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2.3. SAMPLE AND MEASUREMENT 33
this reason, contractibility is a formative construct 18 . Leaving one or more dimensions out
(as often happens with reflective items, for example, to boost scale reliability) alters the
content and meaning of the construct. Contractibility is measured as the weighted summation
of goal clarity, measurability of outputs and knowledge of the transformation process.
For the calculation of the weights of the individual measures, I use a MIMIC model. The
MIMIC model is presented in appendix A at the end of this chapter on page 52. The
remainder of the current subsection describes the contractibility measure primarily from a
conceptual instead of a statistical viewpoint.
The measurement of the individual underlying constructs (goal clarity, measurability of
outputs and knowledge of transformation process) will be discussed next. Goal clarity is
a multi-item construct, evaluated by four questionnaire items. These questions, stemming
from Rainey (1983) and Kruis (2008) have been used together to measure goal ambiguity
by Kruis (2008). I use these items to measure goal clarity (the exact opposite of ambiguity)
by reversing the instrument and averaging the scores. The factor analysis and the
Cronbach’s alpha results agree with this approach, as shown in table 2.5 - Panel A.
Measurability of outputs is a construct evaluated by four items, including an item asking
directly about the measurability of outputs and questions about the goal consistency and
completeness of the output measures. The items load onto one factor with good scale
reliability. The items and statistics are summarized in table 2.5 - Panel B.
The knowledge of the transformation process variable consists of two questionnaire items,
which were averaged to compute the knowledge measure. The items ask about the transparency
of the transformation process for the manager and his knowledge about adjustments
of the transformation process if necessary. As shown in table 2.5 - Panel C, the
two items combined have insufficient scale reliability (Cronbach’s alpha 0.58) 19 . However,
because the factor analysis shows high component loadings and a high level of variance
explained, both items have been included in the knowledge of the transformation processvariable.
Together, goal clarity, measurability of outputs and knowledge of transformation process
form the necessary conditions for contractibility of performance. The measures are summed
according to the weights that are calculated with the MIMIC model, which can be found
in appendix A at the end of this chapter on page 52.
18 For the differences between formative and reflective indicators, and for a discussion of the consequences
of these differences for model specification and measurement, see Bisbe et al. (2007), Diamantopoulos &
Siguaw (2006), and Jarvis et al. (2003).
19 Hair et al. (2010:92) claim that a Cronbach’s alpha value of 0.60 is the lower limit of acceptability.
Also Hair et al. (2010) argue that we need to consider multiple diagnostics to assess a measure’s internal
consistency, including inter-item correlations and confirmatory factor analysis.