simulated on the basis of the CPT. As a case study, this model was applied to the regional municipality of Ugo which is situated in the Tohoku district of Japan. Three types of zoning were examined: (1) no zoning covering for wood production, (2) the current zoning that is actually used, and (3) zoning planned to emphasize wood production. The volume of harvested wood and the statistics for the slope distribution where harvesting occurred were observed under each zoning type. Results showed that future forest resources varied under each zoning type. However, influencing the timing and location of individual forestry activities may enable appropriate regional-scale management to achieve sustainable forest management.

A Hierarchical Game Theoretical Approach for Energy Management of Electric Vehicles and Charging Stations in Smart Grids

By the proliferation of electric vehicles (EVs) in power systems, it is needed to manage their demand energy within a regulated market framework. From the market perspective, integration of different market players, such as the energy producers, aggregators, and loads, could complicate the system operation and management. Therefore, an appropriate model of the market that shows the exact behavior of the system components is needed. In this paper, a new tri-level game theoretical approach for energy management of EVs and EV charging stations (EVCSs) as independent decision makers for their energy scenarios is proposed. To make it practical for a real power system, the system operator is also included in the proposed method as a master decision maker. Therefore, EVs’ and EVCSs’ objectives are to maximize their financial profits, while the system operator indirectly controls their energy scenarios in order to fulfill the system’s technical constraints. To do so, at the highest level of the proposed method, technical goals of the system, which are related to the system operational condition, will be followed as the objective criteria. At the second level of the designed model, the EVCSs financial objectives are optimized. In the third level of the proposed method, it is tried to minimize the EVs’ cost function. The method is tested on an IEEE 9-bus standard system, and the results show a superior performance of the proposed energy management system (EMS) compared with the conventional EMS methods in terms of technical and financial objectives. In this way, it is shown that in the case of considering only one aspect of the system, either financial or technical, the other aspects of the system may not be satisfied. Hence, it is essential to consider both the financial and technical aspects of the system simultaneously, in order to operate the system optimally and securely.

Efficient Dynamic Pinning of Parallelized Applications by Distributed Reinforcement Learning

This paper introduces a resource allocation framework specifically tailored for addressing the problem of dynamic placement (or pinning) of parallelized applications to processing units. Under the proposed setup each thread of the parallelized application constitutes an independent decision maker (or agent), which (based on its own prior performance measurements and its own prior CPU-affinities) decides on which processing unit to run next. Decisions are updated recursively for each thread by a resource manager/scheduler which runs in parallel to the application’s threads and periodically records their performances and assigns to them new CPU affinities. For updating the CPU-affinities, the scheduler uses a distributed reinforcement-learning algorithm, each branch of which is responsible for assigning a new placement strategy to each thread. The proposed framework is flexible enough to address alternative optimization criteria, such as maximum average processing speed and minimum speed variance among threads. We demonstrate analytically that convergence to locally-optimal placements is achieved asymptotically. Finally, we validate these results through experiments in Linux platforms.

Conceptualizations of Catalogers' Judgment through Content Analysis: A Preliminary Investigation

ABSTRACTCatalogers' judgment has been frequently mentioned, but rarely has been researched in formal studies. The purpose of this article is to investigate catalogers' judgment through an exploration of the texts collected in the database of Library and Information Science Source. Verbs, adjectives, and nouns intimately associated with catalogers' judgment were extracted, analyzed, and grouped into 16 categories, which lead to 5 conceptual descriptions. The results of this study provide cataloging professionals with an overall picture on aspects of catalogers' judgment, which may help library school students and graduates and novice catalogers to become independent and confident decision makers relating to cataloging work.

Adolescents' Perspectives on Personalized E-Feedback in the Context of Health Risk Behavior Screening for Primary Care: Qualitative Study.

BackgroundElectronic health screening tools for primary care present an opportunity to go beyond data collection to provide education and feedback to adolescents in order to motivate behavior change. However, there is limited research to guide feedback message development.ObjectiveThe aim of this study was to explore youth perceptions of and preferences for receiving personalized feedback for multiple health risk behaviors and reinforcement for health promoting behaviors from an electronic health screening tool for primary care settings, using qualitative methodology.MethodsIn total, 31 adolescents aged 13-18 years completed the screening tool, received the electronic feedback, and subsequently participated in individual, semistructured, qualitative interviews lasting approximately 60 min. Participants were queried about their overall impressions of the tool, perceptions regarding various types of feedback messages, and additional features that would help motivate health behavior change. Using thematic analysis, interview transcripts were coded to identify common themes expressed across participants.ResultsOverall, the tool was well-received by participants who perceived it as a way to enhance—but not replace—their interactions with providers. They appreciated receiving nonjudgmental feedback from the tool and responded positively to information regarding the consequences of behaviors, comparisons with peer norms and health guidelines, tips for behavior change, and reinforcement of healthy choices. A small but noteworthy minority of participants dismissed the peer norms as not real or relevant and national guidelines as not valid or reasonable. When prompted for possible adaptations to the tool, adolescents expressed interest in receiving follow-up information, setting health-related goals, tracking their behaviors over time, and communicating with providers electronically between appointments.ConclusionsAdolescents in this qualitative study desired feedback that validates their healthy behavior choices and supports them as independent decision makers by neutrally presenting health information, facilitating goal setting, and offering ongoing technological supports.

Beyond individualism: Is there a place for relational autonomy in clinical practice and research?

The dominant, individualistic understanding of autonomy that features in clinical practice and research is underpinned by the idea that people are, in their ideal form, independent, self-interested and rational gain-maximising decision-makers. In recent decades, this paradigm has been challenged from various disciplinary and intellectual directions. Proponents of ‘relational autonomy’ in particular have argued that people’s identities, needs, interests – and indeed autonomy – are always also shaped by their relations to others. Yet, despite the pronounced and nuanced critique directed at an individualistic understanding of autonomy, this critique has had very little effect on ethical and legal instruments in clinical practice and research so far. In this article, we use four case studies to explore to what extent, if at all, relational autonomy can provide solutions to ethical and practical problems in clinical practice and research. We conclude that certain forms of relational autonomy can have a tangible and positive impact on clinical practice and research. These solutions leave the ultimate decision to the person most affected, but encourage and facilitate the consideration of this person’s care and responsibility for connected others.