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52 CHAPTER 2. RPE AT THE BUSINESS UNIT MANAGER LEVEL
2.6 Contractibility MIMIC Model (Appendix A)
This appendix describes the estimation of the contractibility measure, which is used in
the analyses in chapter 2. Contractibility is a requirement for the effectiveness of resultoriented
control systems. According to Speklé & Verbeeten (2008), contractibility consists
of three dimensions that need to be met simultaneously for the effective use of output controls,
such as RPE. These dimensions are the following: 1) the ability to unambiguously
specify goals ex-ante, 2) the ability to measure outputs in a reasonably undistorted manner
(i.e., the output metrics correspond rather well with the actual goals that the unit needs to
accomplish), and 3) the responsible individuals (in this case, the business unit managers)
need to understand the process of transforming efforts into results 32 . In section 2.3.3.2,
these three dimensions are operationalized as goal clarity, measurability of outputs and
knowledge of transformation process. Additionally, section 2.3.3.2 describes the underlying
survey items and descriptive statistics of these measures. Because the three dimensions
simultaneously ‘cause’ contractibility, contractibility is a formative construct.
Contractibility is not observed directly by the survey-instrument. Instead, contractibility
is estimated as a latent construct by using a MIMIC model. MIMIC (Multiple Indicators
for Multiple Causes) is a special case of structural equation modelling. The estimation is
based on a number of measures, including measures that capture the three dimensions presented
above. To specify the latent construct ‘contractibility’, one must first determine the
nature and direction of the relationships between the construct and its indicators (Bisbe
et al. 2007). Contractibility is estimated with two groups of constructs that differ in these
aspects.
The first group consists of formative indicators that capture the three dimensions goal clarity,
measurability of outputs and knowledge of transformation process. Formative indicators
are causal in nature. That is, increases of the formative indicators result in higher degrees
of contractibility. Together, the three dimensions ’define’ contractibility. Leaving out one
or more dimensions (e.g., the unambiguous specification of goals) alters the content and
meaning of the construct. If I only measure contractibility based on the two remaining dimensions,
the resulting construct would be theoretically different from the abovementioned
definition of contractibility. This important difference distinguishes formative constructs
from the more commonly used reflective constructs 33 . Whereas with formative constructs,
a census of indicators is required to describe the construct, reflective constructs may be
32 Speklé & Verbeeten (2008) derive the list of conditions for contractibility from several seminal papers
that apply the conditions (amongst others) to contract-oriented control structures, e.g. Otley & Berry
(1980), Hofstede (1981), and Gibbons (1998).
33 For a more elaborate discussion of the differences between formative and reflective constructs as well
as the consequences of these differences for model specification and measurement, see: Jarvis et al. (2003),
Diamantopoulos & Siguaw (2006), and Bisbe et al. (2007).