Quality Control versus Quality Learning: Measurement, Antecedents, and Performance Implication

1. Quality Control versus Quality Learning: Measurement, Antecedents, and Performance Implication Dongli Zhang PhD Candidate Operations and Management Science Department Carlson School of Management University of Minnesota August 12, 2006 OM Division PhD Consortium Annual meeting of AoM, Atlanta

2. Research overview Committee Members: Dr. Kevin Linderman (Advisor, OMS) Dr. Roger Schroeder (Advisor, OMS) Dr. Susan Meyer Goldstein (OMS) Dr. Geoffrey Maruyama (Educational Psychology) Stage: Proposal development Primary research methodology: Cross-sectional survey

3. Agenda • Motivation • Research questions • Part I: Description of major concepts • Part II: Antecedents of implementation of QC versus QL • Part III: Performance implication of QC versus QL • Methods • Conclusions

4. Motivation Practical • Same QM practices, different results • Some observations from my working experience: one set fits all? • Implement or focus on different QM practices according to some contingency factors. But how?

5. Motivation Research • One limitation of existing studies: all QM practices are treated as one set when examining their implementation and influence on performance (Sitkin et al., 1994) No testing of this theory • Results of QM practices impact on performance is inconsistent. • Contingency approach rather than an assumption of universal applicability is needed (Nair, 2005; Kaynak, 2003; Dale, et al., 2001)

6. Research Questions A central premise of this study is that there exist two different aspects of QM practices that have different objectives: quality control (QC) and quality learning (QL) (Sitkin et al., 1994; Sutcliffe et al., 2000). • Q1: How do we discriminate and measure QC and QL? • Q2: What are the antecedents that influence the implementation of QC and QL? • Q3: What is the relationship between QC, QL, and plant performance? What factors may moderate the relationship (organizational structure, environmental uncertainty)?

7. Part I: Description of QC and QL Common QM precepts Two widely used frameworks:

8. Part I: Description of QC and QL-continued • QC: a set of QM practices that aim to manage the known problems and processes. The objective of QC is to ensure the reliability of outcomes. • QL: a set of QM practices that aim to explore the unknown and to identify and pursue novel solutions. QL keeps organizations open and flexible to new ideas.

9. Part I: Description of QC and QL-continued

10. Part II: Antecedents of implementation of QC versus QL Institutional view QC Institutional mechanisms (Westphal et al., 1997; Ketokivi and Schroeder, 2004) QL Proposition 1a. QC practices are implemented through institutional mechanisms. Proposition 1b. QL practices are implemented through institutional mechanisms.

11. Institutional view QC QL Rational view Rational view (Scott, 2003; Linderman et al., 2005; Evans and Lindsay, 2005 ) Proposition 2a. The implementation of QC practices is driven by the organization’s goals and objectives of low cost and on-time delivery. Proposition 2b. The implementation of QL practices is driven by the organization’s goals and objectives of flexibility and innovation.

12. Part III: Performance implication of QC versus QL QC Performance outcome QL • Org structure • Environmental • uncertainty

13. Define the dependent variable Plant level performance (Klassen and Whybark, 1999; Roth and Miller, 1990) • Cost • Quality • Delivery • Flexibility

14. Organizational structural as a moderator Two types of organizational structure: mechanistic and organic (Burns and Stalker, 1961; Douglas and Judge, 2001) • Mechanistic structure: structured hierarchically and centrally controlled by an authority • Organic structure: more flexible and open-type internal arrangements

15. Organizational structure as a moderator Proposition 3a. Organizations with mechanistic structure that focus on QC result in higher plant level performance than those that focus on QL. Proposition 3b. Organizations with organic structure that focus on QL result in higher plant level performance than those that focus on QC.

16. Environmental uncertainty as a moderator Environmental uncertainty: is proposed as having an influence on the relationship between QM practices and performance in several studies (Benson et al. 1991; Sitkin et al. 1994; Nair, 2005) Environmental uncertainty: • degree of competition, change of customer needs, and rate of product/process change (Benson et al., 1991). • task uncertainty, product/process uncertainty, and organizational uncertainty (Sitkin et al., 1994).

17. Environmental uncertainty as a moderator Proposition 4a. When environmental uncertainty is low, organizations that focus on QC result in higher plant level performance than those that focus on QL. Proposition 4b. When environmental uncertainty is high, organizations that focus on QL result in higher plant level performance than those that focus on QC.

18. Methods • Unit of analysis: plant • Data: a cross-sectional survey, from a research project that lasted for 15 years and collected data for three rounds Round 3: High Performance Manufacturing (HPM) project • HPM data base: • N=189 • Three industries: • Automotive, electronics, and machinery • Six countries: • Japan, Sweden, Finland, Korea, Germany, USA

19. Methods-continued • Measurement Instrument development Based on a comprehensive literature review, draw items from the HPM dataset • Reliability and validity analysis • Structural Equation Modeling (SEM) • Hierarchical moderated regression analysis

20. Conclusions • Among the first attempts that address the theoretical underpinnings of QM by distinguishing its two goals: control and learning • The first empirical test for discriminating them • Incorporating insights from organization theory and management theory into the research on QM • Providing insights for practitioners on implementing QM Potential Contributions

21. Thank You ?