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4.3.2 Allocation Scenarios

Participants will be shown the allocation scenarios twice in the experiment. First on the eye tracker, and then on the self-report. As indicated, the hypotheses will be assessed by two instruments (eye tracker, self-report). On the eye tracker, partici- pants indicated their selection/preference by looking at an asset or portfolio for a proportionately longer amount of time. Participants indicated their selection on the self-report with a tick in the box, as in Tables 4.2 and 4.3. Table 4.2 represents the asset allocation scenario and Table 4.3 represents the portfolio allocation scenario. The left boxes in the allocation diagrams represent the promotion scenarios and the right diagrams represent prevention situations. The situations were not labelled to prevent association with promotion and prevention, and appeared in random order, with some participants seeing the promotion and prevention situations on the left and right respectively, and for some the order was reversed. This is to ensure that the orientations of the allocation scenarios do not affect the results.

To prevent participants from inferring the hypotheses of the experiment, they were asked to write a short essay about how their day went.[1] The question was kept as brief as possible, to ensure that it does not influence the allocation scenario that follows. In a previous study, participants were asked to look at visual illusions instead (Shavit et al. 2010). However, this may not be sufficiently distracting, and the essays written may provide further insight into one's regulatory foci.

In previous research (Zhou and Pham 2004), participants were allowed to dis- tribute the funds they received between the assets as they wished, by indicating how much they would like to allocate into each asset, and how much they prefer each asset, on a scale. However, in this experiment, a scale for participants to indicate their preferences was not provided. Displaying a scale on the eye tracker would result in too many AOIs, which would impair the identification of the most pre- ferred situation on the eye tracker. The eye tracker is a measure for the association between chronic regulatory focus and the allocation scenarios, and thus it is imperative that the results from this measure are unbiased. With multiple AOIs, spurious results may occur, as participants would have far too many areas on the screen to focus on. To overcome this issue, the allocation situations are phrased such that participants would indicate where they would like to place more of the funds they receive.

An AOI was drawn around each of the assets and portfolios. The time partici- pants spend looking at the various AOIs was measured, with the time spent blinking or observing elements that are irrelevant, such as looking at the keyboard or mouse, excluded. The proportion of time spent by a particular participant on the AOI, indicated the selection. For example, if a person spends proportionately more time on the promotion AOI than compared to the prevention AOI, a promotion selection is assumed.

Stocks are associated with promotion, and mutual funds are identified with

prevention (Zhou and Pham 2004). It is not yet known whether chronic regulatory focus affects portfolio allocation, and it is hypothesised that promotion-focused individuals prefer portfolios that may increase, but possibly also decrease in value over time, and prevention-focused individuals prefer those which maintain their value over time, accounting for inflation. This is based on concepts drawn from existing research (Roese et al. 1999; Scholer et al. 2010; Zhou and Pham 2004).

In the allocation scenarios, the means by which the funds are obtained are left unspecified. This phrasing is based on research conducted by Zhou and Pham (2004). The most neutral phrasing for the allocation scenarios is preferred, lest the means by which the funds are obtained affects how the participants allocate the latter. In the scenarios, $6000 is the amount participants have been allocated. This Table 4.2 Asset allocation situation

Table 4.3 Portfolio allocation situation

may be of different value to participants from varying backgrounds, as $6000 may be important to someone earning $10,000 a year, but irrelevant to someone earning

$200,000 a year. To mitigate such effects, a wide variety of participants were drawn upon. Moreover, in the study conducted by Zhou and Pham (2004), a value of

$2000 was assigned for the asset allocation scenarios, with no unusual results.

Zhou and Pham (2004) also used an inheritance scenario, that did not appear to bias the decisions of participants. This is possibly due to limited information given about the source of money, apart from it being 'inherited', and that the primary scope of the text was the allocation situations, rather than the source of funds. However, there exists conflicting research on how inherited funds are treated. It is known that wealth that results from windfalls is rarely saved (Imbens et al. 2001; Zagorsky 2013) and that inheritance tends to increase the possibility of retirement (Brown et al. 2010). On the other hand, studies also state that keeping or investing money appears to be the most common outcome with regard to inheritances (Finch and Mason 2000), perhaps because inherited money is viewed to be 'special' and should be treated differently from other money (Rowlingson and McKay 2005). Given the mixed findings regarding inherited funds and to minimise any bias in how participants allocated the funds received, a very brief and neutral scenario (non-inheritance) was used. Selection of Assets and Portfolios

Asset and portfolio allocation scenarios have been used instead of the asset and account allocation scenarios in previous research (Zhou and Pham 2004). Asset allocation is representative of some of the investment decisions that con- sumers tend to make, and the assets selected are known to be sensitive to different regulatory systems (Zhou and Pham 2004). Portfolio allocation, is more directly reflective of the regulatory focus concept of 'promotion being interested in gaining additions, and prevention concerned with preventing subtractions' (Roese et al. 1999), than when compared to account allocation scenarios in previous research (Zhou and Pham 2004). Portfolios represent a greater portion of the financial allocation decisions undertaken by consumers, as indicated in Sect. 3.1. Portfolio allocation thus acts as a complement to the asset allocation scenarios, to reflect more of the financial choices consumers make.

The relationship between portfolio allocation scenarios and one's chronic reg- ulatory focus has not been empirically tested. Thus, measures were undertaken to make sure that they would yield accurate results. A semi-structured interview was conducted, with a chronic promotion-focused person, who selected both the pro- motion assets and portfolios. The portfolio allocation scenarios were then reviewed by academics familiar with the relevant theories. A pilot study was also conducted, in which 15 participants were asked to write briefly about what they felt with regard to the portfolio allocation scenarios. Participants indicated that both scenarios should provide the same amount of information and be about the same length. The portfolio allocation scenarios were then made more concise. Participants stated that this made the scenarios easier to comprehend. The following section outlines the statistical methods used to analyse the data collected from the eye tracker and self-report.

4.3.3 Statistical Analysis

For this book, the data collected is in terms of categorical variables, such as the participants' regulatory focus and eye tracker selection.[2] The relationship between categorical variables can be explored with cross tabulation, and the Pearson chi-squared test was applied. The chi-squared test investigates whether there exists a significant association between two categorical variables, but does not indicate the strength of association (Field 2009). To gain insight into the strength and direction of effect for the particular variables, and to control for other variables, a simple logit model is suitable. The participants' asset and portfolio selections (eye tracker, self-report) were used as the dependent variables, in each individual logit model. The validity of the hypotheses was be explored, followed by further analyses. The process and relevant results will be explained in the following chapters.

  • [1] Contained in Appendix
  • [2] If promotion-focused participants spent proportionately more time on the promotion assets or portfolios, it will lead to the conclusion that they have selected promotion-based assets or port- folios, with the same going for prevention-focused participants
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