Reliability and validity of speed of upgrade (SOU) and future intent to quickly upgrade (FIU)

The reliability of the SOU and FIU measures is shown in Table 4.32. The disposal consideration scores for SOU and FIU both exhibit good reliability, with CA scores above the acceptable level of 0.7 (Churchill, 1979, de Vaus, 1995).

Table 4.34: Reliability of SOU and FIU

Construct Number of

To assess the validity of SOU and FIU measures, the internal consistency, AVE and correlation matrix were examined, with the results shown in Table 4.34.

Table 4.35: Internal consistency, square roots of AVE and correlation matrix and model fit – SOU and FIU

182

Construct AVE

1 2

SOU 0.85

FIU 0.33 0.81

The initial model internal consistency testing presented in Table 4.35 shows no discriminant validity issues.

Table 4.36: Goodness-of-fit analysis – SOU and FIU

Goodness-of-fit measure

Result Goodness-of-fit measure Result

Model Fit Model comparison

p-value 0.000 TLI 0.960

Cmin/df 4.898 NFI 0.974

RMSEA 0.098 CFI 0.979

As Table 4.36 reveals, the model fit testing shows an acceptable level of absolute and incremental model fits and comparisons.

183 Figure 4.9 Measurement model – SOU and FIU

Due to the acceptable levels of discriminant validity and goodness-of-fit presented in this initial model (Figure 4.9), no alterations were made.

184 4.4 Nomological validity

Validity evidence based on nomological validity is a form of construct validity.

Nomological validity is the degree to which a construct behaves as it should within a system of related constructs (the nomological network) (Lui, Li and Zhu, 2012). In the present research, the evaluation of nomological validity was undertaken via the correlation coefficients. Theoretically, the hypothesised relationships should be supported by the analysis of the empirical data that informs development of a theoretical framework underpinning the research models (Peter and Churchill, 1986).

In this thesis, nomological validity was ensured through the solid theoretical framework developed and outlined in Chapter 2 which enabled the

identification of the relationships between the latent variables. Overall, the data appears to support the expected magnitude and significance of the correlations among the constructs and dimensions, thereby lending support to the concurrent validity.

To demonstrate this, Table 4.37 presents the correlation coefficients for both the initial constructs analysed in this chapter. Following the adaptations made to the measurement model, Table 4.37 presents the correlation coefficients for the constructs revised to meet reliability and validity issues.

185 Table 4.37 Final descriptive scale correlation coefficients

186 4.5 Inter-construct correlation

All constructs exhibited an AVE of above 0.50, which is considered indicative of convergent validity. Furthermore, the AVE for each of the measures has to be greater than the shared variance with any other of the constructs to

suggest discriminant validity (Fornell and Larcker, 1981). Following the

adaptations made to the measurement model, all indicated sufficient construct validity.

In summary, there is support for the assumption of convergent validity and the assessment carried out of the constructs and component observed variables also indicates discriminant validity. As such, they are retained in the

presented format for analysis.

4.6 Demographics

This study collected the following characteristics of the respondents: age, sex, cultural background, marital status, number of dependants, household

income, education, employment, occupation and residential location. Table 3.1 in Chapter 3 presents the breakdown of the sample demographic

characteristics, with 56% of those people surveyed being Australian nationals aged over 45, well-educated professionals living in metropolitan areas.

187 4.7 Chapter summary

This chapter has explained how the constructs discussed in Chapter 2 were operationalised and tested for reliability and validity. The majority of the measurement scale items were drawn from the scales developed and published by academics in the relevant subject fields. Limited existing measurement models were available for VA and DO. As such, the

development of measurement scale items was drawn from the relevant VA and disposal literature. Some of the existing scales were adapted to fit the context of rapid electronic product upgrading; however, the original meaning of the measurement item was not compromised.

The presented measurement scales, both existing and new, were evaluated on the basis of empirical data via CA, factor analysis and correlation analysis.

The results of this chapter demonstrate that, overall, the constructs display acceptable levels of reliability and validity in terms of their content, convergent validity and discriminant validity. Chapter 5 presents the assessment of the constructs in relation to the hypothesised relationships proposed in the conceptual model, as well as the research results and a discussion of the findings.

188 CHAPTER 5

Results and discussion

5.1 Introduction

In the previous chapter, the construct operationalisation was described and the testing revealed the reliability and validity of the constructs used in the conceptual model. Chapter 5 presents the results of the regression analysis undertaken to test the hypotheses listed below.

A consumer’s predisposition to rapidly upgrade (PPRU)

H1: A consumer’s psychological predisposition to rapidly upgrade (PPRU) has a significant and positive impact on speed of upgrade (SOU)

H6: A consumer’s psychological predisposition to rapidly upgrade (PPRU) has significant impact on vicarious adoption (VA)

H7: A consumer’s psychological predisposition to rapidly upgrade (PPRU) has significant impact on vicarious innovativeness (VI)

H8: A consumer’s psychological predisposition to rapidly upgrade (PPRU) has significant impact on disposal orientation (DO)

Product factors (PF)

H2: the product factors (PF) have a significant and positive impact on speed of upgrade (SOU)

H9: the product factors (PF) have a significant impact on disposal orientation (DO)

H11: the product factors (PF) have a significant impact vicarious adoption (VA)

189 Vicarious Innovativeness (VI)

H3: Vicarious innovativeness (VI) has a significant impact on speed of upgrade (SOU)

H10: Vicarious innovativeness (VI) has significant impact on vicarious adoption (VA)

H13: Vicarious innovativeness (VI) has a significant impact on future intent to quickly upgrade (FIU)

Vicarious adoption

H4: Vicarious adoption (VA) has a significant impact on speed of upgrade (SOU)

H14: Vicarious adoption (VA) has a significant impact on future intent to quickly upgrade (FIU)

Disposal orientation (DO)

H5: Disposal orientation (DO) has a significant impact on speed of upgrade (SOU)

H15: Disposal orientation (DO) has a significant impact on future intent to quickly upgrade (FIU)

190 Future intent to quickly upgrade (FIU)

H12: Speed of upgrade (SOU) has a significant impact on future intent to quickly upgrade (FIU)