Superior Decision Research Articles

Contextual Alignment of Ontologies in the eCoin Semantic Interoperability Framework

The prospect of combining information from diverse sources for superior decision making is plagued by the challenge of semantic heterogeneity, as data sources often adopt different conventions and interpretations when there is no coordination. An emerging solution in information integration is to develop an ontology as a standard data model for a domain of interest, and then to define the correspondences between the data sources and this common model to eliminate their semantic heterogeneity and produce a single integrated view of the data sources. We first claim that this single integrated view approach is unnecessarily restrictive, and instead offer the view that ontologies can simultaneously accommodate multiple integrated views provided the accompaniment of contexts, a set of axioms on the interpretation of data allowing local variations in representation and nuances in meaning, and a conversion function network between contexts to reconcile contextual differences. Then, we illustrate how to achieve semantic interoperability between multiple ontology-based applications. During this process, application ontologies are aligned through the reconciliation of their context models, and a new application with a virtual merged ontology is created. We illustrate this alternative approach with the alignment of air travel and car rental domains, an actual example from our prototype implementation.

On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization.

Biased category payoff matrices engender separate reward- and accuracy-maximizing decision criteria Although instructed to maximize reward, observers use suboptimal decision criteria that place greater emphasis on accuracy than is optimal. In this study, objective classifier feedback (the objectively correct response) was compared with optimal classifier feedback (the optimal classifier's response) at two levels of category discriminability when zero or negative costs accompanied incorrect responses for two payoff matrix multiplication factors. Performance was superior for optimal classifier feedback relative to objective classifier feedback for both zero- and negative-cost conditions, especially when category discriminability was low, but the magnitude of the optimal classifier advantage was approximately equal for zero- and negative-cost conditions. The optimal classifier feedback performance advantage did not interact with the payoff matrix multiplication factor. Model-based analyses suggested that the weight placed on accuracy was reduced for optimal classifier feedback relative to objective classifier feedback and for high category discriminability relative to low category discriminability. In addition, the weight placed on accuracy declined with training when feedback was based on the optimal classifier and remained relatively stable when feedback was based on the objective classifier. These results suggest that feedback based on the optimal classifier leads to superior decision criterion learning across a wide range of experimental conditions.

Optimal Marketing Decisions for Feeder Cattle under Price and Production Risk

AbstractIn many parts of the U.S., beef cattle production is a large sector of the agricultural economy, yet few of the cattle are stockered; instead the production is focused on cow-calf operations only. Restricting their Operation to only the first phase of beef production may be limiting the cattle owners’ profit potential. This paper examines the opportunities for Operators to earn additional profit from stockering cattle. Using a representative risk-averse producer, a decision set with seven possible marketing strategies is evaluated for the optimal decision in a Bayesian framework which allows for price and production risk. We find that in many instances retaining the cattle for stockering is a superior decision when done in conjunction with specific hedging strategies utilizing options and futures contracts.

Real Estate Value Chain Connections: Tangible and Transparent

Real estate plays a fundamental connecting role in the value chain. This research addresses the application of the value chain concept to how real estate facilitates the connection of inputs to the value creation process to deliver goods and services to consumers. This research provides the critical linkages in the vocabulary of strategic management. Once identified, the critical real estate value chain connections can lead to insights resulting in superior decision making. In settings emphasizing transparency, the place and space of origin and destination become more important. While a predominant amount of commerce is conducted in tangible contexts, the hypercompetitive conditions of such commerce and the proliferating substitutes for the environments in which such commerce may occur places ever more priority on the role of real estate value chain connections.

User Perceptions of Decision Support Effectiveness: Two Production Planning Experiments*

ABSTRACTDecision support systems continue to be very popular in business, despite mixed research evidence as to their effectiveness. We hypothesize that what‐if analysis, a prominent feature of most decision support systems, creates an “illusion of control” causing users to overestimate its effectiveness. Two experiments involving a production planning task are reported which examine decision makers' perceptions of the effectiveness of what‐if analysis relative to the alternatives of unaided decision making, and quantitative decision rules. Experiment 1 found that almost all subjects believed what‐if analysis was superior to unaided decision making, although using what‐if analysis had no significant effect on performance. Experiment 2 found that decision makers were indifferent between what‐if analysis and a quantitative decision rule which, if used, would have led to significant cost savings. Thus, what‐if analysis did create an illusion of control: decision makers perceived performance differences where none existed, and did not detect large differences when they were present. In both experiments, decision makers exhibited difficulty realizing that their positive beliefs about what‐if analysis were exaggerated. Such misjudgments could lead people to continue using what‐if analysis even when it is not beneficial and to avoid potentially superior decision support technologies.

Pareto optimality for rational comprehensive decision making

Abstract The majority of industrial problems, like real life personal problems, involve the achievement of more than one objective, though there could be different levels of preference for these objectives. Few solution techniques would solve such problems and still retain the original images of the problems. PARETO OPTIMALITY is recommended as a tool for achieving meaningful, factual, systematic solutions to such problems, by retaining their identities, and providing a rational and comprehensive approach towards the generation of superior solution alternatives and decision maker preferred solutions.

Information salience and the discovery of hidden profiles by decision-making groups: A “thought experiment”

Simulations using the DISCUSS model of group decision making assessed the impact of having highly salient unshared information on groups' discovery of hidden profiles. A hidden profile exists when group members individually receive only part of the information favoring a superior decision alternative, but the group collectively can pool this unshared information to identify the superior option. Stasser and Titus (1985, Journal of Personality and Social Psychology, 48, 1476–1478) found that their groups often failed to pool unshared information and did not discover the option supported by their collective knowledge. The simulation results demonstrated that this failure will likely occur across various group sizes and information loads. Moreover, advocacy during discussion interferes with the discovery of a hidden profile. Enhancing the salience of unshared information had relatively little impact except for smaller (four-person) groups whose members adopted an impartial, fact-finding approach (nonadvocacy) to discussion. Also, making unshared information salient when members received the information before discussion was more critical than making it salient when items were selected for discussion.

Developmental perspectives on the localization and detection of auditory signals

Responsiveness of 1-, 3-, and 5-year-old children and adults to octave-band noises at .4 and 10 kHz was assessed with a go/no-go version of visual reinforcement audiometry (VRA) (Moore, Thompson, & Thompson, 1975) and a two-alternative, forced-choice version (Suzuki & Ogiba, 1961; Trehub, Schneider, & Endman, 1980). Infants performed better on the two-alternative, forced-choice version in quiet and in noisy backgrounds, and adults performed better on the two-alternative, forced-choice version in quiet but not in noisy backgrounds. Performance on the two tasks was essentially equivalent for 3- and 5-year-old children. Superior performance on two-alternative VRA over go/no-go may be due to lesser cognitive demands in the case of infants and to the engagement of superior decision strategies in the case of adults.

Cost minimization and uncertain technologies: Absence of deviation costs

Consider a price taking firm which faces a random production technology. The major question arising is how to determine the optimal input quantities. In all contributions toward this problem it is assumed that the entrepreneur maximizes the expected utility of profits. Then the solution technique operates via substitution of the stochastic production function into the profit function and is well known (see for example Feldstein, 1971; Batra, 1975; Pope and Kramer, 1979). However, in the case of cost minimization problems, this procedure does not work if the firm has to pay only for its input requirements. This means that no costs arise for a deviation of the realized production volume from the desired one. In the present paper we analyze two solution procedures for such problems and discuss their implications for the optimal decisions. In Section 2 the general problem is stated. In Section 3 we introduce the concept of the true optimal production policy and derive its unbiased estimator as an operational and, in some aspects, superior decision rule. Then we show that the replacement

“Either a medal or a corporal”: The effects of success and failure on the evaluation of decision making and decision makers

This paper is concerned with judgment by outcomes—justifying decisions and rewarding decision makers in case of success, and condemning both in case of failure. Officers in the Israel Defense Forces evaluated four versions of the same case of decision making in a military setting. In two versions the decision maker obeys his orders, in two he disobeys them to take a normatively appropriate action; one of each decision is successful, one of each fails. Though the cases are identical except for the above differences, successful decisions are considered more justified and to follow from superior decision making processes; decision making processes are perceived as more satisfactory when they lead to success, and successful decision makers are perceived more favorably than their unsuccessful counterparts. Role expectations regarding appropriate action influenced the justification of decisions and perceived favorability of decision makers and interacted with outcome valence in determining the allocation of reward and punishment and the evaluation of the decision making process. The paper discusses implications of the findings to Behavioral Decision Theory, Attribution Theory, and Organizational Learning.

Intelligent alarm handling

Abstract The paper outlines the functional structure of an intelligent alarm system. The alarm system should be regarded as a “joint cognitive system” where the operator's need for information at different abstraction levels is taken into account. The alarm system is divided into a low level alarm handling module, a human operator interface and a superior decision support level. The superior level is further decomposed into modules for: event analysis, diagnosis, goal selection, planning and execution. The module for event analysis is subjected to further analysis. We propose that this module should combine information on incoming alarms with other information on the process state available from the process control system. We describe how this may be achieved by using a newly developed method based on the parsing of the incoming event sequence. The parsing process is based on a DCG grammar the describing causal relations in the plant. Parameter passing and calls to Prolog clauses are applied to propagate additional constraints and build a parse tree. The parse tree is used to give a hierar chic description of the actual process state. The levels in the tree correspond to different abstraction levels in the description of the process state.

Intelligent Alarm Handling

The paper outlines the functional structure of an intelligent alarm system. The alarm system should be regarded as a "joint cognitive system" where the operator's need for information at different abstraction levels is taken into account. The alarm system is divided into a low level alarm handling module, a human operator interface and a superior decision support level. The superior level is further decomposed into modules for: event analysis, diagnosis, goal selection, planning and execution. The module for event analysis is subjected to further analysis. We propose that this module should combine information on incoming alarms with other information on the process state available from the process control system. We describe how this may be achieved by using a newly developed method based on the parsing of the incoming event sequence. The parsing process is based on a DCG grammar the describing causal relations in the plant. Parameter passing and calls to Prolog clauses are applied to propagate additional constraints and build a parse tree. The parse tree is used to give a hierar chic description of the actual process state . The levels in the tree correspond to different abstraction levels in the description of the process state.

CAPITAL ADEQUACY AND THE VALUATION OF LARGE COMMERCIAL BANKING ORGANIZATIONS

AbstractBankers argue that regulatory agencies require excessive capital adequacy. As a consequence, banks cannot achieve optimal capital structure. This study investigates the capital adequacy issue for bank holding companies over the 1974—1983 period, one of the most turbulent periods in recent banking history. During this time, capital is never excessive from the stockholders' viewpoint, and financial markets, on average, perceive capital levels as inadequate. Assuming the public wants no lower capital levels than shareholders, recent regulatory action to require higher capital ratios is a Pareto superior decision.