examining the behavioural intention to save in a …

MALAYSIAN JOURNAL OF CONSUMER AND FAMILY ECONOMICS (2018), VOL. 21

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EXAMINING THE BEHAVIOURAL INTENTION TO SAVE IN A VOLUNTARY RETIREMENT FUND IN MALAYSIA

Radduan Yusof1, Mohamad Fazli Sabri2, Husniyah Abd. Rahim2 and Zuroni Md Jusoh2

Abstract This study utilised the Decomposed Theory of Planned Behaviour (DTPB) to examine the intention to save in voluntary retirement funds in Malaysia. Three hundred and thirty-four (n=334) usable samples were obtained via a purposive multistage cluster sampling technique. The data was analysed to assess the determinants predicted by the DTPB through structural equation modelling using the PLS-SEM. The results revealed that attitude, subjective norms, and perceived behavioural controls have significant effects on a person‟s intention to save in a voluntary retirement fund, albeit to a varying degree. The path analysis indicated perceived behavioural controls as the strongest predictor, followed by attitude and subjective norms. These three constructs explain 58% of the variance in the intention to save in a voluntary fund. When the model in this study further analysed the antecedents of attitude, it found that the relative advantages positively influenced attitude, compatibility had a negative influence, and complexity had no significant value. With regards to subjective norms, both external and internal norms significantly influenced the construct. Finally, both self-efficacy and facilitating conditions had significant effects towards perceived behavioural controls. Predicting a person‟s intention to save in a voluntary retirement fund is an important issue and the findings of this study would have practical implications on policy makers and commercial marketers alike, as it would help to encourage retirement savings through voluntary funds to prevent financial insufficiency in the golden age. Keywords: Voluntary Retirement Fund, Social Security, Decomposed Theory of Planned Behaviours, Retirement

savings

INTRODUCTION Research around the globe has revealed that many people do not save enough during their working life (Pablo Antolin, 2010; Banks & Blundell, 2005). Likewise, this problem is also prevalent in Malaysia (Sabri & Juen, 2014; Samad & Mansor, 2013; Sharma, 2012; Yusuf, 2012). Insufficient pre-retirement planning practices and retirement savings are known to promote major economic problems (Hershey & Henkens, 2014). At an individual level, retirement is a significant life transition and can be a stressful life event if not managed well (Petkoska & Earl, 2009). The 2015 US Retirement Confidence Survey reported that 24% of workers are “not at all confident” about having enough money to live comfortably throughout their retirement years (Ruth Helman, Greenwald, Copeland, & VanDerhei, 2015).

Understanding the determinants related to retirement savings may provide solutions to overcome an individual‟s savings insufficiency. As retirement savings are part of complex financial planning behaviours, it involves a multidimensional model that requires individuals to act (Md Husin & Ab Rahman, 2013) and make decisions on things that they find hard to visualise (Beshears et al., 2013). Making this decision would mean that a person must choose to forego the purchase of other goods and services which provide immediate rewards (Rickwood et al., 2017). As the current pension support system is unable to cope with this problem, it is not viable for governments to continue funding social security and

1 Faculty of Administrative Science & Policy Studies, Universiti Teknologi MARA, Malaysia, [email protected] 2 Department of Resource Management and Consumer Studies, Faculty of Human Ecology, Universiti Putra Malaysia,

[email protected],[email protected], [email protected]

mailto:[email protected]

mailto:[email protected],[email protected]


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pension. Thus, many countries have opted to transfer this responsibility onto the individuals (Teusta, 2016; The World Bank, 2013). Even countries with a healthy and generous pension support system are moving towards promoting the third pillar of social security and encouraging private sectors to provide for retirement (Foster, 2017). Some have even called for retrenchment in the public pension system (Naczyk, 2013). The private retirement system under the Third Pillar of the social security system is now the next progression in pension reforms around the world and the recommended solution for most countries in facing retirement inadequacies including Malaysia. The World Bank and OECD‟s core recommendations for reforming pensions are voluntary pension plans which complement a non-contributory pension and mandatory contributory benefits. It is also a means of raising national savings to reduce fiscal pressure on the public pension system (Antón et al., 2014).

The creation of the third pillar, also referred to as the workers‟ private pensions or workers‟ private savings, often precedes the creation of the mandated second pillar. It offers some coverage to those employed in the informal sector and offers individuals an opportunity to compensate for reduced public spending with their own savings (Adascalitei & Domonkos, 2015; Holzman, 2013). In Malaysia, the third pillar includes voluntary pension-based savings accounts and individual longevity insurance. Both schemes encompass defined contributions as well as defined benefit products (Wuyts, Stinglhamber, Valenduc, & Zachary, 2007). The third pillar has become increasingly important due to increases in individual longevity and an ageing population (Banks & Blundell, 2005; Blundell, Meghir, & Smith, 2002). With the ageing population, countries have adopted various strategies to improve the adequacy of retirement incomes including mandating compulsory savings and counting on employees to up their retirement savings (Feng, 2014). However, while mandating compulsory savings achieved remarkable coverage among employees around the world, voluntary private pension schemes were less attractive to employees (P. Antolin & Whitehouse, 2009; Feng, 2014).

This study contributes to the existing literature by investigating the determinants of an individual‟s intention to save in a voluntary retirement savings and at the same time validating the claim that the DTPB has better explanatory powers than pure TPB. The DTPB is a validated decision-making model that can provide an appropriate framework to understand and predict intention. The DTPB has its origin from the TPB, which in itself is a progression of the Theory of Reason Action (TRA) and both of these theories by Ajzen and Fishbein (2010; 1974; Ajzen & Fishbein, 1977, 1988) were integrated with various other theories such as Rogers‟ (2003) Diffusion of Innovation, Bandura‟s Self-Efficacy (1977) and Triandis‟ Facilitating Condition (1979) characteristics. Decomposing is a term used when the variables of TPB which are attitude, subjective norms and perceived behavioural control are separated into a function of a more specific belief (Taylor & Todd, 1995a, 1997, 1995b). In this study, this model is used to understand the intention to save in a voluntary retirement fund in Malaysia. By decomposing the TPB, the model may provide a better understanding of the construct specified and improve the explanatory power of the model.

LITERATURE REVIEW The determinants of voluntary retirement savings refer to factors that potentially influence intentions to save in private or voluntary retirement funds. The wake of behavioural economist has emphasised the importance of integrating behavioural and psychological factors when understanding financial issues. This has paved the way for studies that have identified factors influencing retirement and planning behaviour (Griffin, Loe, & Hesketh, 2012). The TPB was used as a theoretical model to study finance behaviour and East (1993) was among the first researchers to apply this model in his research. As an overview, behavioural psychology focuses on behaviours and beliefs that move or deter a person into


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action. The central premise is that behaviours are acquired through conditioning via interaction with the environments.

The realm of this research employs the TPB which pertains to the attitude, subjective norms (SN), and perceived behavioural controls (PCB) regarding intention and the behaviour to save in a retirement fund. However, the attitude, SN and PCB need to be decomposed to understand the salient belief behind each of these constructs. In their DTPB, Todd & Taylor (1995) have decomposed the attitudinal, normative and control constructs into specific salient believes. As treating the determinants as a monolithic summation of all the weight as a single factor will not explain the behaviour much, the antecedents are assessed independently with regards to their direct determinants in DTPB (Taylor & Todd, 1995a).

An individual may have different assessments of each of these dimensions and treating „attitude‟ as a monolithic concept may obscure the actual influence of attitude (Taylor & Todd, 1995a). By decomposing beliefs, these relationships should become more explicit, readily understood and thus point to specific factors that may influence behaviour (Rana, Dwivedi, Lal, & Williams, 2015; Taylor & Todd, 1995a). The decomposition of DTPB provides a stable set of beliefs which can be implemented across some settings and overcome the disadvantages of operating in traditional intention models (Mathieson & Mathieson, 1991; Taylor & Todd, 1995a). By decomposing into specific believes, the model becomes managerially relevant by pointing to factors that may influence intention to use, unlike the monolithic factors present in the TPB.

An attitudinal belief means that performing certain behaviours will lead to a particular outcome, weighted by an evaluation of the desirability of that outcome. Understanding the relationship between belief structures and the antecedents of intention requires the decomposition of attitudinal beliefs (Taylor & Todd, 1995a). The cognitive components of belief should not be organised into a single conceptual or cognitive unit. The same was also explained for the decomposition of subjective norms and perceived behavioural control. The DTPB have had many extensions over the years. The differences between each extension in most research are about the dimensions of salient attitudinal, normative and control belief. Most research, however, treats the primary theoretical foundation in the same way. Since the DTPB is an extension of TPB, it is essential that the principle of compatibility in the original model guidelines must be followed. Thus, the measure of intention should be defined with regards to the same target, action, context and time (TACT) elements for specific behaviours (Ajzen, 1991). Attitude and Retirement Savings Attitude has long been considered to be direct and immediate cause of intention and behaviour (Ajzen, 1985, 2001; Ajzen & Fishbein, 1977). Many studies have shown empirical support for the link between attitude and intention, and have proven the significant effect of attitude on behavioural intention (Moons & De Pelsmacker, 2015; Rana et al., 2015; Teo, Zhou, & Noyes, 2016). In the context of individual retirement plan saving intentions, it can be assumed that if an individual is more favourable to a retirement plan, they are more motivated to purchase it than those who are less favourable. Devlin (2012) indicated in his research notes that although there are reasonable levels of commitment involved in reviewing retirement plans on a regular basis, such attitudes are only apparent in a minority of those surveyed. People are far less enthusiastic about the prospect of making financial plans for retirement and are not willing to put in a significant amount of effort.

This shows that while many are committed to the task, actual levels of retirement savings remain far below the levels necessary for a comfortable retirement (Devlin, 2012). A report by Macleod et al. (2012) that explored how attitudes and beliefs affect actual and intended behaviour relating to pension savings found out that attitudes towards pension savings may not be closely associated with different


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pension behaviours. According to them, people increasingly recognise the need to take personal responsibility of financial preparation for retirement. The blame was placed on the pessimism about the economic situation which may affect attitudes. Pension savings do not generate the same satisfaction or motivations as other investments but are a cost without rewards. Many participants likened this to the experience of paying tax (Trenow, Olchawski, Foster, & Heneghan, 2016).

In comparison, investors who have a positive attitude towards retirement planning have a higher propensity to plan (Ameriks, Caplin, & Leahy, 2003; Hanna et al., 2016). Studies in Great Britain in 2012 reported that respondents without any resources for later life were more likely to be struggling financially and were more likely to say that they could not afford to put money aside for retirement. In contrast, the respondents with private pensions felt that they were keeping up with their financial commitments without difficulty and were less likely to say that they could not afford to put away money for retirement (Macleod et al., 2012). Bateman et al. (2014a) explained that in Australia, interests in superannuation are not being transferred to active engagements in retirement savings decision making.

According to Lai and Tan(2009), Malaysian respondents have negative attitudes towards the prospect of retirement as it is a difficult adjustment in their lifestyles. Researchers have also found that Asian people have lower retirement savings compared to people from the United States as they are more likely to get financial support from their children after retirement (Horioka & Watanabe, 1997). Apart from that, some people perceived that they have insufficient income to plan for retirement. Generally, those who are better prepared for their retirement have more positive attitudes towards retirement (Kim, Kwon, & Anderson, 2005). Therefore, this study hypothesises that;

Ha1: Attitude will positively influence saving intentions towards a voluntary retirement fund.

Attitudinal Belief In the DTPB, the dimensions of attitude were divided into antecedents based on the characteristics of innovation from Roger‟s Diffusion of Innovation theory. The critical determinants of adoption for any given products are perceptions of relative advantage, compatibility, and complexity (Todd & Taylor, 1995; Rogers, 1993). The relative advantage refers to the degree to which an innovation provides benefits which supersede those of its precursor (Rogers, 1983). The greater the relative advantage of an innovation, the more rapid its rate of adoption will be. Therefore, relative advantages should be positively related to an innovation‟s rate of adoption (Taylor & Todd, 1995; Rogers, 1983).

In Malaysia, the introduction of the voluntary retirement fund is only in its infancy. The inability of the EPF to support the lifestyle of retirees prompted the Malaysian government to introduce and promote two new programs under the third pillar of social security. This are the 1Malaysia Retirement Saving (1MRS) Scheme in January 2010 and the Private Retirement Scheme (PRS) in 2012 (Samad & Mansor, 2013), which are in support of the 3rd pillar system on top of the existing private insurance type deferred annuities and life insurance schemes. The additional savings in a voluntary retirement fund would enhance the ability of pensioners during the day of retirement, thus providing a relative advantage to those who contribute to the fund.

Complexity represents the degree to which an innovation is perceived to be difficult to understand, learn, operate, or operate (Rogers, 1983). Generally, new ideas that are simpler to understand will be adopted more rapidly than innovations that require the adopter to develop new skills and understandings (Rogers, 1983). Complexity would be expected to be negatively related to attitude. Complexity also exists because of barriers that exist when securing resources to be used for retirement purposes. On the other hand, compatibility is the degree to which the innovation fits with the potential adopter‟s existing values, previous experience and current needs (Rogers, 1983). It is the degree to


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which an innovation is perceived as being consistent with the existing values, experience, and needs of potential adopters. An idea that is not compatible with the common values and norms of a social system will not be adopted as rapidly as an innovation that is compatible (Rogers, 1983). Tornatzkey and Klein (1982) found that an innovation is more likely to be adopted when it is compatible with the value system of the individual. In essence, compatibility should be positively related to attitude. However, since the research subjects do not have any voluntary retirement savings, all items for compatibility in the questionnaire is reverse worded as negative statements. By decomposing attitudinal believes, this study hypothesises that; Ha1a: The Relative advantages of voluntary retirement funds have a positive effect on the attitude

towards saving in a voluntary retirement fund. Ha1b: The compatibility of voluntary retirement funds have a positive effect on the attitude towards

saving in a voluntary retirement fund. Ha1c: The complexity of voluntary retirement funds have a positive effect on the attitude towards saving

in a voluntary retirement fund.

Subjective Norms and Retirement Savings The TPB proposes that subjective norms (SN) which can be defined as the motivation to conform to other people‟s views is an important factor in predicting behaviour. According to the social norm hypothesis, it is predicted that the stronger the social support from friends, family, spouses or social regulation for retirement savings, the more likely an individual will save for his or her retirement (Duflo & Saez, 2002). It is an individual‟s perception about how their significant others think they should or should not conduct behaviours (Ajzen and Fishbein, 1980). If a person sees that those who are more important to them think they should perform a specific behaviour, it is highly likely that they will intend to do so.

On the other hand, it is believed that if their significant others do not agree, their intentions will probably be altered. This means that even if an individual is not in favour of a certain behaviour, he may conduct it regardless under social pressure and influence, or vice-versa (Croy, Gerrans, & Speelman, 2012a). Social forces may also affect retirement savings decisions because they provide a social norm indicating the “right” course of action. Subjective norms can be either injunctive, which refer to social pressure to engage in a behaviour based on the perception of what other people require a person to do, or descriptive norms which refer to social pressure derived from the observed or inferred behaviour of others (Ajzen, 2006).

An individual‟s retirement decisions are also influenced by the early retirement decisions of their spouses (Chou et al., 2014) and peers (Duflo & Saez, 2003). Early parental socialisation and parental direct teaching or encouragement may shape a person‟s attitudes towards considering retirement savings to be important (Van Dalen, Henkens, & Hershey, 2010). An individual who has learnt the importance of savings in childhood can easily be convinced to prioritise retirement savings, through the development of better financial management skills or financial knowledge (Van Dalen et al., 2010). A study has also indicated that the impact of economic socialisation is long lasting and has an influence on economic behaviours in adulthood (Webley & Nyhus, 2006). Thaler (1994) wrote, “The only plausible ways in which people might approximate an optimal saving plan is either by learning from others (such as role models or experts) or by using good rules of thumb”.


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Individuals learn about values and norms related to savings behaviours through the socialisation process. This process might be different, difficult, or even non-existent in low-income households if they did not observe saving behaviours in their families of origin or their peers (Benartzi & Thaler, 2013). Croy et al. (2012a) employing the TPB proved that the subjective norm variable is the most influential predictor of intention in the present Australian superannuation retirement savings. Research in Malaysia by Jamaludin (2012) reported that highly socialized people are likely to invest in their future savings, thus supporting social norms as one of the main factors for retirement planning. Thus, it is posited that:

Ha2: Subjective norms will positively influence saving intentions toward a voluntary retirement fund.

Normative Belief Social norms in the DTPB is divided into interpersonal and external influences (Croy, Gerrans, & Speelman, 2010). Research explaining the salient normative belief construct has many interpretations of its composition. In this study, the internal influence factors in pressure from people who are essential and closest to them that will influence their intention to save such as the family, while external influence is from people whose opinion matters such as friends, colleagues, or financial advisors. Interpersonal influence describes the perceived effects of the opinions and recommendations from essential personalities in the individual‟s life on behavioural intentions (Taylor & Todd, 1995).

It emphasises specific values and needs related to the individuals, which will help to form their expectations, attitudes, and satisfaction levels (Mahlanza, 2015). Internal norms are formed from the views of close family members such as spouse, parents and siblings. These are the people who are important in a person‟s life (Croy, 2010). External norms that affect a person‟s way of thinking are derived from those who are close to a person but not family related. Thus, external norms are the behaviours that are suggested or practised by someone whose opinion is important to a person.

Duflo and Saez (2002) pointed out that peer effects will influence retirement savings decision because many people have not carefully thought about the advantages and disadvantages of particular plans and lack information for making retirement decisions. Belief about social norms may influence an individual‟s decision because of desire to behave similarly to those in their social group. In their experiment, Duflo and Saez (2003) randomly selected participants who were offered cash incentives to attend an information fair about benefits. Those who attended the fair were significantly more likely to enrol in the savings program. More interestingly, the choices of individuals who did not attend the fair were similar to the savings choices of their peers who did attend.

This suggested that although individuals used information from peers when deciding on participation and plan types (Beshears, Choi, Laibson, Madrian, & Milkman, 2015), it did not directly affect the financial attractiveness of saving (Croy et al., 2010; Duflo & Saez, 2003). The same results were demonstrated by Bailey et al. (2004) who showed that both descriptive and injunctive norms have strong effects on retirement saving contribution decisions and social norms have positive direct effects on contribution amounts. Therefore, this study decomposes subjective norms into internal and external influences and hypothesises that,

Ha2a: Internal influence will have a positive effect on the subjective norms towards saving in a voluntary

retirement fund. Ha2b: External influence will have a positive effect on the subjective norms towards saving in a

voluntary retirement fund.


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Perceived Behavioural Control and Retirement Savings The PBC construct is added to overcome the limitations in the TRA model and to apply in context where individuals do not have volitional control to conduct behaviours (Ajzen, 2002). The PBC is an individual‟s perception of the ease or difficulty in conducting certain behaviours. This means that the stronger an individual‟s PBC is, the more likely they are to conduct the behaviour (Ajzen, 2005). The performance of the behaviour is correlated with one‟s confidence in their ability to conduct the behaviour. At the same time, having an increased availability of resources like time, money or opportunities would improve one‟s perceived control and hence increase the possibility of performing behaviours (Ajzen, 1991). Many experimental studies about PBC show that there is a direct and positive link between PBC and behavioural intention (AL Ziadat, 2015; Botetzagias, Dima, & Malesios, 2015; Johnson, 2017; Nelson, 2014).

Studies by Davis & Hustved (2012) have utilized the TPB to investigate the underlying beliefs that affect an individual‟s behaviour when specifically saving for retirement. They concluded that PCB is the most important variable in predicting saving behaviours. Perceived behavioural controls have more strength and participants with higher PBC had their PBC boosted by the experience of successfully saving. Hira, Rock and Liobl (2012) reported that perceived or actual personal controls were not significant in term of ownership of a retirement savings account (IRA/Keogh) but were positively significant in terms of maximizing retirement contribution.

This showed that individuals having higher perceived control tend to save more for retirement. Kimberly pointed out that savings are related to money management strategies (MMB) and strategies to build wealth (WMB), but groups with high PBC need not engage with MMB and WMB because they have enough disposable income to meet financial needs without much effort or emotional stress. A person‟s perceived ability in financial management is shown to be associated with the perceived adequacy of retirement savings (Van Dalen et al., 2010). Hira, Rock, and Liobl (2012) reported that perceived or actual personal control is not significant in terms of the ownership of a retirement savings account (IRA/Keogh), but is positively significant in terms of maximising retirement contribution, which shows that an individual who has higher perceived control tends to save more for retirement. Accordingly, an individual‟s behavioural intentions are motivated by attitude, subjective norms and PBC, therefore the hypothesis that follows are:

Ha3: Perceived Behavioural control will positively influence saving intentions towards voluntary

retirement fund. Control Belief Ajzen (Ajzen, 1985, 1991) explained that to act, a person must have controls such as relevant resources and appropriate environmental opportunities. Ajzen (1991) argues that if behaviours do not have the problem of control, intentions alone are sufficient to predict an individual action. As PBC has an indirect effect on behaviour through behavioural intention, individuals may have positive attitudes towards certain behaviours and perceive that their significant others will support them to act on the behaviours. However, if that individual perceives to have very little or no resources and opportunities to participate in the behaviour, it is unlikely that he or she will have strong intentions to act. The assessment of the necessary resources and opportunities to perform a behaviour successfully depends on the perceived power of each factor to facilitate or inhibit behaviours which are referred as a control beliefs (Conner & Armitage, 1998; Madden, Ellen, & Ajzen, 1992).

Control is defined as internal and external constraining dimensions. External control refers to the environment such as opportunities, dependency on others or barriers. This is akin to the facilitating


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conditions by Triandis which Ajzen and Fishbein used in the development of their theory. On the other hand, internal control relates to self-efficacy or an individual‟s confidence in his or her ability to perform the behaviour to produce a specific outcome such as information, personal deficiencies, skills, abilities, and emotions (Gosselin & Maddux, 2003). It refers to one belief of their capabilities to mobilize motivation, cognitive resources and the course of action needed to meet situational and environmental demands (Bandura, 1977). The PBC antecedents suggested by Taylor & Todd (1995) was developed by adapting Bandura‟s (Bandura, 1977) Self Efficacy Theory and Trandis‟ (1977) Theory of Interpersonal Behaviour about facilitating conditions.

The concept of PBC is similar and is taken from the Bandura‟s (1982) Self-Efficacy Theory. Specifically, in the TPB framework, Ajzen (1991) argues that the perceived behavioural control (PBC) construct is synonymous with self-efficacy. Therefore, the first component pertaining to perceived behavioural control is self-efficacy (Ajzen, 1991) which is defined as being confident of one‟s ability to behave successfully in a situation (Bandura, 1977, 1982). It is also defined as beliefs in one‟s capabilities to mobilise the motivation, cognitive resources and course of action needed to meet a given situational demand (Bandura & Wood, 1989). Individuals are more likely to engage in a particular behaviour if they have control over it and are prevented from performing a behaviour over which they do not have control (Bandura, 1977, 1982) even if the behaviour is supported by positive attitudes or social norms. As described earlier, it is suggested that if intentions are held constant, the increase in PBC are likely to motivate behaviours as PBC has a direct relationship with behaviours.

Behaviour is an individual‟s commitment to perform an action and consists of one or more observable actions performed by the individual (Ajzen & Fishbein, 1977). A person with high self-efficacy will have more effort and persistence when facing obstacles, and if they do not find the behaviour to be easy, they will gain corrective experiences that reinforce their sense of efficacy, thereby eliminating defensive behaviours. Self-efficacy explains that a person‟s behaviour is dependent on a certain outcome. The efficacy outcome is also the conviction that one can successfully execute the behaviour. In other words, although an individual will do something if they know that the behaviour will create an outcome but they will only perform the behaviour if they think they can perform the behaviour. However, expectations alone are not the sole determinant of behaviours. For example, there are many things a person can do successfully but they will not do it if they are lacking the components and capabilities or if they do not have the necessary skills of incentives to do it. The reason for not taking action is doubt or barrier a person faces when performing the behaviour. An individual with high self-efficacy is an individual who is able to cope with this barrier.

The second component of perceived behavioural control is facilitating condition. According to Triandis (Triandis, 1977), facilitating conditions refer to factors that enhance or impede behaviours such as perceived compatibility of the behaviour with the person‟s lifestyle. It is the control which is the individual control belief weighted by the perceived facilitation of the control factor in either inhibiting or facilitating the behaviour. It reflects the perceived difficulty or ease in performing the behaviour and the perceived facilitation acts as an importance weight (Ajzen, 1991). The facilitating conditions (Triandis, 1979) also reflect the availability of resources needed to perform a behaviour. This might include access to time, money and other specialized resources (Shih, Fang, & Shih, 2004).

Ha3a: Self-efficacy will have a positive effect on the perceived behavioural control towards saving in a

voluntary retirement fund. Ha3b: Facilitating conditions will have a positive effect on the perceived behavioural control towards

saving in a voluntary retirement fund.


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Figure 1: Decomposed theory of planned behaviour and hypothesized path

METHODOLOGY

Sampling and Data Collection This study employs a quantitative research technique using the cross-sectional survey approach to determine the characteristics of the population and the regression analysis between the independent and the dependent constructs. The survey questionnaire was made in English, back to back-translated to Bahasa Malaysia and then retranslated to English guided by language experts before being distributed to selected organizations all over peninsula Malaysia in the first quarter of 2018. Prior to the translation process, the questionnaire went through a process to elicit the salient behavioural and outcome evaluations in the items of the questionnaire. Sixty respondents were chosen conveniently from Facebook and 25 answered. The questionnaire was then proofread by academics (6) and professionals (2) who are experts in the area to affirm the strength and language of the questionnaire. The questionnaire was then pilot tested using Google forms to 80 respondents with 39 returns to report the Cronbach Alpha. This was then used to correct and make refinements to the final questionnaire.

The suggested minimum sample size for a PLS-Sem analysis using the G-Power analysis (one tail, effect size=0.3, alpha err prob= 0.05, power (1-B err-prob= 0.85)) is 75 cases or using Chin (2011) 10 times per largest number of paths from independent variables going into the dependent variables is 30 (constructs to attitude). The final questionnaire was sent, and data was collected from all over Peninsular Malaysia using purposive multistage cluster sampling. One thousand two hundred sets of questionnaires were distributed by post to 120 agencies with a public-private sector ratio of 20:80 throughout the 14 states of the Peninsula. The agencies were selected randomly using yellow pages for the private sector and Google search for the public sector. Each envelope sent consisted of 10 English and 5 Bahasa Malaysia questionnaires. The selected agencies were contacted before sending out the questionnaires. The representatives were called again to confirm that the questionnaires had been sent out and another call was made to remind them to return the questionnaires. At every opportunity, the researcher chose to


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meet at random some of the representatives to send and collect the questionnaires. Participation was voluntary but to ensure a high response rate, a Lazada Online shopping draw was offered to each respondent for answering the questionnaire. Out of these, 61 agencies participated and 484 questionnaires were returned ranging from 4 to 15 cases per agency. Upon refinement of the cases, 334 usable sets were used for analysis after the deletion of non-subject respondents (10), already have voluntary savings (52), straight lining unengaged respondents (9), missing value more than 10% or missing all items in single construct (33), items-based z-score outliers (23) and Mahalanobis‟ Distance multivariate outliers (47). The Measurement Items and Scales The final questionnaire contained three sections. The first section collected demographic information, the second collected retirement portfolios and the third part collected information on the constructs of the DTPB model based on Todd and Taylor(1997, 1995b), Azjen (1985, 2002, 2006), Rogers (1983), Bandura (1977), and Triandis(1979). The item measures of attitude, subjective norms, perceived behavioural control, salient normative belief and control belief are adapted from Croy (2012b, 2015) and Mahlanza (2015) through the guidelines of Todd and Taylor (1995). At the same time, items for relative advantages, compatibility and complexity went through a pre-test elicitation process involving 25 participants prior to the pilot test for questionnaire development. This increased the domain specificity towards the Malaysian respondent. To ensure content validity, all the items in the construct were reflective measures.

The participants answered a completed questionnaire with a 5 point Likert scale (1=strongly disagree to 5=strongly agree, with no indicator in between) in the survey to measure the constructs as shown in Appendix 1. Direct items were used for attitude, SN and PCB while the antecedent used the value-expectancy model (A = Σbiei, SN = Σnbjmcj and PBC = Σcbkpf), where the composite scores for the means of each construct were derived by adding up all the items‟ scores and then averaging the sum score. The initial Cronbach‟s Alpha value for each construct are: Intention (.093); Attitude (0.82); Subjective norms (0.89); PCB (0.75); Relative Advantages (0.94); Compatibility (0.89); Complexity (0.73); Internal norms (SIM); External Norms (0.92); Self-Efficacy (0.85); Facilitating Conditions (0.87). All items met the 0.7 reliability (Nunnally, 1978). Although the Cronbach Alpha‟s value met the requirement for construct reliability, some Items were deleted from the analysis due to poor loading, lateral and vertical co linearity issues to fit the requirements in the PLS-SEM measurement model. FINDINGS AND DISCUSSIONS

Respondent Characteristics In terms of respondent demographics as shown in Table 2, the gender of the respondents was almost equally balanced, with the ethnic majority being Malay (78%). Almost 30% of the respondents were working in the public sector while 70% were in the private sector. This amount is close to an accurate representation of the sector division in Malaysia. Most of the respondents were either at the managerial or executive level (65%) whereas 73% had tenures of less than 10 years. The retirement portfolio showed that majority of the respondents heard about the voluntary retirement fund through social media and friends were the largest source of information. In terms of social pressure, friends, colleagues, financial advisors, and parents have at least once advised the respondent to save in a voluntary retirement fund. The majority of the respondent (73%) saved less than 10% of their monthly income with savings account and unit trust being the most trusted savings vehicle. All of these 312 respondents purposively selected for the analysis in this survey did not have any type of voluntary retirement fund.


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Table 1: Demographic Characteristics and Retirement Portfolio (n=334)

Socio demographic characteristic Retirement Portfolio

Variable/ Categories Count % Variable/ Categories Count %

Gender Have info of Private/Voluntary Retirement Saving

Male

Female

172

162

51.5

48.5

Yes

No

210

124

62.9

37.1

Age Monthly income Set aside for retirement

Below 30

31 - 40

41 - 50

Above 50

46.7

36.5

13.2

3.6

46.7

36.5

13.2

3.6

None

1% - 10%

11% - 20%

21% - 30%

more than 30%

missing

83

160

65

12

3

(11)

24.9

47.9

19.5

3.6

.9

3.3

Ethnicity

Malay

Chinese

Indian

Others

263

45

20

6

78.7

13.5

6.0

1.8

Education Level Savings for Retirement (of total respondent)

PMR/ SRP/ LCE or below

SPM/ SPVM, MCE/O-level

STPM/HSC/A-level/ Matric

Certificate/ SKM/MLVK

Diploma

Professional Degree

University Degree

Post Graduate Degree

2

34

10

14

96

24

130

24

6

10.2

3.0

4.2

28.7

7.2

38.9

7.2

Shares

Unit Trust

Saving Account

Fixed Deposit

Bond

Rental Property

Insurance

Other

25

117

188

24

4

37

124

0

7.5

35.0

56.3

7.2

1.2

11.1

37.1

Monthly Income Pension Plan

Poor (Below RM950)

Income Group 1 (B40:RM951-3860)

Income Group 2(M40:RM3861-8319)

Income Group 3 (T20:Above RM8320)

Missing

Income category from Bajet 2018

-

209

93

16

(16)

0

62.6

27.8

4.8

EPF

Public Pension

269

65

80.5

19.4


89

Working Sector

Have heard information of Voluntary saving from: (of total respondent)

Government

Statutory body

Private company

NGO’s

GLC’s

68

26

203

5

32

20.4

7.8

60.8

1.5

9.6

Printed Media

Social Media

Family

Friend

Television

Radio

Employers

Financial Advisor

Other

66

96

51

92

40

18

58

73

2

19.8

28.7

15.3

27.5

12.0

5.4

17.4

21.9

0.6

Working Position

Professional or Managerial

Middle-level manager/ Executive

Technician

Clerical

Production Worker

other

86

132

21

55

9

17

25.7

39.5

6.3

16.5

2.7

5.1

Tenure of Service These people have advice the respondent to save in a voluntary saving: (of total respondent)

Less than 5 years

6 years – 10 years

11 years – 20 years

21 years to 30 years

More than 30 years

151

89

66

22

5

45.2

26.6

19.8

6.6

1.5

Parent

Sibling

Employers

Spouse

Colleague

Neighbour

Friends

Financial Advisor

99

66

62

48

77

15

113

90

29.6

19.8

18.6

14.4

23.1

4.5

33.8

26.9

Model Assessment The extent literature and the DTPB model both support the conceptual design and provide the content validity that integrates the relationship between salient beliefs and attitude, subjective norms, self-efficacy constructs and at the same time, the intention to save in a private retirement fund. In order to better understand the relationship between the antecedents of intention, the decomposition of the belief structures of the antecedent is required. Based on the model in Figure 1, the intention is influenced by attitude, subjective norms and perceived behavioural controls (Azjen). According to the Shimp and Kavas (1984), the cognitive components of belief should not be organized into a single conceptual or cognitive unit. Therefore, based on Todd and Taylor (1995), each antecedent has its salient characteristics. Attitudes are influenced by relative advantages, compatibility and complexity (Rogers, 1983), subjective norms are influenced by internal and external norms (Croy et al., 2010; Mahlanza, 2015) which are both injunctive and descriptive (Ajzen, 1985; Croy et al., 2010), while perceived behavioural control is influenced by self-efficacy (Bandura, 1977) and facilitating conditions (Triandis, 1977). The Partial Least Square Structural Equation Modelling (PLS-SEM) using the Smart PLS 3.0 software was used for theory development and to test the analysis (Hair, Ringle & Sarstedt, 2011).


90

Measurement Model The validation for the measurement model follows the guidelines provided by various researchers (Chin & Dibbern, 2010; Hair, Ringle, & Sarstedt, 2013; Ramayah, Cheah, Chuah, Ting, & Memon, 2018) Hair et al., 2014; Ramayah, 2018, Chin, 2010). Assessment of a reflective measurement model involved the assessment of the indicator reliability (loadings), construct reliability (composite reliability-CR), convergent validity (Average variance extracted-AVE) and discriminator validity (square roots of AVE, cross loading analysis and Heterotrait-monotrait analysis). Passing all these tests provided assurance that the survey items measured the constructs as they were designed to measure. The indicator loadings, CR and AVE, of the reflective constructs are shown in Table 3. Latan & Ramli (2013) suggested that the cut-off value for the outer loadings should be ≥ 0.6 for exploratory research and ≥ 0.7 for confirmatory research. Byrne (2016) suggested a loading of 0.6 as a threshold value if the loading contributes to AVE scores of greater than 0.6. Upon the measurement model analysis, no constructs were deleted from the model. One item, internal norms, had a single indicator measure.

Table 2: Loadings, Construct Validity, Reliability and Average Variance Extracted

Measure Loadinga Rho_Ab CRc AVEd Measure Loadin

gsa Rho_Ab CRc AVEd

Intention Relative advantages

INT1 0.922 0.929 0.954 0.874 SumRA1 0.938 0.944 0.953 0.836

INT2 0.957 0.924 SumRA2 0.923

INT3 0.926 0.943 SumRA3 0.948

Attitude SumRA4 0.854

ATT1 0.868 0.916 0.925 0.675 Compatibility

ATT2 0.841 SumCP1 0.821 0.962 0.913 0.725

ATT3 0.908 SumCP2 0.923

ATT4rc 0.710 SumCP3 0.862

ATT5 0.883 SumCP4 0.794

ATT6rc 0.694

Subjective Norms Complexity

SN1 0.832 0.890 0.922 0.748 SumCX1 0.965 0.944 0.952 0.909

SumCX2 0.942

SN2 0.893 Internal Norms

SN3 0.880 SumInter1 SIM SIM SIM SIM

SN4 0.852 External Norms

Perceived Behavioural Control SumExter1 0.921 0.926 0.952 0.869

PBC1 0.840 0.857 0.884 0.605 SumExter2 0.937

PBC2 0.847 SumExter3 0.941

PBC3 0.826 Facilitating Conditions

PBC4rc 0.642 SumFC1 0.912 0.881 0.920 0.793

PBC5 0.714 SumFC2 0.92


91

SumFC4 0.836

Self-efficacy

SumSE1 0.944 0.887 0.901 0.819

SumSE2 0.865

- SIM - Single item measure a. Items loadings > 0.5 indicates the indicator Reliability (Hulland, 1999, p. 198) b. Rho A > 0.7 indicates indicator reliability (Nunnally, 1978) c. Composite Reliability(CR) > 0.7 indicates internal consistency (Gefen et al., 2000) d. Average Variance Extracted (AVE) > 0.5 indicates Convergent Reliability (Bagozzi and Yi, 1988;

Fornell and Larcker, 1981) The discriminant validity analysis was done by comparing the cross loading between constructs, The Fornell Lacker (1981) criterion and the Heterotrait and monotrait (HTMT) technique (Henseler, Ringle & Sarstedt,(2014) which required all the values to fulfil the criterion of HTMT.90 (Gold, Malhotra, & Segars, 2001) or HTMT.85 (Kline, 2011). The measurement model shows that all indicators load high on its own construct but low on the other constructs and at the same time, they also exhibit sufficient values based on the Fornell-Lacker criterion. This indicates discriminant validity as these two assessments show that the constructs are distinctly different from each other. However, assessment of the HTMT criterion shows that there are items that cross load between constructs which require deletion. Therefore, 1 item each from self-efficacy (SE3) and facilitating condition (FC3) which loads to perceived behavioural controls had to be deleted because of discriminant validity issues of HTMT.90. Table 4 shows the discriminant validity by using HTMT techniques showing that all values fulfil the criterion of HTMT.90. This indicates that the discriminant validity has been ascertained.

Table 3 Discriminant Validity (HTMT Technique)

Variables Atti

tude

Com

patib

ility

Com

plex

ities

Ext

erna

l NB

Fac

ilita

ting

Con

ditio

n

Inte

rnal

NB

Rel

ativ

e

Adv

anta

ge

Sel

f-E

ffica

cy

Sub

ject

ive

norm

s

inte

ntio

n

Attitude

Compatibility 0.136

Complexities 0.067 0.677

External Normative belief 0.572 0.093 0.037

Facilitating Condition 0.533 0.052 0.067 0.728

Internal Normative belief 0.517 0.088 0.04 0.81 0.735

Relative Advantage 0.628 0.056 0.125 0.589 0.619 0.542

Self-Efficacy 0.618 0.101 0.09 0.688 0.89 0.633 0.61


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Subjective norms 0.731 0.061 0.092 0.694 0.532 0.61 0.592 0.567

Intention 0.707 0.149 0.035 0.67 0.595 0.609 0.57 0.632 0.662

perceived Behavioural control 0.755 0.183 0.05 0.665 0.731 0.69 0.59 0.688 0.702 0.803

Structural Model Assessing the structural model using PLS-SEM involves 6 steps. The first step is the assessment of lateral collinearity issue, even when the vertical collinearity is met in the measurement model(Kock & Lynn, 2012). The evaluation of the inner VIF value for the model met the rules of thumb of lower than 5 (Hair, Ringle & Sarstedt, 2011) or even the more stringent value of 3.3 (Diamantopoulos & Sigouw, 2006). The second steps involve assessing the significance and relevance of the structural model relationship through a bootstrapping procedure to avoid type 1 error (Ramayah et al., 2018). Bootstrapping will give the approximate t-values for significant test of the structural path while approximating the normality of the data (Wong, 2013). The model‟s predictive accuracy was tested next via the coefficient of determination R2. The R2 represent the amount of variance in the endogenous construct explained by all the exogenous construct linked to it (Ramayah, 2018). Step 4 require the assessment of the level of effect size of the predictor construct using Cohens f2 (Cohen, 1988). It assesses the relative impact of a predictor construct on an endogenous construct contributes to explain a certain endogenous construct in term of R2. Excluding and reincluding a predecessor construct and estimating its R2 value will provide the effect size of a certain construct. The next step is to assess the predictive relevance (Q2) before finally assessing the predictive relevance effect size (q2) using a blindfolding technique. Table 5 shows the results of the 6 steps structural model assessment using PLS-SEM.

Table 4: Structural Model Assessment

Null Hypo-theses

Hypothesis Relationship

Std Beta

Std Error

t-value Decision f2 q2

5%

CI LL

95%

CI UL

Ha1 Attitude -> Intention

0.280 0.059 4.763 Supported

*** 0.080 0.049 0.189 0.369

Ha2 Subjective Norms -> Intention

0.208 0.051 4.056 Supported

*** 0.051 0.029 0.129 0.296

Ha3 Perceived Behavioural Control -> Intention

0.362 0.062 5.862 Supported

*** 0.163 0.110 0.258 0.461

Ha1a Relative Advantage -> Attitude

0.482 0.056 8.605 Supported

*** 0.252 0.126 0.381 0.563

Ha1b Compatibility -> Attitude

-0.192 0.073 2.640 Supported

*** 0.022 0.000 -0.308

-0.068

Ha1c Complexities -> Attitude

0.028 0.069 0.406 Not significant

0.000 0.012 -0.068 0.162

Ha2a Internal Normative Belief -> Subjective Norms

0.219 0.079 2.778 Supported

** 0.031 0.017 0.098 0.352


93

Ha2b External Normative Belief -> Subjective Norms

0.459 00.75 6.078 Supported

*** 0.135 0.076 0.308 0.561

Ha3a Facilitating Condition -> Perceived Behavioural Control

0.273 0.075 3.643 Supported

*** 0.109 0.023 0.143 0.385

Ha3b Self-Efficacy -> Perceived Behavioural Control

0.362 0.062 5.862 Supported

*** 0.054 0.049 0.258 0.461

***P<0.01, ** p<0.05, *p<0.1, p-values correspond to the probability of erroneously rejecting the null

hypothesis. Commonly used critical values for one-tailed tests are 1.28 (sig. level= 10%), 1.645 (sig. level = 5%), and 2.33 (sig. level = 1 %) (Ramayah, et al. 2018; Hair et al. 2017).

Coefficient of determination (R2): Intention: = 0.542; R2adjusted: Intention= 0.538; Attitude=0.398; Perceived Behavioural Control=0.379; Subjective Norms=0.414. R2 value: 0.75 - substantial, 0.50 - moderate), 0.25 (Hair et al. (2017))

Coefficient of determination Effect size f2: f 2 value: 0.35- large, 0.15 - medium, and 0.02 -small

(Cohen,1988). Q2 Intention = 0.444; Attitude=0.248; Perceived Behavioural Control=0.211; Subjective Norms=0.288.

Values are above 0 means the exogenous constructs have predictive relevance for the endogenous constructs (Hair et al., 2017; Fornell & Cha, 1994)

Predictive relevance effect size (q2) of Predictor Exogenous Latent Variables as according to Q2 value; q2 value: 0.35 -large, 0.15-medium, and 0.02 -small (Henseler et al. 2009)

Almost all the hypotheses in the analysis are significantly supported, except for one hypotheses Ha1c. The rest of the hypotheses as shown in table 5 are found to have a t-value ≥1.645, which is significant at 0.05 level of significance. The relative importance (path coefficient (β)) of the predictor constructs in predicting the dependent constructs, shows that perceived behavioural control(β=0.362) is the most important predictor, followed by attitude (β=0.280) and then subjective norms (β=0.208). These three constructs positively influence intention to save in a voluntary retirement fund, thus supporting hypothesis Ha1, Ha3 and Ha3.Attitude, subjective norms, and perceived behavioural control explain 54 % (R2=0.53.8) of the variance in intention shows a moderate to high level of predictive accuracy. In addition, the effect size (f2) value shows that perceived behavioural control (f2=0.163) have a medium effect in producing the R2 for intention. In contrast, Attitude (f2=0.080) and subjective norms (f2=0.051) have a small coefficient determination effect on R2 for intention. The Stone-Geisser Q2 predictive relevance value are all larger than 0 which indicates that the exogenous constructs have predictive relevance for the endogenous constructs (Hair et., 2017; Stone 1974; Geisser 1974) with the predictive relevance effect size (q2)for PCB is medium (q2=110), while the other two constructs having a small q2 effect.

Decomposing the construct shows that the path coefficient for relative advantages (β=0.482) are moderate and have significant positive influences towards attitude (Ha1a). This is in contrast to


94

compatibility (β=-0.192) which has a small and negative influence towards attitude (Ha1b), and complexity (β=0.028) which is not significant Ha1c. This shows that among the three attitudinal belief variables, relative advantage is the most important predictor for attitude. These three salient attitudinal beliefs explain for 39.8% of the variance for attitude with relative advantage (f2=0.252) having the biggest and largest R2 predictive relevance effect size (f2) while compatibility (f2=0.022) had a small effect and complexity (f2=0.000) had almost no effect on the variance of attitude. In hypotheses Ha2a and Ha2b, both internal norms (β=0.219) and external norms (β=0.459) path coefficients show a positive influence towards subjective norms with a variance of 41%. Out of these two variables, external norms (β=0.459, f2=0.135) were set as the most important predictor of subjective norms. Hypotheses Ha3a on Self-efficacy (β=0.273) and hypotheses Ha3b on facilitating conditions (β=0.362) both positively influenced perceived behavioural controls. In comparison, facilitating conditions are a greater predictor of PCB than self-efficacy. However, both FC (f2=0.054) and SE (f2=0.109) have a small coefficient of determination effect size (f2) toward the variance of PBC (R2=0.379). In addition, the examination of the predictive relevance (Q2) of the model through blindfolding procedures shows that all constructs relevant to a certain endogenous construct has a Q2 value above 0. This indicates that the attitudinal, normative and control belief has sufficient predictive relevance towards attitude, subjective norms, and perceived behavioural controls. CONCLUSION AND IMPLICATIONS This study measures the intention to save in a voluntary private retirement fund in Malaysia using the DTPB model. The findings show that attitude, subjective norms, and perceived behavioural controls have a significant influence on the intention to save in a voluntary retirement fund. The PLS-SEM analysis showed that although the PBC has a moderate influence on intention to save in a voluntary retirement fund, it has the strongest impact when compared to attitude and subjective norms. This indicates that individuals with a high perceived control would have a higher intention to save. Further analysis by decomposing the construct showed that facilitating conditions and self-efficacy significantly influence PBC. Moreover, facilitating conditions seem to be a greater predictor on PBC compared to self-efficacy. Attitudinal belief shows that relative advantage positively influences the intention to save in a voluntary retirement fund while compatibility has a negative influence. This shows that an individual will be attracted to save in these funds if they find it economically beneficial and if it fits their life style. On the other hand, complexity, the notion of an individual‟s perception of the ease or difficulty in conducting certain behaviours is not significant and does not affect a person‟s attitude towards their intention to save in a voluntary fund. The normative belief shows that both internal and external norms will influence a person‟s subjective norm towards saving in a voluntary fund. When deconstructed into specific believes, the model becomes managerially relevant and points to factors that may influence intention to save unlike the monolithic factor present in the TPB.

It has been proposed that individuals having good saving histories and thus higher self-efficacies will be more inclined to save in a retirement fund, but it is imperative that facilitating conditions such as the availability of resources, for example time and money to perform the behaviour, are present to encourage individuals to save in voluntary saving funds. Likewise, the findings of this research show that attitude and subjective norms are also important factors in determining a person‟s will to save which will be augmented if saving in a voluntary fund provides many relative advantages. On the other hand, having external support from friends, colleagues, and financial advisors increases the intention to save in a voluntary retirement fund, more so than from family pressure. Finally, the PLS-SEM analysis also infers that an individual will not find it interesting to save if it is not compatible with their lifestyle and monthly expenses, while complexity in saving has no significant value.


95

In conclusion, the results of this research bear important implications for research and practice. Most studies on retirement savings, in particular on voluntary savings, assessed intention to save through attitude, subjective norms and perceived behavioural controls applied through the TPB model. Limited research has used the DTPB model which accounts for the antecedent of the aforementioned TPB‟s variables in financial services and almost no research has been done in terms of voluntary retirement savings, not to the extent of this researcher‟s knowledge. Thus, this study is the first in Malaysia to look at voluntary savings using DTPB and applying PLS-SEM. The results clearly show that by decomposing the construct into multi-dimensional structures, the understanding of the relationship between salient behavioural belief, the antecedents of intention and intention will improve. From a policy and commercial viewpoint, the findings offer knowledge and understanding about intentions to save in voluntary retirement funds, thus providing viable solutions and valuable strategies. The implication of these results show that for any policy or marketing effort to achieve a high take up of this type of retirement savings, it is important to review the behavioural control of customers, especially with regards to the facilitating conditions. Despite this, the respondents of this study are limited to examining the intention and not the behaviour of those who do not have any kind of voluntary saving. Future research could further explore the current findings to compare not only the intention but also the actual behaviours of respondents that have or do not have voluntary retirement funds.

ACKNOWLEDGEMENT Mohamad Fazli Sabri and Radduan Yusof received funding from the Putra Graduate Initiative Grant

(IPS), Universiti Putra Malaysia (Project Number 9602800, Vote Number 13201).

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Appendix 1: Construct and items measurement

Question: What is your opinion in saving ten per cent (10%) of monthly income to the voluntary retirement fund within the next twelve (12) months?

Intention (Croy, 2010; Mahlanza, 2015; Azjen, 2002; Todd & Taylor, 1995)

INT1 I intend to do it.

INT2 I plan to do it.

INT3 I will make an effort to do it.

Attitude (Croy, 2010; Mahlanza, 2015; Azjen, 2002; Todd & Taylor, 1995)

ATT1 It is beneficial.

ATT2 It will be a pleasant experience.

ATT3 It is good practice.

ATT4RC I will not enjoy it.

ATT5 It would be the right thing to do.

ATT6RC It is worthless.

Subjective Norms (Croy, 2010; Mahlanza, 2015; Azjen, 2002; Todd & Taylor, 1995)

SN1 It is what most people who are important in my life would want me to do.

SN2 It is what most people whose opinion I value would think that I should do

SN3 Most people who are important in my life would do it themselves.

SN4 Many people whose opinion I value would do it themselves.

Perceived Behavioural Control (Croy, 2010; Mahlanza, 2015; Azjen, 2002; Todd & Taylor, 1995)

PBC1 I have the resource and ability to do it.

PBC2 I have complete control to do it.

PBC3 It is entirely up to me to do it

PBC4RC It would be impossible.

PBC5 If I wanted to, I could do it.

Relative advantages (Elicitation, Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

What is your opinion on the advantages with respect to saving in a Voluntary Retirement Fund?


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Behavioural belief Outcome expectation

SumRA1 I will be able to boost my retirement saving.

Being able to boost my retirement saving is important.

SumRA2 It can improve my standard of living. Having a good standard of living is important.

SumRA3 I have the flexibility to determine the amount that I want to.

Having the flexibility to determine the monthly amount to save in this fund is important

SumRA4 I will gain taxation benefits from this savings.

Gaining taxation benefits from saving in a voluntary retirement fund is extremely important.

Compatibility (Elicitation, Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

What is your opinion on the compatibilities and complexities with respect to saving in a Voluntary Retirement Fund?

SumCP1 My current spending needs will be affected.

Having my current spending needs affected due to this savings is bad.

SumCP2 It does not fit my lifestyle. Saving in a fund that does not fit my lifestyle is bad

sumCP3 It will increase my monthly expenditure. It is bad if it increases my monthly expenditures.

SumCP4 It is risky to save in this fund.

If saving in this fund is risky, then it is bad.

Complexity (Elicitation, Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

SumCX1 It is difficult to do. If saving in this fund is difficult, then it is bad.

SumCX2 I do not understand clearly the process and procedure to do it.

If the saving process and procedures are not clear, then it is bad.

Internal Norms (Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

What is your opinion on the following statements regarding saving to a voluntary retirement fund?

Normative belief Motivation to comply

SumInter1 My family thinks that I should save in the fund.

I want to do what my family thinks I should.

External Norms (Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

SumExter1 My employer thinks that I should save in the fund.

I want to do what my employer thinks I should.

SumExter2 Financial advisor thinks that I should save in the fund.

I want to do what a financial advisor thinks I should.

SumExter3 My friends think that I should save in I want to do what my friends think I should.


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the fund.

Facilitating Conditions (Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

Control belief Perceived facilitation

SumFC1 I have the money to save in the fund. Having money to save in the fund is important.

SumFC2 I have the time to make saving in the fund.

It is important to have time to save in the fund.

SumFC3 I have the financial knowledge on how to save in the fund.

Having financial knowledge on how to save in the fund important.

Self-efficacy (Todd & Taylor, 1995, Mahlanza, 2015; Croy, 2010)

SumSE1 If I wanted to, I could easily save in the fund on my own.

Being able to save easily in the fund on my own is important.

SumSE2 I know how to save in the fund, even if there is no one around to tell me how to do it

Knowing how to save in the fund on my own is important.

examining the behavioural intention to save in a …

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