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Learning-Before-Doing and Learning-in-Action: Bridging the Gap Between Innovation Adoption, Implementation, and Performance

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New Approaches to Organization Design

Part of the book series: Information and Organization Design Series ((INOD,volume 8))

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Abstract

Implementation links purpose to outcome. Our model of implementation effectiveness centers on learning – learning-before-doing (preparation) and learning-in-action (adaptation and change catalysis). We explain both the degree of implementation and its impact on various measures of performance (subjective and objective) and test our proposed model on a large, multi-industry sample in the context of implementing the ISO 9000 quality standard. We find that learning-before-doing, an important means for bridging the adoption–implementation gap, is a necessary but not sufficient condition for realizing the benefits of a planned change. To fully bridge the implementation–performance gap, both aspects of learning-in-action – adaptation and change catalysis – must accompany implementation.

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Notes

  1. 1.

    From hereon, the terms “change” and “innovation” are used interchangeably, to mean potentially beneficial alterations in the way an organization functions.

  2. 2.

    As Klein and Sorra (1996: 1057) comment: “Implementation is the transition period during which targeted organizational members ideally become increasingly skillful, consistent, and committed in their use of an innovation. Implementation is the critical gateway between the decision to adopt the innovation and the routine use of the innovation within an organization.”

  3. 3.

    Orlikowski (2002: 250) takes an even stronger view that stresses that knowledge and practice reciprocally constitute each other.

  4. 4.

    We avoid using the term “learning-by-doing” even though it is close to “learning-in-action” because learning-by-doing is identified with learning curve effects (Argote, 1999).

  5. 5.

    This concept expands on Greve and Taylor’s (2000) idea of technological innovation as being a catalyst for additional organizational changes.

  6. 6.

    H3 is operationalized in an identical manner to the following hypothesis – Extent of implementation moderates the relationship between change catalysis and performance; the greater the extent of implementation, the more positive will be effect of change catalysis on performance. Hence, the operationalization (as an interaction term’s effect on performance) captures both arguments leading to H3.

  7. 7.

    Before the interviews, we constructed an interview guide that had open-ended questions about the company’s experience with ISO 9000. During the site visit, we heard general presentations. We interviewed people from the functions of: auditing (both internal and external), quality management, manufacturing, engineering, software development, and documentation. Typically, the interviews lasted from 1 to 1.5 hours and were taped. We also took handwritten notes, and while on-site collected relevant documents. The interview team discussed its impressions with company representatives and had off-site debriefings.

  8. 8.

    In companies with more than one ISO 9000 registrations, we ran the analyses with measures corresponding to their first registration. For the 55 public companies, on the date we finalized the survey, the mean and standard deviation of the time passed since first facility registration were 43.0 and 15.6 months, respectively. Time since last facility registration was 41.8 months (14.9 standard deviation). We also ran analyses with measures relative to the most recent registration. Results were very similar to using the first registration time frame.

  9. 9.

    This variable was incorporated only in the models predicting self-reported measures; it is constant for the Compustat performance measures because all time-relevant performance measures were obtained from Compustat.

  10. 10.

    The formulation of the path analysis is as follows. (The following notation is used here: Internal Integration [II], External Coordination [EC], Implementation [IM], Adaptation-in-use [AD], Change Catalysis [CC], Performance [PR].)

    The first two element in the top equation are the direct effects of internal integration and external coordination on performance. Substituting the last three equations into the first one yields the following:

    Specific numerical values for all models are available from the authors upon request.

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Acknowledgments

This chapter was supported in part from a grant from the NSF, Decision, Risk Analysis, and Management Division (SES-9905604). McGraw Hill Quality Systems and Plexus Corporation sponsored the survey of ISO 9000 registrants upon which this chapter is based. Gove Allen of the University of Minnesota designed the Internet site that was used to carry out the survey. Gove helped us gather additional data to supplement the survey from the Compustat data base. The authors wish to acknowledge Ayala Cohen, Shmuel Ellis, Martin Gannon, Jørn Flohr Nielsen, Roger Schroeder, and Charles Snow for their comments on this chapter and earlier drafts. This chapter also benefited from the comments of anonymous reviewers of the NSF proposal.

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Authors and Affiliations

  1. Faculty of Industrial Engineering and Management, Technion – Israel Institute of Technology, 32000, Haifa, Israel

    Eitan Naveh

  2. College of Business Administration, California State University, 92096, San Marcos, CA, USA

    Ofer Meilich

  3. Carlson School of Management, University of Minnesota, 55455, Minneapolis, MN, USA

    Alfred Marcus

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  1. Eitan Naveh
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  2. Ofer Meilich
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Correspondence to Eitan Naveh .

Editor information

Editors and Affiliations

  1. Aarhus School of Business, University of Aarhus, Haslegaardsvej 10, Aarhus V, 8210, Denmark

    Anne Bøllingtoft

  2. Aarhus School of Business, University of Aarhus, Haslegaardsvej 10, Aarhus V, 8210, Denmark

    Dorthe Døjbak Håkonsson

  3. Aarhus School of Business, University of Aarhus, Haslegaardsvej 10, Aarhus V, 8210, Denmark

    Jørn Flohr Nielsen

  4. Dept. of Management & Organization, Pennsylvania State University, University Park, 16802, U.S.A.

    Charles C. Snow

  5. Aarhus School of Business, University of Aarhus, Haslegaardsvej 10, Aarhus V, 8210, Denmark

    John Ulhøi

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Naveh, E., Meilich, O., Marcus, A. (2009). Learning-Before-Doing and Learning-in-Action: Bridging the Gap Between Innovation Adoption, Implementation, and Performance. In: Bøllingtoft, A., Håkonsson, D., Nielsen, J., Snow, C., Ulhøi, J. (eds) New Approaches to Organization Design. Information and Organization Design Series, vol 8. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0627-4_7

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