The knowledge strategy orientation scale: individual
perceptions of firm-level phenomena.
by Miller, Brian K.^Bierly, Paul E., III^Daly, Paula S.
--and--. 1998. "Fit Indices in Covariance Structure Modeling:
Sensitivity to Underparameterized Model Misspecification."
Psychological Methods 3: 424-453.
--and--. 1995. "Evaluating Model Fit." Chapter in
Structural Equation Modeling: Concepts, Issues, and Applications. Ed. R.
H. Hoyle. Thousand Oaks, CA: Sage. pp. 76-99.
Ichijo, K. 2002. "Knowledge Exploitation and Knowledge
Exploration: Two Strategies for Knowledge Creating Companies."
Chapter in The Strategic Management of Intellectual Capital and
Organizational Knowledge. Eds. C. W. Choo and N. Bontis. New York, NY:
Oxford University Press. pp. 477-483.
Joreskog, K. and D. Sorbom. 2004. LISREL 8. 71 [computer software].
Chicago, IL: Scientific Software International.
Judd, C. M., R. Jessor and J. E. Donovan. 1986. "Structural
Equation Models and Personality Research." Journal of Personality
54: 148-196.
Katila, R. and G. Ahuja. 2002. "Something Old, Something New:
A Longitudinal Study of Search Behavior and New Product
Introduction." Academy of Management Journal 45: 1183-1194.
Kline, R. B. 1998. Principles and Practices of Structural Equation
Modeling. New York, NY: Guilford.
Knott, A. M. 2002. "Exploration and Exploitation as
Complements." Chapter in The Strategic Management of Intellectual
Capital and Organizational Knowledge. Eds. C. W. Choo and N. Bontis. New
York, NY: Oxford University Press. pp. 339-358.
Lee, J., J. Lee and H. Lee. 2003. "Exploration and
Exploitation in the Presence of Network Externalities." Management
Science 49: 553-570.
Levinthal, D. and J. G. March. 1993. "The Myopia of
Learning." Strategic Management Journal 14 (Winter Special Issue):
95-112.
March, J. G. 1991. "Exploration and Exploitation in
Organizational Learning." Organization Science 2: 71-87.
McNamara, P. and C. Baden-Fuller. 1999. "Lessons from Celltech
Case: Balancing Knowledge Exploration and Exploitation in Organizational
Renewal." British Journal of Management 10: 291.
Meng, X-L., R. Rosenthal and D. B. Rubin. 1992. "Comparing
Correlated Correlation Coefficients." Psychological Bulletin 111:
172-175.
Miles, R. E. and C. C. Snow. 1978. Organizational Strategy,
Structure and Process. New York, NY: McGraw-Hill.
Nunnally, J. C. 1978. Psychometric Theory, 2nd ed. New York, NY:
McGraw-Hill.
Payne, S. C., J. F. Finch and T. R. Tremble. 2003. "Validating
Surrogate Measures of Psychological Constructs: The Application of
Construct Equivalence to Archival Data." Organizational Research
Methods 6: 363-382.
Porter, M. 1980. Competitive Strategy. New York, NY: Free Press.
Rosenkopf, L. and A. Nerkar. 2001. "Beyond Local Search:
Boundary-spanning, Exploration, and Impact in the Optical Disk
Industry." Strategic Management Journal 22: 287-306.
Sharfman, M. 1998. "On the Advisability of Using CEOs as the
Sole Informant in Strategy Research." Journal of Managerial Issues
10 (3): 373-392.
Snow, C. C. and D. C. Hambrick. 1980. "Measuring
Organizational Strategies: Some Theoretical and Methodological
Problems." Academy of Management Review 5: 527-538.
Thompson, B. and L. G. Daniel. 1996. "Factor Analytic Evidence
for the Construct Validity of Scores: A Historical Overview and Some
Guidelines." Educational and Psychological Measurement 56: 197-208.
Volberda, H. W. 1996. "Toward the Flexible Form: How to Remain
Vital in Hypercompetitive Environments." Organization Science 7:
359-374.
Zack, M. H. 1999. "Developing a Knowledge Strategy."
California Management Review 41 (3): 125-145.
Brian K. Miller
Assistant Professor of Management
Texas State University
Paul E. Bierly, III
Assistant Professor of Management
James Madison University
Paula S. Daly
Assistant Professor of Management
James Madison University
Table 1
Pattern Matrix for Principal Axis Factor
Analysis in Sample One
Factor
1 2
Explorer 1 .763 -.057
Explorer 2 .674 .048
Explorer 3 .626 .044
Explorer 4 .356 .243
Exploiter 1 .159 .535
Exploiter 2 .047 .300
Exploiter 3 -.135 .993
Exploiter 4 .282 .429
Note: Largest factor loadings in bold.
Table 2
Item Level Knowledge Strategy Orientation Scale Descriptive
Statistics and Correlations
1 2 3 4
Mean 2.77 3.07 2.57 2.84
Standard deviation 1.15 1.07 1.05 1.00
Skewness 0.39 0.06 0.44 0.06
Kurtosis -1.12 -1.39 -0.67 -1.07
Explorer 1 0.51 ** 0.37 ** 0.42 **
Explorer 2 0.61 ** 0.20 * 0.19
Explorer 3 0.32 ** 0.25 * 0.48 **
Explorer 4 0.40 ** 0.42 ** 0.29 **
Exploiter 1 0.23 * 0.34 ** 0.32 ** 0.21 *
Exploiter 2 0.30 ** 0.38 ** 0.17 0.07
Exploiter 3 0.29 ** 0.42 ** 0.01 0.25 *
Exploiter 4 0.31 ** 0.17 -0.02 0.06
Mean 2.94 3.05 2.69 2.89
Standard deviation 1.06 0.94 1.06 1.05
Skewness 0.39 0.05 0.38 0.22
Kurtosis -1.36 -1.56 -0.79 -0.99
5 6 7 8
Mean 3.49 4.00 3.43 3.62
Standard deviation 0.97 0.81 0.93 0.87
Skewness -0.86 -1.10 -0.65 -1.11
Kurtosis -0.40 1.31 -0.71 0.43
Explorer 1 0.33 ** 0.16 0.30 ** 0.26 **
Explorer 2 0.41 ** 0.19 0.27 ** 0.31 **
Explorer 3 0.47 ** 0.28 ** 0.30 ** 0.27 **
Explorer 4 0.33 ** 0.35 ** 0.30 ** 0.13
Exploiter 1 0.46 ** 0.48 ** 0.48 **
Exploiter 2 0.46 ** 0.48 ** 0.32 **
Exploiter 3 0.58 ** 0.36 ** 0.32 **
Exploiter 4 0.29 ** 0.32 ** 0.33 **
Mean 3.70 3.94 3.47 3.66
Standard deviation 0.80 0.80 0.92 0.90
Skewness -0.88 -1.14 -0.59 -0.86
Kurtosis 0.36 1.45 -0.52 -0.17
Note: N = 98. Sample Two statistics in upper right side of table;
Sample Three statistics in lower left side of table.
* p < .05 (two-tailed), ** p < 0.01 (two-tailed).
Table 3
Fit Statistics for the Knowledge Strategy Orientation Models
Model [chi square] df [DELTA] [DELTA]df
[chi square]
Sample Two (a)
2-Factor Model 39.60 19 33.64 1
1-Factor Model 73.24 20 -- --
Sample Three (a)
2-Factor Model 35.43 19 12.85 1
1-Factor Model 48.28 20 -- --
Model p-value CFI RMSEA SRMR
Sample Two (a)
2-Factor Model 0.000 0.92 0.097 0.065
1-Factor Model 0.000 0.79 0.160 0.098
Sample Three (a)
2-Factor Model 0.000 0.95 0.093 0.066
1-Factor Model 0.000 0.91 0.120 0.080
(a) N = 98
Note: [DELTA][chi square] = change in Chi-square;
[DELTA]df = change in degrees of freedom; CFI = comparative
fit index; RMSEA = root mean square error of approximation;
SRMR = standardized root mean square residual.
Table 4
Completely Standardized Factor Patterns (a) for Alternative
Models of Knowledge Strategy Orientation in Three Samples
1-Factor Models
Sample Two Sample Three
Item Knowledge Strategy Factor
Explorer 1 0.71 (0.45) 0.61 (0.28)
Explorer 2 0.69 (0.54) 0.54 (0.25)
Explorer 3 0.37 (0.12) 0.61 (0.34)
Explorer 4 0.49 (0.22) 0.52 (0.27)
Exploiter 1 0.47 (0.35) 0.75 (0.59)
Exploiter 2 0.43 (0.29) 0.46 (0.33)
Exploiter 3 0.56 (0.36) 0.57 (0.38)
Exploiter 4 0.34 (0.14) 0.46 (0.28)
2-Factor Models
Sample Two Sample Three
Item Explorer Exploiter Explorer Exploiter
Explorer 1 0.80 (0.56) -- 0.76 (0.44) --
Explorer 2 0.75 (0.65) -- 0.57 (0.28) --
Explorer 3 0.40 (0.14) -- 0.66 (0.40) --
Explorer 4 0.55 (0.28) -- 0.61 (0.37) --
Exploiter 1 -- 0.61 (0.57) -- 0.78 (0.64)
Exploiter 2 -- 0.46 (0.34) -- 0.49 (0.36)
Exploiter 3 -- 0.68 (0.54) -- 0.59 (0.41)
Exploiter 4 -- 0.39 (0.19) -- 0.48 (0.31)
(a) [R.sup.2] values in parentheses.
Table 5
Correlations and Z-tests for Relationship between Focal
Constructs and Distinctive Competencies
Distinctive Sample Three Correlations
Competencies Explorer Exploiter Z score
Radical Innovation
Research and development .42 ** .38 ** 0.454
Product technology .40 ** .44 ** -0.499
New product development .56 ** .38 ** 2.152 *
Speed to market .60 ** .41 ** 2.344 *
Incremental Innovation
Process technology .29 ** .47 ** -2.021 *
Customer preferences .02 .26 * -2.468 *
Cost reduction .26 * .42 ** -3.048 *
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