Purchasing insurance – the roles of individual differences in time perspectives and regulatory foci

ABSTRACT

Objective

The present studies focused on the role of time perspectives (TPs) and regulatory foci (promotion and prevention) in explaining people’s purchases of car, accident, home, life, and travel insurance.

Method

Two correlational studies on nationwide Polish samples (N = 1,093 and N = 1,047) were conducted.

Results

The first study showed that, after controlling for age and sex, higher levels of Future TP and lower levels of Past Negative TP were related to the propensity to make voluntary purchases of car, life, home, and accident insurance. Higher levels of Present Hedonistic TP and lower levels of Present Fatalistic TP were related to the propensity to buy travel insurance. The second study identified significant positive roles of both promotion and prevention regulatory foci in explaining people’s possession of all five types of insurance considered.

Conclusions

TPs (mainly Future and Past Negative) and regulatory foci (promotion and prevention) seem to be important in explaining people’s insurance-related behaviours.

KEY POINTS

What is already known about the topic?

1. Insurance decisions are influenced by many psychological variables, e.g., social norms, previous personal experience, emotions and cognitive biases and heuristics

2. Future time oriented individuals focus on future consequences of today decisions and have a greater propensity to save and to invest money

3. Prevention focused individuals try to avoid the negative consequences of unexpected event, so they prefer to invest in financial tools which are characterized by minimal risk

What this topic adds?

1. People declaring possession of car, life, home and accident insurance policies were characterized by lower levels of past negative TP and higher levels of future TP than those not possessing such policies

2. Individuals declaring possession of all types of insurance (life, accident, car, home, and travel) were more prevention oriented than those not having such insurance

3. Individuals declaring possession of all types of insurance (life, accident, car, home, and travel) were more promotion oriented than those not having such insurance

KEYWORDS:

• Buying insurance
• promotion regulatory focus
• prevention regulatory focus
• regulatory foci
• time perspectives
• voluntary insurance

Introduction

The importance of obtaining various types of insurance has been widely recognized, especially among societies in highly developed countries (Feyen et al., 2011). Over the past decade, the global insurance market’s gross written premium has increased greatly from 4,102 to 5,193 billion USD.¹ Moreover, in OECD countries, the insurance penetration rate rose from 8.7% in 2008 to 8.9% in 2018.² Although these statistics show a positive trend in insurance purchasing, many people still do not insure themselves and their property. For example, more than 100 natural catastrophes where registered in Europe during 2018 at a cost of 16 USD billion, but only 37% of these losses were insured.³ It is therefore important to consider what drives people’s insurance purchasing preferences towards the end of understanding why some people obtain insurance while others do not.

The issue of when and why people buy insurance has traditionally been studied by classical economists, who claim that people are fully aware of risks relating to losses when considering whether to acquire insurance policies, and that consumers try to maximize expected utility when making decisions (Brzezicka & Wiśniewski, 2014). According to Utility Theory (Von Neumann & Morgenstern, 1944), humans are risk averse, and in situations where they have a choice between a sure option and a lottery of equal expected value, they tend to prefer the former option. Consequently, the propensity to buy insurance should be natural: people should prefer to spend a small sum of money for sure as this protects them from higher potential losses. However, numerous studies in the fields of economics and psychology have demonstrated that classical economic models do not fully explain consumers’ insurance purchasing decisions (Kunreuther et al., 2013). Moreover, financial psychology and behavioural economics studies have suggested that sociodemographic and psychological variables play important roles in explaining insurance decisions.

With respect to psychological variables, studies show that insurance decisions are influenced by social norms (Tyszka & Konieczny, 2016), previous personal experience (Tyszka & Konieczny, 2016; Weinstein, 1989), emotions (Zaleskiewicz et al., 2002), and cognitive biases and heuristics (Johnson et al., 1993; Shapira & Venezia, 2008). Further, although the role of individual differences has received little attention, an internal locus of control is associated with a higher demand for flood insurance (Robinson & Botzen, 2020), the personality traits of conscientiousness and neuroticism are positively related to travel insurance purchasing (Sarman et al., 2020), while emotional instability and conscientiousness are negatively associated with the likelihood of buying life insurance (Smith, 2019).

However, research into the role of individual traits in explaining financial behaviours has consistently identified a much longer list of personality traits that should be considered when trying to understand people’s financial decisions. Thus, the above mentioned (very short) list of individual dispositions relating to insurance purchasing is probably not comprehensive and is worth extending. To identify further individual difference variables that may be significant in the context of buying insurance, it is useful to look at two important aspects of insurance purchasing decisions.

First, a decision as to whether to buy insurance entails a choice between incurring a small immediate cost in order to avoid a potential larger future loss or spending the money on something else, thereby risking a potential substantial future loss. This type of decision requires mental time travel, and is an example of an intertemporal choice involving tradeoffs between consequences (positive and negative) that will occur at different points in time (Frederick et al., 2002). Second, such a decision involves the extent of a person’s need to protect themselves against potential losses and to feel secure (Ganderton et al., 2000; Korstanje & George, 2017): as Tykocinski (2008, p. 1347) notes, “when people buy insurance policies, they are in a sense buying peace of mind”. In most cases, insurance is a tool to reduce financial risk. To summarize, purchasing insurance allows a person to secure their future financial and material situation, and individuals who decide to buy insurance should be those who feel a need to protect themselves against possible negative future events and be motivated to act to meet this need. Importantly, individuals differ in how they perceive tradeoffs between the present and future, and differ in their motivation to achieve security and avoid the risk of losses.

In this paper we focus on two psychological constructs – Time Perspective, which is related to the perception of time and Regulatory Foci, which refers to people’s motivation to achieve security. Those individual traits were chosen on the basis of the results of previous studies that showed the significant and non-negligible role of both of this traits in explaining financial behaviour related to securing the financial future (e.g., by saving, see e.g., Cho et al., 2014; Sekścińska et al., 2018), reducing financial risk (e.g., by investing only in safe assets; see e.g., Florack & Harman, 2007; Jochemczyk et al., 2017; Leonard et al., 2019; Zhou & Pham, 2004) and financial behaviours associated with an intertemporal choice (saving, investing, indebtedness; see e.g., Cho et al., 2014; Sekścińska et al., 2016).

Time perspective

Time perspective (TP; Zimbardo & Boyd, 1999; Zimbardo & Boyd, 2008) is a well-documented personality construct describing an individual’s relationship with time. Stolarski et al. (2018) provide a concise history of TP research. Based on empirical studies, Zimbardo and Boyd distinguished five TP dimensions: Past Negative (PN), Past Positive (PP), Present Hedonistic (PH), Present Fatalistic (PF), and Future (F). PN reflects an aversive view of the past, which might result from unpleasant events, negative reconstructions of past experiences, or a mixture of both. PP is associated with a warm, sentimental attitude towards the past, as well as deriving pleasure from reliving memories. PH describes an orientation towards the present and immediate pleasure, risk taking and enjoyment, and a disregard for the future consequences of one’s actions. PF reflects a helpless and hopeless attitude towards one’s present and future, together with beliefs that the future is predestined, cannot be influenced by one’s actions, and that the present must be borne with resignation as it is controlled by “fate”. Finally, F is related to behaviour dominated by a striving for future goals and rewards, and a focus on the future consequences of current decisions. Importantly, individual differences in TP have been associated with a wide range of outcomes that involve tradeoffs between present and future consequences, such as tradeoffs involving health-related behaviours (Daugherty & Brase, 2010; Henson et al., 2006), and tradeoffs relating to financial decisions.

To date, studies have shown that a future TP is positively related to the making of financial decisions that may secure the financial future of the decision maker. Zsótér (2018) demonstrated that TP affects financial well-being, specifically, that individuals belonging to an “anxious aware cluster” (considering their financial situations to be severely constrained) tend to exhibit the strongest future-oriented TPs. Also, the studies of Sekścińska et al. (2018) showed that a future TP is positively related to a propensity to save and to invest money, but in a relatively safe way: future-oriented people preferred less risky investment options (e.g., bonds) over riskier options (e.g., stocks). Other studies have shown negative relationships between a future TP and financial risk taking (Jochemczyk et al., 2017; Leonard et al., 2019), and other types of choices, e.g., ethical, gambling, health/safety, social, and recreational choices (Jochemczyk et al., 2017; Keough et al., 1999). Given that a future TP involves focusing on the future consequences of current decisions, and that it is positively related to making safe financial decisions and avoiding risks, it is reasonable to assume that future-oriented people should exhibit a propensity to acquire insurance to minimalize the likelihood of future losses and to maintain “peace of mind” in present.

Another TP that might be related to insurance purchasing decisions is the Present Hedonistic TP, which involves a focus on present pleasures derived from material goods and current experiences, without a person thinking about the future consequences of the decisions they are presently making. To date, studies have shown a positive relationship between a present hedonistic TP and risk taking. The studies of Sekścińska et al. (2018) showed that people with a higher present hedonistic TP tend to build riskier investment portfolios, preferring risky investment options over less risky ones. Moreover, present hedonistic TP scores are also positively correlated with propensities to take ethical, gambling, investing, health/safety, social, and recreational risks (Jochemczyk et al., 2017). Thus, a Present Hedonistic TP is likely to be negatively associated with the propensity to buy insurance to avoid an unspecified threat that may appear at an indefinite point in the future or to reduce the present anxiety level (achieving “peace of mind”).

A final TP that might be related to buying insurance is the Past Negative TP. Since people scoring high on the Past Negative TP dimension tend to concentrate on previous aversive experiences, exhibit a more conservative and cautious approach, and have difficulty in shifting their attention towards the future, it is reasonable to think that they may find it difficult to make the intertemporal choices involved in purchasing insurance. Such reasoning is confirmed by a study showing increasingly higher past negative TPs to be related to an decreasing preference for investments and savings (which are related to mental time travelling) over immediate consumption (Sekścińska et al., 2018).

Regulatory foci

In his self-regulation Higgins (1997, 1998) described two motivational systems which he termed regulatory foci: promotion focus and prevention focus. It should be noted that these motivational systems are separate and cannot be treated as two ends of a continuum. A promotion focus describes people who are prone to concentrate on their personal development and accomplishments. This focus is motivated by a need for growth. A prevention focus describes people who are focused on their duties and responsibilities. Such people go to great lengths to try to avoid negative consequences associated with unexpected events, and are motivated by a need to feel secure (Higgins, 1998). Thus, prevention-focused individuals are likely to be driven by a need to secure their financial future, and they are likely to see purchasing insurance as an effective way of helping them maintain their future financial safety and “peace of mind” at the present time. While relationships between regulatory foci and insurance-related behaviour have not previously been investigated, studies of other financial behaviours support the idea that relationships should exist. For example, among other observations, previous research has shown that inducing a prevention focus makes people more prone to save and less prone to invest their money (Sekścińska et al., 2016). There are many motives for saving: people may do this out of greed (to allow future consumption of goods that would otherwise be unavailable to them – a promotion goal) or out of fear (to secure themselves from the need to reduce their consumption – a prevention goal; Sekścińska & Markiewicz, 2020). Previous studies have shown that, in contrast to promotion-oriented individuals, prevention-focused individuals are more willing to save towards the end of achieving prevention-related goals (Cho et al., 2014). A prevention focus also seems to be important in determining financial risk taking: a prevention motive supports investment in balanced mutual funds and individual retirement accounts (IRAs), but not in stocks (which are more risky financial instruments; Sekścińska et al., 2016; Zhou & Pham, 2004). Moreover, other studies have shown that prevention-motivated people prefer to invest in financial tools which are characterized by minimal risk, perceiving them to be relatively safe (Florack and Hartmann, 2007). Also, Scholer et al. (2010), found that prevention-oriented individuals were more likely to be risk-seeking in the context of loss framing only when a risky option made a return to the status quo available. When a sure option was available, a prevention motivation predicted risk aversion. Taking into account the results of the abovementioned studies, we expected that a prevention focus would make people more prone to purchase insurance as this reduces the risk of losing money, and as a result may help them maintain their future financial safety and “peace of mind” at the present time.

The current studies

The main purpose of the two present studies was to analyse the extent to which TP and regulatory focus variables are associated with making decisions to obtain different types of voluntary insurance: car,⁴ accident, home, life and travel insurance.

In line with the existing literature, we formulated the following research hypotheses:

H1: A greater future TP predicts the possession of all types of insurance policy (Study 1).

H2: A greater past negative TP predicts the lack of possession of all types of insurance policy (Study 1)

H3. A greater present hedonistic TP predicts the lack of possession of all types of insurance policy (Study 1).

H4. A prevention regulatory focus is conducive to the possession of all types of insurance policy (Study 2).

The research literature to date does not appear to provide evidence to formulate hypotheses regarding the roles of a past positive TP, a present fatalistic TP, and a promotion regulatory focus in explaining people’s insurance decisions. Nevertheless, these variables were included in the study in an exploratory vein.

Both of the current studies were conducted in 2019 using an online panel of participants, and informed consent was obtained from all participants. As compensation for people’s participation, they were awarded points that could subsequently be exchanged for rewards of their choice offered by the platform running the studies. Each participant participated in only one study. The Ethics Board of the University of Warsaw‘s Faculty of Psychology approved the studies.

Study 1. Time perspectives and voluntary insurance choices

Study 1 aimed to establish whether people possessing and not possessing different types of voluntary insurance differ in their time perspectives.

Method

Participants

The study was conducted on a representative nationwide Polish sample (N = 1,093; 558 women; age range = 18 to 87 years, M = 35.0, SD = 12.2).

Measures

Time perspectives

The short version of the Zimbardo Time Perspective Inventory (SZTPI, Zhang et al., 2013) was used. The SZPI’s items tap the five TPs – past negative (PN), past positive (PP), present fatalistic (PF), present hedonistic (PH), and future (F) – and each TP is measured by three items. For example, an item measuring future TP is “When I want to achieve something, I set goals and consider specific means for reaching those goals”. Participants are asked to ask themselves the question: “How characteristic or true is this of me?” on a 5-point scale: from 1 – very untrue to 5 – very true. The score for each TP is the sum of the responses to its items, possible scores ranging from 3 to 15.⁵

Types of insurance possessed

Participants indicated all the types of voluntary insurance that they currently possessed (or, in the case of travel insurance, had possessed during the last 12 months) on a list of nine types of insurance. But analyses were only conducted for five types of insurance: car (comprehensive), accident, home, life and travel insurance. The other four types of insurance were specific to the Polish market and very rarely taken-out (only 4% to 7% of participants possessed these).

Procedure

Participants completed the SZTPI questionnaire, and then declared if they currently had a car, flat/house and if they had travelled during the last 12 months. Then they indicated the types of insurance they possessed (or had possessed with respect to travel insurance). People who said that they did not have a car, flat/house and/or had not travelled during the last year were excluded from relevant analyses. Finally, sociodemographic data were collected.

Results and discussion

Descriptive statistics for all the variables analysed, and tests of relationships between demographic variables and TPs, are presented in an Appendix.

Subsequent to mean centring of TP trait and age variables, five logistic regression analyses were conducted to determine relationships between the time perspective dimensions and possession of the five types of insurance. Although this led to problems concerning multiple comparisons, it was not possible to implement a within subjects analytical model because the sets of people answering questions about the different insurance types were not exactly the same. These differences in samples for each type of insurance occurred because of the lack of a complete overlap in types of insurance possessed, e.g., homeowners did not always own a car that needed to be insured, and they had not always been on vacation in the past year. Demographic variables were introduced to models in the first step of each analysis, while time perspectives were included in a second step (see Table 1).⁶

Table 1. Logistic regression analyses regressing the possession of different types of insurance on time perspectives and demographic variables (Study 1)

	Model 1				Model 2
	B	Wald	p	OR	B	Wald	p	OR
Car insurance
Constant	−1.19	15.92	< .001	0.30	−1.00	10.75	.001	0.37
Sex	−0.02	0.02	.89	0.98	−0.05	0.14	.71	0.95
Age	0.02	7.08	.008	1.02	0.01	3.35	.07	1.01
Past Negative TP					−0.07	7.57	.006	0.94
Past Positive TP					−0.03	0.54	.46	0.98
Present Fatalistic TP					−0.03	0.60	.44	0.97
Present Hedonistic TP					0.03	0.67	.41	1.03
Future TP					0.09	4.61	.03	1.09
Nagelkerke pseudo R^2	1.1%				3.6%
Chi-square	7.13, df = 2, p = .03				23.71, df = 7, p = .001
Home insurance
Constant	−0.48	2.86	.09	0.62	−0.31	1.16	.28	0.73
Sex	0.02	0.18	.67	0.94	−0.06	0.17	.68	0.94
Age	−0.06	18.29	< .001	1.02	0.02	11.26	.001	1.02
Past Negative TP					−0.05	4.32	.04	0.95
Past Positive TP					0.03	0.61	.47	1.02
Present Fatalistic TP					−0.04	1.52	.22	0.96
Present Hedonistic TP					−0.02	0.17	.68	0.99
Future TP					0.09	5.35	.02	1.10
Nagelkerke pseudo R^2	2.7%				5.0%
Chi-square	18.92, df = 2, p < .001				35.30, df = 7, p < .001
Travel insurance
Constant	−2.14	28.79	< .001	0.12	−2.12	26.40	< .001	0.12
Sex	0.18	0.84	.36	1.20	0.21	0.37	.54	1.13
Age	−0.002	0.09	.77	1.00	−.003	0.13	.71	1.00
Past Negative TP					−0.06	3.41	.07	0.95
Past Positive TP					0.02	0.26	.61	1.02
Present Fatalistic TP					−0.13	8.17	.004	0.88
Present Hedonistic TP					0.14	7.42	.006	1.15
Future TP					0.06	1.17	.28	1.06
Nagelkerke pseudo R^2	0.2%				4.4%
Chi-square	0.89, df = 2, p = .64				23.44, df = 7, p = .001
Life insurance
Constant	−0.09	0.12	.73	0.92	0.10	0.26	.71	1.10
Sex	−0.37	8.87	.003	0.69	−0.40	0.13	.002	0.67
Age	0.01	3.13	.08	1.01	0.01	0.01	.36	1.01
Past Negative TP					−0.07	0.02	.002	0.94
Past Positive TP					0.01	0.03	.78	1.01
Present Fatalistic TP					0.01	0.03	.69	1.01
Present Hedonistic TP					0.02	0.03	.51	1.02
Future TP					0.08	0.04	.02	1.08
Nagelkerke pseudo R^2	1.4%				3.5%
Chi-square	11.33, df = 2, p = .004				28.54, df = 7, p < .001
Accident insurance
Constant	−1.09	18.13	<.001	0.34	−0.94	12.77	< .001	0.39
Sex	−0.21	0.03	.87	0.98	−0.02	0.04	.85	0.98
Age	0.04	47.99	< .001	1.04	0.03	35.33	< .001	1.03
Past Negative TP					−0.05	6.43	.01	0.95
Past Positive TP					0.05	2.74	.10	1.05
Present Fatalistic TP					−0.02	0.26	.61	0.98
Present Hedonistic TP					−0.005	0.02	.88	1.00
Future TP					0.08	5.14	.02	1.08
Nagelkerke pseudo R^2	6.1%				8.7%
Chi-square	51.48, df = 2, p < .001				73.58, df = 7, p < .001

The first steps of the analyses for car and life insurance showed that women possessed each type of insurance significantly more often than men. Moreover, people who possessed life and accident insurance were older than those who did not, and people possessing home insurance were younger than those without it.

After introducing time perspectives into the models, the role of sex only remained significant for life insurance, and age remained a significant predictor of the possession of home and accident insurance. Two time perspectives were significant predictors of the possession of four of the five types of insurance analysed: people declaring possession of car, home, life, and accident insurance were characterized by lower levels of Past Negative TP and higher levels of Future TP than those not possessing these types of insurance. Moreover, people possessing travel insurance were less present fatalistic and more present hedonistic than those without it.

In summary, two types of TP appeared to be important in explaining insurance behaviours and preferences, Future TP being positively predictive and Past Negative TP being negatively predictive, these observations being in line with our expectations. The only exception to the above was for travel insurance, where there was a negative role of Present Fatalistic TP and a positive role of Present Hedonistic TP (these types of TP were not predictive for any other type of insurance).

Study 2. Regulatory focus and voluntary insurance choices

Study 2 aimed to establish whether people taking out and not taking out various types of voluntary insurance differ in their levels of promotion and prevention regulatory focus.

Method

Participants

The study was conducted on a representative nationwide Polish sample (N = 1,047; 522 women; age range = 18 to 87 years, M = 36.74, SD = 12.82).

Measures

Regulatory focus

The Regulatory Focus Questionnaire (RFQ; Higgins et al., 2001) was used to measure participants’ promotion and prevention foci. The questionnaire consists of 11 items; six belong to the promotion scale (e.g., Compared to most people, are you typically unable to get what you want out of life?), and five to the prevention scale (e.g., Growing up, would you ever “cross the line” by doing things that your parents would not tolerate?). Participants respond to questions on a 5-point Likert scale, response anchors depending on the question, e.g., “never or seldom” to “very often”, or “never true” to “very often true”, or “certainly false” to “certainly true”. A participant’s score for both types of focus is the sum of their answers to the questions comprising each scale.⁷

Types of insurance possessed

Were determined as in Study 1.

Procedure

The procedure was the same as in Study 1, except that participants completed the FRQ instead of the ZTPI. Data were collected as the first part of a larger online survey. The later parts of the survey related to a different study conducted by another team of researchers.

Results and discussion

Descriptive statistics for all the variables analysed, and tests of relationships between demographic variables and regulatory focus scores, are presented in the Appendix.

The regulatory focus and age variables were mean centred before a further five logistic regression analyses were conducted to determine relationships between the promotion and prevention foci and possession of the five types of insurance. Again, demographic variables were introduced in a first step of each analysis, and then the two regulatory focus variables were entered on a second step (see Table 2).⁸

Table 2. Logistic regression analysis regressing the possession of different types of insurance on regulatory focus and demographic variables (Study 2)

	Model 1				Model 2
	B	Wald	p	OR	B	Wald	p	OR
Car insurance
Constant	−1.19	15.92	< .001	0.30	−3.07	24.78	< .001	0.05
Sex	−0.02	0.02	.89	0.98	0.03	0.03	.86	1.03
Age	0.02	7.08	.008	1.02	0.01	4.00	.046	1.01
Promotion					0.07	6.97	.008	1.07
Prevention					0.05	4.88	.05	1.05
Nagelkerke pseudo R^2	1.1%				3.7%
Chi-square	7.08, df = 2, p = .03				24.52, df = 4, p < .001
Home insurance
Constant	−0.64	5.07	< .001	0.53	−2.66	19.76	< .001	0.07
Sex	−0.16	1.39	.24	0.85	−0.12	0.78	.38	0.89
Age	0.03	30.47	.02	1.03	0.03	21.70	< .001	1.03
Promotion					0.07	7.34	.007	1.07
Prevention					0.07	8.44	.004	1.07
Nagelkerke pseudo R^2	4.7%				7.2%
Chi-square	32.64, df = 2, p < .001				50.22, df = 4, p < .001
Travel insurance
Constant	−2.14	30.99	< .001	0.12	−5.66	48.82	< .001	0.003
Sex	0.01	0.19	.94	1.01	0.10	0.24	.63	1.00
Age	0.01	0.01	.36	1.01	0.001	0.03	.85	1.00
Promotion					0.13	17.76	< .001	1.14
Prevention					0.07	5.52	.02	1.07
Nagelkerke pseudo R^2	0.02%				5.0%
Chi-square	0.87, df = 2, p = .65				27.88, df = 4, p < .001
Life insurance
Constant	0.12	0.24	.63	1.13	−1.66	9.79	.002	0.19
Sex	−0.50	15.87	< .001	0.60	−0.48	13.91	< .001	0.62
Age	0.10	4.53	.03	1.11	0.07	2.06	.15	1.08
Promotion					0.07	9.20	.002	1.07
Prevention					0.04	4.44	.04	1.05
Nagelkerke pseudo R^2	2.4%				4.4%
Chi-square	19.11, df = 2, p < .001				34.55, df = 4, p < .001
Accident insurance
Constant	−0.81	9.66	.002	0.44	−2.76	24.69	< .001	0.06
Sex	−0.12	0.94	.33	0.88	−0.77	0.35	0.55	0.93
Age	0.34	43.78	< .001	1.40	0.30	32.30	< .001	1.35
Promotion					0.06	6.21	.01	1.06
Prevention					0.08	12.27	< .001	1.08
Nagelkerke pseudo R^2	5.8%				8.3%
Chi-square	46.33, df = 2, p < .001				67.05, df = 4, p < .001

The first steps of the analyses for all types of insurance apart from travel insurance revealed that age had a significantly positive role in explaining people’s possession of insurance. Also, women possessed life insurance more often than men. Neither age nor sex explained the possession of travel insurance during the last 12 months. For the most part, the roles of the demographic variables remained significant after introducing the two regulatory focus variables into the models (the only exception was for the role of age in the model for life insurance). Results for final models revealed significant positive roles of both promotion and prevention foci in explaining people’s possession of all the types of insurance considered: people taking out all five types of insurance were more promotion oriented and more prevention oriented than those not taking out these types of insurance.

To summarize, both a promotion and a prevention focus seem to be important in explaining people’s insurance-related behaviours: people possessing all the types of insurance analysed were higher in both types of regulatory focus than those not possessing insurance.

General discussion

We have presented two studies investigating the roles of time perspectives and regulatory foci in explaining people’s decisions to voluntarily purchase insurance.

People declaring possession of four out of five types of insurance policy (car, home, life, and accident policies) were characterized by lower levels of past negative TP and higher levels of future TP than those not possessing such policies (in line with H1 and H2). So, consistent with Sekścińska et al. (2018), there was evidence that future-oriented people are less inclined to take risks when making financial decisions, this being manifested by them striving to protect their financial wellbeing by buying insurance. Our findings here are also in line with Hershey and Mowen (2000) observation that future-oriented individuals report better financial preparedness for retirement. The results obtained for the past negative TP were in agreement with Higgins (1998) portrayal of past-negative oriented people as having difficulty in shifting their attention towards the future, and with the previous studies of Sekścińska et al. (2018) showing a lower past negative TP to be related to an increased preference for investments and savings over immediate consumption. Thus, our results are consistent with the idea that people characterized by a high future TP recognize the value of providing for their future, irrespective of whether this involves investing, saving or purchasing insurance, while people characterized by a high past negative TP find it difficult to make intertemporal financial choices, whether this involves investing, saving or purchasing insurance.

Important positive and negative roles of the present hedonistic and present fatalistic TPs were respectively observed for travel insurance. While these results were unexpected (e.g., seeH3 in the Introduction), tentative explanations of them are possible. First, the decision to buy travel insurance is made either at the time a trip is bought (when a decision maker is focusing on the pleasures related to their trip) or just before departure (when possible unspecified threats may occur within the next few days rather than at some indefinite time in the future). Thus, for people characterized by a high present hedonistic TP, purchasing travel insurance may be an effective risk reduction strategy to prevent their expected moments of pleasure being spoilt. Second, the findings for the present fatalistic TP are consistent with the idea that less fatalistic individuals feel they can influence what happens to them and do not simply rely on fate in their hopes of experiencing pleasure, but, rather, seek to guarantee that they will have pleasant experiences by purchasing insurance.

Our findings showed that people declaring possession of all types of insurance (life, accident, car, home, and travel) were more prevention oriented than those not having these types of insurance (supporting H4). Moreover, the study also revealed an important role of promotion focus in explaining people’s insurance behaviours, people possessing all types of insurance being more promotion oriented than those not possessing them. Thus, people with a strong promotion focus and people with a strong prevention focus appear to have a tendency to buy insurance, but their motivations are likely to differ: prevention-oriented people are likely to decide to buy insurance to avoid the loss of something they already possess, while promotion-oriented people may purchase insurance to avoid situations which will not allow them to achieve their future goals. To illustrate, imagine that John has a car. If John is prevention oriented, he is probably afraid of losing it and will focus on the car per se. If John is promotion oriented, he is again probably afraid of losing his car, but instead of focusing on the car per se he will focus on further goals/rewards related to having the car. Of course, this explanation is speculative and requires verification in future studies.

The present studies revealed that gender and age were also implicated in the possession of insurance. With respect to sex differences, the findings that females in both of our studies possessed life insurance more frequently than men are in agreement with Powell and Ansic (1997) claim that women tend to have a lower preference for risk taking when making financial decisions. These observations are consistent with the fact that women are generally more risk averse (Gandolfi & Miners, 1996), and the present findings can be explained by the idea that purchasing life insurance gives women a sense of security, not only for themselves but also for their partners and children, who would become beneficiaries of the purchased policies on their death. Thus the possession of life insurance may let the women reduce their anxiety level at the present time (maintain “peace of mind”) and help their families to protect the financial status quo if something bad would happened to the insured person.

Both of the present studies also revealed age differences in the possession of insurance. People possessing life and accident insurance were older than those who did not, and in the second study the same finding was observed for home and car insurance. This corresponds with data showing that patterns of risk taking change across people’s life span, the propensity to take risks peaking in adolescence and early adulthood, and then decreasing with age (Figner et al., 2009). However, a change in the level of risk accepted throughout life is not the only possible explanation for what has been observed in our studies. Maybe, the effect observed for home and car insurance simply results from the fact that people have more insurable goods that with age, and thus have more goods that they don’t want to lose. Moreover, another possible explanation is rooted in the culturally specific dependency and reflects the cohort effect of older people in Poland simply feeling less secure due to historical events and buying insurance gives them the peace of mind. The relationships observed for health and life insurance may reflect the fact that in the course of life people become responsible not only for ourselves, but also for other family members, and become more aware of the risks associated with their own health. Moreover, the collected life experiences may make people more sensitive to possible unexpected accidents that may happen to them. The possible explanations mentioned above are only examples and are certainly not exhaustive of the list of explanations worth considering. Undoubtedly, further research is needed to better understand the relationship between age and insurance buying.

While the current results are promising, the methods used in the studies have some limitations. Although both the SZTPI and RFQ are commonly used international research tools (and they have been previously used on Polish samples), the indices for the fit between the present data and the factor structures claimed by the authors of the SZTPI and RFQ cannot be considered excellent, and some indices were slightly below the levels usually considered acceptable. However, all regression weights were significant (p < .001) and quite high (for the RFQ at least 0.59, and for the SZTPI at least 0.72), and there were no potential discrimination issues for the different TP subscales and RFQ subscales, correlation coefficients being much lower than the recommended 0.85 maximum.

The psychological determinants of insurance purchasing have been little studied, however, such purchases can be highly important in securing a household’s financial situation. While our studies help to fill gaps in the current state of knowledge, they should only be considered to be a starting point for further work. For example, it would be worth taking a closer look at the insurance-buying motivations of people with differing time perspectives and regulatory foci. From an applied perspective, understanding the dependencies observed in the currently described studies may provide impetus for the creation of educational programmes and campaigns aimed at increasing interest in buying various types of insurance among people who do not currently possess insurance.

Ethical approval

All procedures were performed in accordance with the ethical standards of the institutional and/or national research committees, and the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The Ethics Board of the University of Warsaw’s Faculty of Psychology approved the studies.

Informed consent

Informed consent was obtained from all participants in both studies.

Disclosure statement

The authors declare that they have no conflicts of interest.

Data and original materials availability statement

Complete data sets for both of the present studies can be found at the following Open Science Framework (OSF) location: https://osf.io/xpv2w/?view_only=73e83da15bbc4e3c899cecc16e2f0e66

The original materials used to conduct this research are available upon e-mail request: [email protected]

Supplementary material

Supplemental data for this article can be accessed https://doi.org/10.1080/00049530.2021.1898915.

Additional information

Funding

This work was supported by the Faculty of Psychology, University of Warsaw, from the funds awarded by the Ministry of Science and Higher Education in the form of a subsidy for the maintenance and development of research potential in 2019 [501-D125-01-1250000 zlec. 5011000618]. The funding source had no involvement in study design, the collection, analysis and interpretation of data, the writing of this report, or in the decision to submit the article for publication.

Notes

1. Polish insurance market. Report 2018. GUS.

2. https://stats.oecd.org/Index.aspx?QueryId=25444

3. Ibid.

4. We investigated the taking out of comprehensive car insurance: voluntary car insurance that goes beyond basic, compulsory insurance.

5. The SZTPI factor structure claimed by its authors was tested using confirmatory factor analysis. This produced model fit indices that were either acceptable or only slightly below the usually accepted levels as noted by Hu and Bentler (1999): RMSEA = .0.08, PClose < .001; CFI = .90; TLI = .89; SRMR = .075; Χ2/df = 683.08/105 = 6.50. All regression weights were significant (p < .001) and quite high (at least 0.72). Correlation coefficients for each pair of TPs ranged from r = −.022. to r = .316, these not indicating any discrimination issues.

6. We also conducted further steps of analyses in which two-, three-, four-, five-, six-, and seven-way interactions between the predictor variables were introduced. However, for all the insurance types, none of the additional blocks of variables were significant, and, for the most part, none of the variables describing interaction effects were significant predictors (there was only one exception – a three-way interaction between present hedonistic TP, age and sex was a significant predictor of the purchasing of accident insurance).

7. Again, the FRQ structure proposed by its author was tested using confirmatory factor analysis. This produced model fit indices that were either acceptable or only slightly below the usually accepted levels as noted by Hu and Bentler (1999): RMSEA = .0.08, PClose < .001; CFI = .932; TLI = .913; SRMR = .067; Χ2/df = 332.62/55 = 6.04. All regression weights were significant (p < .001) and quite high (at least 0.59). The correlation coefficient for the two RFQ subscales was r = .13, this not indicating any discrimination issues.

8. We conducted further steps of analyses in which two-, three- and four-way interactions between predictor variables were introduced. However, none of the additional block of variables were significant for any of the insurance types, and none of the variables describing interaction effects were significantly predictive.