Commercial Decision Research Articles

Intelligent Data Mining and Decision System for Commercial Decision Making

Information system and data mining are important resources for the investors to make decisions. Information theory pointed that the information is increasing all the time, when the corporations build their millions of databases in order to improve the efficiency. Database technology caters to the needs of fully developing the information resources. This essay discusses the problem of decision making support system and the application of business data mining in commercial decision making. It is recommended that the intelligent decision support system should be built. Besides, the business information used in the commercial decision making must follow the framework of a whole system under guideline, which should be designed by the company. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3977

A demographic survey of unwanted horses in Ireland in 2011 and totals for 2012 and a comparison with 2010.

This report compiles the available information on unwanted horses in Ireland for 2011 and 2012 and builds upon the previous report for the period 2005 to 2010. Similar trends are present in the high value responsible ownership category and the practicing veterinary profession although extensively involved in horse welfare, euthanises a small proportion of Ireland’s unwanted horses. Welfare groups have limited resources and a limited ability to deal with such an extensive problem, which has involved very large numbers of horses. Local authorities continue to have to devote significant efforts and calls on public finances to deal with unwanted horses. Those that they have to deal with are, in the main, not identifiable by either passports or microchips. Category 2 plants and abattoirs continue to provide the principal means of disposal of unwanted horses. The need for abattoirs continues to increase and it is essential that these facilities remain in operation. They processed more than 49,000 horses between 2010 and 2012. The samples they have to submit for Trichinella testing are the most sensitive indicator of the extent of the unwanted horse problem and the most immediate source of information on when it may begin to abate. Trichinella sample numbers and this by inference, horses ponies and donkeys sent to slaughter have fallen by some 35% from 2012 numbers, in the year to date (2013). This may reflect the commercial decision to cease horse slaughter by two slaughterhouses that had hitherto provided this service. Their commercial decision was not in any way related to the identification of fraudulent mislabeled beef in other plants.

Adopting a Commercial Clinical Decision Support for Imaging Product: Our Experience

WHY COMMERCIAL DECISION SUPPORT Clinical decision support (CDS) has emerged as a tool to improve patient care across many specialties [1]. Broadly defined, CDS is a method of delivering organized clinical knowledge and recommendations to a clinician to assist in selecting the best course of action for a specific clinical scenario. With regard to imaging, the purpose of CDS is to assist a referring physician in requesting the most appropriate imaging study for a specific clinical scenario [2]. CDS for imaging has been integrated into electronic ordering systems at other institutions with success. Some institutions have reported adoption across virtually all specialties, reduction in low-yield imaging, and even elimination of the need for preauthorization by thirdparty payers when using CDS [3-6]. Therefore, one can reasonably infer that a successful CDS system for imagingcouldnotonly improvepatientcare but might also aid in cost containment and compliance with meaningful use requirements [7,8]. As a result of the positive gains reported at other institutions, our department embraced CDS for computerized physician order entry (CPOE) of imaging studies. However, successful implementation of CDS into the CPOE for imaging studies has only been reported at institutions with “homegrown” CDS programs, which are programs developed by and for the institutions at which they were ultimately used, an approach that likely mitigated or eliminated many of the potential problems associated with CDSCPOE integration. The objective of this paper is to describe our experience at the University of Colorado attempting to integrate a third-party commercial CDS product into our health care system.

Judicial review of government’s economic policies in the Commonwealth Caribbean

This piece considers decisions of the Commonwealth Caribbean where applicants have sought to challenge the economic rational or commercial decision of government in enacting legislation without expressly saying so. The courts have considered the question of whether parliament can legislate a reduction of salaries of public servants and privatize aspects of the public service. In the main, the courts in the Commonwealth Caribbean have been able to deal with the legal issue raised without opining on the underlying rationale for the legislation passed by parliament.

‘Keeping unbroken ways’: the role of the Railway Clearing House Secretariat in British freight transportation, c.1923–c.1947

With the amalgamation of Britain's rail network in 1923, the role of the Railway Clearing House (RCH) in co-ordinating, operating and commercial decision making might have been expected to diminish. Instead the Clearing House secretariat extended its involvement in pricing and co-ordination between the ‘big four’ railway companies and even became the basis for the new nationalised industry in 1947. This paper explores the RCH as a venue for discussion and negotiation, where routines were articulated and codified, extending those within individual railway companies. In so doing, the RCH is revealed as an extension of the managerial hierarchy of each separate firm.

Text summarization as a decision support aid

BackgroundPubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data.MethodsWe downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed.ResultsFor the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists.ConclusionSemantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.

Rethinking information delivery: using a natural language processing application for point-of-care data discovery

This paper examines the use of Semantic MEDLINE, a natural language processing application enhanced with a statistical algorithm known as Combo, as a potential decision support tool for clinicians. Semantic MEDLINE summarizes text in PubMed citations, transforming it into compact declarations that are filtered according to a user's information need that can be displayed in a graphic interface. Integration of the Combo algorithm enables Semantic MEDLINE to deliver information salient to many diverse needs. The authors selected three disease topics and crafted PubMed search queries to retrieve citations addressing the prevention of these diseases. They then processed the citations with Semantic MEDLINE, with the Combo algorithm enhancement. To evaluate the results, they constructed a reference standard for each disease topic consisting of preventive interventions recommended by a commercial decision support tool. Semantic MEDLINE with Combo produced an average recall of 79% in primary and secondary analyses, an average precision of 45%, and a final average F-score of 0.57. This new approach to point-of-care information delivery holds promise as a decision support tool for clinicians. Health sciences libraries could implement such technologies to deliver tailored information to their users.

Networks of practice for co-construction of agricultural decision support systems: Case studies of precision dairy farms in Australia

The on-farm use of commercial decision support systems (DSSs) presents learning and adaptation challenges for farmers and their social learning networks. A study of six Australian dairy farms installing new precision dairy farming technology was undertaken to develop an in-depth picture of the issues occurring at the interface where precision farming data and decision-making meet. A qualitative exploratory case study method was used, with farmers each interviewed up to five times from pre-installation until 2years of use. A three-phase learning trajectory was observed amongst farmers involving early learning, consolidation, and advanced use. Farmers exhibited experiential learning but also learned via interaction with a network of on- and off-farm contacts forming a network of practice around the new users. This precision dairy farming network of practice formed a vital method of exchanging knowledge on how to best use technology and data in farming systems, with DSSs acting as a boundary object for learning. Externalisation of tacit knowledge into an explicit form suitable for DSSs was a major focus of this social learning. Co-construction of DSS knowledge in the emerging network was impeded by the absence of potentially important agents, in addition to the incomplete links between existing agents such as technology retailers and farmers. A technological innovation systems perspective is used to propose an improved framework to make greater use of translators and intermediaries. It is aimed at improving links amongst the community to more effectively aid farmers in creating new knowledge in agricultural DSS use.

Iron-Containing Intermetallic Phases in Al-Si Based Casting Alloys

Iron is the most common impurity in aluminium and its alloys. It is not easily removed and it can cause adverse effects to ductility and castability, particularly in the popular Al-Si based casting alloys. The choice of whether to use alloys based on primary aluminium (low Fe levels, high cost) or secondary aluminium (moderate/high Fe levels, cheaper) for a cast product is often a commercial decision. However, a compromise may be necessary between the desire for reduced metal cost and the need to maximise casting productivity via reduced defect formation and to minimise the deleterious effect of iron on mechanical properties. This paper discusses the various sources of iron, how it enters aluminium alloys, the way that iron leads to the formation of complex intermetallic phases during solidification and how these phases can adversely affect mechanical properties (especially ductility) and lead to the formation of excessive shrinkage defects. The formation of the iron-containing β phase will be highlighted using the latest in situ solidification study using synchrotron X-radiation. The paper offers guidelines to the practical levels of iron that can be tolerated and how to minimise the negative effects of iron.

Comparing Drug-Drug Interaction Severity for Clinician Opinion to Proprietary Databases

Purpose: Commercial clinical decision support software (CDSS) may overestimate the severity of drug-drug interactions (DDI) because of their broad application; whereas, clinicians with knowledge of the patient should be able to better assess DDI severity. The purpose of this project was to compare DDI severity for clinician opinion in the context of the patient’s clinical status to the severity of proprietary databases. Methods: This was a single-center, prospective evaluation of DDIs at a large, tertiary care academic medical center between October 11, 2010 and November 5, 2010 in a 10-bed cardiac intensive care unit (CCU). A pharmacist identified DDIs using two proprietary databases. The physicians (fellow and attending) and pharmacists (rounding and distribution) caring for the patients evaluated the DDIs for severity while incorporating their clinical knowledge of the patient. Severity was ranked on a scale ranging from A to D and X. Results: A total of 61 patients were included in the evaluation and experienced 769 DDIs. The most common DDIs included: aspirin/clopidogrel (n=21, 2.7%), aspirin/insulin (n=21, 2.7%) and aspirin/furosemide (n=19, 2.5%). Pharmacists ranked the DDIs identically 73.8% of the time, compared to the physicians who agreed 42.2% of the time. Pharmacists agreed with the more severe proprietary database scores for 14.8% of DDIs versus physicians at 7.3%. Among the five contraindicated DDIs, two were rated as category B (minor severity/no action needed) and three as category C (moderate severity/monitor therapy) by the majority of the reviewers. Overall, clinicians agreed with the proprietary database 20.6% of the time while clinicians ranked the DDIs lower than the database 77.3% of the time. Conclusions: Proprietary DDI databases generally label DDIs with a higher severity rating as compared to clinicians who are caring for patients. Developing a DDI knowledgebase for CDSS requires careful consideration of the source of the severity information and should include clinician input in order to create clinically meaningful alerts.

Decision Criteria for Climate Projects

Summary This article analyzes commercial decision criteria for climate projects. The latter will normally be executed by private players, for whom decision criteria developed from a commercial perspective are important. But such criteria are also important for the government in calculating the size of subsidies required for various measures. A ranking of different solutions in a socioeconomic context must rest on calculations made from a commercial perspective. Examples of the subjects covered include the calculation of abatement unit costs and cost estimating for climate projects. The carbon-capture project at the Kårstø gas-fired power station in southwest Norway is used as a case throughout the analysis.

AN EVALUATION OF STUDENT SATISFACTION WITH GIS PROJECT FOR DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE COURSES

AITP as a worldwide society of information technology business professionals has accommodated a Business Intelligence – Geographical Information Systems (GIS) contest in its annual collegiate conference in the past five years. The contest requires participants to use a commercial GIS application, Excel, and decision making knowledge to solve a ‘real-world’ business problem. It has been well received by contestants and used by some instructors attending the conference. This study reported the adoption and implementation of the GIS project in its Decision Support Systems/Business Intelligence courses by a large mid-western university. A survey was carried out to find the participants’ attitude and perception of the project. Research results show that the GIS project is appropriate for DSS/BI courses and well received by Information Systems undergraduate and graduate students.

The cargo throughput response to factor cost differentials–an analysis for the port of Hong Kong

Previous studies on port cargo throughput have been simplified. The regression models are mainly based on the autoregressive time series, in which the port throughput is regressed against the lagged value from the preceding time period. Most factors are assumed exogenous to port throughput. This approach is based on the premise that ports are oligopoly markets and many factors (e.g. port charges) are not available for inclusion in research. The main objective of this study is to include the costs of using the port in the regression model so as to reflect real commercial decision. Due to port costs generally not being available, the real estate prices and other factors are chosen as proxy variables to indicate indirectly the costs and benefits of using the port under study.

A flock-tailored early warning system for low pathogenic avian influenza (LPAI) in commercial egg laying flocks

The aim of this study was to develop and evaluate an early warning system (EWS) for commercial egg laying flocks to detect the subtle mortality and egg production changes that characterize low pathogenic avian influenza virus (LPAIV) infections. An EWS will create an alert when the recommended ‘trigger point’ is reached or exceeded. Previously used EWSs are based on fixed alert levels, while the proposed EWS customizes the alert level to each flock. While a fixed approach may be valid for highly pathogenic diseases, it results in a lower detection probability for low pathogenic diseases. The EWS was based on daily data collected from flocks affected by the 2000–2004 H6N2 LPAI epidemic in California. Three EWSs were evaluated: (1) EWS1, which is triggered when the observed mortality increase or production decrease exceeds more than “ x” times the expected daily value (2.75–3.50 times the expected mortality), (2) EWS2, which is triggered when the observed mortality increase or production decrease exceeds more than “ y” times during each of 2 consecutive days the expected daily values (1.75–2.15 times the expected mortality), and (3) a combination of the two. The EWSs were evaluated according to three parameters: detection delay (days) of a LPAI outbreak, false alerts (%) and outbreaks missed (%). Results showed that an egg production-based EWS added no benefit to a mortality-based system, mainly because H6N2 LPAI-related egg production decrease always occurred after increase in mortality. Combining the two EWSs resulted in a reduced detection delay and no missed outbreaks, but at the expense of a slight increase in the number of false alerts triggered. The system presented in this study also outperformed fixed EWSs in all three evaluated parameters. The proposed EWS, if used as part of a poultry cooperative program and combined with a rapid laboratory diagnosis, could be a useful tool in the detection and control of LPAI outbreaks and other poultry diseases. Built in a spreadsheet, the system could be inexpensively, easily and quickly incorporated into a commercial egg production farm decision support system. In addition, the proposed system could be quickly adjusted to changing epidemic situations, and easily customized to individual flocks.

Commercial Library Decision Support Systems: An Analysis Based on Collection Managers' Needs

In the current environment of widely dispersed and disparate electronic data sources, collection managers increasingly need tools such as decision support systems to routinely perform common types of collection analysis: collection comparison, usage, package deals, and resource sharing. Four commercial decision support systems, Serials Solutions’ 360 Counter, Thomson Reuters’ Journal Use Reports, Swets’ ScholarlyStats, and Serials Solutions’ Ulrich's Serials Analysis System, are considered for their strengths in the above types of analysis and across five additional dimensions: Project COUNTER (Counting Online Usage of Networked Electronic Resources) reports supported, analysis tools, custom data sources supported, reporting features, and product support. Current issues and future trends are discussed.

An analysis of perceived prominent decision making areas in commercial Springbuck ( Antidorcas marsupialis ) production decision making

The development of the highly individualistic commercial springbuck (Antidorcas marsupialis) production systems and the resulting growth in the commercial value of the springbuck has opened a new realm of game management decision making. These relatively undomesticated production systems demand sophisticated technical and preference decisions in an effort to reconcile ecological, commercial and management principles and practices into efficient production units. This paper endeavours to identify and define the relative prominence of different decision making areas in commercial springbuck production decision making, using qualitative and quantitative techniques associated with phenomenological studies. Overall indications are that a clear understanding exists that different challenges (of achieving perceived optimum efficiency) attract different sets of decisions. The array of decision making areas subjectively associated with the achievement of perceived optimum efficiency suggests the complexity of the decision making process in commercial springbuck production systems. A major need for research and information generation and distribution (extension) concerning the effects of herd structure and management on commercial springbuck production is identified. Keywords : Game ranch management, decision making, risk perception, springbuck. South African Journal of Agricultural Extension Vol. 36 (1) 2007: pp. 249-268

Evaluating subtle stratigraphic traps: prospect to portfolio

Abstract A compilation of 85 stratigraphic traps demonstrates the variety of trapping mechanisms and the scope for developing new concepts by matching geological models with features in 3D seismic volumes. However, aspects of quantitative evaluation may discourage exploration. Investors require assurance in the form of probabilistic evaluations of risk and value but information critical to the evaluation of new stratigraphic concepts is likely to be lacking. As estimates of risk and uncertainty vary with information, prospects evaluated with radically different levels of information must be ranked with care. The requirements for quantitative project ranking and portfolio optimization have to be reconciled with the need to ‘venture into the unknown’. The character of stratigraphic prospects dictates different evaluation methods from those used to evaluate structural prospects. This, together with the high degree of sensitivity of value to evaluation methodology, can also lead to inconsistencies in ranking. Within the context of a company’s overall strategy and risk tolerance, organizational and cultural factors may influence prospect selection. In particular over-emphasis on quantitative methods may not have the intended effect. A common understanding, amongst technical and commercial disciplines and decision makers, of the background to quantification is essential. Factors which encourage the progression of stratigraphic prospects include a dedicated geoscience effort, a separate ‘growth’ portfolio of new concepts, a formal structure for progressing these and a stable organization.

Commercial Plans In Medicaid Managed Care: Understanding Who Stays And Who Leaves

Although the rapid increase in Medicaid managed care during the early 1990s attracted commercial plans to the program, by the late 1990s commercial plan participation in Medicaid had begun to decline. This study examines the role of Medicaid policies, plan characteristics, and local health care market conditions in a commercial plan's decision to exit. We find that many of the factors that influence commercial plans' decisions to exit Medicaid are within the control of state policymakers and program administrators, including capitation rates, service carve-outs, mandatory enrollment policies, and the number of Medicaid enrollees and areas served by the plan.

Caractéristiques de l'information, surcharge d'information et qualité de la prédiction

Résumé Dans un contexte de surcharge d’information, la psychologie cognitive nous apprend que le fait d’augmenter la quantité d’information disponible nuit à la qualité de la prédiction. Il est essentiel de faire la distinction entre données pertinentes, redondantes et non pertinentes, et d’examiner leurs effets respectifs sur la qualité de la prédiction. L’auteur pose l’hypothèse selon laquelle seules les données redondantes nuisent à la qualité de la prédiction. Il s’est livré à une expérience dans le cadre de laquelle les sujets simulaient une prise de décision d’octroi d’un prêt commercial. La quantité de données disponibles a été modifiée de façon qu’elle soit faible, moyenne ou élevée, ce qui a donné lieu à trois versions de la demande de crédit. Chaque prêteur prévoyait la santé financière de six entreprises emprunteuses. L’expérience a permis de constater que l’augmentation de la quantité de données redondantes nuit à la qualité de la prédiction. Selon les résultats obtenus, une stratégie d’information possible consisterait à cibler les utilisateurs et à leur fournir seulement les données pertinentes à leur tâche. Les résultats démontrent aussi l’utilité des aides à la prédiction dans un contexte de surcharge d’information.

決定木分析による都市型アミューズメント施設の来訪者特性評価

決定木分析による都市型アミューズメント施設の来訪者特性評価