Data CollectionThis chapter delves in to the data collection and screening procedures.
It is presented in 4 sections: section 6.1 elaborates the development of the constructs in the questionnaire and the procedures for data collection. Section 6.
2 discusses demographic features of the respondents. Section 6.3 and 6.4 elaborate the procedures used for measuring the validity and reliability of the factor constructs from the collected data set. The Questionnaire and Data CollectionThe questionnaire used for this study was made of three sections, containing 45 questions, presented as Appendix C. The questions were derived from three previous studies done by Bateman (2000), Lillrank and Kano (1989) and Doolen et al. (2003). Based on questionnaire developed by Bateman (2000) to measure the implementation of the four building block, 16 questions were adopted.
Based on questionnaire developed Lillrank and Kano (1989) to evaluate the shop floor management tools, 12 questions concerning the implementation of QCCs and Teians were adopted. The balance 17 were derived from the questions developed by Doolen et al. (2003) to measure the improvement outcomes. The constructs of the questionnaire and research domainsA questionnaire construct is an attribute or characteristic inferred from research (Hayes, 2008). Keeping in mind the research objectives, the constructs (or scales) in the questionnaire for this study was derived from the literature pertaining to: Lean Production shop floor management, continuous improvement and improvement outcomes (as discussed in Chapter 2 and 3).
Forza (2002) and Hensley (1999), opined that the constructs in production management are complex and have multiple facets. Keeping in mind this observation, multi-items constructs were used. Apart from this, suggestions made by Oppenheim (1992) and Flynn (1990) were also followed to use the pre-existing and tested constructs from past empirical studies due to two specific reasons: (1) to ensure their content validity; and (2) the objective of this study was to test the causal relationships between the application of shop floor management tools and the performance of Kaizen. Thus, the complexity of the construct development process and validation was reduced to a minimum (Prajogo, 2002). The development of the constructs, included in the hypothesised model, was based on the three domains described in Figure 6.1. Figure 6.
1 Domains of literature used as sources for questionnaire constructs Structure of questionnaireThe questionnaire, used for this study, constituted four sections and 45 questions (Appendix C). The first section declared the objectives of the questionnaire, assurance of confidentiality of the responses, brief instructions on how to complete the questionnaire and information depicting respondent’s profile, which included educational qualifications, job title in the organisation, number of years working in the organisation, number of years of participation in improvement activities and group improvement position. The second section of constructs was based on Lillrank and Kano (1989) to evaluate the implementation of QCCs and Teians. The third section was made of constructs based on Bateman (2000) to measure the implementation of the four building block shop floor management tools and finally, section four was derived from Doolen et al. (2003) to measure the improvement outcomes.
Questionnaire scalingThe production management research encompasses many issues and concepts which are not directly observable (Hensley, 1999; Karlsson, 2009). In order to capture, measure, and translate these issues and concepts in a more methodical and formalised way (Miller and Salkind, 2002; Corbetta, 2003), taking help of the technique of scaling commonly used (Flynn et al., 1990; Saunders et al., 2007).
Corbetta (2003, p164-165) articulated that scaling is “a set of procedures drawn up by social research to measure human beings and society”; To be precise, each scale consists of a set of items, and each item measures a single component (i.e., statement, question, behaviour, test, response, attribute).
