Total Quality Management and the Choice of Information and Reward Systems

This paper examines the association between the use of advanced manufacturing practices and the choice of information and reward systems, and explores the impact of these choices on organizational performance. Although advanced manufacturing practices such as total quality management (TQMI) have been widely adopted over the past decade, surveys indicate that most of these initiatives have not yielded significant economic benefits (e.g., Mathews and Katel [1992] and The Economist [1992]). Many accounting researchers charge that the poor performance of many new manufacturing initiatives is due in part to continued reliance on traditional management accounting systems that do not provide appropriate problem-solving data, performance measures, and reward systems.1 We conduct an exploratory analysis of these claims using a

[1]  S. F. Buck A Method of Estimation of Missing Values in Multivariate Data Suitable for Use with an Electronic Computer , 1960 .

[2]  Hans-Werner Kaas,et al.  Does Quality Pay , 1994 .

[3]  E. Beale,et al.  Missing Values in Multivariate Analysis , 1975 .

[4]  David I. Levine,et al.  Product quality and pay equity between lower-level employees and top management: An investigation of distributive justice theory. , 1992 .

[5]  A. Meyer,et al.  Lasting Improvements in Manufacturing Performance: In Search of a New Theory , 1990 .

[6]  David A. Garvin,et al.  Quality Problems, Policies, and Attitudes in the United States and Japan: An Exploratory Study , 1986 .

[7]  C. Fornell,et al.  Canonical Correlation Analysis As A Special Case Of A Structural Relations Model. , 1981, Multivariate behavioral research.

[8]  M. Aoki Horizontal vs. Vertical Information Structure of the Firm , 2013 .

[9]  Robert S. Kaplan,et al.  Measures for Manufacturing Excellence , 1990 .

[10]  Kasra Ferdows,et al.  Influence of Manufacturing Improvement Programmes on Performance , 1990 .

[11]  J. M. Groocock,et al.  The cost of quality , 1974 .

[12]  M. C. Jensen,et al.  Science, Specific Knowledge and Total Quality Management , 1994 .

[13]  Thomas H. Johnson,et al.  Relevance Lost: The Rise and Fall of Management Accounting , 1987 .

[14]  A. V. D. Ven,et al.  Alternative forms of fit in contingency theory. , 1985 .

[15]  Jayant V. Saraph,et al.  An Instrument for Measuring the Critical Factors of Quality Management , 1989 .

[16]  Roderick J. A. Little Regression with Missing X's: A Review , 1992 .

[17]  M. Bartlett THE STATISTICAL SIGNIFICANCE OF CANONICAL CORRELATIONS , 1941 .

[18]  C. Drury,et al.  New manufacturing technologies and management accounting systems: Some evidence of the perceptions of UK management accounting practitioners , 1994 .

[19]  Shirley J. Daniel,et al.  Linking quality strategy with management control systems: Empirical evidence from Japanese industry , 1991 .

[20]  Roger G. Schroeder,et al.  Determinants of Quality Performance in High- and Low-Quality Plants , 1995 .

[21]  R. Kaplan Measuring manufacturing performance: a new challenge for managerial accounting research , 1983 .

[22]  David F. Larcker,et al.  THE USE OF CANONICAL CORRELATION ANALYSIS IN ACCOUNTING RESEARCH , 1980 .

[23]  H. Hotelling The most predictable criterion. , 1935 .

[24]  Roger W. Berger,et al.  Guide to Quality Control , 1982 .

[25]  A. V. D. Ven,et al.  The Concept of Fit in Contingency Theory. , 1984 .

[26]  Rajiv D. Banker,et al.  Reporting manufacturing performance measures to workers: An empirical study , 1993 .

[27]  Joseph Moses Juran Juran on Leadership For Quality , 1989 .

[28]  David J. Krus,et al.  Interpretation of canonical analysis: Rotated vs. unrotated solutions , 1976 .

[29]  S. Snell,et al.  Strategic Compensation for Integrated Manufacturing: The Moderating Effects of Jobs and Organizational Inertia , 1994 .

[30]  L. L. Cummings,et al.  FEEDBACK AS AN INDIVIDUAL RESOURCE: PERSONAL STRATEGIES OF CREATING INFORMATION , 1983 .

[31]  Eli P. Cox,et al.  The Optimal Number of Response Alternatives for a Scale: A Review , 1980 .

[32]  Thomas H. Davenport,et al.  Process Innovation: Reengineering Work Through Information Technology , 1992 .

[33]  W. Edwards Deming,et al.  Out of the Crisis , 1982 .

[34]  R. M. Durand,et al.  Approximating Confidence Intervals for Factor Loadings. , 1991, Multivariate behavioral research.

[35]  Philip B. Crosby,et al.  Quality Is Free: The Art of Making Quality Certain , 1979 .

[36]  R. Cudeck,et al.  Applications of standard error estimates in unrestricted factor analysis: significance tests for factor loadings and correlations. , 1994, Psychological bulletin.

[37]  C. Fornell,et al.  Customer Satisfaction, Market Share, and Profitability: Findings from Sweden , 1994 .