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Advances in Social Sciences Research Journal – Vol. 11, No. 1

Publication Date: January 25, 2024

DOI:10.14738/assrj.111.16267.

Kantarelis, D. (2024). Wellbeing and Fair Thrill-Seeking Rewards (*). Advances in Social Sciences Research Journal, 11(1). 175-187.

Services for Science and Education – United Kingdom

Wellbeing and Fair Thrill-Seeking Rewards (*)

Demetri Kantarelis

Department of Economics, Finance & Accounting, Grenon School of Business,

Assumption University, 500 Salisbury Street, Worcester, MA 01609, USA

ABSTRACT

A theory for wellbeing is proposed, developed on the assumption that consumers,

deciding based on various risk-preference attitudes, consider fair thrill-seeking

activities for inclusion in a portfolio of goods and services. Fair are those activities

governed by rules or regulations, those that enable consumers to safely get an

adrenaline shot; for example, skydiving, is considered fair (safe) when it follows

rules and regulations and unfair (unsafe) if undertaken subject to non-compliance

with, or lack of, rules and regulations. More specifically, it is assumed that consumer

wellbeing depends on a fair diversified portfolio of risk-preference expected

reward outcomes and their variabilities. In turn, by relying on a simulation-based

thought experiment, it is shown that consumers may choose to place more or less

importance (expenditures) on various fair rewards to end up with optimum

solutions that resemble conventional modern portfolio theory results.

Keywords: Microeconomic theory, consumer economics, portfolio theory, thrill-seeking

markets.

(*) I am grateful to Helen Kantarelis for useful brainstorming on the theme and to the

anonymous reviewers for useful and constructive comments. All remaining errors are mine.

INTRODUCTION

A consumer portfolio includes many durable and non-durable goods as well as services that

offer, among others, peace of mind, healthcare, education, and entertainment. In addition, the

portfolio includes thrill-seeking activities which Zuckerman (1994) defines as “the seeking of

varied, novel, complex, and intense sensations and experiences, and the willingness to take

physical, social, legal, and financial risks for the sake of such experience” such as whitewater

rafting, skydiving, skiing, bungee jumping, or starting a new business venture. Thrill-seeking

activities can supply many psychological benefits, but they also carry risks. According to

Psychology Today (2024), “sensation-seekers tend to report less stress, more positive

emotions, and greater life satisfaction. In addition to these beneficial outcomes, however,

sensation-seeking may be accompanied by dangers as well.” Zuckerman (1994) created a

Sensation Seeking scale to assess each of the following four components: Thrill and Adventur- Seeking (driving fast, parachuting), Experience-Seeking (Drug Experimentation, Alternative Life

Cycle), Disinhibition (Partying, Many Sexual Partners, Gambling), Boredom Susceptibility

(Cannot Tolerate Repetition, Restlessness). Inspired by Zuckerman’s research, Carter (2023)

has created a quiz which measures an individual’s sensation-seeking degree of preference.

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Advances in Social Sciences Research Journal (ASSRJ) Vol. 11, Issue 1, January-2024

Services for Science and Education – United Kingdom

Societies, overtime, have been trying to minimize danger associated with certain thrills. For

example, the thrill from car speeding with mandatory seatbelts, the thrill from business growth

through loans with strict credit scoring and tough bankruptcy laws, the thrill from flying like

Superman with labeling on the package carrying a child's Superman costume that reads

“wearing of this garment does not enable you to fly” 1. However, in this protective societal

environment coexist many thrill-seeking activities that have become profitable marketed

commodities offered in televised games, nutritional additives, extreme sports, footwear, and

complementary lines of clothing. I assume that thrill-seeking activities may be categorized as

quantitatively or qualitatively fair / unfair. For example, participation in a lottery enables

consumers to quantify fairness. 2 I define as qualitatively fair activities those activities that may

not be fittingly quantified, and I assert that such activities are governed by societal norms,

safety protocols, and various rules and regulations against unethical and illegal pursuits. For

example, skydiving, is considered safe when it follows rules and regulations set up by the

Federal Aviation Administration (2024) and the United States Parachute Association (2024).

Qualitatively unfair thrill-seeking activities are undertaken subject to non-compliance with, or

lack of, norms, rules, and regulations, such as among others, snow skiing down the mountain

despite an avalanche warning, compulsive or pathological gambling, illegal speeding, use of

unhealthy, illicit, or unsafe products / services / substances that may imperil those who use

them and society at large.

In this paper I am concerned with fair thrill-seeking activities or services, and I assume that the

consumer who chooses not to undertake such an activity is risk-averse whereas the one who

chooses to do so is risk-loving. For example, it is estimated, as reported by today.yougov.com

(2023), that 29% of Americans embark on regulation-abiding snow skiing which implies that

71% Americans are risk-averse towards snow skiing and 29% risk-loving. But not every

activity undertaken by the 71% segment is risk-averse or every activity undertaken by the 29%

segment is risk-loving. In the remaining of the paper, I propose a portfolio-type wellbeing

model in section II and then I use a simulation-based numerical example or thought experiment

in section III. In turn, I discuss implications and some real world data in section IV and conclude

with a summary and conclusion in section V.

A PORTFOLIO-TYPE WELLBEING MODEL

I assume that consumers simultaneously consider risk-averse and risk-loving activities or

services depending on rewards and tolerability of risks. More specifically, I assume that

consumer wellbeing depends on a diversified portfolio of risk-preference expected reward

outcomes and their variabilities. For example, given random monetary returns, a consumer, for

peace of mind (a factor contributing to happiness), may wish to buy home insurance coverage,

screen the decision through a risk-averse reward function and calculate a set of risk-averse

1 This quotation is part of the title of a book by Koon, Powell and Carrol (2008).

2 Quantitatively, the concepts of fair / unfair may be explained, as per convention, in conjunction with a game of luck

or lottery:

- A game is fair to both house and player when Expected Value = 0. For example, the player has a 50/50 chance of

making or paying $10.

- A game is unfair or more than fair to the house when the player’s Expected Value < 0. For example, the player has a

50/50 chance of making $10 and paying $20.

- A game is unfair or more than fair to the player when the player’s Expected Value > 0. For example, the player has a

50/50 chance of making $20 and paying $10.

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Kantarelis, D. (2024). Wellbeing and Fair Thrill-Seeking Rewards (*). Advances in Social Sciences Research Journal, 11(1). 175-187.

URL: http://dx.doi.org/10.14738/assrj.111.16267

expected rewards. Simultaneously, the same consumer, for a rush of adrenaline (a factor that

also contributes to happiness), may wish to undertake regulation-abiding skydiving, screen the

decision through a risk-loving reward function and calculate a set of risk-loving expected

rewards. Additionally, the consumer may wish to invest in risky assets for maximum return

subject to a risk-neutral reward function and calculate a set of risk-neutral expected rewards.

In turn, the consumer may consider the sets of expected rewards as assets to form a portfolio

with the objective to maximize expected wellbeing as a function of expected portfolio return

and portfolio risk subject to percentages of importance for each product, service or activity

included in the decision. To further clarify, consider a game of luck between house and player

from the point of view of the player who owns a certain amount of money (M). The house

proposes a zero-fee game involving random gains and losses based on which the player

calculates a set of wealth values (W) consisting of [(M + gain), (M - loss)]. The game is played in

many trials and each trial is based on a new random probability distribution 3. The player

screens W through a reward function Ri = Ri(W) and derives a distribution of random expected

reward observations E(Ri), their rate of return Xi with mean E(Xi) and sample standard

deviation S(Xi) 4. In turn, the player considers a portfolio of E(Xi) distributions and calculates

expected portfolio return (EPR) as well as portfolio standard deviation (PSD), conditioned on

the percentages of importance (ki) placed on each i. Undertaken thrill-seeking activities may be

equally or unequally weighted in terms of importance. I assume that importance may be

expressed as a percentage (the higher the more important) and that all assigned percentages

sum up to “1”. I also assume that “1”, the sum of k percentages, may be considered a proxy for

income available to the consumer. For example, the consumer would be willing to allocate a

higher percentage of income on thrill activity A than on B (both assumed normal and weak

substitutes) because A is more important or appealing. Functions (1) to (3) below summarize

the above, where (2) and (3) form the portfolio’s efficient frontier (EF):

∑ ki

n

i=1 = 1 (1)

EPR = Expected Portfolio Return = ∑ ki

n

i=1 E(Xi

) (2)

PSD = Portfolio Standard Deviation = [∑ ∑ kikjCov(XiXj

n

j=1,j≠i

n

i=1

)]

1

2

(3)

Finally, the consumer chooses (2) and (3) to maximize expected wealth E(W) subject to (1), or

Maximize E {W [EPR, PSD]} (4)

subject to ∑ ki

n

i=1 = 1. Wealth function (4) may be specified to reflect risk-aversity with less or

more risk-tolerance. With a thought experiment, I will show that the optimization process

generates results like those in Figure 1; the figure portrays EPR against PSD - the efficient

frontier (EF) - in conjunction with two possible, simultaneously considered, expected wealth

3 Circumstances in life change periodically, in some cases daily. For example, the probability of home fire tomorrow may

be lower or higher than today depending on various causes such as improved or worsen safety, random events, crime,

etc.

4 Alternatively, Wi values specific to the Ri function could be used.