The Relationship Between Leisure Satisfaction and Individual Innovativeness Behavior: A Study of Young Individuals

ABSTRACT

This study aims to categorize the leisure satisfaction and innovativeness levels of young individuals and thereby reveal the effect of leisure satisfaction on individual innovativeness behavior. A study group of 639 young individuals between the ages of 15-24 in Turkey was surveyed. The data were analyzed with SPSS 15 and AMOS 18 software. The effect of leisure satisfaction of young individuals on individual innovativeness behavior was tested by Structural Equation Modeling, with results determining that the leisure satisfaction of young individuals was high (x̄ = 3.61) and innovativeness behavior levels low (x̄ = 63.50). A positive, low-level and significant relationship was found between leisure satisfaction and individual innovativeness behaviors determined to be in the “Early Majority” group. Therefore, leisure satisfaction is an important predictor of individual innovativeness behavior, with such satisfaction explaining 45% of those behaviors.

Keywords: Young Individuals, Leisure, Leisure satisfaction, Individual innovativeness.

INTRODUCTION

Leisure is accepted as a period in which individuals freely participate in activities, experience positive emotions such as happiness, fun and pleasure, and make new friendships (Iwasaki et al., 2010; Thangavhuelelo, 2013). Merelas-Iglesias and Sanchez-Bello (2019) associate leisure with pleasurable and rewarding experiences that take individuals out of their daily routine and away from the stress and complexity of life. Hurd et al. (2023) define leisure time as a period of time that is free from the time allocated to basic life activities and work responsibilities, without senses of obligation and compulsion. In this respect, the positive utilization of time contributes to the physical, social and health development of individuals, the quality of life and the wellbeing of societies (Cho, 2019). Modern societies with high awareness of this often keep leisure at the top of the issues they attach importance to (McLean and Hurd, 2012).

Individuals participate in various activities in their leisure time (Li et al., 2021). These activities play a key role in developing social relationships and reducing the stress and tension caused by a busy work life (Soyer et al., 2019). Wang et al. (2012) explain leisure activities as the voluntary participation of individuals in activities outside of their daily routines and state that these activities are an important component of a healthy lifestyle. Describing the benefits of participating in leisure activities as unlimited, Eskiler et al. (2019) stated that individuals gain psychological, educational, social, relaxation, and aesthetic benefits. Takiguchi et al. (2023) state that leisure time activities activate positive emotions related to self-actualization, perceived wellbeing, and also prevent stressful experiences. To gain these benefits, it is necessary to provide satisfaction by experiencing positive emotions and perceptions after the activities (Misra and McKean, 2000). Leisure satisfaction is defined as the positive feelings that individuals create, elicit or gain as a result of engaging in leisure activity choices (Yuh, 2022). Mannell and Kleiber (1997) define leisure satisfaction as the fulfillment of desires and needs that occur after leisure activities, and Lepp (2018) defines it as an indicator of how satisfied one is with one’s leisure routine. Leisure satisfaction is a subjective state based on individuals’ previous experiences, expectations, achievements and feelings of fulfillment while participating in activities (Kuo et al., 2021). The fact that individuals obtain the desired benefit in leisure activities, fulfill their needs, and feel satisfied with these activities can provide important information for them to lead happier and more satisfying life. Moreover, it can help to develop and even enrich these activities following their satisfaction levels (Yerlisu Lapa, 2013).

Leisure satisfaction reflects individuals’ experiences after fulfilling their needs and desires for relaxation, rest, entertainment and other personal interests in their lives (Chick et al., 2020). Studies have shown that leisure satisfaction has a positive effect on many issues in individuals’ lives. For example, while leisure satisfaction affects overall life satisfaction and quality (Walker and Ito, 2017; Zhou et al., 2021), subjective wellbeing (Tian et al., 2020), job satisfaction (Koç and Er, 2020), freedom from loneliness and depression (Chang et al., 2019; Siyahtaş and Donuk, 2020), and student university life adjustments (Sönmez and Gürbüz, 2022), it also influences individuals’ happiness (Spiers and Walker, 2008) and personality characteristics (Liu, 2014; Lu and Kao, 2009). Innovativeness behavior is among these personality characteristics (Yenice and Alpak Tunç, 2019). However, to talk about innovativeness behavior, the concept of innovation needs to first be explained.

Innovation means the use of new methods in social, cultural and administrative terms (Kılıçer, 2011). The level of innovativeness and acceptance of innovation by individuals who are at the center of innovation is defined as individual innovativeness (Korucu and Olpak, 2015). In modern societies, innovation is seen as an important key to development in every aspect of technology (Kılıçer and Odabaşı, 2010). Yuan and Woodman (2010) have defined individual innovativeness as developing innovation and accepting and implementing this innovation. In another definition, individual innovation can be explained as the willingness to search for, find and implement new approaches to problem solving using today’s technology (Heydari et al., 2023). Innovativeness is stated as a behavior underlying an individual’s personality structure (Hurt et al., 1977). Variations in individual personality characteristics bring about differences in innovativeness behavior (Kılıçer, 2011). Therefore, the characteristics of innovativeness behavior such as acceptance of innovation, desire for change and risk-taking vary from individual to individual (Özgür, 2013). Considering this difference, Rogers (1995) categorized individuals exhibiting innovativeness behavior into five different groups: innovators, early adopters, early majority, late majority, and laggards. Innovators take initiative for innovation. These individuals desire change and are risk-takers who accept innovation (Coklar, 2012). Early adopters are willing to innovate and try to take risks, but also try to eliminate uncertainty about innovation by informing other members of society (Ikiz and Asici, 2017). The early majority are individuals who are cautious and hesitant to take risks. They adopt “wait and see” behaviors and want to measure other people’s reactions to innovation (Yi et al., 2006). The late majority do not tend to use technology unless they need it very much. They are skeptical toward innovation (Özgür, 2013; Yi et al., 2006). Laggards are prejudiced against innovation and skeptical of new ideas. These individuals never adopt innovation unless necessary (Yuksel, 2015).

Briefly, leisure is an important tool to increase the development, welfare and socioeconomic indicators of societies. Developed societies attach great importance to leisure and its activities. These activities and the satisfaction obtained contribute to the personality development of individuals (Lee et al., 2017). On the other hand, developing societies need individuals always willing and open to innovation. Indeed, it is seen that the driving force of the development of societies is innovation (Özsağır, 2012). In this context, this study aimed to examine the effect of leisure satisfaction on individual innovativeness behavior. This article asks the following research questions: I. What is the level of leisure satisfaction of young individuals? II. At what level and category are the individual innovativeness behaviors of young individuals? III. Is there a significant relationship between the sub-dimensions of the Leisure Satisfaction Scale and the sub-dimensions of the Individual Innovativeness Scale? And IV. Does leisure satisfaction affect individual innovativeness behavior?

METHODOLOGY

We aimed to examine the effect of leisure satisfaction on the individual innovativeness behaviors of young individuals between the ages of 15-24 living in Türkiye. Analysis was performed using Structural Equation Modeling.

POPULATION AND SAMPLE OF THE STUDY

The cohort studied was young individuals between the ages of 15-24 and the sample consisted of 698 young individuals selected between 15 December 2022 and 15 March 2023. Of these, 635 young individuals were required with a confidence level of 99% and a margin of error of ±5% according to the sample calculation, whose universe was known. A total of 698 people were first selected, which is 10% more than the sample number required for the research, and were asked to complete the questionnaire. During the evaluation of the data, 59 young individuals who filled out the questionnaire incompletely and/or did not meet the criteria for inclusion were excluded from the study. The study was completed with 639 individuals, a sufficient number.

Among the 639 young individuals constituting the research group, 416 were male (65.1%) and 223 were female (34.9%), and the average age was 16.75±2.37. It was understood that 97.5% of the participants were students, 83.7% were in high school education and 16.2% were in university education. It was determined that 43.7% of the individuals’ income was equal to their expenses and 82% of them preferred sport activities for leisure.

CRITERIA FOR INCLUSION/EXCLUSION IN THE SAMPLE

• Being a literate person,

• Living in Türkiye,

• Being between the ages of 15-24,

• Using at least one hour for leisure per week,

• Participating in at least one leisure activity (sportive/social/artistic and cultural) per week,

• Accepting participation in the research project.

Exclusion Criteria

• Not residing in Türkiye,

• Being under 15 years old or over 25 years old,

• Not completing the questionnaire forms completely.

DATA COLLECTION TOOLS

A personal information form, Leisure Satisfaction Scale (LSS), and Individual Innovativeness Scale (IIS), were used to obtain data collected through online Google Forms questionnaires. The personal information form consisted of 13 questions created by researchers following the relevant literature (Sertkaya, 2022). The LSS was developed by Beard and Ragheb (1980) to measure the leisure satisfaction levels of individuals and translated into the Turkish language by Gökçe and Orhan (2011)  as a result of a validity and reliability study. The scale, which consists of six sub-dimensions, is a 5-point Likert type (with 1- Almost Never True, to 5- Almost Always True). There are four items in each of the six sub-dimensions of the scale, consisting of 24 items: psychological (1-4), educational (5-8), social (9-12), relaxation (13-16), physical (17-20) and aesthetic (21-24). Cronbach Alpha coefficients for the sub-dimensions of the scale were found to have values ranging from .76 to .80, and the overall internal consistency was found to be .90 (Gökçek and Orhan, 2011). In this study, the internal consistency of the overall scale was calculated as .95. The IIS was developed by Hurt et al. (1977) and adapted into Turkish by Kılıçer and Odabaşı (2010). The scale has a total of 20 items, 12 of which are positive (items 1, 2, 3, 5, 8, 9, 11, 12, 14, 16, 18 and 19) and eight negative (items 4, 6, 7, 10, 13, 15, 17 and 20). The scale has a five-point rating between “Strongly Disagree” and “Strongly Agree”. The scale consists of four sub-dimensions: “Resistance to Change” (4, 6, 7, 10, 13, 15, 17 and 20), “Opinion-leading” (1, 8, 9, 11 and 12), “Openness to Experience” (2, 3, 5, 14 and 18) and “Risk-Taking” (16 and 19). Cronbach’s alpha coefficient for the overall scale was 0.82 and the test-retest reliability was 0.87. In this study, the internal consistency of the scale was calculated as .87. Innovativeness score with the help of the scale was calculated by adding 42 points to the score obtained by subtracting the total score obtained from negative items from the total score obtained from positive items. The lowest score obtainable from the scale was 14 and the highest score was 94. There were innovativeness levels and categories determined according to the mean scores obtained by individuals from the IIS. Accordingly, individuals were interpreted as “Innovative” if the calculated score was above 80 points and as “Laggard” if the calculated score was below 46 points. Individuals with a score above 68 were considered to be highly innovative, while individuals with a score below 64 were interpreted as low in innovativeness (Kılıçer and Odabaşı, 2010).

According to the scores calculated on the scale, individuals can be categorized in terms of innovativeness level and innovativeness, as presented in table 1.

Table 1
Levels and categories of IIS according to score ranges.

DATA ANALYSIS

The research data were analyzed with Statistical Package for the Social Sciences (SPSS) 15 and Analysis of Moment Structures (AMOS) 18 programs. Descriptive statistics (mean, standard deviation, minimum, maximum, number and percentage) were used. The suitability of the data for normal distribution was decided considering skewness, kurtosis values and the multivariate normality test. According to Tabachnick and Fidell (2013), skewness and kurtosis values of ±1.5 indicate that the data are suitable for normal distribution conditions. Therefore, the data of this research were found to be suitable for normal distribution as a result of ±1.5 and a multivariate normality test. In the analysis of the data, Pearson correlation analysis was used to determine the relationships between the phenomena, followed by Structural Equation Modeling with AMOS software.

ETHICAL CONSIDERATIONS AND STUDY LIMITATIONS

This research was unanimously determined to be ethical as a result of the evaluations of the Istanbul University-Cerrahpaşa Social and Human Sciences Research Ethics Committee. This research, for which permission to use the scales was obtained, was conducted following the ethical principles of the Declaration of Helsinki. Individual consent was obtained from participants aged 18 years and over, and parental consent was obtained from those under 18 years of age. The fact that only young individuals between the ages of 15-24 were included in this study and participated online created a limitation in terms of generalizability.

RESULTS

Descriptive statistics of the scales used in the study are presented in table 2. The highest mean was obtained in “relaxation (x̄=3.85)” and the lowest mean was obtained in “psychological (x̄=3.48)” sub-dimensions. The highest mean was obtained from “resistance to change (x̄=24.02)” and the lowest mean was obtained from the “risk-taking (x̄=6.91)” sub-dimension.

Table 2

Scale score distributions.

Table 3 shows the fit values of the research model established to test the Structural Equation Modeling. In this context, the fit indices of the model were determined as: the chi-square goodness of fit (χ2/df) was 6.05; the root mean square error of approximation (RMSEA) was .09; the Standardized Root Mean Square Residual (SRMR) was .04; the comparative fit index (CFI) was .95; the goodness of fit index (GFI) was .93; the adjusted GFI (AGFI) was .90; and the normed fit index (NFI) was .94 (Schermelleh-Engel et al., 2003; Meydan and Şeşen, 2015). It was understood that the chi-square and CFI values were not within acceptable limits. When the modification values were analyzed, we saw improvements were necessary. Taking these values into consideration, covariances were calculated between the error variances of the LSS and the IIS. After the modification values were improved, the fit indices reached a good fit level (χ2/df=3.07; RMSEA=.05; SRMR=.03; CFI=.98; GFI=.97; AGFI=.95; NFI=.97).

Table 3

Model Fit Values.

Table 4 shows the correlation results between the research scales and sub-dimensions. According to the results of the analyses; positive and low-level significant relationships were found between the sub-dimensions of the LSS and the sub-dimensions of the IIS.

Table 4

Correlation results related to LSS-IIS.

Note:       F1: Leisure Satisfaction, F2: Psychological, F3: Educational, F4: Social, F5: Relaxation, F6: Physical, F7: Aesthetic; F8: Individual Innovativeness, F9: Resistance to change, F10: Opinion-leading, F11: Openness to experience, F12: Risk-taking **P<,01 *P<,05.

Table 5 presents the estimation results of the Structural Equation Modeling, standardized regression coefficients (β₀), non-standardized regression coefficients (β₁), critical ratio (C.R.) and  significance (p) values for structural relationships.

Table 5

Parameter Estimations for the Structural Model.

Note:  RE: Relaxation; SO: Social; AE: Aesthetic; PS: Psychological; ED: Educational; PH: Physical; RC: Resistance to change; RT: Risk-taking; OE: Openness to experience; OL: Opinion-leading; *** p < 0.001.

When the paths in the model and the parameter estimations of the model were analyzed, all tested paths were statistically significant. When the results of the structural equation model established for the research question were examined, it was determined that leisure satisfaction (β=.67; p<0.05) predicted individual innovativeness behavior in positively and significantly. In other words, leisure satisfaction explains 45% of the total variance of individual innovativeness behavior. The results of the paths related to the research model are presented in figure 1.

Figure 1

Structural Equation Modeling regarding the effect of leisure satisfaction on individual innovative behavior.

PS: Psychological; ED: Educational; SO: Social; RE: Relaxation; PH: Physical; AE: Aesthetic; RC: Resistance to change; OL: Opinion-leading; OE: Openness to experience; RT: Risk-taking.

DISCUSSION

While this study aimed to determine the effect of leisure time satisfaction on individual innovativeness behavior; it also aimed to determine the leisure satisfaction levels, individual innovativeness levels and innovativeness categories of young individuals. Our results showed that individuals reached high satisfaction in the leisure activities they participated in (x̄=3.61). When the sub-factors were analyzed, it was determined that the highest satisfaction was reached in the relaxation sub-dimension (x̄=3.85), while the lowest satisfaction was reached in the psychological sub-dimension (x̄=3.48). Zhang and Zhu (2018) also examined satisfaction levels of women participating in leisure activities. The findings of the study showed that women reached high satisfaction in the relaxation dimension. In a study conducted by Cho (2023), it was observed that university students achieved the highest satisfaction in the relaxation sub-dimension. Other studies support our results (Ngai, 2005; Muzindutsi and Masango, 2015; Serdar et al., 2018; Tokay Argan and Mersin, 2021; Twilley et al., 2022; Ma and Li, 2023). Leisure has three basic functions: relaxation, entertainment, and development (Karaküçük, 1995). Therefore, it can be said that young individuals evaluate their leisure following its purpose and reach high satisfaction.

When the individual innovativeness levels and categories of young individuals were analyzed, it was determined that they were at a low level and in the “questioning” category (x̄=63.50). There are many studies examining individual innovativeness behaviors in different sample groups in Türkiye that support our own results (Özgür, 2013; Yılmaz Öztürk and Summak, 2014; Korucu and Olpak, 2015; Örün et al., 2015; Demircioğlu et al., 2016; Çetin and Bülbül, 2017; Atalay, 2018; Bodur, 2018; Tarhan and Doğan, 2018; Utli and Vural Doğru, 2018; Yenice and Yavaşoğlu, 2018; Yılmaz and Beşkaya, 2018; Ünal and Tosun, 2022; Şen and Kahramanoğlu, 2023). The obtained results suggest that young individuals living in Türkiye are hesitant and cautious toward innovation, do not want to take risks and wait for others’ reactions before adopting an innovation.

Another question created within the context of this research project whether there is a relationship between the sub-factors of the LSS and the sub-factors of the IIS. When the results were analyzed, a moderately significant positive correlation was detected between leisure satisfaction and the “opinion-leading” and “openness to experience” sub-factors of IIS (r=.55; p<.01), while a weakly significant positive correlation was detected between all other sub-factors between the two scales (p<.01). In other words, as individuals’ satisfaction in leisure increased, their individual innovativeness behaviors also increased. The lack of a similar study on the subject in the literature made it difficult to make comparisons with different studies. However, it is a known fact that satisfaction with one’s leisure time plays an important role in individual development. Therefore, it can be said that the findings were as expected.

This study mainly aimed to examine the effect of leisure satisfaction on individual innovativeness behavior. Leisure satisfaction has a positive effect on many aspects of individuals’ lives. Kuo et al. (2021) determined that leisure satisfaction positively affected learning performance. Chick et al. (2016) found that leisure satisfaction strongly predicts both life satisfaction and self-assessed health. Leisure satisfaction is positively related to job satisfaction and negatively related to burnout (Lee et al., 2022), and affects subjective wellbeing (Chen and Kim, 2022), work motivation (Dal and Bulgan, 2021) and perceived stress (Chung et al., 2020). Our contribution is to determine that change in individual innovativeness behavior is caused by leisure satisfaction.

CONCLUSION AND SUGGESTIONS

Innovation is an indispensable and necessary phenomenon of the modern age. The development, progress and influence of societies is enabled by the innovation of young individuals. However, research results have shown that the level of innovativeness of young individuals in Türkiye is low and that they are cautious and not risk-taking in terms of innovation.

On the other hand, with the advancement of technology and the increase in mechanization, the leisure of individuals increases day by day. Young individuals who spend their leisure time doing sportive, social, cultural and artistic activities reach high satisfaction. Research results reveal that leisure satisfaction has a significant effect on individual innovativeness behavior. In fact, almost half of individual innovativeness behavior is explained by the satisfaction obtained in leisure.

In order for young people to increase their individual innovativeness behavior levels and be in the early adopter and innovator categories, it is recommended that they should find leisure in activities that provide satisfaction. The present study was conducted with Turkish youth. The results of the study can be compared with similar studies with young people in different countries. It is recommended to repeat this study with different age or various sample groups. In further research, the possible effects of different independent variables on leisure satisfaction and individual innovativeness behavior could be determined. Free time should be taken into account when trying to improve the individual innovativeness behavior of young people. Strategies to be developed for leisure time activities can provide young people with different experiences. With this, the innovative behaviors of individual s can increase.

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