Customizability
Scales
THE EFFECTS OF CUSTOMIZABILITY AND REUSABILITY ON PERCEIVED
PROCESS AND COMPETITIVE PERFORMANCE OF SOFTWARE FIRMS
(Nidumolu
and Knotts, 1998)
Construct: Nidumolu and Knotts (1998, p.111)
postulated that increases in customizability are associated with increases
in process flexibility and process predictability in software development.
Customizability is defined by Nidumolu and Knotts (1998)
as the ability of the software development approach to be tailored to
the specific needs of individual projects.
Description: The final
measures for customizability consist of seven item facet scales. All
items are assessed using 5-point Likert-type scales:
1. Can be
used effectively for a variety of projects
2. Can be
customized by individual project teams to suit their context
3. Permit a
range of responses to different types of requirements
4. Permit a
range of responses of different types of technologies
5. Can be adapted
to the quality goals of individual projects
6. Can be
adapted to the productivity goals of individual projects
7. Can be
adapted to suit the resource levels available to individual projects
Development: Because the customizability
construct has not been studied empirically in previous MIS research,
measurement scales had to be developed by identifying individual concepts
emphasized by researchers. These concepts were then used to create individual
items and the measurement scales were subsequently subjected to a variety
of analyses for assessing their reliability and validity.
The scales
were first assessed for content validity. Expert review was used to verify
content validity during a pretest, where the measurement items for the
constructs were assessed by five academics specializing in information systems
and 10 software development professionals in industry. All reviewers completed
the questionnaire and also responded to the following questions.
1. Were there
items that should have been included in the questionnaire, but were not?
2. Were there
items on the questionnaire that should be deleted because they were irrelevant?
3.
Were there
items on the questionnaire that that should be reworded to reduce ambiguity?
Upon
completing the questionnaire, the reviewers were interviewed and asked to
describe their interpretation of the questions, in order to compare them with
the original intent. The final questionnaire, modified as a result of the
pretest, was then used for the survey
(cf.
Nidumolu and Knotts, 1998, pp.113-114).
Samples: The study questionnaire was mailed
to a random sample of 100 firms selected from approximately 350 available
software firms. A strategy of intensive sampling was selected, resulting
in a 58% response rate. The key informant who received the survey was
typically the vice president (VP) or chief technology officer (CTO).
On an average, about four follow-up contacts were made with each firm.
Altogether, 36 unusable second-respondent questionnaires were returned,
resulting in 62% response rate in the follow-up sampling.
The median
software firm in the sample had been in business for the previous 15
years, employed 35 full-time employees, grossed $3 million in sales
annually, introduced about one product each year, and had been using
its current software development approach for the past six years (cf.
Nidumolu and Knotts, 1998, pp.112-113).
Validity: Results from exploratory factor analysis
using varimax rotation were pooled together to test construct validity
for customizability. The analysis showed that all the customizability
items loaded on one factor (Table B1, p118). Reliability assessment,
using the Cronbach alpha coefficient, measures the internal consistency
of the scale items. In this study, the reliability for customizability
was 0.88 (Table B4, p. 120). Basic statistics (Table 1, p. 113) suggested
that the sample had wide variation in organizational characteristics,
and therefore no systematic bias was indicated. External validity was
enhanced in addition to a high response rate of 58%.
In addition, there were eleven parameters to be estimated in the research model
(Figure 1, p.115). Given a rule of thumb of sample size to number of
parameter ratio of at least 5:1, the study’s ratio, 5.3, exceeded the
minimum. Consequently, statistical conclusion validity was verified.
Alpha was set at 0.05 and the power at 0.8, according to convention
(cf. Nidumolu and Knotts, 1998, pp.132-133).
Scores: Overall measure means and standard
deviations are provided in Table B4. The customizability construct had
a mean of 3.7 and standard deviation of 0.76 (cf. Nidumolu and Knotts,
1998, pp.136).
Results showed
that customizability does have a significant influence on process predictability
and flexibility, and therefore on perceived competitive performance.
Customizability had a total standardized effect of 0.35 on perceived
competitive performance, explaining over 12% of the latter’s variation.
Sources:
Nidumolu, Sarma and Gary W. Knotts. (1998) “The Effect of Customizability
and Reusability on Perceived Process and Competitive Performance of
Software Firms.” MIS Quarterly, 4(3), pp. 105-136
Other Evidence: N/A
Other Sources: N/A
References: N/A