Mark I. Hwang

The effect of user engagement on system success: a meta-analytical integration of research findings

The effect of user involvement on system success is an important topic yet empirical results have been controversial. Many methodological and theoretical differences among prior studies have been suggested as possible causes for inconsistent findings. This research is an attempt to resolve inconsistent data despite differences that may exist in prior studies. Data from 25 studies were meta-analyzed to test the separate effects of user participation and user involvement on six system success variables. Results showed that user participation had a moderate positive correlation with four success measures: system quality, use, user satisfaction, and organizational impact. The correlation between user participation and individual impact was minimum. User involvement generally had a larger correlation with system success than did user participation. Overall, these findings indicate that both user involvement and user participation are beneficial, but the magnitude of these benefits much depends on how involvement and its effect are defined.

AUDIT QUALITY, CORPORATE GOVERNANCE, AND EARNINGS MANAGEMENT: A META-ANALYSIS

Earnings management is of great concern to corporate stakeholders. While numerous studies have investigated the effects of various corporate governance and audit quality variables on earnings management, empirical evidence is rather inconsistent. This meta-analysis identifies 12 significant relationships by integrating results from 48 prior studies. For corporate governance, the independence of the board of directors and its expertise have a negative relationship with earnings management. Similar negative relationships exist between earnings management and the audit committees independence, its size, expertise, and the number of meetings. The audit committees share ownership has a positive effect on earnings management. For audit quality, auditor tenure, auditor size, and specialization have a negative relationship with earnings management. Auditor independence, as measured by fee ratio and total fee, is also a deterrent to earnings management.

Information dimension, information overload and decision quality

The impact of information load (both under and overload) on decision quality is an important topic, yet results of empirical research are inconsistent. These mixed results may be due to the fact that information load itself is a function of information dimension. A meta-analysis of 31 experiments reported in 18 empirical bankruptcy prediction studies was conducted to test the effect of two information dimensions: information diversity and information repetitiveness. Results indicated that both information dimensions have an adverse impact on decision quality: provision of either diverse or repeated information can be detrimental to prediction accuracy. The findings have implications for information suppliers and researchers who are interested in improving the quality of human decision making.

Factors influencing the continuance intention to the usage of Web 2.0: An empirical study

New business models and applications have been continuously developed and popularized on the Internet. In recent years, a number of applications including blogs, Facebook, iGoogle, Plurk, Twitter, and YouTube known as Web 2.0 have become very popular. These aforementioned applications all have a strong social flavor. However, what social factors exert an influence onto their use is still unclear and remains as a research issue to be further investigated. This research studies four social factors and they are subjective norm, image, critical mass, and electronic word-of-mouth. A causal model of the satisfaction and continuance intention of Web 2.0 users as a function of these four social factors is proposed. Results indicate that user satisfaction with Web 2.0 applications significantly affects electronic word-of-mouth, which in turn significantly influences their continuance intention. In addition, subjective norm, image and critical mass all have a significant impact onto satisfaction, which in turn has an indirect significant influence on electronic word-of-mouth. Finally, all social factors have a significant direct impact on continuance intention. Finally, implications for service providers and researchers are discussed.

A fuzzy neural network for assessing the risk of fraudulent financial reporting

While financial reporting fraud has become more prevalent and costly in recent years, fraud detection has been badly lagging. Several recent studies have examined the feasibility of various computer techniques in business and industrial applications. The purpose of this study is to evaluate the utility of an integrated fuzzy neural network (FNN) for fraud detection. The FNN developed in this research outperformed most statistical models and artificial neural networks (ANN) reported in prior studies. Its performance also compared favorably with a baseline Logit model, especially in the prediction of fraud cases.

The Effect of Implementation Factors on Data Warehousing Success: An Exploratory Study

Data warehousing is an important area of practice and research, yet few studies have assessed its practices in general and critical success factors in particular. Although plenty of guidelines for implementation exist, few have been subjected to empirical testing. In order to better understand implementation factors and their effect on data warehousing success, perceptions of data warehousing professionals are examined in a cross sectional survey. Best subsets regression is used to identify the specific factors that are important to each success variable. Since different companies may have different objectives or emphases in their data warehousing endeavors, the results are useful in identifying the exact factors that need attention and in providing a basis for prioritizing those factors. The results also suggest several promising directions for continued research on data warehousing success.

Building a Knowledge Base for MIS Research: A Meta-Analysis of a Systems Success Model

This study was conducted to create a knowledge base for MIS research. Building on two previous theoretical models, a systems success model relating six independent variables external environment, organizational environment, user environment, IS operations environment, IS development environment, and information systems to four success variables use, satisfaction, individual impact, and organizational impact was developed. This model was tested using data from 82 empirical studies in a meta-analysis. Results showed that all but one independent variable, external environment, had a significant relationship with success variables. In addition, each independent variable had varying strengths of relationships with different success variables. The findings yield important guidelines for the selection of variables in future research. The validated systems success model is general and theory based, and is useful in providing directions for future research.

Personality traits and simultaneous reciprocal influences between job performance and job satisfaction

Purpose – This paper aims to test the relationships among three important variables in the management of Chinese employees: personality trait, job performance and job satisfaction. A causal model is developed to hypothesize how personality trait affects job performance and satisfaction and how job performance and satisfaction simultaneously affect each other. Design/methodology/approach – The survey was conducted from October to November 2009. In total, 414 questionnaires were distributed and 392 were returned. Using data collected, the theoretical model is empirically validated. Structural equation modelling using LISREL 8.8 is used to test the causal model. Findings – Job performance and job satisfaction have a bilateral relationship that is simultaneously influential. All Big Five personality traits significantly influence job performance, with agreeableness showing the greatest effect, followed by extraversion. Extraversion is the only personality trait that shows a significant influence over job sati...

Assessing moderating effect in meta-analysis: a re-analysis of top management support studies and suggestions for researchers

Meta-analysis has been increasingly used as a knowledge cumulation tool by IS researchers. In recent years many meta-analysts have conducted moderator analyses in an attempt to develop and test theories. These studies suffer from several methodological problems and, as a result, may have contributed to rather than resolved inconsistent research findings. For example, a previous meta-analysis reports that task interdependence moderates the effect of top management support to render it a non-critical component in systems implementation projects when task interdependence is low. We show that this conclusion is the result of uncorrected measurement error and an erroneous application of a fixed effects regression analysis. We discuss other pitfalls in the detection and confirmation of moderators including the use of the Q statistic and significance tests. Our recommended approach is to break the sample into subgroups and compare their credibility and confidence intervals. This approach is illustrated in a re-analysis of the top management support literature. Our results indicate that top management support is important in both high and low task interdependence groups and in fact may be equally important in both groups. Guidelines are developed to help IS researchers properly conduct moderator analyses in future meta-analytic studies.