Decision-relevant Information Research Articles

Customer accounting and customer profitability analysis for the order handling industry—A managerial accounting approach

Market-oriented businesses are concerned with customer satisfaction and business profitability, both in the longer term. Thus the marketing managers need updated decision-relevant information (marketing metrics) with respect to the set of processes that are leading to customer values and economic customer values. The attention of this study is focused on the profitability aspects of marketing. The context is the business-to-business order-handling industry, i.e. four exporting companies and 176 of their customers in 36 various markets. A market-oriented accounting framework that can be included as a natural part of a managerial accounting system is introduced and discussed, and financial reports as well as graphic representations and key figures for various levels of a market hierarchy are presented. The findings with respect to the profitability of orders, customers and markets are presented and the managerial implications are discussed.

THE ROLE OF COGNITIVE INFORMATION PROCESSING IN HEALTH POLICY & EVIDENCE BASED HEALTH CARE.

The current trend in health care policy has evidenced the growing popularity of utilizing evidenced-based health information to make key decisions regarding health policies such as access-to-care, funding, and immunization programs. However, evidenced-based health care functions under an assumption of decision rationality. This paper contends health policy makers are generally unable to follow the basic tenants of evidenced-based health care rational decision making due to influences experienced during the processing of relevant decision information. A cognitive information processing framework is presented and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the manner in which they process decision relevant information.

On the soundness of altering granular information

Computer based multi-source and information fusion is often an intermediate step in the deduction of decision-relevant information. Fuzzy sets provide a useful formalism for the representation of the types of uncertain granular information that appear as inputs and outputs of these fusion systems. When our ultimate goal is the derivation of human oriented decision-relevant information we must often alter the output of these fusion systems to provide information in a form more readily accessible to the human recipient. In this work we introduce and investigate a measure of soundness which can be used to calculate the validity of various alterations of fuzzy granular information in the course of transforming outputs of fusion systems into forms more useful for human comprehension and manipulation. An important role in this work is played by the idea of similarity.

Sampling and pooling of decision-relevant information: Comparing the efficiency of face-to-face and GSS supported groups

Past research has suggested that decision-making groups, when communicating face-to-face (FtF), suffered from information sharing biases that affected the quality of the final decision: they tended to discuss previously-shared information before they started to discuss information not known to all, and discussed more of previously-shared than unshared information. In our study we examined these effects in groups that interacted FtF or using a group support system (GSS). Four-member groups discussed a requirements elicitation task in which some requirements were known to all members before starting their discussion, while other requirements were known only to two members of the group. Both GSS and FtF groups exchanged a large percentage of the shared requirements. However, the GSS groups were more effective in communicating unshared requirements. On average, FtF groups discussed shared requirements sooner and unshared requirements later than did GSS groups. Our study also compared empirical results with predictions from an information-sampling model of group discussion in order to assess the effectiveness of the model in computer-mediated group communication.

Working Within and Beyond the Cochrane Collaboration to Make Systematic Reviews More Useful to Healthcare Managers and Policy Makers

Participants in the Cochrane Collaboration conduct and periodically update systematic reviews that address the question, "What works?" for healthcare interventions. The Cochrane Library makes available quality-appraised systematic reviews that address this question. No coordinated effort has been undertaken to conduct and periodically update systematic reviews that address the other types of questions asked by healthcare managers and policy makers, to adapt existing reviews to highlight decision-relevant information (including the factors that may affect assessments of a review's local applicability) or to facilitate their retrieval through a "one-stop shopping" portal. Researchers interested in evaluating new methodological developments, health services and policy researchers interested in conducting and adapting systematic reviews, and research funders all have a role to play in making systematic reviews more useful for healthcare managers and policy makers.

Sampling and pooling of decision-relevant information

Past research has suggested that decision-making groups, when communicating face-to-face (FtF), suffered from information sharing biases that affected the quality of the final decision: they tended...

Applying SERVQUAL to Diagnose Hotel Sector in a Tourist Destination

ABSTRACT This paper investigates the feasibility of applying SERVQUAL to measure the quality ofservice provided by the establishments of a tourism subsector (hotels) of a tourist destination (Cantabria, an autonomous region in northern Spain), in order to obtain relevant information for decision-making by those in charge of the tourist administration and industry associations of the region. In the specific case of the subsector we have chosen, the most significant variables for a strategic diagnosis, and which have therefore been incorporated into the analysis, are the legal category of the establishment and the geographical zone where it is located. The results of the study have allowed us to identify the categories of establishments, and the zones which require special attention, as well as the sort of interventions needed.

Uncertainty in biokinetic parameters on bioremediation: Health risks and economic implications

Human health risk assessment is one of the rapidly evolving tools used in the management of contaminated aquifers. Health risk assessments have been traditionally based on the point estimate approach. Due to the uncertainty and variability inherent in subsurface properties and exposed human population characteristics, probabilistic risk assessment is becoming widely accepted. This study is focused on understanding the uncertainty in biokinetic parameters in describing biodegradation under natural and enhanced remediation conditions. The uncertain parameters considered in this work are key biokinetic parameters and the uncertainty is assessed using the predicted receptor maximum concentration, maximum of 30-year average concentration, time to reach maximum concentration, maximum mass of decay, and the time for maximum decay. The results of this analysis were extended to health risk assessment and risk-based economic analysis. The paper discusses the approach and methodology adopted in this study and the implication of uncertainty of key parameters on decision-relevant information.

Automatic identification of oil spills on satellite images

A fully automated system for the identification of possible oil spills present on Synthetic Aperture Radar (SAR) satellite images based on artificial intelligence fuzzy logic has been developed. Oil spills are recognized by experts as dark patterns of characteristic shape, in particular context. The system analyzes the satellite images and assigns the probability of a dark image shape to be an oil spill. The output consists of several images and tables providing the user with all relevant information for decision-making. The case study area was the Aegean Sea in Greece. The system responded very satisfactorily for all 35 images processed. The complete algorithmic procedure was coded in MS Visual C++ 6.0 in a stand-alone dynamic link library (dll) to be linked with any sort of application under any variant of MS Windows operating system.

A Meta-Modeling Approach to Designing e-Warehousing Systems

A business application that leverages the Internet for selling products and services or for information dissemination is called an e-business solution. In the past few years, organizations have moved aggressively towards deploying e-business solutions to improve process efficiencies, be competitive, access new markets, increase market share, reduce costs and satisfy an array of other business drivers. Within the domain of e-business initiatives, particular emphasis has been provided on e-warehousing initiatives. The differentiating facet of e-warehousing initiatives is that they are high-impact solutions that affect various parts of the organization, and ultimately the business goals of the enterprise, by providing relevant decision-making information at the manager's desktop, irrespective of geographic location. Despite this, many of these initiatives are technology based and have lacked strategic level sponsorship, leading to compromised results. Development of e-warehousing systems should be viewed as a strategic business initiative with distinctly different business models and processes. Traditional design approaches alone are not suited to such strategic initiatives. E-warehousing initiatives require new models for design in the early stages of development. In the later stages, traditional design approaches are applicable. In this article, we propose a meta-modeling approach for e-warehousing initiatives. The model has four components: developing business goals and strategies, defining functional business processes, developing an e-warehousing integration architecture, and designing metrics for evaluating the performance of the e-warehousing initiative. This model is illustrated by using an e-warehousing initiative for a government agency.

Cancer Outcomes Research and the Arenas of Application

In 2004, an estimated 1.5 million persons in the United States will be diagnosed with cancer; about 560 000 will die from cancer; and more than 9.5 million will be undergoing curative treatment, coping with progressive disease, or living free of cancer after successful therapy (1). But many of these survivors still feel the aftershocks and downstream side effects arising from diagnosis and treatment, and many are fearful of recurrence. Substantial progress in reducing the suffering and death caused by cancer is being pursued by the National Cancer Institute (NCI) and cancer agencies and organizations worldwide through a variety of initiatives, programs, and projects. At the NCI, these efforts emphasize the joint importance of basic and applied scientific discovery, the development and testing of promising interventions, and the delivery of quality care to prevent, detect, and treat cancer and to improve the length and quality of life of cancer survivors (2). It is therefore vital for decision makers, at all levels, to have a firm understanding of just how effectively the fruits of discovery and development are being applied to enhance cancer care delivery in ways that reduce suffering and death. The scientific pursuit of such decision-relevant information is the central business of cancer outcomes research. The overall aim of this Monograph is to provide an empirically grounded review and evaluation of the peer-reviewed literature in cancer outcomes research. The intent is to identify both important recent contributions and the challenges that remain in bringing scientifically sound information to bear in cancer care decision making. DEFINING CANCER OUTCOMES RESEARCH

Accounting for Stock Options

Employee stock options differ substantially from traded options. Most expire within 90 days of the termination of employment, and are forfeited if the employee leaves before vesting. The major accounting standards boards are in agreement that options should be expensed, but companies have legitimate complaints about the proposed methods. For example, the proposals create accounting incentives for firms to lay off employees who hold unvested and nearly worthless options. We propose a simple accounting system, based on 90 day option prices, that addresses these legitimate objections. The system produces objective, transparent, and decision-relevant information. Firms are given signifcant fexibility regarding the amortization of unvested option expense. This fexibility is created, without distorting incentives, by our use of market-based prices whenever an option expense is recognized.

Shared knowledge and subgroup influence during decision‐making discussions

AbstractIt was predicted that preference factions within decision‐making groups would have greater influence to the extent that faction‐member preferences are based on a common pool of decision‐relevant information. Such factions are said to exhibit high informational commonality (IC). Four‐person groups decided how much money to invest in each of two pharmaceutical companies developing new cholesterol‐lowering drugs. Prior to discussion, information about these companies and drugs was distributed among members such that two would initially prefer investing in one company and two would initially prefer investing in the other company. Further, whereas half of the information held by members of one preference faction was held in common between them (high IC), almost none of the information held by those in the other faction was held in common between them (low IC). It was found that groups invested more money in a given company when that company was initially preferred by their high‐IC faction. Additionally, high‐IC factions exerted greater influence on members' private allocation preferences. These effects appear to have been due to the ability of members in the high‐IC factions to work together in a more coordinated manner to argue their position. Copyright © 2004 John Wiley & Sons, Ltd.

Mobile decision support for transplantation patient data

In high-critical medical fields instant information delivery is essential. Task-flow analyses within the transplantation unit of the Technische Universität München revealed that valuable time could be saved in pre-transplantation management being able to retrieve data of organ receivers ubiquitously. Inspired by this clinical scenario, a mobile application was designed and implemented providing surgeons with decision-relevant information on potential organ receivers. It assists them in considering the prospects of forthcoming organ transplantations and facilitates decision making and documentation with regard to high security demands. The described system services three organ receiver lists and is used by the surgeons in every transplantation procedure. After a 6-month period of clinical usage, the system has been evaluated in terms of handling, clinical benefit and total time savings. Intuitive, ubiquitous access to decision-relevant patient data and authenticated documentation were the major improvements with average total time savings of 50 min in comparison to the old system.

Mobile decision support for transplantation patient data

In high-critical medical fields instant information delivery is essential. Task-flow analyses within the transplantation unit of the Technische Universität München revealed that valuable time could be saved in pre-transplantation management being able to retrieve data of organ receivers ubiquitously. Inspired by this clinical scenario, a mobile application was designed and implemented providing surgeons with decision-relevant information on potential organ receivers. It assists them in considering the prospects of forthcoming organ transplantations and facilitates decision making and documentation with regard to high security demands. The described system services three organ receiver lists and is used by the surgeons in every transplantation procedure. After a 6-month period of clinical usage, the system has been evaluated in terms of handling, clinical benefit and total time savings. Intuitive, ubiquitous access to decision-relevant patient data and authenticated documentation were the major improvements with average total time savings of 50 min in comparison to the old system.

Informational Centrality and Member Participation During Group Decision Making

This study examined whether participation during group decision-making discussions is affected by the degree to which members hold predominantly shared versus predominantly unshared decision-relevant information. Altogether, 115 three-person, same-sex groups completed a decision-making task in which a majority of the information held by a randomly selected target member either was also held by other members of the group (shared information) or was held by the target member alone (unshared information). It was found that in comparison to target members who held mostly shared information, targets who held only unshared information claimed fewer speaking turns and contributed fewer information-based comments during discussion. Further, holding unshared information appeared to depress participation to a greater extent than holding shared information facilitated participation, relative to a standard of equal participation across all members. These participation effects subsequently influenced target members’ agreement with their group’s eventual decision, with lower participation resulting in lower agreement. Thus, in addition to the negative consequences that unequally distributed information can have for the group as a whole, the present findings highlight a parallel set of negative consequences that can exist for individual members of the group.

Patterns of the use of information for decision making by administrative staff of a university in Nigeria

Reports a study of the use of information for decision making by administrative staff at the Delta State University, Abraka, Nigeria. It explores the working experience of the respondents, sources of information for official decision making, areas of decisional information use, frequency of utilisation of adequate and relevant information for decision making, and problems encountered by the administrators while seeking information for making decisions. Concludes with recommendations which could help administrative staff improve their use of information for decision making.

Use of the mediplus patient database in healthcare research.

Public health systems require fast and precise analyses of physicians' day-to-day diagnoses and therapy behavior regarding qualitative, safety or economical aspects. A partnership between physicians in practices and a database organization (IMS Health, Frankfurt, Germany) which has been in existence for more than 10 years has developed a procedure for documenting various types of studies with regard to diagnosis and therapy behavior. This endeavor has facilitated scientific progress by providing precise analytical information and guidelines. The database used has the name mediplus. It is a longitudinal patient database with anonymous access to a representative and valid panel of physicians and patients in Germany. A total of more than 1,000 medical practices and over 75 million prescriptions have been documented in a cross and/or longitudinal section. The longest time period per patient is more than 10 years starting in 1989, with monthly updates. Analyses have been obtained detailing prescription behavior of doctors regarding diabetes therapy and enable recommendations to be made regarding the therapy of migraine and the eradication of Helicobacter pylori infections. Information is also retrievable on drug safety studies in general and the extent to which hospitals influence the prescription behavior of doctors treating patients after discharge. The mediplus patient database combines all decision relevant information on physicians, patients, diagnoses and course of therapies and thus makes possible the investigation of the courses of diseases and therapy patterns. The monthly update enables trends to be identified at an early stage. The mediplus database is an ideal instrument for the enforcement of quantitative and qualitative analyses of patient histories because it directly links the individual diagnoses with the corresponding therapies. The database is currently undergoing extension with additional specialist groups such as pediatricians, neurologists, orthopedists, urologists, ENT specialists, surgeons and pulmonologists.

A New Direction in AI: Toward a Computational Theory of Perceptions

Fast-forward (FF) was the most successful automatic planner in the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS '00) planning systems competition. Like the well-known hsp system, FF relies on forward search in the state space, guided by a heuristic that estimates goal distances by ignoring delete lists. It differs from HSP in a number of important details. This article describes the algorithmic techniques used in FF in comparison to hsp and evaluates their benefits in terms of run-time and solution-length behavior. Humans have a remarkable capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Familiar examples are parking a car, driving in city traffic, playing golf, cooking a meal, and summarizing a story. In performing such tasks, humans use perceptions of time, direction, speed, shape, possibility, likelihood, truth, and other attributes of physical and mental objects. Reflecting the bounded ability of the human brain to resolve detail, perceptions are intrinsically imprecise. In more concrete terms, perceptions are f-granular, meaning that (1) the boundaries of perceived classes are unsharp and (2) the values of attributes are granulated, with a granule being a clump of values (points, objects) drawn together by indistinguishability, similarity, proximity, and function. For example, the granules of age might be labeled very young, young, middle aged, old, very old, and so on. F-granularity of perceptions puts them well beyond the reach of traditional methods of analysis based on predicate logic or probability theory. The computational theory of perceptions (CTP), which is outlined in this article, adds to the armamentarium of AI a capability to compute and reason with perception-based information. The point of departure in CTP is the assumption that perceptions are described by propositions drawn from a natural language; for example, it is unlikely that there will be a significant increase in the price of oil in the near future. In CTP, a proposition, p, is viewed as an answer to a question, and the meaning of p is represented as a generalized constraint. To compute with perceptions, their descriptors are translated into what is called the generalized constraint language (GCL). Then, goal-directed constraint propagation is utilized to answer a given query. A concept that plays a key role in CTP is that of precisiated natural language (PNL). The computational theory of perceptions suggests a new direction in AI -- a direction that might enhance the ability of AI to deal with realworld problems in which decision-relevant information is a mixture of measurements and perceptions. What is not widely recognized is that many important problems in AI fall into this category.

Use of multi-attribute decision analysis for designing operations system framework in telecommunications management network

This paper is concerned with the design of an Operations System (OS) framework for implementing a proper telecommunications network in Korea Telecom. Since several types of OS frameworks are under consideration, the telecommunication network manager should now choose the best alternative for use later in establishing the infrastructure of operations systems. The decision making is done in this paper by means of a Multi-Attribute Decision-Making (MADM) analysis. A point to be noted in the present case is that the decision relevant information such as attribute weights and values of alternatives are not known exactly. Rather, these are to be taken in the form of rankings and/or bounds. To deal with such incomplete information, we employ a mathematical programming model-based MADM approach to the choice of an optimal OS framework design. This approach enables us to check dominance of alternatives and to obtain a set of non-dominated alternatives from evaluating five alternatives in reference to Telecommunications Management Network (TMN) standards. Scope and purpose Telecommunications Management Network (TMN) can be stated as a globalized and unified skeleton to meet the advanced operational environments of telecommunications networks and to handle heterogeneous and complex network elements. Although there are various subjects that should be addressed to accomplish TMN, we confine our attention to dealing with one important subject, design of an Operations System (OS) framework. This is necessary to manage telecommunications resources including networks in effective manner and for use as guidance in developing individual operations systems and in constructing a network management center. Several types of OS frameworks have been suggested by TMN standards. It is hence needed to evaluate each of these OS frameworks and then to choose an appropriate one in Korean TMN situation. Since this evaluation involves multiple criteria (or attributes), it is realized in this paper by a Multi-Attribute Decision-Making (MADM) analysis approach. The decision relevant information such as trade-off weights and individual criterion values are elicited from expert opinions which, however, is rather incomplete than exact numerical values. The decision making process with the incompletely identified information is presented in this paper.