Field Study Method

Quantitative techniques were used to collect and analyse data in this study using a cross- sectional survey design. Quantitative research adheres to the post-positivist principles adopted by the present thesis, because it revolves around testing and confirming hypotheses formed on the basis of existing theory (Neuman, 2011). With the post-positivist paradigm emphasis on expansion of the scope of a theory and reduction of specific theories into more general theories (Hunt, 1991), the employment of a survey design is the technique aligned with the principles of this approach. After establishing the underlying causal mechanisms of CPBI through experimentation, survey studies could be applied to further delineate the application and generalisability of the theory in the real world (Hoyle et al., 2002; Mitchell & Jolley, 2013). Due to the underlying limitation of the field study, it was not possible to measure the pre-CPBI and test for its effect on CPPI and post-CPBI. More details are provided below.

5.2.1 Product Category, Brand Names and Design

Ideally, and following previous studies, the mobile phone category and brand names of Apple, Samsung, Nokia and Motorola were targeted for the field study. During thesis data collection and initial thesis writing activities (September 2013 to March 2014) none of the above mobile phone brands introduced a new mobile phone. However, both Apple and Nokia companies introduced a new product in to the tablet market in late 2013. On 22 October 2013, Apple

announced the release of the iPad Air and within a month, on 22 November 2013 Nokia launched its new tablet named Nokia Lumia 2520.

The tablet category was deemed an appropriate product category for the field study because (a) the two categories (i.e., mobile phone and tablet) are tied together in terms of usage and user profiles such that the boundaries among a smart mobile phone, a tablet and a “phablet” (a portmanteau of the words phone and tablet - is a class of mobile device designed to combine the functions of a smartphone and tablet; Wikipedia, n.d.) are becoming increasingly blurred; (b) most of the mobile phone brands, especially the selected brand names of Apple, Samsung, Nokia and Motorola have been active in both mobile phone and tablet markets with several well-established products available to consumers; and (c) similar to the mobile phone category, the tablet category offers variation in CPBI.

It should be mentioned that the researcher was not able to measure pre-CPBI included in the pretest–posttest design of the laboratory study. The researcher (similar to any other consumer in the market) was informed about the introduction of iPad Air and Nokia Lumia 2520 tablets after their companies’ official announcement. The moment an innovation is introduced to the market, the pre-CPBI would effectively change to post evaluation of CPBI. This was also the case for any other previously launched innovations by these brands. The only way for a full replication of the proposed model was to perform a pretest–posttest field study in cooperation with an existing mobile phone company such as Samsung. This approach while potentially fruitful, would be very time consuming, expensive, probably unachievable and beyond the thesis scope. Thus, in this study the focus was on post-CPBI evaluations of Apple and Nokia in the tablet market after launching iPad Air and Lumia 2520. Specifically, the field study re-examined four out of six proposed relationships, excluding the effects of pre-CPBI on CPPI (Hypothesis 2) and pre-CPBI on post- CPBI (Hypothesis 3). List of field study hypotheses are provided below.

Hypothesis 1: Perceived technological newness positively impacts consumer perceived product innovativeness.

Hypothesis 4: Consumer perceived product innovativeness positively impacts consumer perceived brand innovativeness.

Hypothesis 5: Consumer perceived brand innovativeness positively impacts attitudes toward the brand.

Hypothesis 6: Consumer perceived brand innovativeness positively impacts consumer purchase intention.

5.2.2 Participants

A total of 420 American consumers varying in sex and age participated in this study. Sample characteristics are detailed in Section 5.3.1 Sample Characteristics. The participants were

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generated and randomly assigned to one of the two surveys (Apple iPad Air vs. Nokia Lumia 2520) in cooperation with a professional marketing research agency (Qualtrics). Similar to laboratory model testing study, the sample size has been estimated to ensure the statistical assumptions of SEM (minimum n = 200) are met (Bentler & Chou, 1987).

5.2.3 Data Collection Procedures and Instrumentation

Data were collected in early 2014. Participants were randomly assigned to one of the two surveys using Qualtrics online consumer panel facilities. Two versions of online questionnaire were developed. Each questionnaire contained five sections (see Appendix D for the sample questionnaire) and each section appeared in a separate page. A schematic representation of the instrumentation is shown in Figure 5.1. In brief, sections one, two and five of the questionnaire were constant across the two survey instruments. The third section measured CPPI for the target innovation (Apple iPad Air and Nokia Lumia 2520 tablet) and varied across the two versions of the questionnaire. The fourth section measured the post-CPBI for Apple and Nokia in the tablet market and again varied across the two versions of the questionnaire15. The order of sections three and four were counter-balanced within each version of the questionnaire.

First, respondents read online materials containing general instructions and a brief cover story explaining that the research was aimed at exploring their perceptions of different brands and products in the tablet market. In section one, participants were required to rate scale items assessing the brand familiarity of the target brand (a covariate). Section two consisted of age and gender quotas requested by the researcher. To ease the process of screening out those respondents who did not meet the quota requirements, these two demographic questions were moved to the beginning of the questionnaire. Next, the product innovation picture (which was adopted from its company website) was shown to the respondents, followed by scales measuring technological newness, CPPI and product innovation – brand fit. In section four, the brand logo of the target brand was printed and respondents were required to rate the post-CPBI of the target brand (i.e., Nokia Lumia 2520), brand attitude and purchase intention. Finally, section five asked for some demographics, participants’ previous purchase experience of the target tablet brand, participants’ current tablet brand and one open-ended question for any comments from respondents. Participants then saw the “Thank You” page. Similar to the procedures detailed for laboratory model testing study, the questionnaire included a few IMC items to detect satisficing respondents (see also Section 4.2.3.1

15 _{Similar to the procedures explained in Chapter 4, to ensure the understandability and readability the questionnaire,}

it was first pilot tested on 20 students at UQ Business School. Results supported readability of the questionnaire as all questions were attempted by the respondents with no missing data. In addition, respondents were interviewed about the clarity of the structure and overall understandability of the instrument. Based on the results it was concluded that no question functioned oddly and the structure of the survey questionnaire was perceived clearly.

Detecting satisficing respondents for more details). Respondents who failed to fill out IMC questions correctly were automatically screened out of the study. See Appendix D for the sample questionnaire.

Participant consent and information form

Section 1: Brand familiarity covariate measures for the target brand and the target new product

Section 2: Gender and age questions

Section 3: Target tablet innovation followed by scales measured technological newness, CPPI and product innovation-brand fit

Section 4: Target tablet brand followed by scales measured CPBI, brand attitude and purchase intention

Section 5: Demographics, previous purchase experience and open-ended questions for any comments

Figure 5.1 Summary of design and instrumentation for the field study

5.2.4 Measures and Measurement

The laboratory model testing measures were used in the present field study. See Appendix D for the sample questionnaire and scale items of the field study. See also Appendix E for a glossary of the measures used in this thesis.

5.2.5 Model Estimation and Evaluation

The approaches used in the laboratory CPBI model testing study were adopted for the field CPBI model testing study. Anderson and Gerbing’s (1988) two step approach was utilised to estimate the CPBI processing model using AMOS 21. Multiple Group Confirmatory Factor Analysis (MGCFA) was also used to test for the CPBI construct validity across Australian and American consumers. Fit indices and cut-off values included were Chi-square (χ2, p > 0.05), root

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mean square error of approximation (RMSEA ≤ 0.08), standardised root mean-square (SRMS ≤ 0.08), Tucker-Lewis index (TLI ≥ 0.95) and comparative fit index (CFI ≥ 0.95). Factor loadings (λ) above 0.5 and absolute standardised residual covariance values less than 2.58 were deemed as acceptable. Standardised regression weights (β) less than 0.2 are considered as weak, between 0.2– 0.3 mild, between 0.3–0.5 moderately strong, between 0.5–0.8 strong, and more than 0.8 are considered extremely strong. To compare fit of nested models the chi-square difference test exhibiting a probability < 0.05 was used.