Exploring the Interplay of Cultural Restraint: The Relationship between Social Media Motivation and Subjective Happiness

Abstract

This study aims to investigate the intricate relationship between social media motivations and subjective happiness, utilizing a novel framework based on the uses and gratifications theory and cultural restraint. Through a quantitative analysis using structural equation modeling (SEM) of a sample of 391 young Jordanian adults, the findings reveal a surprising positive correlation between social media motivations and subjective happiness, with cultural restraint emerging as a critical moderator in this dynamic. Cultural restraint negatively moderates the relationship between social media motivations and subjective happiness. By shedding light on the powerful role of cultural factors in shaping our relationship with social media, this study offers essential insights for practitioners seeking to enhance user experiences and maximize well-being. This research expands upon existing knowledge, providing a fresh perspective on the interplay between motivation and happiness, and highlighting the potential for understanding cultural restraint to unlock greater happiness and fulfillment in the digital age. The findings indicate that the positive impact of social media motivations on subjective happiness may be influenced by the level of cultural restraint within a society.

1. Introduction

The rapid spread of social media platforms worldwide has made them a daily habit for many users. Social media is a popular application that has emerged from the evolution of Web 2.0 technology, used by people to maintain contact and share videos of themselves, places, pets, and other valuable things (Alhabash and Ma 2017; Choi and Noh 2020; Al-Majali et al. 2021). While social media has positive effects, such as providing a platform for socializing and promoting awareness, it can also negatively impact subjective happiness. Many studies have explored the link between social media use and subjective happiness, revealing that the motivations behind social media use play a crucial role in determining its impact (Kim et al. 2020; Verduyn et al. 2017). Understanding the correlation between social media motivations and subjective happiness is important, as it can inform strategies for promoting healthy social media use and enhance overall well-being.

The popularity of internet/social media studies is reflected in several recent studies (Kwon and Park 2020; Doğan 2016). Some studies have associated electronic media usage with lower psychological well-being (Twenge 2019; Mathers et al. 2009). However, Doğan (2016) found social media usage to be an essential predictor of happiness and life satisfaction.

The correlation between social media platforms and subjective happiness, whether positive or negative, remains a topic of controversy. Studies support both sides, with some suggesting that social media platforms have a positive relationship with subjective happiness or well-being, particularly social media, which allows individuals to communicate and socialize freely (Chiu et al. 2013; Phu and Gow 2019). Happiness and well-being are often used interchangeably, and Tien et al. (2021) defines happiness as an individual’s perception of pleasure throughout life. The individual’s emotional well-being determines their subjective well-being (Armbrecht and Andersson 2020; Hashemiannejad et al. 2016; Veenhoven 2012).

Previous studies have focused on the impact of social media platforms on happiness, rather than the motivations that drive their use. The use and gratification theory suggests that understanding motives is key. This study explores the impact of social media motivations on subjective happiness, discussing the latest research findings and practical implications. It aims to fill the gap in the previous literature by answering the following question:

Q1: What is the relationship between social media motivation and subjective happiness?

The relationship between social media platforms and subjective happiness remains unsettled, with some studies suggesting it is beneficial while others claim it is harmful. The impact of social media platforms on happiness remains a topic of debate in the literature. Some studies suggest that social media use is beneficial for happiness, as it provides opportunities for social interaction, self-expression, and social support (Valkenburg and Peter 2009; Oh et al. 2014). On the other hand, there are studies that claim social media use can be harmful to happiness due to factors such as social comparison, FOMO (fear of missing out), and excessive screen time (Vogel et al. 2014; Kross et al. 2013; Verduyn et al. 2017). This highlights the complex relationship between social media use and subjective happiness, warranting further investigation to better understand the underlying mechanisms and factors at play. Understanding and explaining these inconsistent findings are essential for clarifying the possible consequences of social media use (Pelet et al. 2017; Tosun 2012; Kim and Lee 2011). The difference in results may be related to culture, particularly as studies are conducted in different countries. Hofstede’s Model of Cultural Values provides a dimension named indulgence versus restraint, which reflects the extent to which a society responds to basic human needs. A high IVR score suggests that feelings and primitive human needs are less constrained by social norms and restrictions regarding the enjoyment of life, while a low IVR score indicates that such needs are more regulated by strict social norms (Hofstede et al. 2010). Cultural restraint plays a key role in controlling the motivation of social media platforms and their impact on human behavior (Hatamleh et al. 2020). Studies that consider cultural dimensions arrive at contradictory conclusions regarding their influence on online behavior (Chwialkowska and Kontkanen 2017).

Therefore, this study aims to fill the gap in the previous literature by answering the following question:

Q2: What is the moderating role of cultural restraint on the relationship between social media motivation and subjective happiness?

2. Literature Review

2.1. Theoretical Foundation

2.1.1. Usages and Gratifications Theory (UGT)

UGT is an age-old concept that provides a deep understanding of the motives and uses of media platforms and their power. In line with Katz et al. (1973), as mentioned in Ruggiero (2000), social and psychological benefits can be derived from mass media exposure. Media research commonly uses the UGT approach to understand why and for what people use media (McQuail 1983). In order to better understand media use motivations, this study uses the UGT conceptualization.

To effectively use media, one must understand the psychological and social contexts in which it occurs (Rubin 2002). Media consumption may be a path for individuals to fulfill their information needs, and a subtradition of media effect studies exists, focusing on uses and gratifications. (UandG) (McQuail 1994).

Research has shown that non-interactive electronic media has fewer personal characteristics than interactive media (teletext or videotext). Cowles (1989) suggests that media gratification will be a good subject for upcoming research in digital media, and such research will be most effective when it takes place within the context of an individual’s absolute media atmosphere.

The UGT has been improved throughout the years by several media scholars to obtain a superior understanding of user motivations. Initially, 35 needs of mass media were developed and consequently categorized into five main classifications by Katz et al. (1973): (1) cognitive needs (knowledge, understanding, and acquiring information); (2) affective needs (pleasure, emotion, and feeling); (3) individual integrative needs (stability, status, and credibility); (4) social integrative needs (interacting with friends and family); and (5) tension release needs (diversion and escape) (Khan 2017).

There are several motivations that drive individuals to use social media. One of the most commonly cited motivations is socialization, which refers to the desire to connect with others and maintain relationships. Social media allows individuals to stay in touch with friends and family, meet new people, and join online communities (Lin and Lu 2011).

Another motivation for using social media is self-presentation. Social media platforms enable individuals to construct and manage their online identities, express their opinions and values, and showcase their accomplishments. This can lead to increased self-esteem and validation, as well as the ability to form new social connections (Luo and Hancock 2020; Fox and Rooney 2015).

Entertainment is another key motivation for social media use. Social media offers a variety of entertaining content, including videos, photos, and memes. It also provides a platform for sharing and discovering new forms of entertainment (Khan 2017; Hatamleh et al. 2020; Turel and Serenko 2020).

Furthermore, information seeking is a motivation for social media use. Many individuals use social media to keep up with news and current events, learn about products and services, and gain knowledge about specific topics (Buzeta et al. 2020; Hatamleh et al. 2020).

Recent studies have explored the motivations behind social media use based on the UGT framework. For example, Buzeta et al. (2020) studied Facebook, Lee et al. (2023) and Hatamleh et al. (2020) studied social media, Khan (2017) studied YouTube, and Sheldon and Bryant (2016) studied Instagram. These studies identified seven primary motivations: (1) information seeking, (2) information giving, (3) self-status, (4) social interaction, (5) entertainment, (6) being fashionable, and (7) relaxation.

Additionally, the advent of social media platforms further expanded the scope of UGT research. Ellison et al. (2007) found that Facebook users derived gratifications such as relationship maintenance, social capital, and self-presentation. Sundar and Limperos (2013) identified three main gratifications for Twitter users: information, social presence, and self-expression. Furthermore, Alhabash and Ma (2017) found that users sought information, entertainment, and social interaction from the internet. LaRose and Eastin (2004) discovered that people used the internet for habituation, social interaction, and information seeking.

In summary, the uses and gratifications theory (UGT) has been a valuable tool for understanding the motivations behind media consumption, including social media use.

2.1.2. Hofstede Cultural Dimensions Indulgence vs. Restraint (IVR)

Cultural differences play a crucial role in shaping human behavior, attitudes, and beliefs. One such dimension of culture that has garnered significant attention in recent years is the concept of cultural indulgence versus restraint. Cultural indulgence refers to cultures that value pleasure and gratification, while cultural restraint refers to cultures that emphasize self-control and suppression of desires. This dimension has been shown to have critical implications for a range of outcomes, including individual behavior, economic development, and political ideology (Hofstede et al. 2010).

Cross-cultural research has shown significant differences in the level of cultural indulgence versus restraint across different cultures. For example, countries in Latin America, the Caribbean, and Southern Europe tend to score higher on the indulgence dimension, while countries in East Asia and the Middle East tend to score lower (Hofstede et al. 2010; Minkov 2011). These differences can be explained by a variety of factors, including religion, climate, and historical and political factors. For instance, countries with a strong religious tradition, such as Saudi Arabia, tend to have lower scores on the indulgence dimension due to the emphasis on self-control and suppression of desires (Schwartz 1999).

In 2010, a final dimension was included to capture more recent research conducted related to happiness. In part, this dimension was derived from research conducted by Bulgarian sociologist Michael Minkov, who created the extensive World Values Survey (Chudnovskaya and O’Hara 2022). Human needs and desires are highly valued in indulgent societies; to conform to society’s norms, a restrained society curbs desires and withholds pleasures. “Indulgent cultures will tend to focus more on individual happiness and well-being, leisure time is more important, and there is greater freedom and personal control. This is in contrast with restrained cultures where positive emotions are less freely expressed and happiness, freedom, and leisure are not given the same importance” (Ruiz-Equihua et al. 2020).

In contrast, cultures that score higher on the restraint dimension tend to have stronger social norms and a greater emphasis on self-discipline, which can lead to higher levels of savings and economic development (Weber 1905; Minkov 2011). Moreover, cross-cultural studies have shown that indulgence versus restraint is associated with different political ideologies, with cultures that score higher on the indulgence dimension tending to be more politically liberal and cultures that score higher on the restraint dimension tending to be more politically conservative (Inglehart and Baker 2000; Minkov 2011).

According to Hofstede et al. (2010), several unique characteristics of IVR that indicate either restraint or indulgence can be observed within any culture. The use of IVR in organizations or national settings has remained largely unstudied, despite the recommendation in Hofstede et al. (2010) that it requires more research (Aleqedat et al. 2022; Chudnovskaya and O’Hara 2022).

This study will take place in Jordan, a developing Arab nation located in the Middle East. Globalization has led to Jordan’s involvement in change and a desire to transition from a traditional to a modern country. Developing countries have restrained cultures according to the Hofstede categorization. In Jordan, the cultural dimension scored 43 out of 50, which indicates a restrained culture. In societies where norms influence people’s satisfaction, and their satisfaction is restricted (Aleqedat et al. 2022).

Given this context, it is important to consider the role of cultural restraint in understanding the relationship between social media motivation and subjective happiness. By examining these factors in a restrained culture such as Jordan, this study aims to provide valuable insights into the moderating role of cultural restraint on this relationship. Ultimately, this research may contribute to developing more effective strategies for promoting healthy social media use and enhancing overall well-being in culturally diverse settings.

3. Hypothesis Development: Subjective Happiness, Social Media Motivation, and Culture Restraint

In society, being happy is a primary goal (Diener 2000). Happiness is something every person wants, as well as the desire of parents to see their children happy (Diener and Lucas 2004). To gain a greater knowledge of the meanings and implications of happiness, studies generally concentrate on definitions or their sources. Despite the importance of happiness for young people, little research has been conducted on this topic (Freire and Ferreira 2020). As a matter of fact, happiness is a complicated matter to examine.

Happiness is a complex emotion that has been studied extensively in the field of psychology. Researchers have proposed various definitions of happiness, often emphasizing different aspects of the emotional experience.

One of the most widely accepted definitions of happiness is the subjective well-being model, which defines happiness as a positive evaluation of one’s life (Diener et al. 1999). According to this model, happiness is composed of three components: positive affect (experiencing positive emotions), negative affect (experiencing negative emotions), and life satisfaction (the cognitive evaluation of one’s life).

Another popular definition of happiness is proposed by the positive psychology movement, which focuses on the concept of flourishing. Longobardi et al. (2020) define happiness as a state of “complete mental, physical, and social well-being,” which encompasses not only positive emotions but also meaningful engagement, positive relationships, and a sense of purpose in life.

In contrast to the subjective happiness and positive psychology definitions, some researchers have proposed that happiness is not a single, unified emotion, but rather a collection of distinct positive emotions. Fredrickson’s (2001) broaden-and-build theory suggests that positive emotions such as joy, gratitude, and love all contribute to the experience of happiness, by broadening individuals’ attentional focus and building personal resources that contribute to well-being.

Several variables have been implicated as positively or negatively influencing happiness in the literature. Individuals have dual responsibilities when it comes to social media use. Social media platforms have a positive effect on individuals’ happiness; in one sense, social media enhances life satisfaction and provides ample opportunities for self-expression or status (Talwar et al. 2019; Malik et al. 2016). In the same vein, Kaur et al. (2021b) report that self-disclosure is positively correlated with online subjective happiness.

Among the gratifications offered by social media are the opportunities to share information and self-status (Talwar et al. 2019). Consequently, gratifications could result in online subjective happiness, such as entertainment, social interaction, obtaining information, and other benefits associated with social media. Hence, it is natural to assume that social media motivation is a primary reason for subjective happiness (Kaur et al. 2021a). In addition, Phu and Gow (2019) confirm that greater use of social media platforms increases users’ friendships and supports their subjective happiness.

The rapid growth of social media platforms has transformed the way individuals communicate and interact with one another. Research suggests that people use social media for various motivations, such as information seeking, information giving, self-status, social interaction, entertainment, being fashionable, and relaxation (Whiting and Williams 2013). These motivations might influence individuals’ subjective happiness, which is a self-reported measure of how happy or satisfied a person feels with their life (Lyubomirsky and Lepper 1999).

In light of the use and gratification theory discussed previously and the above discussions, this study will test the following hypothesis:

H1. 

Social media motivation (“information seeking,” “information giving,” “self-status,” “social interaction,” “entertainment,” “being fashionable,” and “relaxation”) have a positive relationship with subjective happiness.

The rationale behind this hypothesis is that social media can provide individuals with opportunities for social support, self-expression, and a sense of belonging, which are essential components of subjective happiness (Valkenburg and Peter 2009). For example, information seeking and giving can help individuals stay connected with friends and family, and being informed about current events and trends might contribute to their overall well-being (Oh et al. 2014). Similarly, self-status, social interaction, and entertainment can lead to increased self-esteem and social connectedness, which are known to contribute to subjective happiness (Valkenburg and Peter 2009). Lastly, using social media for relaxation and being fashionable may provide users with a sense of escapism and enjoyment, which can positively impact their subjective happiness (Turel and Serenko 2012).

The widespread use of social media has become a common feature across many cultures, and its impact on subjective happiness has been a topic of research interest. However, the relationship between social media use and happiness may be influenced by the degree of cultural restraint present in a particular culture (Lin et al. 2016).

Recent studies suggest that cultural restraint moderates the relationship between social media engagement and subjective happiness (Hu et al. 2018). Social media motivation encompasses the reasons individuals engage with social media, such as socializing, entertainment, or information seeking. Individuals from cultures with high levels of cultural restraint tend to use social media for practical or informational purposes rather than for socializing or entertainment. As a result, social media use may have a less significant impact on their subjective happiness compared to those from cultures with lower levels of cultural restraint, who primarily engage with social media for socializing or entertainment (Chua and Chang 2016).

People from different cultures may value various aspects of life, leading to distinct perceptions of individual well-being under similar objective circumstances (Dorn et al. 2007). The concept of indulgence versus restraint highlights the importance of societal norms in restraint-oriented societies, which regulate gratification in different aspects of life (Fournier 2022). Hofstede’s theory did not specifically address the virtual world, such as social media platforms. Nevertheless, cultural restraint influences motives and uses in both real and virtual environments. Consequently, higher cultural restraint is associated with lower individual happiness (Su 2022).

The rise of social media has significantly affected individuals’ psychological well-being, including subjective happiness—a self-reported measure of life satisfaction and happiness (Lyubomirsky and Lepper 1999). While social media offers a platform for social interaction and self-expression, it can also promote social comparison and FOMO (fear of missing out), potentially undermining subjective happiness (Vogel et al. 2014). Furthermore, culture plays a critical role in shaping people’s behaviors, attitudes, and values, and may moderate the relationship between social media motivation and subjective happiness.

Considering Hofstede’s cultural dimension of indulgence versus restraint and the above discussion, the following hypothesis will be tested:

H2. 

Cultural restraint moderates the relationship between social media motivation and subjective happiness.

This hypothesis is informed by the cultural dimension of indulgence versus restraint, as proposed by Hofstede et al. (2010). In high-restraint cultures, people are more likely to suppress their desires and impulses in order to conform to societal norms and expectations, whereas individuals from indulgent cultures are more likely to pursue personal gratification and enjoyment (Hofstede et al. 2010). Therefore, it is plausible that individuals from high-restraint cultures may be less influenced by social media motivations, as they are more likely to prioritize societal norms over personal desires, resulting in a weaker relationship between social media motivation and subjective happiness. Please refer to Figure 1, which provides a summary of the hypotheses developed for this study.

4. Methodology

In this study, a quantitative research approach was employed to investigate the relationship between various independent variables and a moderating variable. Given the prevalence of self-administered questionnaires in Jordanian settings and their higher response rates, this method was chosen for data collection.

A convenience sampling technique was utilized in this study. Convenience sampling is a non-probability sampling method that relies on factors such as availability, proximity, or expertise of the individuals being studied, rather than randomness (Bougie and Sekaran 2019). The target population for this study consisted of university students and young adults of the public. According to the Department of Statistics in Jordan, there are approximately two million young adults in the country aged between 18 and 25.

To collect the data for this convenience sample, participants were given self-administered questionnaires. The instructions provided to the participants emphasized this study’s purpose, confidentiality, and anonymity. Participants were informed about the voluntary nature of their participation and their right to withdraw at any point without any repercussions. They were also instructed to answer the questions honestly and to the best of their ability. Upon completion, participants were thanked for their time and contribution to this study.

4.1. Selection of Sample Size

The present study adhered to the estimation of sample size according to Krejcie and Morgan’s sample size table (Krejcie and Morgan 1970). The present study’s subjects consisted of approximately two million young adults and more from six sampling segments that were divided into two parts. The first part had three sampling segments of young adults from public places, while the second part had three sampling segments of universities in Jordan. Krejcie and Morgan’s sample size table specifies that a 384-individual sample size is recommended for a given population of one million young adults. Hence, the sample size for this study was finalized at (N = 440) young adults from the six sampling segments of public places and universities in Jordan. After distribution, 391 valid questionnaires were received.

4.2. Data Analysis

This study investigated hypotheses and analyzed the developed research model using partial least squares (PLS) analysis. PLS allows the examination of multiple relationships simultaneously. Specifically, PLS models can be used to investigate complex models that include a number of variables and relationships and can accommodate small samples. PLS-structural equation modeling (PLS-SEM) incorporates both an outer and an inner model (Hair et al. 2014). In the outer model, constructs and indicators are evaluated for their reliability and validity, while in the inner model, hypotheses are evaluated for their significance.

5. Measurements Scale, Construct Reliability, and Validity

There are four items on the subjective happiness scale. Each item was rated between 1 (Completely Disagree) and 7 (Completely Agree). All items were rated on a 7-point Likert scale. The results of the four items were averaged, with a higher average score indicating a higher level of subjective happiness. The subjective happiness scale demonstrated good convergent validity and discriminant validity (Lyubomirsky and Lepper 1999).

Social media motivations (information seeking, information giving, self-status, social interaction, entertainment, being fashionable, and relaxation) items were adopted from Khan (2017) and Whiting and Williams (2013). The items were rated from 1 (very unlikely) to 7 (very likely) on a Likert scale of 1–7. A high degree of reliability and convergent validity was demonstrated for the social media motivations scale.

A 4-item scale measuring culture restraint was adopted from Al Omoush et al. (2012). Each item was rated on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Hair et al. (2021, p. 77) explains that composite reliability rho values of 0.60 to 0.70 are considered acceptable in exploratory research, while values between 0.70 and 0.90 range from “satisfactory to good.”

Table 1. Measurements scale, construct reliability, and validity: composite reliability (CR) and average variance extracted (AVE).

Variables		Items		CR	AVE
Social Media Motivation-Second Order	Information Seeking—First Order	IS1—“I use social media to obtain information about things that interest me.” IS2—“I use social media to keep up with current issues and events.” IS3—“Social media helps me to store useful information.” IS4—“I use social media to learn about what is new.”	(Khan 2017) CR = 0.862	0.962	0.845
	Giving Information—First Order	GI1—“I can provide others with information using social media.” GI2—“I use social media to contribute to a pool of information.” GI3—“I use social media to share information that might be entertaining to others.” GI4—“I use social media to share information that might be useful to others.”	(Khan 2017) CR = 0.852
	Self-Status—First Order	ST1—“I use social media to impress other users.” ST2—“I use social media to make myself look cool.” ST3—“I use social media because I want to be popular.”	(Khan 2017) CR = 0.854
	Social Interaction—First Order	SI1—“Social media allows me to stay in touch with other users.” SI2—“Social media lets me meet interesting people.” SI3—“Social media makes me feel like I belong to a community.” SI4—“Social media connects me with people who share some of my values.”	(Khan 2017) CR = 0.919
	Entertainment—First Order	E1—“Social media helps me pass the time when I am bored.” E2—“Social media helps me to get away from pressures.” E3—“I use social media to play.” E4—“Social media can help me to experience enjoyable media content.” E5—“Social media is full of excitement.” E6—“Social media is unique.”	(Whiting and Williams 2013) CR = 0.907
	Relaxation—First Order	R1—“Social media helps me to relax.” R2—“Social media relieves stress.” R3—“Social media provides me with many hours of leisure.” R4—“Social media takes my mind off things.”	(Whiting and Williams 2013) CR = 0.840
	Fashionable—First Order	F1—“I use social media to look fashionable.” F2—“I use social media to look stylish.” F3—“I use social media because everyone else is doing it.”	(Khan 2017) CR = 0.811
Culture Restraint		CR1—“I believe that emotions should not be shown openly on social media.” CR2—“I typically wait for the correct time to comment on certain issues on social media.” CR3—“I think that I should be able to enjoy my life using social media.” CR4—“I think that I should be able to enjoy my leisure time using social media.”	(Al Omoush et al. 2012)	0.870	0.707
Subjective Happiness		SH1—“In general, I consider myself.” SH2—“Compared to most of my peers, I consider myself: SH3—“Some people are generally very happy. They enjoy life regardless of what is going on, getting the most out of everything. To what extent does this characterization describe you?” SH4—“Some people are generally not very happy. Although they are not depressed, they never seem as happy as they might be. To what extent does this characterization describe you?”	(Lyubomirsky and Lepper 1999)	0.908	0.784

shows composite reliability for all constructs was between 0.811 and 0.962, which is considered “satisfactory to good.” Furthermore, the results of the average variance extracted (convergent validity) are at an acceptable level, which should be AVE ≥ 0.50 (Hair et al. 2021). As shown in Table 1, all variables have average variance extracted values greater than 0.50.

An item’s factor loading indicates how well it represents its underlying construct. It is recommended to have a factor loading of over 0.70 (Vinzi et al. 2010). All items had factor loadings between 0.73 and 0.91.

In this study, we propose that social media motivation is a second-order construct. Second-order constructs, also known as higher-order constructs, are latent variables that are influenced by multiple first-order constructs (Becker et al. 2012). In the case of social media motivation, it can be conceptualized as an overarching construct that encompasses various underlying dimensions, such as information seeking, information giving, self-status, social interaction, entertainment, being fashionable, and relaxation (Whiting and Williams 2013; Khan 2017). The existence of these multiple dimensions provides theoretical evidence supporting the classification of social media motivation as a second-order construct.

Furthermore, we argue that social media motivation is reflective in nature. Reflective constructs are characterized by the presence of indicators that are caused by the latent variable and are expected to covary (Hair et al. 2021). In the context of social media motivation, the underlying dimensions (e.g., information seeking, information giving, self-status, social interaction, entertainment, being fashionable, and relaxation) are manifestations of the broader social media motivation construct. These dimensions are expected to covary as they all contribute to explaining the overall motivation for using social media platforms (Alhabash and Ma 2017; Smock et al. 2011).

The existing literature on social media motivation supports the reflective nature of the construct. For instance, research by Sheldon and Bryant (2016) and Quan-Haase and Young (2010) found that the various dimensions of social media motivation were highly correlated, indicating the presence of a common underlying factor, which is consistent with the reflective model assumption.

By considering social media motivation as a reflective second-order construct, our research aligns with the theoretical underpinnings of the phenomenon and enables a more comprehensive understanding of its role in influencing user behavior on social media platforms. It is important to note that this conceptualization has implications for the subsequent stages of our research project, such as the choice of estimation techniques and the interpretation of results.

6. Results and Discussion

The foundation for evaluating a structural model is to test hypotheses that align with research questions. In this study, a research framework was developed, and two research hypotheses were proposed. To evaluate the structural model, Lowry and Gaskin (2014) suggest identifying the significant and effective paths that support the hypotheses and assessing the model’s predictive quality. Four criteria must be met to determine the adequacy of the structural model, involving the significance of path coefficients, the coefficient of determination (R2), the effect size (F2), and the predictive relevance (Q2) and effect size (Q2). Figure 2 depicts the structural model utilized in this research. In addition to the primary analysis, this study utilized bootstrapping to enhance the accuracy and confidence interval estimation of the sample parameters. Following the recommendations of Hair et al. (2021), our analysis was based on 5000 resamples, which ensured a robust and reliable estimation. For a detailed overview of the bootstrapping settings, please refer to

Table 2. Bootstrapping settings.

Selected Option	Reference
Sub-samples	5000	Hair et al. (2021)
Sign changes	No sign changes
Number of results	Complete bootstrapping
Cases	391

.

The Heterotrait–Monotrait (HTMT) ratio is a measure employed to assess discriminant validity in structural equation modeling (SEM) and confirmatory factor analysis (CFA). Discriminant validity concerns the degree to which different constructs’ measures are distinguishable. Henseler et al. (2015) proposed the HTMT ratio as an alternative to the traditional Fornell–Larcker criterion for evaluating discriminant validity.

Each cell in the HTMT matrix represents the HTMT ratio between a pair of constructs. Values near or greater than 1 suggest a lack of discriminant validity between the constructs, while values considerably lower than 1 indicate that the constructs are distinct. A typical threshold in the literature ranges from 0.85 to 0.90, but the choice of threshold is context-dependent.

To evaluate discriminant validity in our study, we utilized the Heterotrait–Monotrait (HTMT) ratio method, as recommended by Henseler et al. (2015). The HTMT ratios for all construct pairs were below the selected threshold of 0.85, signifying sufficient discriminant validity among the constructs (refer to

Table 3. Heterotrait–monotrait ratio (HTMT) matrix.

	Culture Restraint	Social Media Motivation	Subjective Happiness
Culture Restraint	0.773
Social Media Motivation	0.801	0.297
Subjective Happiness	0.225	0.282	0.153

for the HTMT matrix).

The bootstrapping procedure in

Table 4. Hypotheses testing results.

Hypotheses	Original Sample	Standard Deviation	T Statistics	p Values	Result
H1. Social media motivation → subjective happiness	0.282	0.060	4.660	0.000	supported

shows the T-values, significance levels, and P-values of the determinants of subjective happiness and social media motivation. All the path coefficients revealed a significance level of 0.05, utilizing the bootstrapping results. The results demonstrated that H1 was supported. Meanwhile, the highest contribution to subjective happiness was from social media motivation (β = 0.282, t-value (4.660) > 1.96).

According to Field (2013), R² is the variance in a variable shared with another. An R² value is calculated by squaring the correlation values between predicted and dependent constructs (Field 2013). Furthermore, R² indicates how the independent construct affects the dependent construct (Pallant 2011). For dependent constructs, R² values are classified as strong (0.75), moderate (0.50), or weak (0.25) (Hair et al. 2021).

Table 5. R² output.

Endogenous Construct	R2	Relationship
subjective happiness	0.79	Strong

presents the R² values from the bootstrapping technique. The R² result for subjective happiness was 0.79, which was considered strong as it indicated that 79% of the variance in subjective happiness could be justified by social media motivations (entertainment, being fashionable, giving information, information seeking, relaxation, self-status, and social interaction).

Based on Hypothesis (1), it is evident that motives for using social media platforms are positively correlated with subjective happiness. The results of this study are in line with many other studies on the use of social media platforms. Malik et al. (2016) stated that individuals are more satisfied with their lives because of social media and have plenty of opportunities to express themselves or to achieve a status that enhances their happiness. Further, social media usage has been widely found to be an important predictor of happiness, psychological well-being, and life satisfaction for individuals (Doğan 2016).

Firstly, research suggests that social media use can have positive effects on subjective happiness when used for social support and social interaction. For instance, a study by Kim et al. (2020) found that using social media for social support was positively associated with subjective well-being. Similarly, using social media for social interaction was also found to be positively associated with subjective well-being. Therefore, if people use social media to connect with friends and family, receive emotional support, and engage in meaningful conversations, it can enhance their subjective happiness.

However, the motivations behind social media use can also have negative effects on subjective happiness. For instance, using social media for social comparison, envy, and seeking validation has been found to be negatively associated with subjective well-being (Verduyn et al. 2017). Social media can create unrealistic expectations and promote a culture of comparison, where people constantly compare their lives to others and feel inadequate. This can lead to feelings of envy, depression, and anxiety, ultimately reducing subjective happiness.

Furthermore, social media use can also lead to addiction, which can negatively impact subjective happiness. Social media addiction is characterized by excessive use of social media, leading to neglect of other important activities and responsibilities, and negative effects on psychological well-being (Andreassen et al. 2017). Addiction to social media can lead to feelings of loneliness, anxiety, and low self-esteem, reducing subjective happiness.

According to Phu and Gow (2019), the increased use of social media platforms leads to increased friendships and subjective happiness among users. Further, H1 results support Kaur et al.’s (2021b) study report that self-disclosure and self-status increase online subjective happiness. Additionally, H1 results support the idea that social media provides individuals with freedom in communicating and socializing, and that social media usage is positively related to well-being (Chiu et al. 2013).

Despite this, Mathers et al. (2009) concluded that electronic media use negatively affected psychological well-being. Moreover, numerous previous studies have also extensively discussed the negative effects of social media use on individuals’ well-being—for instance, cyber stalking, fear of missing out, sleep problems induced by social media use, and negative emotions induced by social media use, including jealousy, anxiety, depression, and fatigue. Individuals’ subjective happiness is negatively affected by all these consequences of social media usage (Kaur et al. 2020, 2021a; Dhir et al. 2021; Tandon et al. 2021; Kumar Swain and Pati 2019).

However, it should be noted that previous studies focused on the use of social media platforms, while this study focused on the motivation of social media platforms, and therefore the results of H1 are completely new.

A moderator has features that may alter the path of a relationship between two constructs and shift the magnitude of the relationship (Hair et al. 2014). In the present study, the moderating effect of cultural restraint was incorporated into the model. The bootstrapping process was run with 5000 bootstrap samples as well as 391 bootstrap cases. To conduct the significance test for the moderator, the “no sign changes” option was used, and the mean was replaced for the missing values (Hair et al. 2021).

Table 6. The moderation analysis.

H2	Original Sample	Standard Deviation	T Statistics	p Values	Result
Culture Restraint → Subjective Happiness	−0.198	0.114	1.734	0.083	Supported
Social Media Motivation → Subjective Happiness	0.444	0.123	3.621	0.000
(Moderation) Culture Restraint × Social Media Motivation → Subjective Happiness	−0.102	0.051	2.006	0.045

and Figure 3 demonstrates the result for the path linking cultural restraint as a moderator, and the t-value was 2.006 (>1.96) with p = 0.045 (<0.05). Thus, H2 was supported, as the moderating effect of cultural restraint was statistically significant.

Figure 4 shows the principle of the moderating variable “culture restraint”; the red line represents the value of culture restraint with an SD less than −1, the lowest value, where the influence of social media motivations on happiness was at its peak. Additionally, according to the green line, social media motivation on subjective happiness was weak when culture restraint SD values exceeded +1. Consequently, the greater the cultural resistance, the lower the influence of social media platforms on happiness, hence the decrease in subjective happiness.

The result of H2 agrees with Hofstede’s cultural dimensions theory of indulgence versus restraint. Restraint is an indication that social norms curtail and regulate such gratification. Furthermore, based on H2 in this study, cultural resistance controls the influence of motives on happiness, and motives based on gratification are determined by society’s rules and the values a person is raised with. High-restraint cultures control the satisfaction of their desires and value conforming to strict social norms regarding acceptable behavior. Therefore, the indulgence vs. restraint cultural dimension is highly relevant when theorizing the importance of entertainment motives and users’ perceived freedom to respond publicly to firm-generated content in social media (Chwialkowska and Kontkanen 2017). In addition, empirical studies have provided initial support for this hypothesis.

For instance, a study conducted in China found that cultural restraint moderated the relationship between social media use and subjective well-being, with the effect being stronger for individuals with lower levels of cultural restraint (Hu et al. 2018).

The concept of indulgence versus cultural restraint refers to the degree to which a culture allows individuals to pursue pleasure and immediate gratification versus the degree to which it restricts these behaviors in favor of more long-term goals (Hofstede 2011). This cultural dimension has been found to have a moderating effect on the relationship between social media motivation and subjective happiness. Specifically, cultures high in indulgence tend to have a weaker relationship between social media motivation and subjective happiness, while cultures high in cultural restraint tend to have a stronger relationship.

Research has found that social media use can have both positive and negative effects on subjective happiness, depending on the motivation for use (Kircaburun and Griffiths 2018). For example, seeking social interaction and giving or receiving information can increase happiness, while using social media for self-promotion or escapism can decrease it (Tarafdar et al. 2015; Caplan 2010). However, cultural restraint can moderate these effects, as it influences the extent to which individuals are allowed to pursue these motivations.

The habit of smiling as a suspect is common in restrained societies because people are less happy and have less leisure time to enjoy themselves (Aleqedat et al. 2022). This concept from Hofstede’s theory aligns with H2; however, Al Omoush et al. (2012) examined the impact of cultural values on Facebook as a case study. Indulgence versus restraint, the sixth dimension of culture, is not yet empirically validated on social media, confirming that cultural restraint does not affect social media motivation and usage. Based on this result, it is recommended to test indulgence versus restraint differently, for example, as a moderating variable. Hofstede’s cultural dimensions aside, social media users can plan their activities and share information based on the motivation that drives their target audience and platform providers (Pal 2018).

Moreover, despite its importance as a moderator, cultural restraint has not received much attention. Cultural restraint has been studied either as a dependent variable (Enkh-Amgalan 2016), an independent variable (Rabaa’i 2016; Irawan 2017; Aleqedat et al. 2022), or a dependent variable (Al Omoush et al. 2012; Enkh-Amgalan 2016). Cultural restraint is not well investigated as a moderating factor since there is very little research on it.

7. Contribution

The present study aims to address multiple gaps, making several important contributions in a balanced and measured manner. Theoretical contribution: This study highlights that the theory of use and gratification has a fundamental limitation, as it explains the use and motives behind any medium and its impact. However, the theory does not provide any explanation as to why the effect of motives of use may differ from one study to another. This study partially addresses this issue by combining the theory of use and gratification with the cultural dimension of “indulgence versus restraint.” Cultural restraint governs the motives of use based on societal norms, and while Hofstede applied the theory to the real world, this study applies the theory to the virtual world. The results suggest that cultural restraints are appropriate for use in the virtual world and produce outcomes compatible with the real world.

Empirical contribution: The present study offers a comprehensive model to explain the relationship between cultural restraint, motivations, and subjective happiness. Given the cultural values of restraint that preserve customs, traditions, and societal rules, the present study provides a context for an ongoing discussion about why and how people in restrained nations are motivated to use social media, as well as the extent of its success and sustainable growth. A further contribution of this study is the examination of the relationship between social media motivations, cultural restraint, and subjective happiness.

Prior studies focused on the use of social media platforms without considering motivations for using them or the cultural context. In this study, cultural restraint is introduced for the first time as a moderating variable between motivations and subjective happiness, adding a new dimension to the existing literature.

By combining the theoretical and empirical contributions, this study provides a more nuanced understanding of the complex relationships between social media motivations, cultural restraint, and subjective happiness. This approach allows for a more comprehensive exploration of how cultural factors may influence social media use and its effects on individual well-being. By avoiding exaggerations and maintaining a balanced perspective on the impact of the results, this study encourages further research in this area, promoting a deeper understanding of the interplay between cultural dimensions, social media motivations, and subjective happiness across different contexts and populations.

8. Limitations and Future Research Directions

In future research, we recommend further exploration of the role of social media as a virtual space contributing to people’s happiness. This study primarily examined the impact of social media motivations on subjective happiness and the influence of cultural restraint on the relationship between these motivations and happiness. To validate and generalize these findings, additional research on this topic is essential.

Moreover, this study focused on indulgence versus restraint as a moderating variable based on cultural dimensions. Future research should also investigate other dimensions, such as individualism/collectivism, masculinity/femininity, uncertainty avoidance, and long-term versus short-term orientation.

A limitation of this study is its focus on the Jordanian context, which limits the generalizability of the findings to other countries. To enhance the applicability of these results, further research should be conducted in other regions, including the broader Middle East and North Africa.

It is important to note that this study employed the convenience sampling technique, which may introduce potential biases and limit the generalizability of the findings. For future research, we recommend using a simple random sampling method to enhance the representativeness of the sample and reduce potential biases, ultimately improving the applicability of the results.

Taking these limitations and suggestions for future research into account, it is essential to continue examining the complex relationships between social media motivations, subjective happiness, and cultural dimensions across various contexts and populations.

9. Conclusions

In this study, it was concluded that social media motivations and cultural restraints are key factors that impact subjective happiness. To enhance subjective happiness, social media motivations (information seeking, information giving, self-status, social interaction, entertainment, fashion, relaxation) play a significant role. An individual’s motivations for using social media platforms greatly influence their level of happiness. There is a correlation between a higher level of motivation for social media use and a higher level of subjective happiness related to social media use. However, cultural resistance is a crucial element in the relationship between subjective happiness and motivations, as it controls how social media motivations influence subjective happiness. It has been demonstrated that the greater the cultural restraint, the less social media motivations have an influence on subjective happiness, resulting in a decrease in subjective happiness. In the virtual world, particularly on social media platforms, individuals in restrained nations may be less happy due to cultural restraint.

Through this research, it has been concluded that social media motivations and cultural restraints are key factors that impact subjective happiness. This study revealed that social media motivations, such as information seeking, social interaction, and entertainment, have a significant influence on an individual’s level of happiness. In fact, a higher level of motivation for social media use is correlated with a higher level of subjective happiness related to social media use. However, cultural resistance is a crucial element in this relationship, as it controls how social media motivations influence subjective happiness. Our findings suggest that the greater the cultural restraint, the less influence social media motivations have on subjective happiness, resulting in a decrease in overall subjective happiness. Specifically, individuals in cultures with higher levels of restraint may be less happy in the virtual world, particularly on social media platforms. By understanding these factors, individuals and practitioners can take steps to promote healthy social media habits that enhance subjective happiness while considering cultural restraints.