AN APPROXIMATION TO THE HYPERCUBE MODEL WITH PATROL-INITIATED ACTIVITIES: AN APPLICATION TO POLICE

This paper applies the patrol-initiated-activity hypercube queuing model to historical data from a police agency. The model allows servers to handle both calls assigned by a central dispatcher and activities initiated by the servers. By duplicating a fairly complex dispatch strategy, the model was found to predict both assigned and server-initiated work loads accurately for the overall system and individual servers. The model is apparently ineffective in predicting small unit-travel-time differences for this police agency.     

STOCHASTIC COST-VOLUME-PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

In this paper we incorporate a linear demand function to model the price-volume causal relationship into stochastic cost-volume-profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

FORECAST EVALUATION OF LIVINGSTON DATA ON INFLATION RATES AND INFLATION UNCERTAINTY*

Livingston data on expected inflation rates have been used extensively in the financial literature, especially in investgating the relationship between nominal interest rates and expected inflation rates; however, the data have not been subjected to a thorough analysis of forecast accuracy. The objective of this paper is to analyze the forecast properties of Livingston data using a wide variety of time and frequency domain methods over an extended sample period and for selected subperiods.     

EMPIRICAL AND JUDGMENT-BASED SALES-FORCE DECISION MODELS: A COMPARATIVE ANALYSIS*

Multiple-predictor empirical and single-predictor judgment-based models represent the two basic types of sales-force decision models (SDMs). The important similarities and differences between the two modeling approaches are identified and discussed. The SDM literature is reviewed to determine how each model type has been applied and to evaluate previous attempts at model validation. A research study designed to compare the normative sales-call allocations generated from each modeling approach is presented. Study results indicate that empirical and judgment-based SDMs would produce similar normative guidelines. The implications of this finding are discussed.     

CATEGORY WIDTH COGNITIVE STYLE AS A FACTOR IN ACCOUNTANTS' PERCEPTIONS OF ACCOUNTING INFORMATION

This paper reports the findings of a laboratory experiment designed to investigate the relationship of category width (CW) cognitive style with accountants' perceptions of accounting information. Subjects drawn from large accounting firms in Sydney, Brisbane, and Melbourne, Australia, were classified into broad, medium, and narrow categories following the test devised by Pettigrew [19]. Subjects were requested to state their level of confidence in decisions they had made after receiving (1) conventional accounting information or (2) conventional accounting information and human resources accounting (HRA) information using a one-group pretest-posttest design. The results indicated a significant relationship between CW cognitive style and the accountants' confidence in their decisions. Furthermore, CW cognitive style moderated the accounting-information/decision-making relationship.     

全球自觉资本主义:从自觉的角度透视经济管理和经济责任

今天,日益增长的全球资本主义经济是一张复杂的动态的网络,这个网络由社会、文化以及反映我们个人和大众的意识的经济体制构成。随着意识创造并联结了所有事物这一观点被人们日渐认可,以及全球责任感的增强,资本主义经济体制可以切实地被改变,从而促进经济的长期繁荣。     

Meeting at the Thin Places: Synchronicities in Clinical Practice

Unusual events, beyond mere coincidences, may occur during the course of psychotherapy. Yet, clinical training often does not prepare therapists how to understand and potentially engage with these encounters. The aim of this report is to explore the emergence of synchronistic events in therapy, while providing two clinical case composites to illustrate the author’s central points. Drawing on the Celtic concept of “thin places,” a new understanding of synchronicities and the therapeutic relationship is offered.