Advances in management accounting vol 15

ADVANCES IN MANAGEMENT ACCOUNTING i ADVANCES IN MANAGEMENT ACCOUNTING Series Editors: Marc J Epstein and John Y Lee Volumes 1to14: Advances in Management Accounting ii ADVANCES IN MANAGEMENT ACCOUNTING VOLUME 15 ADVANCES IN MANAGEMENT ACCOUNTING EDITED BY MARC J EPSTEIN Harvard University and Rice University, USA JOHN Y LEE Pace University, USA Amsterdam – Boston – Heidelberg – London – New York – Oxford Paris – San Diego – San Francisco – Singapore – Sydney – Tokyo JAI Press is an imprint of Elsevier iii JAI Press is an imprint of Elsevier The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA First edition 2006 Copyright r 2006 Elsevier Ltd All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: permissions@elsevier.com Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN-13: 978-0-7623-1352-5 ISBN-10: 0-7623-1352-8 ISSN: 1474-7871 (Series) For information on all JAI Press publications visit our website at books.elsevier.com Printed and bound in The Netherlands 06 07 08 09 10 10 iv CONTENTS LIST OF CONTRIBUTORS ix EDITORIAL BOARD xi STATEMENT OF PURPOSE AND REVIEW PROCEDURES EDITORIAL POLICY AND MANUSCRIPT FORM GUIDELINES INTRODUCTION Marc J Epstein and John Y Lee xiii xv xvii AN EXPERIMENTAL INVESTIGATION OF STRATEGIC BUDGETING: A TECHNIQUE FOR INTEGRATING INFORMATION SYMMETRY Tamara Kowalczyk, Savya Rafai and Audrey Taylor LOW-INTENSITY R&D AND CAPITAL BUDGETING DECISIONS IN IT FIRMS Hanna Silvola 21 BUDGETING, PERFORMANCE EVALUATION, AND COMPENSATION: A PERFORMANCE MANAGEMENT MODEL Al Bento and Lourdes Ferreira White 51 v vi CONTENTS ANALYZING THE INVESTMENT DECISION IN MODULAR MANUFACTURING SYSTEMS WITHIN A CRITICAL-THINKING FRAMEWORK Mohamed E Bayou and Thomas Jeffries 81 CEO COMPENSATION AND FIRM PERFORMANCE: NON-LINEARITY AND ASYMMETRY Mahmoud M Nourayi 103 EMPIRICAL ANALYSIS OF THE RELIABILITY AND VALIDITY OF BALANCED SCORECARD MEASURES AND DIMENSIONS Emilio Boulianne 127 HAS THE EMERGENCE OF THE SPECIALIZED JOURNALS AFFECTED MANAGEMENT ACCOUNTING RESEARCH PARADIGMS? Nen-Chen Richard Hwang and Donghui Wu 143 DECISION OUTCOMES UNDER ACTIVITY-BASED COSTING: PRESENTATION AND DECISION COMMITMENT INTERACTIONS David Shelby Harrison and Larry N Killough 169 USING KNOWLEDGE MANAGEMENT SYSTEMS TO MANAGE KNOWLEDGE RESOURCE RISKS Nabil Elias and Andrew Wright 195 IFAC’S CONCEPTION OF THE EVOLUTION OF MANAGEMENT ACCOUNTING: A RESEARCH NOTE Magdy Abdel-Kader and Robert Luther 229 Contents A NOTE ON THE IMPORTANCE OF PRODUCT COSTS IN DECISION-MAKING John A Brierley, Christopher J Cowton and Colin Drury vii 249 DECISION CONTROL OF PRODUCTS DEVELOPED USING TARGET COSTING Robert Kee and Michele Matherly 267 TRUST AND COMMITMENT: INTANGIBLE DRIVERS OF INTERORGANIZATIONAL PERFORMANCE Jane Cote and Claire K Latham 293 This page intentionally left blank viii LIST OF CONTRIBUTORS Magdy Abdel-Kader Brunel Business School, Brunel University, Uxbridge, UK Mohamed E Bayou School of Management, University of Michigan-Dearborn, MI, USA Al Bento Merrick School of Business, University of Baltimore, MD, USA Emilio Boulianne John Molson School of Business, Concordia University, Quebec, Canada John A Brierley University of Sheffield, Sheffield, UK Jane Cote Washington State University, WA, USA Christopher J Cowton University of Huddersfield, Huddersfield, UK Colin Drury University of Huddersfield, Huddersfield, UK Nabil Elias Belk College of Business, University of North Carolina, Charlotte NC, USA David Shelby Harrison School of Business, University of South Carolina-Aiken, SC, USA Nen-Chen Richard Hwang College of Business Administration, California State University-San Marcos, CA, USA Thomas Jeffries QQuest Corporation, MI, USA Larry N Killough Virginia Polytechnic Institute and State University, VA, USA ix 312 JANE COTE AND CLAIRE K LATHAM Procedures and advice are the primary components of acquiescence measured in this study Propensity to Leave (Outcome) Expectations regarding continuation of the relationship are measured similarly to Lusch and Brown (1996) We elicited this propensity with three items that explore expectations regarding whether the relationship is a longterm alliance and whether contract renewal is virtually automatic Cooperation (Outcome) Three items defined our measure of cooperation Adapted from both Heide and John (1992) and Anderson and Narus (1990), we assessed whether the practice respondents view problems as being solved jointly, whether there is commitment to improvements that benefit the relationship as a whole, or whether reciprocal favors exist Functional Conflict (Outcome) To measure functional conflict we assessed respondent’s perceptions of the extent to which conflict exists in the relationship (Kumar et al., 1992) Three items were used to measure this construct Decision-Making Uncertainty (Outcome) Decision-making uncertainty measures whether the physician practice has sufficient information to make routine decisions in a manner acceptable to both parties Using data from our interviews, we created this measure to assess respondent’s views of the extent to which participants were confident in their ability to make future decisions Routine decisions such as medical procedure coverage, processing a complex claim, reimbursement timing, and problem resolution were included in this four-item measure RESULTS Structural Equation Model Analysis We use structural equation modeling (SEM) (using EQSTM 6.0 SEM software), with maximum likelihood estimation technique, to test the structural model presented in Fig and our specific hypotheses The SEM process centers on two stages, validating the measurement model using confirmatory factor analysis and fitting the structural model through path analysis with Trust and Commitment: Intangible Drivers of Interorganizational Performance 313 latent variables It permits us to examine the full model simultaneously, as opposed to one path at a time, as well as to examine the hypothesized causal relations among the six antecedents, trust and commitment, and six performance metrics In addition to the benefit of testing the model overall rather than coefficients individually, other advantages of SEM are greater flexibility of assumptions than multiple regression, the use of confirmatory factor analysis to reduce measurement error and the ability to model mediating variables Our findings are presented in Table and Fig Fig illustrates the model and identifies the results of the structural equation analysis It provides the path coefficients for each causal link and the R2 coefficient for each mediating and outcome construct Table presents the construct correlation matrix to provide an alternative method for evaluating the causal associations Various fit indices may be used to evaluate descriptively whether the estimated model is not different than the hypothesized model (Carmines & McIver, 1981) Table presents the fit statistics The overall model has an adequate goodness of fit index (Comparative Fit Index (CFI)) of 0.898 (Bollen IFI ¼ 0.900), given the complexity of the model and the substantial number of constructs, indicators and paths (Williams & Holahan, 1994; Bollen, 1989) An alternative measure, w2, indicates the difference between the estimated and observed correlation matrix A low w2 (high P-value) indicates there is no difference, that is, the specified model recaptures the observed correlation matrix completely Conversely, a high w2 and low Pvalue, as is evident here (w2 ¼ 512.0857, P-value ¼ 0.000), suggests there is a statistical difference between the observed and estimated correlation matrix indicating the model is not perfectly capturing the observed correlation matrix Because of statistical power, however, a low w2 is achieved infrequently.2 When N is large and there exists a greater potential for problems with the traditional w2 test, the use of the ratio of the w2 estimator divided by its degrees of freedom as a measure of fit is appropriate (Bollen, 1989) Bollen (1989) presents support for an adequate fit as a value less than 3.3 Our model achieves an acceptable 1.695 Tests of the Causal Hypotheses Breckler (1990) emphasizes the key importance of evaluating the fit of individual equations within the model in addition to testing the global fit All of the individual path coefficients are significant at Po0.05 except for those paths involving shared values The results for strength of the individual antecedents leading to our mediating variables, trust and commitment, are 314 Table Correlation Matrix Legal Shared CommuValues nication Opportun- Commitistic ment Behavior Trust Financial Acquiesc- Propensity Perform- ence to Leave ance Cooper- Functional Decision ation Conflict Making Uncertainty Legal Termination costs 0.168 (2.128)ÃÃ 0.176 (2.229)ÃÃ 0.097 (1.241) 0.095 (1.171) 0.229 (2.794)ÃÃ À0.031 (À0.390) À0.046 (À0.586) 0.075 (0.799) 0.100 (1.209) 0.113 (1.443) 0.051 (0.651) 0.118 (1.500) À0.197 (À2.477)ÃÃ 0.502 À0.121 (5.749)ÃÃ (À1.542) À0.475 0.125 À0.359 (À6.264)ÃÃ (1.556) (À4.598)ÃÃ 0.682 À0.061 0.593 À0.528 ÃÃ ÃÃ (9.504) (À0.732) (7.937) (À8.123)ÃÃ 0.724 À0.152 0.554 À0.644 0.761 (10.618)ÃÃ (À1.911) (7.553)ÃÃ (À12.605)ÃÃ (18.559)ÃÃ 0.681 À0.094 0.438 À0.312 0.609 0.695 (7.234)ÃÃ (À1.199) (5.156)ÃÃ (À3.958)ÃÃ (8.211)ÃÃ (10.052)ÃÃ 0.230 0.002 0.197 À0.127 0.393 0.302 0.313 (2.481)ÃÃ (0.024) (2.121)ÃÃ (À1.313) (4.380)ÃÃ (3.343)ÃÃ (3.416)ÃÃ 0.574 À0.069 0.420 À0.500 0.827 0.639 0.538 0.477 (7.595)ÃÃ (À0.832) (5.290)ÃÃ (À7.411)ÃÃ (21.646)ÃÃ (11.706)ÃÃ (7.028)ÃÃ (5.599)ÃÃ 0.525 À0.044 0.571 À0.470 0.602 0.640 0.439 0.289 0.551 (5.968)ÃÃ (À0.569) (6.369)ÃÃ (À6.179)ÃÃ (8.101)ÃÃ (9.033)ÃÃ (5.162)ÃÃ (3.135)ÃÃ (7.231)ÃÃ À0.549 0.073 À0.473 0.524 À0.585 À0.659 À0.558 À0.352 À0.626 À0.646 (À6.181)ÃÃ (0.936) (À5.490)ÃÃ (7.001)ÃÃ (À7.816)ÃÃ (À9.376)ÃÃ (À6.261)ÃÃ (À3.858)ÃÃ (À8.451)ÃÃ (À6.971)ÃÃ 0.573 0.031 0.472 À0.387 0.563 0.533 0.453 0.368 0.495 0.535 À0.567 (6.388)ÃÃ (0.395) (5.487)ÃÃ (À4.987)ÃÃ (7.461)ÃÃ (7.215)ÃÃ (5.300)ÃÃ (4.042)ÃÃ (6.374)ÃÃ (6.059)ÃÃ (À6.332)ÃÃ ÃÃIndicates statistically significant at Po0.05 JANE COTE AND CLAIRE K LATHAM 0.040 (0.519) Benefits 0.482 (5.574)ÃÃ Shared values À0.200 (À2.522)ÃÃ Communication 0.298 (3.665)ÃÃ Opportunistic À0.242 behavior (À3.041)ÃÃ Commitment 0.526 (6.875)ÃÃ Trust 0.531 (7.186)ÃÃ Financial 0.507 performance (5.809)ÃÃ Acquiescence 0.381 (4.202)ÃÃ Propensity to 0.451 leave (5.727)ÃÃ Cooperation 0.441 (5.179)ÃÃ Functional À0.412 conflict (À4.898)ÃÃ DecisionÀ 0.382 making uncertainty (4.585)ÃÃ Termination Benefits Costs Legal Outcomes Mediating Acquiescence R2=0.175 0.418** (H9) 0.171** (H1) 0.827** (H10) Relationship Commitment R2=0.667 0.191** (H2) Relationship Termination Costs Relationship Benefits Shared Values 0.251** (H11) 0.210** (H12) 0.176** (H3) 0.619** (H8) 0.061 (H4) Propensity To Leave R2=0.684 -0.030 (H5) Cooperation R2=0.461 Financial Performance R2=0.489 0.474** (H14) 0.530** (H13) Trust R2=0.589 -0.700** (H15) Functional Conflict R2=0.490 0.396** (H6) 0.572** (H16) Communication -0.525** (H7) Opportunistic Behavior i) Coefficients above straight single-headed arrows indicate standardized regression weights, e.g., the 0.171 on the line between Legal and Relationship Commitment ( ** indicates statistically significant at P