Journal of Business Research 89 (2018) 455–461 Contents lists available at ScienceDirect Journal of Business Research journal homepage: www.elsevier.com/locate/jbusres The pursuit of virtual happiness: Exploring the social media experience across generations Orie Berezana,1, Anjala S. Krishenc, ⁎,1 T , Shaurya Agarwalb, Pushkin Kachrooc a California State University, Dominguez Hills, 1000 E. Victoria Street, Carson, CA 90747, USA California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA 90032, USA c University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, NV 89154, USA b A R T I C L E I N F O A B S T R A C T Keywords: Social media networking Affect balance Virtual happiness Self-determination theory Generational cohorts FsQCA Social media environments can transform and reinforce life experiences, influencing self-concept and providing happiness. The goal of this research is to examine social media networking as an experiential phenomenon, wherein consumers pursue virtual happiness by satisfying the self-determination theory (SDT) needs of relatedness, competence, and autonomy. Beginning with the memory connection to self-concept, the study proposes an experiential outcome circle for social media to virtual happiness. A circle depicts the idea that self-concept motivates social media behavior, which influences the self-concept. Happiness, or affect balance, is a potential outcome of this connection. The study analyzes n = 504 social media networking participants using generational cohorts with fuzzy set qualitative comparative analysis (fsQCA). This study suggests the metaphors for each generation based on the following SDT recipes: (1) “we” for generation Y with relatedness and competence, (2) “me” for generation X, with autonomy and competence, and (3) “be” for baby boomers with competence. 1. Introduction Happiness can be an endless and often relentless goal for individuals in society. As consumers, individuals often traverse the marketplace, acquiring goods and services, on the path to happiness. Guevarra and Howell (2015) indicate that experiences or experiential products, such as travel, video games, or electronic devices, offer greater happiness than material ones, such as jewelry or clothing. Because the consumption of experiences versus material goods can lead to greater selfdefinition, these experiences may also result in higher levels of happiness (Bhattacharjee & Mogilner, 2014). In effect, social media platforms are also experiential products. Social media can transform and continually reinforce life experiences, both positively and negatively (Scheinbaum, 2017). For example, many social media platforms allow members to share their consumption experiences, enabling self-reflection, growth, and learning, potentially affecting their happiness (Bosangit & Demangeot, 2016). By facilitating social media experiences that positively affect the happiness and subjective well-being of target markets, marketers can more effectively engage with consumers. When an experience leads to a memory, it is more likely to shape an individual's self-concept (Carter & Gilovich, 2012). Such experiences, whether they are ordinary (common and frequent) or extraordinary ⁎ 1 (beyond everyday life), determine and affect a consumer's happiness (Bhattacharjee & Mogilner, 2014). Social media networking involves the active consumption of an experience because it allows individuals to share moments that later become a set of memories, carefully timelined and linked to virtual others throughout cyberspace. The enjoyment and happiness resulting from such shared experiences are influenced by motivations to belong and confidence in social information (Raghunathan & Corfman, 2006). As people age and traverse through different life stages, not only does their definition of happiness itself shift (Mogilner, Kamvar, & Aaker, 2011), but also their view of their lifespan, also known as the future perspective (Strough et al., 2016). Differences in the meaning of happiness stem from several types of arousal; whereas happiness for younger people can result from high states of arousal such as excitement, older people can achieve happiness from low states of arousal such as peacefulness. In a meta-analytic study of subjective well-being, Pinquart (2001) finds that as age increases, overall positive affect decreases, and high and low arousal and emotional states decline. Social media experiences enable both empowerment activities as well as social interactions. Yuksel, Milne, and Miller (2016) empirically validate differences in younger versus older consumers. They find that collegeaged consumers gain more value from socialization than older Corresponding author. E-mail addresses: oberezan@csudh.edu (O. Berezan), anjala.krishen@unlv.edu (A.S. Krishen), pushkin@unlv.edu (P. Kachroo). First two authors contributed equally. https://doi.org/10.1016/j.jbusres.2017.11.038 Received 17 June 2017; Received in revised form 25 November 2017; Accepted 28 November 2017 Available online 06 December 2017 0148-2963/ © 2017 Elsevier Inc. All rights reserved. Journal of Business Research 89 (2018) 455–461 O. Berezan et al. Fig. 1. Conceptual framework. allow individuals to be shaped by their physical and virtual experiences. The idea of a malleable self-concept has relevance when individuals feel that they are adapting to self-descriptive groups that have high psychological utility (Sim, Goyle, McKedy, Eidelman, & Correll, 2014). As such, even the process of aging itself is considered a socially constructed subjective phenomenon that results from positioning in society and an acceptance of the identity labels associated with “elderly” or “old age” (Barnhart & Peñaloza, 2013). In a study on the social media networking practices of college-aged users, Krasnova, Widjaja, Buxmann, Wenninger, and Benbasat (2015) indicate that the consumption of social information can lead to increases in envy and self-enhancement strategies and ultimately lower cognitive and affective well-being. According to a study on the happiest 10% of college students, Diener and Seligman (2004) conclude that while students need positive social relationships for their well-being, these relationships alone are not sufficient. Because linkages exist between studies on aging and generational cohorts, these are two separate but intertwined concepts. The formation of self-concept can be strongly tied to social identity, especially during younger years because it is malleable and needs further development. At the same time, generational cohorts share social, cultural, and technological experiences, that can lead to similar identity structures. consumers. Yuksel and colleagues surmise that generation effects could be the reason for this difference, and the recent research also indicates that social media provides different cognitive responses (in terms of satisfaction) with a basis in various motivational antecedents per generation (Krishen, Berezan, Agarwal, & Kachroo, 2016). The goal of the present research is to examine social media networking as an experiential phenomenon wherein consumers pursue virtual happiness in their everyday exchanges. The present study views happiness as a potential affective outcome of social media experiences and builds on the research regarding age and generational differences. First, the study offers a conceptual framework that combines the definition of self-concept, self-determination theory (SDT), and happiness (see Fig. 1). Then, through a quasi-convenience sample of 504 subjects, the study explores various motivation recipes according to SDT for each generation, using fuzzy set qualitative comparative analysis (fsQCA). Finally, the study presents conclusions, implications, and limitations to offer a broader understanding of social media networking, generational motivations, and SDT. 2. Conceptual framework 2.1. Self-concept definition and generations Because teenagers are still forming their self-identity, their activity on social media networks provides insights into their identity construction and self-enhancement (Doster, 2013). In their qualitative study of generation Y consumers, Noble, Haytko, and Phillips (2009) identify the socialization issues of freedom and self-identity (finding oneself) as their key purchasing motivations. Individuals can change their beliefs and behaviors through implicit experience-taking when they spontaneously assume the mindset of a character in a fictional novel (Kaufman & Libby, 2012). To do this, they must temporarily set aside their self-concept and allow themselves to adopt the internal traits of the narrative character. Social media is an experiential phenomenon wherein consumers identify with the characteristics of others in virtual space. Several theories, including self-verification theory, self-determination theory, and uniqueness theory, discuss identity construction as having a set of six key motives: self-esteem, continuity, distinctiveness, belonging, efficacy, and meaning. Identity structure can be delineated into cognitive and affective dimensions, with happiness serving as the strongest predictor of self-esteem, efficacy, and belonging (Vignoles, Regalia, Manzi, Golledge, & Scabini, 2006). Another interesting aspect of self-concept is the self-synchronization process that occurs as part of the construction of a socially adaptive identity, which Kawakami et al. (2012) find can enhance survival likelihood. This socially adaptive identity will change over time and through different experiences that 2.2. Self-determination theory, social media networking behavior, and happiness Self-determination theory posits that three basic psychological needs drive behavior and lead to growth, development, and well-being. They are relatedness, autonomy, and competence (Ryan & Deci, 2000; Sheldon, Abad, & Hinsch, 2011). Relatedness provides a feeling of belongingness, namely the need to connect with and develop close and affectionate relationships with others (Baumeister & Leary, 1995). The need for autonomy involves a sense of freedom and the ability to control one's own life in a way that enhances one's sense of identity (Deci & Ryan, 1985). Lastly, the need for competence refers to feelings of being able to control one's environment and the results of one's actions (Ryan & Deci, 2000). According to SDT, people must satisfy all three of these needs to experience the height of well-being, or happiness (Deci & Ryan, 2000). Indeed, the research shows that the satisfaction of these psychological needs may be a predictor of well-being, relationship quality, and happiness (Deci & Ryan, 2008; Sapmaz, Doğan, Sapmaz, Temizel, & Tel, 2012). To some degree, each of these needs motivates behaviors in daily experiences, including virtual lives. In terms of social media behavior, the research primarily evaluates SDT as a predictor of satisfaction, a cognitive outcome (Krishen et al., 2016). Ong, Chang, and Lee (2015) were among the first to explore factors that influence website-related emotions in their study on Facebook users. They stress 456 Journal of Business Research 89 (2018) 455–461 O. Berezan et al. arguably enhances its validity. As it takes a larger span of time into account, SPANE is considered to be less limiting than previous scales such as ABS and PANAS that measure affective aspects of subjective well-being (Jovanovic, 2015; Li, Bai, & Wang, 2013). The present study uses SPANE to evaluate subjective affect balance (positive minus negative reported feelings) of participants in relation to their social media behaviors over their most recent four weeks, thereby providing a measure of happiness. Fig. 1 presents a conceptual framework that combines self-concept and generations, social media networking, SDT, and affect balance, or happiness. This framework identifies the generational cohorts of gen Y, gen X, and baby boomers as salient groups to study. As the literature proposes, individuals in older generations can form memories more readily from either extraordinary or ordinary experiences whereas those from younger generations normally require extraordinary experiences to form meaningful memories. These memories then translate into a self-concept. Beginning with the memory connection to selfconcept, the present study proposes an experiential outcome circle for social media to virtual happiness. A circle depicts the idea that selfconcept motivates social media behavior, which in turn influences one's self-concept. Happiness, or affect balance, is a potential outcome of this connection. Table 1 Construct items. Construct Autonomy Relatedness Competence SPANE-P SPANE-N SPANE-B Items 1. 2. 3. 4. 5. I feel like I can be myself. I often feel like I have to follow other member's commands. If I could choose, I would do things differently. The tasks I have to do are in line with what I really want to do. I feel free to use social media networks in the way I think they can best be used. 6. I feel forced to do things I do not want to do. 1. I don't really feel connected with other people. 2. I feel part of a group. 3. I don't really mix with other people. 4. I can communicate with people about things that really matter to me. 5. I often feel alone when I am communicating with people. 6. Some people I communicate with are close friends of mine. 1. I really master my social media networking tasks. 2. I feel competent using them. 3. I am good at the things I do on them. 4. I have the feeling that I can even accomplish the most difficult social media networking tasks. 1. Positive 2. Good 3. Pleasant 4. Happy 5. Joyful 6. Contended 1. Negative 2. Bad 3. Unpleasant 4. Sad 5. Afraid 6. Angry Fuzzy construct derived from SPANE-P and SPANE-N 3. fsQCA study 3.1. Sampling and measures Data collection involves an online survey that uses a snowball collection method (n = 504); subjects are screened based on identification of their generational cohort and their membership in social networks. Snowball sampling is a quasi-convenience data collection methodology that allows for specified sampling frames (such as generational cohorts), while providing an acceptable level of bias and reducing potential estimation problems (Chen, Chen, & Xiao, 2013). Previous research utilizes this technique, for example when exploring online preferences including privacy issues (Krishen, Raschke, Close, & Kachroo, 2017), service employee affect (Rayburn, 2014), or when targeting specific demographic cohorts (Berezan, Raab, Krishen, & Love, 2015). As the present study explores social media networking, online sampling is an appropriate collection technique; while the generational cohorts are not the exact same size, they do provide acceptable ecological validity in the social media environment. All measures involved in this study are existing and validated scales, and all of the constructs have acceptable reliabilities of 0.7 or higher. Table 1 contains the scale details, and Table 2 provides the respondent demographics. the fact that emotions (affect) are as important as satisfaction (cognition) in determining happiness, both of which can ultimately motivate users to increase their behavioral commitment to a website. The current study answers their call for research by evaluating social media networking from the lens of a generational cohort as it relates to the definition of self-concept in determining one's sense of well-being, or happiness. 2.3. Affect balance and happiness No single definition exists for the term happiness, and every individual has their own perspective of what makes them happy. When asked to describe what makes them happy, people respond with vastly different answers, from sunshine to dancing, health to wealth, and successful children to a long-term love relationship. Researchers use subjective well-being (SWB) to recognize the fact that happiness is subjective and therefore individuals evaluate their own life based on their own standards (Deci & Ryan, 2008; Diener, Nickerson, Lucas, & Sandvik, 2002). Ryan and Deci (2001) recognize both hedonic (pleasure-related) and eudaimonic (meaning-related) aspects of SWB and identify hedonic well-being as focusing on happiness. Subjective wellbeing incorporates both positive and negative affect and considers the balance between the two as an aspect of happiness in measuring mood and emotion based on what is occurring in one's life. Bradburn's (1968) affect balance scale (ABS) is one of the most widely established in measuring SWB. The positive and negative affect scale is empirically validated, and the most commonly used scale in literature (PANAS; Diener et al., 2010). The hedonic balance scale evaluates positive and negative affect with three items each (HBS; Schimmack, Diener, & Oishi, 2002). A newer measure of affective well-being is the scale of positive and negative experience (SPANE; Diener et al., 2010). SPANE evaluates six self-reported positive and six self-reported negative feelings based on the participants' recall of the past four weeks, which 3.2. Procedure and analysis The survey uses a set of Likert scales to gather data as well as a set of demographic questions. To analyze the data, fsQCA allows for the identification of recipes for happiness based on generational cohorts (Emmenegger, Schraff, & Walter, 2014). The initial step in fsQCA is data calibration; or the mapping of the original values for all conditions into membership scores that range from zero to one. The survey data is divided into the following generational cohorts as per previous research: baby boomers from 1946 to 1964, gen X from 1965 to 1983, and gen Y or millennials from 1984 to 2002 (Elmore, 2014; Markert, 2004). Originally the study received 565 survey responses. Removing 61 responses due to incomplete data yielded a final data set consisting of n = 504 respondents. In the final data set, each generational cohort has an acceptable sample size for fsQCA with n = 46 for baby boomers, n = 165 for gen X, and n = 293 for gen Y. Tables 3, 4, and 5 provide the multiplicative construct scores and fuzzy-set thresholds for each of the generations, respectively. SPANE is used to assess the positive, negative, and overall affect 457 Journal of Business Research 89 (2018) 455–461 O. Berezan et al. Table 2 Sample demographics. Baby boomers Gender Highest level of education Employment status Male Female Other Total Less than high school degree High school Some college but no degree Associate degree in college (2 years) Bachelor's degree in college Master's Degree Doctorate Professional Degree Total Student only Employee for 20 h or more per week plus student Employee for over 30 h per week or full-time employee Unemployed or retired Total Reliability Autonomy Relatedness Competence SPANE-P SPANE-N Range of construct score Threshold for full non membership Maximum point of ambiguity Threshold for full membership 1–117,649 1–117,649 1–2401 1–117,649 1–117,649 1400 1080 12 4096 1 13,400 12,096 256 21,600 288 67,228 72,030 864 74,088 5400 Reliability Range of construct score Threshold for full non membership Maximum point of ambiguity Threshold for full membership Autonomy Relatedness Competence SPANE-P SPANE-N 1–117,649 1–117,649 1–2401 1–117,649 1–117,649 1764 784 16 3072 1 16,464 12,500 432 18,000 256 84,035 86,436 2401 74,088 11,250 Autonomy Relatedness Competence SPANE-P SPANE-N Reliability Frequency Percentage Frequency Percentage N % N % N % 22 24 47.83 52.17 0.00 100.00 4.35 17.39 32.61 13.04 19.57 8.70 0.00 4.35 100.00 0.00 6.52 58.70 34.78 100.00 53 110 2 165 5 18 48 32 46 15 32.12 66.67 1.21 100.00 3.03 10.91 29.09 19.39 27.88 9.09 0.00 0.61 100.00 6.06 7.88 78.18 7.88 100.00 113 177 3 293 1 34 104 112 34 7 38.57 60.41 1.02 100.00 0.34 11.60 35.49 38.23 11.60 2.39 0.00 0.34 100.00 24.57 45.73 29.01 0.68 100.00 3 27 16 46 1 165 10 13 129 13 165 1 293 72 134 85 2 293 scale. First, the two positive and negative constructs for affect are calculated and calibrated by using the standard fsQCA procedure: SPANEP and SPANE-N. The second step is to subtract the negative feelings score (SPANE-N) from the positive feelings score (SPANE-P); the resultant difference score can vary from − 1 (unhappiest) to +1 (happiest). In essence, a respondent with a score of + 1 indicates that s/he very rarely or never experiences any negative feelings and very often or always has all positive feelings. Because fsQCA requires the constructs to be the fuzzy scale of zero to one, we further process the resulting difference to determine the final score of the affect balance (SPANE-B). The absolute value of the minimum negative term is added to the difference (shifting) followed by the division of the maximum resulting number (scaling) to obtain the new construct SPANE-B. 3.3. Estimating complex causal statements (recipes) The sample is split into two subsamples, the first is a training sample (n = 23 for baby boomers, n = 83 for gen X, and n = 147 for gen Y), with the second subsample (n = 23 for baby boomers, n = 82 for gen X, and n = 146 for gen Y) providing validation for the results. 4. Results 4.1. Using original calibrated constructs Table 5 Construct descriptions: gen Y. Construct Percentage 2 46 Table 4 Construct descriptions: gen X. Construct GenY Frequency 46 2 8 15 6 9 4 Table 3 Construct descriptions: baby boomers. Construct GenX Range of construct score Threshold for full non membership Maximum point of ambiguity Threshold for full membership 1–117,649 1–117,649 1–2401 1–117,649 1–117,649 1728 686 64 1920 15 13,125 8000 625 18,000 1000 67,228 72,030 2401 63,504 15,625 The outcome construct (SPANE-B) is measured in terms of the three antecedent variables of interest, which are autonomy, relatedness, and competence. Tables 6, 7, and 8 show the recipes in the complex, parsimonious, and intermediate solutions for the three age groups. The frequency cutoff used for the three generational cohorts is 4, 13, and 19 respectively, and the consistency cutoff of 0.80 is used for the analysis. Many of the solutions qualify with high individual consistency scores that are above 0.8, along with the raw coverages meeting the desired values that fall in the range of 0.25 to 0.65 as suggested by Woodside (2013). Tables 6, 7 and 8 highlight solutions meeting the desired cutoff criterion for consistency and raw coverage. balance of the survey participants over the last four weeks (Diener et al., 2010). SPANE can derive an overall affect balance score, but can also be divided into positive and negative scales for feelings. Since the constructs in fsQCA are calculated by multiplying the corresponding items rather than adding/subtracting, the present study identifies a suitable method to derive the calibrated affect balance using a fuzzy 4.2. Testing for predictive validity To test for predictive validity, the sample randomly assigns cases to the training subsample (n = 23 for baby boomers, n = 83 for gen X, and n = 147 for gen Y) and to the testing subsample (n = 23 for baby 458 Journal of Business Research 89 (2018) 455–461 O. Berezan et al. Table 6 Solutions for baby boomers group. Table 7 Solutions for gen X group. Complex solution Frequency cutoff: 4.00 Consistency cutoff: 0.811242 ~ Competence Solution coverage: 0.711116 Solution consistency: 0.696637 Parsimonious solution Frequency cutoff: 4.00 Consistency cutoff: 0.811242 ~ Competence Solution coverage: 0.711116 Solution consistency: 0.696637 Intermediate solution Frequency cutoff: 4.00 Consistency cutoff: 0.811242 ~ Competence Solution coverage: 0.711116 Solution consistency: 0.696637 Complex solution Raw coverage Unique coverage Consistency 0.711116 0.711116 0.696637 Raw coverage Unique coverage Consistency 0.711116 0.711116 0.696637 Raw coverage Unique coverage Consistency 0.711116 0.711116 0.696637 Frequency cutoff: 13.00 Consistency cutoff: 0.838187 Relatedness Competence ∗ ~autonomy ~Competence ∗ autonomy Solution coverage: 0.813097 Solution consistency: 0.726422 Parsimonious solution Frequency cutoff: 13.00 Consistency cutoff: 0.838187 Competence Relatedness Autonomy Solution coverage: 0.864556 Solution consistency: 0.699646 Intermediate solution frequency cutoff: 13.00 consistency cutoff: 0.838187 relatedness Autonomy ∗ ~ competence ~Autonomy ∗ competence Solution coverage: 0.813097 Solution consistency: 0.726422 Predictive validity testing Training sample (n = 23) Overall solution Overall solution consistency coverage 0.600191 0.710061 Validity sample (n = 23) Overall solution Overall solution consistency coverage 0.610170 0.705925 Raw coverage Unique coverage Consistency 0.630011 0.420490 0.434671 0.185470 0.067722 0.074225 0.759688 0.804320 0.822092 Raw coverage Unique coverage Consistency 0.641298 0.630011 0.654995 0.074847 0.048862 0.083956 0.759221 0.759688 0.770014 Raw coverage Unique coverage Consistency 0.630011 0.434671 0.420490 0.185470 0.074225 0.067722 0.759688 0.822092 0.804320 Predictive validity testing Training sample (n = 83) Overall solution Overall solution consistency coverage 0.750772 0.796130 boomers, n = 82 for gen X, and n = 146 for gen Y). The test then performs a series of fsQCA to examine the recipes for SPANE-B (Wu, Yeh, & Woodside, 2014) in relation to the seven antecedents. Next, the overall solutions from the training and validation samples are compared for their ability to predict the same recipes. The last sections of Tables 6, 7 and 8 summarize the results from these analyses. The results show similar consistency and coverage for both the testing and training data sets. Overall, findings indicate that social media networking ingredients for happiness differ according to generational cohorts as follows: (1) for gen Y, relatedness and competence, (2) for gen X, autonomy and competence, and (3) for baby boomers, competence. Validity sample (n = 82) Overall solution Overall solution consistency coverage 0.764440 0.771703 present study, overlaying the generations and their social media experiences with SDT. Self-definition is malleable at a younger age. As individuals age, their self-definition becomes more defined. At an early age (gen Y and millennials in the present study), social media can allow individuals to help themselves in society. Through interacting with others, this group meets their need for relatedness and develops their individual sense of self. This is where social influence and social acceptance play a key role in the pursuit of virtual happiness for millennials. They use posting, liking, tagging, sharing, and other behaviors to help create their selfidentities (Raab, Berezan, Krishen, & Tanford, 2016). In essence, they choose social media as a way of pursuing an online identity that can lead to virtual happiness. The present study refers to gen Y as the “we” cohort wherein social influence can potentially play a key role, and therefore a balance of relatedness and competence is the recipe for virtual happiness. Hence, a key motivation for gen Y individuals when using social media is relatedness. However, because countless entities are often involved in satisfying the need of relatedness at this “we” stage, individuals have less control over the social influences that act upon their sense of well-being. This is consistent with the literature on the impact of ordinary and extraordinary events on happiness (Bhattacharjee & Mogilner, 2014). Their research shows that when individuals are younger, extraordinary experiences define one's self-concept more; whereas as they age, extraordinary experiences influence one's self-concept less and ordinary experiences have more influence. Applying this idea to the present study, gen Y individuals' need for relatedness may typically be met by more extraordinary experiences such as meeting and interacting with new and interesting people. Specific to social media, this need may include being innovative in the use of multiple social media platforms, including ones such as Instagram, Snapchat, and YouTube and finding ways to increase 5. Conclusions and implications The present research explores subjective well-being and the role that psychological needs play as motivating factors in many aspects of the virtual experience. Existing research connects happiness and aging and argues that aging impacts the preoccupation with negative life events (Strough et al., 2016). This preoccupation leads to lower overall positive emotional well-being and affect balance (Pinquart, 2001). To extend the research on social media and aging (Krishen et al., 2016), the present research explores the overlap of psychological needs with the social networking experience. It focuses on participants' affect balance according to their past four weeks of social media networking. By calibrating affect balance using a fuzzy SPANE, the present study proposes a new qualitative mechanism to evaluate subjective wellbeing. This study applies SDT and SPANE to the social media experience and assesses the positive, negative, and overall affect balance of participants, thereby giving an indication of which set of ingredients can lead to virtual happiness. Findings indicate that the pursuit of virtual happiness varies with different generations, yet competence spans all of them. Fig. 2 depicts the emergent metaphor from the findings of the 459 Journal of Business Research 89 (2018) 455–461 O. Berezan et al. and move away from the need to be as high in relatedness. In general, gen X is more independent than gen Y (Howe & Strauss, 2007; Pew Research, 2010). At this stage, the need for autonomy becomes paramount to self-concept and happiness. The present research metaphorically suggests that gen X individuals may look into a mirror and evaluate who they are and whether the person in the mirror is in sync with their self-concept; hence, it is the “me” or “Is this me?” stage. Rather than pursuing social media behaviors that result in and create social influence, this cohort may seek to ensure that their social networking behaviors accurately reflect who they are as individuals and portrays them as independent. Finally, further development due to age and life experiences (baby boomers) brings individuals to a place where they have little to prove to others or to themselves. Therefore, the present research conceptualizes the metaphor for baby boomers to be – “I am who I am” or “Let it be” – the “be” stage. People at this stage may feel little social pressure to be anything other than what and who they perceive themselves to be. The recipe for virtual happiness at the “be” stage mainly relies on the need for competence. Baby boomers focus on personal growth and self-fulfillment but are not necessarily as comfortable with new technology and platforms (such as social media networking) as the younger generations (Littrell, Ma, & Halepete, 2005; Obal & Kunz, 2013). Since they have less social pressure, their recipe for virtual happiness is much simpler. This group must satisfy the need for competence, or in this study, have the knowledge and ability to effectively use social media. Table 8 Solutions for gen Y group. Complex solution Frequency cutoff: 19.00 Consistency cutoff: 0.842207 Autonomy Competence ∗ relatedness Solution coverage: 0.730945 Solution consistency: 0.737053 Parsimonious solution Frequency cutoff: 19.00 Consistency cutoff: 0.842207 Relatedness Autonomy Solution coverage: 0.779532 Solution consistency: 0.717298 Intermediate solution Frequency cutoff: 19.00 Consistency cutoff: 0.842207 Autonomy competence ∗ relatedness Solution coverage: 0.730945 Solution consistency: 0.737053 Raw coverage Unique coverage Consistency 0.640082 0.497912 0.233033 0.090863 0.750415 0.805499 Raw coverage Unique coverage Consistency 0.649212 0.640082 0.139450 0.130320 0.749425 0.750415 Raw coverage Unique coverage Consistency 0.640082 0.497912 0.233033 0.090863 0.750415 0.805499 6. Limitations and future research Predictive validity testing Training sample (n = 147) Overall solution Overall solution consistency coverage 0.723481 0.700231 Validity sample (n = 146) Overall solution Overall solution consistency coverage 0.728661 0.703811 The present study offers insights into the behavioral motivations for social media use across generations from a SDT perspective. However, this study also has limitations that lay the groundwork for future research. One such limitation centers on the differences between age and generational cohorts. Whereas individuals within each generational cohort share experiences and motivations that make them similar in some ways, the aging process itself also shifts the individual definitions of, and thereby the recipes for, happiness. Therefore, future research can conduct longitudinal studies that overlay both generational cohorts and aging as a process to determine the antecedents to virtual happiness in social media behavior. The present study is limited due to the grouping of multiple social media networking platforms into one complex entity per generation. Instead, a future study could investigate relatedness in these platforms. This cohort actively seeks to develop their self-concept through highly active social networking activity and platforms. It is also important to consider that millennials in general are group-oriented and have developed in a more connected world than previous generations (Obal & Kunz, 2013), which may influence their higher need for relatedness in social networking to achieve virtual happiness. As people gain more life experiences, such as in gen X, they develop Fig. 2. Self-concept, social media, and motivations. 460 Journal of Business Research 89 (2018) 455–461 O. Berezan et al. individual platforms of interest as a variable itself and delineate differences in platform preferences across generations. Another potential limitation of this study is its method and sample characteristics; future research can use other qualitative and quantitative methodologies and gather larger samples to further validate these findings. Building on the current findings as well as others including Berezan, Krishen, Tanford, and Raab (2017), Krishen et al. (2016), and Noble et al. (2009), additional quantitative designs can uncover direct relationships and test theoretical models to triangulate these qualitative findings. Future research can also explore the impact of cross-cultural differences on social media antecedents to happiness. Finally, a further understanding of social media motivations and behaviors through the overlay of both emotional and cognitive outcomes presents another future opportunity for research. Krasnova, H., Widjaja, T., Buxmann, P., Wenninger, H., & Benbasat, I. (2015). 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