Research instrument design
The research instrument used consists of a self-reported survey questionnaire to collect the required data and to test the established hypotheses. The research instrument was developed by applying the best practices and good design principles as follow:
A cover letter was used to introduce the study and its purposes were clearly stated.
The questions were grouped into sections on the basis of their relevance and relationship.
Simple instructions were provided at the beginning of the questionnaire and at each section.
The questions were free from subjective tones in order to prevent bias.
The questions were applicable and answerable by most participants.
On the basis of the research purposes, this study can be divided into three sections. Therefore the questionnaire consisted of four sections: A) Contextual Factors; B) Knowledge sharing types; C) KMS and innovation and D) participant background.
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The participant background section was added as a fourth section in order to provide a descriptive analysis of the survey respondents. This section contained demographic information such as participants’ age, gender, tenure, education and department. Given that this section was included for primarily for informative purpose, the related questions were located at the end of the research instrument. This allowed the researcher to begin the questionnaire with items that were the primary focus of the research.
Research instrument translation
The constructs that composed the research instrument were originally developed in English.
Applying the same procedures as Song, Kim and Kolb (2009), translation procedures were conducted according to these criteria: (1) clarity, (2) common language, (3) cultural adequacy, and (4) contextual understanding to ensure that the items were applicable to the Taiwanese nonprofit organization. Furthermore, the final version was reviewed by two bilingual professionals including the researcher’s thesis advisor, and an experienced professional working in a Taiwanese nonprofit organization for more than 20 years in order to establish the content and face validity of the final survey instrument.
Research instrument validity and reliability
Using SPSS19.0, reliability analysis was carried out on the basis of Bartee, Grandjean and Bieber (2004) theory based questionnaire as Cronbach’s alpha coefficient and Cronbach’s alpha item if deleted. In addition corrected item total correlation was also taken into account in examining the internal consistency of the research instrument. Finally, the research instrument construct validity was assessed through factor analysis on the basis of guidelines provided by Hair et al. (2006). See Table3.1.
Using Smart PLS, reliability and validity analyses included average variance extracted, composite reliability, loadings, and Cronbach’s alpha. Content validity was established by adopting measurements that have already been used and validated in relevant research. The operational measures of each construct are presented in (Table 3.2, p. 58) and discussed as follow:
56 Information Technology
Information technology survey items were adopted from Rhodes et al.’s (2008) study which analyzed organizational context factors on knowledge transfer and organization performance.
The Cronbach alpha for the overall five items in the scale was .92.
Top Management Support
Top management questionnaire was applied to measure the participants’ perceptions of support from upper management. The items for this scale were adopted from Kang, Kim, and Chang’s (2008) research which investigated the effect of knowledge sharing on work performance. This scale is composed of three items and the overall Cronbach alpha was .74.
Collaborative Culture
This scale was aimed to measure the general level of collaboration among employees by using the three items developed by Hurley and Hunt (1998). The Cronbach alpha for this measure was .72.
Organization Structure
Organization structure was assessed by using the four items drawn from Kang, Kim and Chang’s (2008) study which analyzed the influence of organizational dimension factors, individual dimension factors, and characteristics of knowledge dimension on knowledge sharing. It contained four items and the Cronbach alpha was .90.
Tacit Knowledge Sharing
Tacit knowledge sharing was measured by four items drawn from Lin’s (2007) study which analyzed the antecedents and mediators of tacit knowledge sharing. The author developed the scale based on previous research by Bock and Kim (2002) and Daft (2001). The Cronbach alpha for this construct was .88.
57 Explicit Knowledge Sharing
Explicit knowledge sharing scale items were drawn from Holste’s (2003) doctoral dissertation which examined the effect of trust on intra-organizational knowledge sharing and use. The cronbach alpha for his study was .90.
Innovation
The five items in innovation questionnaire were drawn from Hurley and Hult (1998)’s study which examined organizational characteristics impact on innovation. The Cronbach alpha of the questions items developed was .82.
KMS
KMS scale items were drawn from Shih and Morisson (2009) KMS effective knowledge service questionnaire in Morisson’s (2009) master thesis. This measure contained 11 items and the Cronbach’s alpha for the study was .86.
Table 3.1
Hair et al. (2006) guidelines for factor loading cutoff points based on sample size.
Sample Size needed for significance Factor Loading
350 .30
250 .35
200 .40
150 .45
120 .50
100 .55
85 .60
70 .65
60 .70
50 .75
58 Table 3.2
Content validity- Previous studies’ results for internal consistency reliability tests
Authors Constructs Items
(39)
Cronbach’s Alpha
Rhodes et al. (2008) Information Technology 5 .92
Kang et al. (2008)
The targeted organization for this research was a nonprofit organization that had implemented KM initiatives. Data collection was carried out in various stages. In the first stage, the researcher sent a letter and a sample of the survey questionnaire to the targeted nonprofit organization explaining the purpose of the study and requesting permission for distributing the questionnaire. Survey questionnaires were used as a method for gathering the data because they are considered efficient data collection method. In addition, survey methodology was used to collect the data for testing the research hypotheses because it enhances the generalizability of the results (Dooley, 2001). Convenience sampling was used for data collection in order to retrieve a larger number of completed responses quickly and efficiently.