The questionnaire used in this study can be found in Table 1. Attempts to use existing measurement related to each construct were taken, however measures of some constructs especially those of the brand antecedents were specifically developed for the study. A cautious approach was taken in the measurement of these brand evaluative responses, so that specific constructs explaining such responses that are relevant to the context of share investments, rather than product purchase decisions, can be identified. Although specifically developed, the measures of RISK, RTN and TRS have been mapped to the measures used in behavioural finance literature including Bryne, Delgado-Ballester and Munuera-Aleman, Ganzach, Ellis, Pazy and Ricci-siag and Nilsson. Similarly, the measures of FAM construct were developed based on ideas proposed by Aspara and Tikkanen. 7-point Likert scale items were used to measure these exogenous constructs. On the other hand, measures of endogenous variables (INT_INV and AT_BR) were based on existing measures used in earlier studies in related fields (Karson and Fisher, 2005; MacKenzie, Lutz and Belch, 1986). To be consistent with the measures of exogenous variables, both 7-point Likert scale items and 7-bipolar points semantic differential items were used to represent the endogenous variables. Note however that the questions directed at the construct of INT_INV were adapted from the questions commonly used in product-purchase situation to suit the investing context of the present study. All of the measures for exogenous and endogenous variables have been adequately piloted and found to be reliable and unambiguous.
Data from the 136 responses were first refined. In doing so, an exploratory factor analysis was run on all original measures before the model with valid measures was finalized for hypothesis testing. This analysis has resulted in three original indicators being dropped. These were RISK2, RTN4 and TRS1. The final model with respective valid indicators is given in Figure 3. Data analysis was based on partial least squares (PLS) path modeling to test hypotheses included in the research model. This method was chosen due to normality assumptions of the data distribution have not been met and small sample size of 136 responses. The specific PLS tool used in the present study is a freeware application, SmartPLS, developed by Ringle, Wende and Will.

Table 1: Measures of Latent Constructs

Perceived Risk (RISK)
RISK1 – It is a risky decision to invest in WL.
RISK2 – I am sure that WL is a right investment choice.b
RISK3 – WL has uncertain future.
RISK4 – I better invest my fund somewhere else other than in WL.
RISK5 – I think investing in WL is highly risky.
Perceived Returns (RTN)
RTN1 – WL is financially sound.
RTN2 – Investing in WL seems to be able to generate me high returns.
RTN3 – I believe WL will perform satisfactorily in the future.
RTN4 – WL has sufficient resource to grow in the future.
RTN5 – I think investing WL is highly rewarding.
Trust (TRS)
TRS1 – WL is unreliable.b
TRS2 – I can rely on the promises made by WL.
TRS3 – WL management is competent to run its business.
TRS4 – I believe that WL will not hide important information from its investors’ knowledge.
TRS5 – WL has reliable members of board of directors.
TRS6 – In my opinion, WL is trustworthy.
Brand Familiarity (FAM)
FAM1 – I am very familiar with the company’s name.
FAM2 – I know a lot about the company’s main nature of business.
FAM3 – The company is highly recognised.
FAM4 – I always hear the company’s name mentioned in the media
FAM5 – I often see the company’s advertisements in the media.
FAM6 – I know that the company does business in Australia.
FAM7 – I know that the company is listed on the Australian Securities Exchange.
FAM8 – When I hear the company’s name, I immediately recall a particular product.
Attitudes towards Brand (AT_BR)c
AT_BR1 – Unfavourable О Favourable
AT_BR2 – Bad О Good
AT_BR3 – Negative О Positive
AT_BR4 – Weak О Strong
Intention to Invest (INT_INV)
If I actually had the money to investd;
INT_INV1 – the likelihood of me investing in WL is…
INT_INV2 – the probability that I would buy WL’s share is…
INT_INV3 – my willingness to buy WL’s share is…
If I actually thought of investing;
INT_INV4 – WL is definitely one of my choices.
INT_INV5 – I would refer WL’s shares to others.
INT_INV6 – I would talk positively about WL to others.


Figure 3: Research Model with Valid Indicators