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The long‐term survival of a business is dependent upon meeting market needs through a long‐term value creation process. Traditional performance measurement systems have been criticized as being too narrowly focused on financial figures and functional level performance such that they often fail to capture organizational long‐term business success. In contrast, the balanced scorecard calls on managers to first make a commitment to introduce an array of measures or scorecards that will guide their decisions away from the narrowly focused financial measures. These scorecards, in turn, serve as dials on a dashboard and guide businesses into greater profitability as managers position themselves to better serve their employees, customers, and shareholders at large. Using information collected from 83 electronics companies located within the USA, results from the study provide support for the balanced scorecard. Specifically, findings show that manufacturing plants that have strategically linked their corporate goals or objectives to their performance measurement systems, via the scorecard, performed better than those that do not.

Analyses the effects of age on the level of job satisfaction of accountants in Singapore. Four categories of accountants namely, government auditors, internal auditors, non‐auditor accountants, and external auditors were identified according to the nature of work performed by each, i.e. job‐type. Results of a three‐way analysis of variance (ANOVA) show that both age and job type, taken individually, have a direct significant effect on job satisfaction. In addition, there is also an interaction effect between age and job‐type on job satisfaction. In general, older accountants are more satisfied with their jobs than their younger counterparts. However their satisfaction increases at varying rates depending on their job types.

Illustrates the use of the Bayesian decision‐tree approach in making auditing decisions. First reviews the audit process and shows that the outcomes of auditing decisions depend not only on the courses of action but also on some uncontrollable chance events. Explains the Bayesian decision‐tree approach and the concepts of prior and posterior probabilities and expected values. Also illustrates the framework within which the approach is applicable. Shows how the Bayesian decision‐tree approach can be applied in auditing situations (e.g. substantive testing and the review of other auditor′s work). Finally, suggests some probability results that can be used in other auditing contexts. Offers additional insights into the use of Bayesian methods in auditing and presents auditors with a tool which they can use in making auditing decisions.

This study seeks to evaluate the stability of financial ratios across industry and over time. The sample comprises companies listed on the Stock Exchange of Singapore from 1980 to 1991 over six industry groupings. A set of 29 most commonly used ratios was selected for the study. Descriptive statistics, factor analysis and analysis of variance were performed. From the factor analysis results, eight representative ratios were identified. Analysis of variance and multiple comparisons were subsequently performed for each representative ratio to test if it is significantly different across industry and over time. The results indicate that financial ratio averages of the various industries are significantly different. This implies that the appropriate benchmark for evaluating company performance and position should be industry‐specific instead of economy based. Also, five of the representative ratios are significantly different over time and not all the industrial averages move consistently over time (i.e., interaction effects of industry and time exist). Thus, industry averages are not necessarily appropriate benchmarks for setting and evaluating performance through time.

This study surveys the level of job satisfaction among government auditors in Singapore and investigates the factors affecting their job satisfaction. A questionnaire is administered in mid July 1990 to all the 150 government auditors in the Auditor‐General's Office in Singapore, resulting in a usable response rate of 76%. Descriptive statistics, t‐tests, wilcoxon Z tests, and Chi‐square tests of independence are used to analyse the data. Results of the survey show that government auditors in Singapore are very satisfied with their supervisors and co‐workers but very dissatisfied with the opportunities for promotion. Overall, however, they are satisfied with their jobs. Further, it is found that demographic factors such as sex, number of years in the present position, previous job, and income affect job satisfaction. Finally, the results show that the following factors are important determinants of Job satisfaction among government auditors in Singapore: (1) control over work, (2) frequency of sudden demands, (3) perceived necessity of overtime, (4) effect of sudden demands, (5) administrative supports, (6) interaction with supervisor, (7) physical work environment, (8) preparation for future career goals, and (9) extra‐organizational job opportunities.

This survey studies the factors influencing the turnover intention of accountants in Singapore with a view to develop a turnover prediction model. Twenty variables were studied. Results show that 18 of these variables are significantly different between accountants who intend to turnover and those who do not. Through the use of stepwise logit analysis, a turnover prediction model with only six variables was developed. In‐sample and holdout overall accuracy rates of the turnover model are 88.2% and 87.4%, respectively.

This article discusses the limitations of existing going‐concern discriminant models and explores the use of weighted probit analysis to construct a classification model for the auditor to use in making going/non‐going concern decisions. The model is constructed using probit analysis with the weighted exogenous sample maximum likelihood (WESML) procedure on a matched sample of 80 going and non‐going concerns. Using the Lachenbruch′s U method of computing holdout accuracy rates, the probit model classifies going/non‐going concerns with an accurate rate of 82.50 per cent for non‐going concerns, 100.00 per cent for going concerns, and 91.50 per cent overall. These accuracy rates are higher than those of the sample auditors, which are 40.00, 97.50, and 68.75 per cent, respectively. The model is expected to be useful as a going‐concern prediction model, a persuasive analytical tool, and a defensive device.

Going concern is a fundamental concept in accounting and auditing and the assessment of a firm's going concern status is not an easy task. Several going concern prediction models based on statistical methods to assist auditors have been suggested in the literature. This study explores and compares the usefulness of neural networks, decision trees and logistic regression in predicting a firm's going concern status. The sample data comprise financial ratios for 165 going concerns and 165 matched non‐going concerns. The classification results indicate the potential usefulness of data mining techniques in a going concern prediction context. Further, the decision tree going concern prediction model outperforms the logistic regression and neural network models. Data mining techniques such as neural networks and decision trees are powerful for analysing complex non‐linear and interaction relationships, and hence can supplement and complement traditional statistical methods in constructing going concern prediction models.

To study the audit expectation gap, a survey questionnaire listing 13 possible company audit objectives was administered to 500 auditors and 500 non‐auditors in Singapore. The overall response rate is 48.7% (i.e., 487). ANOVA and multiple comparison (SNK) results show that auditors perceive significantly more strongly than non‐auditors that giving a true and fair opinion and providing aid and advice on accounting matters are important and appropriate company audit objectives. On the other hand, non‐auditors perceive significantly more strongly than auditors that detecting and preventing major errors, fraud or illegal acts; satisfaction of the requirements of authorities; and ensuring the accuracy of financial accounts are important and appropriate company audit objectives. Overall, it can be concluded that an audit expectation gap with respect to company audit objectives exists between auditors and non‐auditors and that the latter place a significantly greater demand on audits and auditors than what auditors themselves perceive their roles and responsibilities to be.