Set Of Decisions Research Articles

Proposed Increase in Foreign Player Quota in Top-Tier Maltese Football: An In-Depth Investigation of Local Attitudes

This exploratory study focused on the Maltese mens football Premier Leaguein light of a proposed increase in the foreign player quota. Currently, there seems to betwo main diverging fronts vis--vis this development: those in favour, as represented bytop clubs, and the players union, which is largely against. The research paradigm chosento investigate the attitudes around this quota increase consisted of a web-based survey(N=436). Maguires (2011) theoretical framework based on three points of conflict betweenclubs and national federations, with regard to prioritising winning and commercialisationover player development, was used as a basis for the study. Data analysis involved acombination of descriptive and inferential statistics to test a series of hypotheses, usingthe respondents role in local football as the independent variable, and attitude towardsthe foreign quota proposal as the main outcome of interest. The findings indicated generalscepticism towards any positive effects resulting from a foreign quota increase, withthe parents/guardians being the category least supportive of a prospective increase.Results generally suggested that the foreign quota should not be viewed in isolation, butas one of a set of important decisions needed to overcome several perennial problems ofMaltese football. Most respondents considered Maltese players to be at a disadvantagevis--vis foreigners, with a majority also considering that foreign influx has had a positivespillover on the level of local players. Moreover, it is unlikely that a quota increase wouldimprove the leagues competitive balance or attract more fans at stadia. In line with theliterature reviewed, findings indicated that the identification of a roadmap that satisfies allstakeholders is unlikely.

Сomponent strategies of foreign economic development

The main components of the foreign economic development strategy are considered in the article.
 The success of the enterprise's foreign economic activity depends on a large number of internal reserves and external factors, among which the choice of the enterprise's foreign economic development strategy plays a significant role.
 The foreign economic development strategy of the enterprise is one of the components of the general strategy of the enterprise and is an action plan of the enterprise, which is directly related to entering the foreign market and winning the desired market share, expanding and maintaining the desired competitive position on it. And it is also a set of management decisions regarding the narrowing of the entire set of possible foreign economic actions of the enterprise to the set of the most effective from the point of view of the long-term goals formulated in the general strategy of the enterprise.
 Strategic development of the enterprise is a mandatory provision in the formation of increasing the competitiveness of the enterprise on the market and optimization of its activities.
 Understanding strategy as a plan of actions allows enterprises to decide on the main types of actions to enter foreign economic markets and to consolidate their position on these markets. On the other hand, the understanding of strategy as a general direction of development in foreign economic activity requires coordination of this type of strategy with the general choice of all existing directions, therefore it is important to determine its economic essence.
 Thus, it is possible to draw conclusions regarding the disclosure of the essence of the concept of "foreign economic development strategy" - a clearly defined sequence of actions in the process, which is based on a functional approach in interaction with systemic, situational and process approaches to the management of the enterprise's foreign economic activities, aimed at the development and implementation of the foreign economic strategy activities as part of the general strategy of the enterprise based on its respective capabilities and taking into account the changes occurring in the external and internal environment for effective functioning, increasing the level of competitiveness and development in general.

Siamese Neural Networks on the Trail of Similarity in Bugs in 5G Mobile Network Base Stations

To improve the R&D process by reducing duplicated bug tickets, we used the idea of composing a BERT encoder as a Siamese network to create a system for finding similar existing tickets. We proposed several different methods of generating artificial ticket pairs to augment the training set. Two phases of training were conducted. The first showed that only approximately 9% of pairs were correctly identified as certainly similar. Only 48% of the test samples were found to be pairs of similar tickets. With fine-tuning, we improved that result to 81%, which is a number describing a set of common decisions between the engineer in the company and the solution presented. With this tool, engineers in the company receive a specialized instrument with the ability to evaluate tickets related to a security bug at a level close to an experienced company employee. Therefore, we propose a new engineering application in corporate practice in a very important area with Siamese network methods that are widely known and recognized for their efficiency.

Technoeconomic Evaluation of Electricity Generation from Concentrated Solar Power Technologies in Ghana

This work estimates the annual energy that could be generated from a concentrated solar power (CSP) plant. The optimal location used for this analysis was selected based on a set of multicriteria decision-making (MCDM) methods employed in an earlier research. The paper also determines the financial viability of implementing a CSP plant within the selected location. A 100 MW CSP plant for the said location was modelled and simulated using the System Advisor Model (SAM) software with data from the online database of the National Renewable Energy Lab (NREL) available from the SAM software. Using a solar multiple of 2.0 with a TES of 6 hours, the plant generated an estimated annual energy of 306.850 GWh with a capacity factor of 35.10% and gross-to-net conversion of 89.10%. The months with the highest generation were from November to March while July to September had the least generation. Generation begins from 8 am, rising to a peak around 12 pm to 4 pm and gradually declines into the night. Results from the financial analysis produced a net present value (NPV) of USD 156,287,433.72 after the plant life of 25 years, indicating profitability of the project. Results from the sensitivity analysis showed that the project NPV became negative only when the base case capital cost, electricity price, and revenue were, respectively, increased by 15%, reduced by 10%, and reduced by 13%.

Consequences of equivalency metric design for energy transitions and climate change

Assessments of the climate impacts of energy technologies and other emissions sources can depend strongly on the equivalency metric used to compare short- and long-lived greenhouse gas emissions. However, the consequences of metric design choices are not fully understood, and in practice, a single metric, the global warming potential (GWP), is used almost universally. Many metrics have been proposed and evaluated in recent decades, but questions still remain about which ones perform better and why. Here, we develop new insights on how the design of equivalency metrics can impact the outcomes of climate policies. We distill the equivalency metric problem into a few key design choices that determine the metric values and shapes seen across a wide range of different proposed metrics. We examine outcomes under a hypothetical 1.5 or 2 ∘C policy target and discuss extensions to other policies. Across policy contexts, the choice of time parameters is particularly important. Metrics that emphasize the immediate impacts of short-lived gases such as methane can reduce rates of climate change but may require more rapid technology changes. Differences in outcomes across metrics are more pronounced when fossil fuels, with or without carbon capture and storage, play a larger role in energy transitions. By identifying a small set of consequential design decisions, these insights can help make metric choices and energy transitions more deliberate and effective at mitigating climate change.

FOOD ALLERGEN IMMUNOTHERAPY IS ASSOCIATED WITH A POSITIVE IMPACT ON PATIENT/CAREGIVER-REPORTED WELL-BEING AND SOCIAL INCLUSION

<h3>Introduction</h3> 5-10% of children globally are affected by food allergies, and patients and caregivers suffer from high levels of emotional distress and anxiety. Immunotherapy is gaining recognition as a safe method to treat food allergy. Increased stress and anxiety levels are associated with lower quality of life (QOL), higher activity impairment, and higher suicidal ideation. Few studies have explored patient/caregiver reported outcomes from immunotherapy. <h3>Methods</h3> 61 patients/caregivers completed a survey measuring Patient-Reported Outcomes Measures to assess perceived effects of immunotherapy treatment on general and emotional well-being and the ability to participate in activities of daily living. The survey was distributed through allergist offices and online support groups for patients/caregivers pursuing food allergen immunotherapy, and was open to patients who were either currently pursuing immunotherapy or who had done so previously. Procedures followed were in accordance with the Helsinki Declaration as revised in 2013. <h3>Results</h3> 77% of patients/caregivers reported improvement in general state of well-being with immunotherapy treatment. 65.6% reported improvement in emotional well-being. 70.5% reported improvement in the ability to perform social activities. However, there was not a clear association of food allergen immunotherapy with the ability to participate in physical activities, with 70.5% of patients/caregivers reporting no change. <h3>Conclusion</h3> In this preliminary survey, food allergen immunotherapy treatment was associated with improvement in patient/caregiver-reported well-being and improved ability to participate in social activities. Given the importance of QOL indicators on the decision to pursue food allergen immunotherapy, these results will help to inform the shared decision-making process and set realistic expectations for outcomes.

New technology product introduction strategy with considerations for consumer-targeted policy intervention and new market entrant

The emergence of new technology products brings systematic changes to the market, and appropriate responses to such changes are essential for the survival and success of firms. This study investigated producers' optimal new product introduction (and positioning) strategies in various situations that require different sets of decisions. Specifically, we considered the diffusion of hybrid electric vehicles and battery electric vehicles (BEVs) in the South Korean automotive market. A model incorporating the strategic, forward-looking behaviors of both producers and consumers was used to derive producer's optimal new product introduction plan based on long-term market forecasting. Then, we conducted simulation analyses to investigate the benefit of forward-looking planning and how optimal strategies change depending on the policy interventions and market entrance of the new producer. The results show that a forward-looking strategy could improve the market performance of new products by up to 40 % compared to the myopic strategy, and the plan adjustment of the incumbent in response to competition could reduce competition-related losses by up to 9 %. Finally, stronger policy intervention and new market competition will motivate producers to introduce more, less-expensive BEVs in their product portfolio. Such responses significantly expand the BEV market, which is also a socially desirable outcome.

Hermeneutics of the Law

One of the most ancient forms of thinking about law is what is today known as positivist or normativist. It focuses on the product presented in the name of the law, the textual representation which not only simply includes, but directly embodies the law. In other words, it is a corpus, whether it is a code, a properly issued rule or a set of ad-hoc decisions: this is the law itself. This represents a short-circuited ready form for cognition, which the conscious follower and the professional agent of the law will both use as a tool. In addition, however, presumably ages later, there emerges a completely different version of the idea of law, rooted in a culture that forecasts the hermeneutic way of thinking. If in the former an approach based on epistemology can be discerned, the latter takes a more ontological approach instead. This focuses, beyond the given text, upon its interpretation and on the understanding that may be drawn from the text, and thus ultimately on the content which the law is supposed to message to the law abider and enforcer alike. In other words, it is concerned with the genuine meaning that actually affects and influences its addressees. Moreover, it is clear that, in contrast to text-centricity, the hermeneutic approach is also aimed at what sociological examination relating to the law reveals: finding the lebendes Recht [living law], separated from the positives Recht, setting some law in action next to the law in books.

The Role of ctDNA in Gastric Cancer.

Simple SummaryDNA release from tumour cells (call circulating tumour DNA) into the blood stream can be found in patients with gastric cancer through a blood test call a liquid biopsy. This less invasive test can assess the genetic make-up of tumours to provide important information on the mechanisms of cancer development, identify mutations which can be targeted with drugs and could be used to screen for patients with gastric cancer. This article will review the current and future uses of liquid biopsies in gastric cancer.Circulating tumour DNA (ctDNA) has potential applications in gastric cancer (GC) with respect to screening, the detection of minimal residual disease (MRD) following curative surgery, and in the advanced disease setting for treatment decision making and therapeutic monitoring. It can provide a less invasive and convenient method to capture the tumoural genomic landscape compared to tissue-based next-generation DNA sequencing (NGS). In addition, ctDNA can potentially overcome the challenges of tumour heterogeneity seen with tissue-based NGS. Although the evidence for ctDNA in GC is evolving, its potential utility is far reaching and may shape the management of this disease in the future. This article will review the current and future applications of ctDNA in GC.

“After the floods, he says he is an environmentalist”: Understanding blended roles and organizational boundaries in decision-making under uncertainty during unprecedented floods in Wayanad, India

An increase in unprecedented environmental crises as a result of climate change and human influence has amplified calls for recognizing the complexity of decision-making under uncertainty (DMUU). How decision-makers act in institutional settings under uncertainty has, however, received limited attention in decision-making in planning practice. This article investigates DMUU in the context of Wayanad, a peri urban hill district in Kerala, India through two decision settings; the response to unprecedented heavy monsoon floods in 2018 and 2019 as a case of short-term uncertainty, and policy and plan making regarding quarrying in ecologically sensitive areas as a case of long-term uncertainty. Through empirical findings from semi-structured interviews of 58 decision-makers from state and non-state actors, the article discusses individual and collective actions made before, during and after the floods by combining insights on DMUU from spatial planning and governance literature underpinned by spatial-temporal and political ecology narratives. The article argues that factors such as community resourcefulness and decentralized governance appeared to facilitate effective decision-making under short-term uncertainty. However, the same factors did not have an intrinsic influence on decision-making under long-term uncertainty with current ways of decision-making regarding quarrying in ecologically sensitive areas likely obstructing sustainable long-term planning and land use transformation in Wayanad. The article concludes with recommendations for potential improvements in decision-making under long-term uncertainty in contexts with weak institutional mechanisms, chronic vulnerabilities and resource scarcity, through structural organizational change, cross-sectoral decision-making arenas, and decision-making frameworks that foregrounds heuristic, flexible, incremental, and cumulative actions across scales over time.

Multi-Stage Partner Selection for Firms’ Non-Core Offerings: A Study of The Telecom Sector of India

Partner selection is critical for organisational performance for both core and non-core offerings of a firm. Using a multiple-case study, we analyse the partner selection process related to the firm’s non-core offerings. The analysis suggests that partner selection is a multiple-stage process rather than a single-stage process. Partners are evaluated against the first set of criteria comprising value offering and technological complexity, generating possible decision sets through trade-off. Once the first stage decision is favourable, partners are assessed against another set of criteria at the next stage. For low technological complexity, the criteria are propensity to scale up and competitive advantage, whereas for high technological complexity, the criteria are organisational compatibility and technological sophistication. The decision sets from the final stage conclude partner selection and possible on boarding.

Parallel and comparative use of three multicriteria decision support methods in an environmental portfolio problem

Environmental management problems are often portfolio problems where the task is to find a set of actions that meets different objectives (e.g., the reduction of greenhouse gas emissions) and constraints (e.g., costs). We report experiences from deploying multiple operations research (OR) methods in a real decision-making setting and discuss the insights gained from this process. The applied methods were Multi-Attribute Value Theory (MAVT), the project portfolio selection tool Your Own Decision Aid (YODA) and Robust Portfolio Modelling (RPM). The methods were applied in a portfolio case evaluating three peatland rewetting options (“No action”, “Restoration”, “Damming”) for 79 drained peatland stands in an important recreational and nature conservation area in southern Finland. The pros and cons of the methods were evaluated, as well as their key methodological challenges, in a participatory environmental portfolio case. The applied methods yielded similar results in terms of the superiority of rewetting options. The strength of MAVT was its ability to highlight the strengths and weaknesses of all three rewetting options for a single peatland stand. YODA's strength was its simplicity and the possibility to apply it independently via the Internet. RPM made it possible to determine the priority of peatland stands within constraints, even without precise preference information. To our knowledge, this is the first systematic evaluation of three methods representing different ‘method categories’ (MAVT, multi-criteria elimination, portfolio decision analysis) applied to a real environmental problem.

Competition among public good providers for donor rewards.

We present experimental evidence for decision settings where public good providers compete for endogenous rewards which are donations (transfers) offered by outside donors. Donors receive benefits from public good provision but cannot provide the good themselves. The performance of three competition mechanisms is examined in relation to the level of public good provision and transfers offered by donors. In addition to a contest where transfers received by public good providers are proportional to effort, we study two contests with exclusion from transfers, namely a winner-takes-all and a loser-gets-nothing. We compare behavior in these three decision settings to the default setting of no-contest (no-transfers). Results for this novel decision environment with endogenous transfers show that donors offer transfers (contest prizes) at similar levels across contests and contributions to the public good are not significantly different in the three contests settings, but are consistently and significantly higher in all contests compared to the setting with no-transfers. Initially, the winner-takes-all setting leads to a significantly higher increase in public good contributions compared to the other two contests; but this difference diminishes across decision rounds.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10683-022-09766-7.

LINEAR PROGRAMMING MODEL OF PRODUCTION, INVENTORY AND DISTRIBUTION PROBLEM BASED ON RANDOM SAMPLING

A linear programming model using the random sampling technique was used for the optimization of the products in the production line of Nigerian Bottling Company (NBC), Lagos, which has many production facilities and multi-products systems. Products from the company are distributed to a number of depots across the country of which the demand for each product is known. The problem of interest involves determining what product/s should be made, how much of each product should be produced and where production should take place. The objectives of the company are to minimize the total cost as well as maximize the total sales revenue based on the set of decisions including demands, capacity restriction and budget constraints. Linear Programming software solver (LiPs) was used to solve large linear programming problems based on the mathematical model developed. The model improved the profit of the company under study by 5%.

Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis

BackgroundBuilding continuity of care by enabling optimal collaboration between hospitals and community pharmacies is critical. However, existing research on healthcare efficiency has largely focused on hospital services, and few studies have evaluated hospital services alongside pharmaceutical services. ObjectiveTo set up a dynamic network production model to assess the divisional efficiency of hospital and pharmacy utilizations and to investigate the dynamic changes and spatial differences for a more productive utilization of healthcare services. MethodsA dynamic network data envelopment analysis was applied on two interdependent healthcare divisions, hospitals and community pharmacies, in order to assess utilization efficiencies in both divisions simultaneously. Subsequent analyses were performed with a set of decision making units consisting of Taiwan's cities. Data were gathered from the Ministry of Health and Welfare and the Bureau of National Health Insurance, spanning 2014–2019. ResultsThe mean scores for overall healthcare, hospital, and pharmacy among cities were 81.9%, 89.2%, and 76.7% respectively. It appears that pharmacy is not very efficient, possibly because of the low rate of prescription release. A 13.26% reduction in pharmacists in the pharmacy sector is suggested, but the number of community pharmacies remains the same in cities and counties in 2019, based on the results of the slack-based measure. The bootstrapped-truncated regression indicated the different business districts had statistically significant determinants of overall efficiency, including hospital efficiency and pharmacy efficiency. ConclusionsThis study illustrated the inefficient operations of most hospital and pharmacy divisions in Taiwan's southern cities. It is hoped to draw the government's attention to the existing inefficiency in the allocation of healthcare and pharmaceutical resources. For future studies, a dynamic network model can be adapted to introduce the Malmquist productivity index in order to compare divisional productivity changes over time. Other topics for future research include handling undesirable outputs (quality variables) and information on input/output prices.

NATIONAL LAND COVER MAPPING USING VARIOUS REMOTE SENSING DATASETS IN GEE

National land-cover maps are essential for the development of the countries as land-use patterns have shifted dramatically throughout the world in the previous decades. With the latest development in the remote sensing community, the power and ease of web-mapping and web-based map and GIS services have increased. This work investigates several datasets for land cover categorization on a national scale across North Macedonia (25,713 km2) using Sentinel images within Google Earth Engine (GEE), a cloud computing platform designed to store and process huge data sets for analysis and ultimate decision making. Both single and synergetic use of Sentinel-1 and Sentinel-2 satellite images have been investigated. The basic land-cover components are generated, upon which the more detailed final land-cover/land-use data were derived and defined. Comparing the results of the datasets indicate the influence of the radar data over the optical data in land cover classification. Also, the influence of the investigated data over every class is calculated. The results showed that the various datasets lead to different overall accuracy. Also, the different datasets performed differently over single classes, even though their overall accuracy was the same. As a result, a high accuracy national-level land cover classification has been created. The results have been compared to the latest Corine data. The results can be critical to making informed policy, development, planning, and resource management decisions. This provided the standardized references from which landscape changes could be determined and quantified.

Efficient Learning of Interpretable Classification Rules

Machine learning has become omnipresent with applications in various safety-critical domains such as medical, law, and transportation. In these domains, high-stake decisions provided by machine learning necessitate researchers to design interpretable models, where the prediction is understandable to a human. In interpretable machine learning, rule-based classifiers are particularly effective in representing the decision boundary through a set of rules comprising input features. Examples of such classifiers include decision trees, decision lists, and decision sets. The interpretability of rule-based classifiers is in general related to the size of the rules, where smaller rules are considered more interpretable. To learn such a classifier, the brute-force direct approach is to consider an optimization problem that tries to learn the smallest classification rule that has close to maximum accuracy. This optimization problem is computationally intractable due to its combinatorial nature and thus, the problem is not scalable in large datasets. To this end, in this paper we study the triangular relationship among the accuracy, interpretability, and scalability of learning rule-based classifiers. The contribution of this paper is an interpretable learning framework IMLI, that is based on maximum satisfiability (MaxSAT) for synthesizing classification rules expressible in proposition logic. IMLI considers a joint objective function to optimize the accuracy and the interpretability of classification rules and learns an optimal rule by solving an appropriately designed MaxSAT query. Despite the progress of MaxSAT solving in the last decade, the straightforward MaxSAT-based solution cannot scale to practical classification datasets containing thousands to millions of samples. Therefore, we incorporate an efficient incremental learning technique inside the MaxSAT formulation by integrating mini-batch learning and iterative rule-learning. The resulting framework learns a classifier by iteratively covering the training data, wherein in each iteration, it solves a sequence of smaller MaxSAT queries corresponding to each mini-batch. In our experiments, IMLI achieves the best balance among prediction accuracy, interpretability, and scalability. For instance, IMLI attains a competitive prediction accuracy and interpretability w.r.t. existing interpretable classifiers and demonstrates impressive scalability on large datasets where both interpretable and non-interpretable classifiers fail. As an application, we deploy IMLI in learning popular interpretable classifiers such as decision lists and decision sets. The source code is available at https://github.com/meelgroup/mlic.

When law students think like audit litigation attorneys: Implications for experimental research

Prior research suggests that drivers of audit litigation periodically change, requiring continuing research to understand them. Yet, our understanding of the factors influencing the judgments of audit litigation attorneys—who resolve most audit disputes via settlement—remains limited, primarily due to the limited availability of these attorneys for experimental research. We seek to remedy this impediment by examining judgments of audit litigation attorneys, law professors, and law students to assess whether law students—an accessible pool of participants with technical legal knowledge—can proxy for audit litigation attorneys in some settings. Our results suggest that law students can reasonably proxy for audit litigation attorneys in decision settings more reliant on the application of technical legal knowledge primarily acquired in law school, relative to the application of strategic legal knowledge primarily acquired through legal experience. We validate a theoretical model and provide guidance on when law students should and should not be used as proxies. Our findings open fruitful avenues for future research of important audit litigation topics that have not been sufficiently examined, likely due to researchers’ lack of access to audit litigation attorneys.

IoT based sustainable smart waste management system evaluation using MCDM model under interval-valued q-rung orthopair fuzzy environment

Waste management has a crucial role for human health and well-being. The novel waste collection technologies, information and communications technologies (ICTs) and Internet of Things (IoT) play important roles in the field of municipal waste management considering sustainability aspects such as economic, social and environmental. Considering future development and the sustainability of the environment, selecting the most appropriate smart technology to manage waste collection may have long-term impacts. This paper aims to evaluate the smart waste collection systems based on IoT with respect to uncertain parameters by applying modified Entropy measure and Multi-Criteria Decision Making (MCDM) method for the local municipal in Istanbul. To deal with uncertainty and vagueness associated with the decision-making process Interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) is employed in the process. As a result, the waste collection system developed using RFID, GIS and GPRS is selected as the most appropriate smart waste collection system based on IoT for municipal. To validate results and prove robustness of the proposed method in the decision making, Sensitivity and Comparative analysis are conducted at the end of the study.

Concordance between influential adverse treatment outcomes and localized prostate cancer treatment decisions

BackgroundAlthough treatment decisions for localized prostate cancer (LPC) are preference-sensitive, the extent to which individuals with LPC receive preference-concordant treatment is unclear. In a sample of individuals with LPC, the purpose of this study was to (a) assess concordance between the influence of potential adverse treatment outcomes and treatment choice; (b) determine whether receipt of a decision aid predicts higher odds of concordance; and (c) identify predictors of concordance from a set of participant characteristics and influential personal factors.MethodsParticipants reported the influence of potential adverse treatment outcomes and personal factors on treatment decisions at baseline. Preference-concordant treatment was defined as (a) any treatment if risk of adverse outcomes did not have a lot of influence, (b) active surveillance if risk of adverse outcomes had a lot of influence, or (c) radical prostatectomy or active surveillance if risk of adverse bowel outcomes had a lot of influence and risk of other adverse outcomes did not have a lot of influence. Data were analyzed using descriptive statistics and logistic regression.ResultsOf 224 participants, 137 (61%) pursued treatment concordant with preferences related to adverse treatment outcomes. Receipt of a decision aid did not predict higher odds of concordance. Low tumor risk and age ≥ 60 years predicted higher odds of concordance, while attributing a lot of influence to the impact of treatment on recreation predicted lower odds of concordance.ConclusionsRisk of potential adverse treatment outcomes may not be the foremost consideration of some patients with LPC. Assessment of the relative importance of patients’ stated values and preferences is warranted in the setting of LPC treatment decision making.Clinical trial registration: NCT01844999 (www.clinicaltrials.gov).