1. 1/15/2016 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. 1/15/20162 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 Research overview

3. 1/15/20163 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. 1/15/20164 Motivation  Some observations from my working experience: one set fits all? Practical  Same QM practices, different results  Implement or focus on different QM practices according to some contingency factors. But how?

5. 1/15/20165 Motivation  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) Research

6. 1/15/20166 Research Questions  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)? 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).

7. 1/15/20167 Part I: Description of QC and QL Common QM precepts Two widely used frameworks: Dean and Bowen, 1994 Customer Focus Continuous Improvement Team Work Sitkin, Sutcliffe, and Schroeder, 1994 Customer Satisfaction Continuous Improvement Systems View of Organization

8. 1/15/20168 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. 1/15/20169 Part I: Description of QC and QL -continued QCQL Customer Focus Identify and fulfill current customers’ needs Anticipate customers’ needs and respond Continuous Improvement Monitor current processes to make sure they are under control Improve process incrementally or radically Systems View of Organization Working within each function Task-related training Focus on integration between functions Multi-functional training

10. 1/15/201610 Institutional view QC QL Part II: Antecedents of implementation of QC versus QL Institutional mechanisms (Westphal et al., 1997; Ketokivi and Schroeder, 2004) Proposition 1a. QC practices are implemented through institutional mechanisms. Proposition 1b. QL practices are implemented through institutional mechanisms.

11. 1/15/201611 Institutional view Rational view QC QL 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. 1/15/201612 Part III: Performance implication of QC versus QL QC QL Performance outcome Org structure Environmental uncertainty

13. 1/15/201613 Define the dependent variable Plant level performance (Klassen and Whybark, 1999; Roth and Miller, 1990)  Cost  Quality  Delivery  Flexibility

14. 1/15/201614 Organizational structural as a moderator Two types of organizational structure: mechanistic and organic (Burns and Stalker, 1961; Douglas and Judge, 2001)  Organic structure: more flexible and open-type internal arrangements  Mechanistic structure: structured hierarchically and centrally controlled by an authority

15. 1/15/201615 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. Org structure Focus on QC Focus on QL MechanisticHigh performanceLow performance OrganicLow performanceHigh performance

16. 1/15/201616 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. 1/15/201617 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. Uncertainty Focus on QC Focus on QL LowHigh performanceLow performance HighLow performanceHigh performance

18. 1/15/201618 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. 1/15/201619  Measurement Instrument development Based on a comprehensive literature review, draw items from the HPM dataset Methods -continued  Reliability and validity analysis  Structural Equation Modeling (SEM)  Hierarchical moderated regression analysis

20. 1/15/201620 Conclusions Potential Contributions  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

21. 1/15/201621 Thank You