Toward the Extension of Antecedents of Compulsive Buying: The Influence of Personal Values Theory

Abstract

Although a great deal of research has been conducted on compulsive buying, little if any, research has explored compulsive buying from a wider theoretical perspective, encompassing all types of values as potential drivers of compulsive buying. In particular, no comprehensive research has been conducted in the diagnosis of mechanisms that direct the development of compulsive buying from the perspective of personal values theory. Thus, the objective of the current research was to explore compulsive buying within Schwartz’s value model, as well as examining the role particular values play as predictors of compulsive buying. Data were obtained from randomly selected students (young adults), whose ages ranged from 17 to 25 years-old, enrolled at professional and high schools, and at universities in Poland. Personal values were measured by the Polish version of Personal Values Questionnaire, while compulsive buying propensity was assessed by the Polish version of the Richmond Compulsive Buying Scale. Generally, the study’s hypotheses were supported by SEM analysis. That is, those who held values comprising “Self-Enhancement” and “Openness to Change” were more likely to be compulsive buyers. In contrast, those who held values comprising “Self-Transcendence” and “Conservation” were more likely to be non-compulsive buyers. Compulsive buyers were more self-focused, hedonistic, power- and achievement-oriented than non-compulsive buyers. Finally, values that emphasized importance of communal rather than individualistic goals appeared to prevent compulsive buying.

Keywords

Values theory compulsive buying behavior antecedents of compulsive buying young consumers compulsive and non-compulsive buyers

Introduction

Compulsive buying behavior has long been considered among psychologists, psychiatrists, and consumer researchers as the “dark side of consumption” (Moschis, 2017), for its negative consequences for both consumers and society at large (Guo & Cai, 2011; Roberts, 1998). Researchers have noted the “march” of globalization and excessive consumerism, boosted mainly by rich economies of respective countries, as antecedents of compulsive buying (S. Miles, 1998; Mróz, 2009). The result is uncontrolled spending habits of individual consumers (Gardarsdottir & Dittmar, 2012; Schneider & Kirchgassner, 2009), who without logic and reason, spend more money and buy more goods that are necessary for one’s basic comfort, survival, or success. Compulsive buying can be caused by depression, anxiety, negative feelings, or low self-esteem (Christenson et al., 1994; Edwards, 1993; Faber & O’Guinn, 1992; O’Guinn & Faber, 1989; Scherhorn et al., 1990) which precipitates unrestrained purchasing that can result in financial problems, unmanageable debts, or feelings of post-purchase dissatisfaction and guilt (Gardarsdottir & Dittmar, 2012).

Given the problems compulsive buyers may experience, understanding how compulsive buying tendencies are developed is an imperative for both researchers interested in identifying various antecedents of compulsive buying, and for public policy decision-makers undertaking prevention actions to reduce the development of such behavior. Prior research on compulsive buying has been focused on areas related to neuro/biology (e.g., Koob & Volkow, 2016; Kyrios et al., 2018), demographics (e.g., Christenson et al., 1994; Mueller et al., 2011), psychology (e.g., Claes & Müller, 2017; Harnish & Bridges, 2015; Otero-López & Villardefrancos, 2015), sociology and consumer studies (Japutra et al., 2019; Kukar-Kinney et al., 2009; Maccarrone-Eaglen & Schofield, 2019; O’Guinn & Faber, 1989; Roberts & Tanner, 2000); yet surprisingly, little research has explored compulsive buying in the context of values theory (e.g., Bilsky et al., 2011; Schwartz, 1992, 1994, 2012). In other words, no comprehensive research has been conducted within a personal value perspective that would thoroughly identify the mechanisms that may direct the development of compulsive buying. As Faber and O’Guinn (1992) argued, a deeper understanding of the other influences/antecedents bearing responsibility for compulsive buying behavior still awaits investigation. In this regard, consumer studies indicated that values impact individuals’ desires and needs (e.g., Homer & Kahle, 1988; Kim et al., 2002), attitudes toward socially responsible consumption (Lee & Cho, 2019), and e-shopping behavior (Jayawardhena, 2004; Koo et al., 2008). Additionally, values have been shown to influence perception of service quality (Ladhari et al., 2011), preferences for specific products (Pitts & Woodside, 1983), as well as Internet use (Schiffman et al., 2003). A rare exception to this were studies that focused on examining the relationship between consumers’ materialism and compulsive behavior (see Dittmar, 2005a, 2005b; Dittmar et al., 1996; Richins & Dawson, 1992). However, this examination of the relationship between compulsive buying and materialism was detached from investigating other equally important value types. Thus, there exists a significant theoretical gap in understanding how personal values impact compulsive buying. In the current work, we employ values theory (e.g., Bilsky et al., 2011; Schwartz, 1992, 1994, 2012), as the lens to examine the role and influence of particular values on compulsive buying (e.g., Harnish et al., 2017; Mowen & Spears, 1999; O’Guinn & Faber, 1989; Ridgway et al., 2008; Roberts, 1998).

The structure of this article is as follows. First, the literature on compulsive buying briefly is reviewed. Next, Schwartz’s (1992, 1994, 2012) theory of personal values is presented. After that, hypotheses concerning the relationships between specific types of values and compulsive buying behavior are presented. The relationships are tested with structural equation modeling using data obtained from a representative sample of young consumers (17 to 25-year-olds) living in Poland (a member of the European Union). We focused on young adult consumers because prior research (Harvanko et al., 2013; Roberts & Roberts, 2012; Yurchisin & Johnson, 2004) indicated that youth are the most vulnerable to social and market influences, peer pressure, and compulsive buying as compared to older adults. After presenting the research findings, we discuss the theoretical and practical implications of research.

Prior research on the antecedents of compulsive buying

Compulsive buying behavior reflects a reaction of consumers to negative events and feelings (O’Guinn & Faber, 1989). The act of purchasing provides compulsive buyer with short-term pleasure, but in the long-term, results in negative consequences for the individual and society (Higgins, 1997). As Faber (2004) explained, this phenomenon can be qualitatively similar to standard forms of buying in a consumer culture, apart from the different level of frequency which accompanies such behavior. Given this, McElroy et al. (1994, 1995) conceived compulsive buying as an uncontrollable act which causes severe pain for individuals comparable to that of addiction (see also Flight et al., 2012; Gardarsdottir & Dittmar, 2012). Similarly, Monahan et al. (1996) argued that compulsive buying is associated with the irresistible desire for buying that is accompanied by a sudden drop in tension after a purchase. Note that compulsive buyers not only experience recurring acts of problematic buying, but also undesirable, recurring thoughts about buying (Grougiou et al., 2015). In other words, they suffer from a type of obsessive and compulsive disorder (Ridgway et al., 2008). That is, it is a type of buying, that contains elements of standard buying behavior, but occurs so often that it can be diagnosed as a pathological habit because of the lack of control or limited control individuals have over the behavior (Elliott, 1994). For a recent review on compulsive buying, see Harnish et al., 2018b; Trotzke et al., 2017).

Personal values research

As noted, research exploring compulsive buying behavior explained from the perspective of a complete framework of values appears to be lacking. As mentioned earlier, a rare exception were studies that focused on examining the relationship between consumers’ materialism and compulsive behavior (see Dittmar, 2005a, 2005b; Dittmar et al., 1996; Richins & Dawson, 1992). Interestingly, the measurement of the relationship between compulsive buying and materialism was detached from investigating other equally important value types (Belk, 1988; Burgess, 1992; Ger & Belk, 1996). Nevertheless, prior research revealed that compulsive buyers had a higher materialistic orientation (Mowen & Spears, 1999; O’Guinn & Faber, 1989), perceived materialistic consumption as an “aid” in repairing one’s mood, and facilitated the development of one’s self-identity (Dittmar & Drury, 2000).

Materialists, like compulsive buyers, possess low self-esteem, report a poor quality of life, and are generally dissatisfied with life (Richins & Dawson, 1992; Roberts & Clement, 2007; Sirgy et al., 1998). Perhaps because of this worldview, materialists often look for excitement, self-fulfillment, fun and enjoyment. Within a purchasing situation, materialists seem to embody a hedonistic orientation toward consumption (see Horváth & Adigüzel, 2018; Moen, 2016; O’Shaughnessy & O’Shaughnessy, 2002; Zhong & Mitchell, 2012). As such, materialists acquire possessions for the purpose of exhibiting them to others in order to raise their status and self-esteem (Clarke & Micken, 2002). This is because those who focus on material possessions suffer from feelings of insecurity, unhappiness, and discontent (Kasser & Ahuvia, 2002). As Kasser and Ahuvia (2002) concluded, materialism connects mainly with extrinsic goals that emphasize rewards and require the approval of others, and because these goals are contingent upon the approval of others, attaining them is always frustrating and ultimately unsatisfying.

The present work extends our understanding of how other values affect compulsive buying by extending previous lines of research to include other value types based on Schwartz’s theory of universal values (e.g., Schwartz, 1992, 1994, 2012). To understand how universal values impact compulsive buying, in the next section we define value types and their meanings, along with respective measures and the measurement model.

Meaning of personal values

Braithwaite and Scott (1991) explained that personal values determine humans’ life standards, for they are part of daily actions, as well as shape future directions of activities (see also A. Miles, 2015). According to Rokeach (1979), personal values represent “ … an organized set of preferential standards that are used in making selections of objects and actions, resolving conflicts, invoking social sanctions, and coping with needs or claims for social and psychological defenses of choice made or proposed … ” (p. 263). As Rokeach (1973) claimed, personal values are multifaceted standards that guide human beings in a variety of ways. They lead individuals to take particular positions on social issues and predispose them to favor one “ideology” over another. They also are standards employed to evaluate and judge others and ourselves (Morris, 1956). Similarly, Kluckhohn (1951) argued that “ … a value is a conception, distinctive of an individual or characteristic of a group which influences the selection from available modes, means, and ends of action,” (p. 395) consequently personal values focus on specific actions and rewards depending on the internal predisposition of individuals and their social-group relationships. That is, values represent cultural imperatives that lead to specific actions undertaken in private life and connect to other members in the society (Lesthaeghe & Moors, 2000).

Schwartz advanced our understanding of personal values (Schwartz, 1992, 1994; Schwartz & Bilsky, 1987, 1990) by proposing a model that classifies personal values. As Schwartz (1992, 1994; Schwartz & Bilsky, 1987, 1990) postulated, multiple single values express the same broad, underlying motivation. Moreover, values should be interpreted in context of six main features (Schwartz, 1992, 1994), namely: (1) values are concepts or beliefs; (2) about desirable goals and end-states or behaviors; (3) transcending in specific situations; (4) guiding the evaluation of persons, behavior, and events; (5) ordered by relative importance; and (6) imposing relative importance of values which guide actions within other values. In regard to the first assumption “values are beliefs,” Schwartz postulated that when values are activated, they must become infused with feelings. For instance, people for whom “Independence” is important, should be aroused when their independence is threatened. According to the second assumption, one can think that if some values are important in one’s life, these should be natural motivators in pursuing goals; whereas, the third aspect explains that values refer to specific actions, objects, or situations. For example, being “Obedient” and “Honest” will be of great relevance in specific places or situations like the workplace or school, or during interactions with friends. In a similar way, the fourth aspect guides the selection or evaluation of actions, policies, and events. In other words, people decide what is good or bad, what can be justified or invalidated, or what is worth doing or avoiding, based on possible consequences for their values. Finally, the fifth assumption states that “values are ordered by their importance,” while the sixth assumption indicates which values guide actions within other values. For example, attending church usually connects with the values of “Tradition” and “Conformity,” and, thus rejects the way of life based on the values of “Hedonism” and “Stimulation.” In sum, the trade-off among relevant, competing values, shapes human behaviors (Bardi & Schwartz, 2003; Schwartz, 2015). Note that the fifth and sixth assumption proposed by Schwartz plays an essential role in our research because it not only associates various personal values with compulsive buying by relative importance but identifies which individual values guide actions within other values. In other words, by examining the potential influence of different values on compulsive buying behavior, a set of values rather than one specific value is explored, thus exceeding the isolated form of examining the impact of only one personal value on compulsive buying.

Schwartz’s model of personal values

Schwartz proposed a structure of ten basic personal values that are recognizable in all societies and cultures; whereas, his strategy of values measurement has received support from research conducted in over 80 countries (e.g., Bilsky et al., 2011; Cieciuch et al., 2014; Davidov et al., 2008; Schwartz, 2014; Schwartz et al., 2001, 2017). Indeed, two measurement instruments proposed by Schwartz, the Schwartz Values Survey (SVS) and the Portrait Value Questionnaire (PVQ) have been tested in numerous studies (e.g., Sagiv, Schwartz et al., 2011), although the latter is used most widely (Cieciuch & Schwartz, 2012; Roccas et al., 2017; Schwartz, 2012; Schwartz et al., 2001) because it provides the most innovative, comprehensive and elaborate picture of values theory, allowing researchers to obtain a deeper sense and essence of universal values (Roccas et al., 2017).

Schwartz (1992, 1994) claimed that personal values can be organized into a coherent structure that explain all individual decision making, attitudes and behavior, as well as many other aspects of human life. In his model, Schwartz (1992, 1994) proposed that values standing close together share similar motives, whereas values that conflict each other, are placed on the opposite axis of a quasi-circular, dimensional factor structure (Cieciuch & Schwartz, 2012). For instance, values that conflict with one another are “Benevolence” and “Power;” whereas, “Conformity” and “Security” are compatible. The model is called “quasi-circular” because values are placed on a circle, but they are not equally spaced (Schwartz & Boehnke, 2004). The idea of a continuum arrangement of values, however, implies that the domain of values can be partitioned into broader, or more fine-grained, value constructs, depending on how finely one wishes to discriminate motives (Cieciuch & Schwartz, 2012; Schwartz et al., 2001). Given this, the model proposes four higher-order value types and ten first-order values. The four higher-order values are: (1) “Openness to change” (consisting the first-order values of “Stimulation,” “Self-direction,” and “Hedonism”), (2) “Self-enhancement” (based on first-order values, “Achievement” and “Power”), (3) “Conservation” (based on the first-order values of “Tradition,” “Conformity,” and “Security”) and (4) “Self-transcendence” (containing two first-order values, “Universalism” and “Benevolence”). All four higher-order values form two bipolar dimensions, where “Openness to change” values contrast with “Conservation” values and “Self-enhancement” values contrast with “Self-transcendence” values.

Conceptual model of relationships between value types and compulsive buying

Because Schwartz’s model of values was developed in a cross-cultural context and has demonstrated to be valid across many countries and studies (Cieciuch & Schwartz, 2012; Roccas et al., 2017; Schwartz, 2012; Schwartz et al., 2001), it underpins the present conceptual work. In the subsequent section, the postulated hypotheses are presented detailing the impact personal values have on compulsive buying. These hypotheses are presented in Figure 1(a) and (b), along with their expected effects. Based on them, we assume the causal flow from values to compulsive buying behavior to be consistent with the essence of values as drivers of consumer behaviors (see Burgess, 1992; Schwartz, 2012). All theoretical assumptions, underlying postulated relationships are discussed in subsequent sections. However, note that the postulated relationships between values and compulsive buying is considered in two interrelated analytical variants, according to which we tested the first postulated relationships of specific value types (i.e., “Self-Direction, “Stimulation”, “Hedonism”, “Achievement”, “Power”, “Security”, “Conformity”, “Tradition”, “Benevolence”, “Universalism”) with compulsive buying by implementing four analytical models, split by four main value dimensions (“Openness to Change”, “Self-enhancement”, “Conservation”, “Self-transcendence”). In the second stage of analysis, instead of using a four-model solution as in the prior analysis, we treated values as four distinct ‘value constellations’ (see Cieciuch & Schwartz, 2012) and examined their relationships with compulsive buying in a single integrated model. In other words, we explored both the isolated relationships between respective values and compulsive buying, and encompassed the entire set of values in a global configuration that allowed us to assess the relative importance of the ‘value constellations’ relative to one another.

Figure 1.

(a) Models diagnosing relationships between values as self-direction, stimulation, hedonism, achievement, power and young consumers’ compulsive buying behavior. Note: The ellipses denoted by symbols SD, ST, HE, AC, PO represent exogenous latent variables (personal values) and ellipses denoted as P-RCBS (OCB, IB) reflect endogenous latent variables (compulsive buying behavior). The arrow indicates the direction of the impact of cause and effect, i.e. the influence of personal values on compulsive buying behavior. Marks given in brackets reflect the stated hypotheses. Due to model complexity of the path diagram, one has left out the indicators of measurement models for the respective latent variables. (b) Models diagnosing relationships between values as Security, Conformity, Tradition, Benevolence, Universalism and young consumers’ Compulsive Buying Behavior. Note: The ellipses denoted by symbols SE, CO, TR, BE, UN represent exogenous latent variables (personal values) and ellipses denoted as P-RCBS (OCB, IB) are the same as in (a).

Also noteworthy is that, in the present work, we tested the hypothesized relationships from the perspective of young adult consumers. In this regard, we followed the guidelines of Christenson et al. (1994) and Schlosser et al. (1994) who claimed that the tendency to buy compulsively occurs among young people around the age of 18. Other research suggests that the onset of compulsive buying occurs between the ages of 18 and 25 (Harvanko et al., 2013; Yurchisin & Johnson, 2004). Thus, being a younger person appears to be a predictive factor for compulsive buying (Maraz et al., 2016). Indeed, the development of compulsive buying tendencies typically dissipate with an increase in age (Dittmar, 2005b). Thus, we focused on young adults in the current research.

The hypothesized relationships are tested across two groups: young compulsive and non-compulsive buyers. According to d’Astous (1990), there is a strong, generalized urge to buy, which characterizes young consumers at different levels, and most likely, at different times (see also Maraz et al., 2016). Thus, less extreme forms of compulsive buying also are worth studying because an average consumer may show at least some degree of vulnerability toward compulsive buying, or may be in an early stage of developing compulsive buying tendencies. Both groups, with their specific professed values, may foster their receptivity for compulsive buying tendencies, or weaken and reject it.

Self-direction, stimulation and hedonism—Openness to change dimension

Young individuals may have intrinsic goals and strong desires for constant personal development that develop talents that enhance their quality of life. They may focus on exploration and strive for self-efficacy (e.g., Allport et al., 1960). Indeed, youth is characterized by the developmental, natural need of exploring life and the establishment of an independent, adult identity employing whatever expressive means are available, including the use of material goods (Benson et al., 2010). Young adults also are thought to be mainly oriented on the “Self-Direction” dimension. By stressing the importance of self-reliance and self-gratification, youth strive to maintain independent thoughts and actions, as well as leading a life according to their own creativity, freedom, and curiosity (see also Maio & Olson, 1995; Verplanken & Holland, 2002). Those with a strong orientation on “Self-Direction,” usually desire autonomy and independence (Kohn & Slomczynski, 1993). As a consequence, this value stresses the importance of individualism and the arcelingt of intrinsic needs. Similarly, “Stimulation” highlights individualism, however, in contrast to “Self-Direction,” it is associated with self-excitement, which is pursued through variety seeking (Olsen, Tudoran, Honkanen, & Verplanken, 2016), including the realization of new challenges in life (Schwartz, 2012). “Stimulation” as a value represents self-affirmation and the ongoing search for novelties and vital challenges. Because “Stimulation” is grounded on assumptions like a varied and exciting life, it also pertains to “Hedonism” (O’Shaughnessy & O’Shaughnessy, 2002), which motivates an individual to search for pleasure and sensuous gratification for oneself. This is also why hedonic consumers seek mainly affective experiences and derive from it pleasures or personal gains (Alba & Williams, 2013; Horváth & Adigüzel, 2018; Moen, 2016). Importantly, “Hedonism” promotes freedom and the individual’s pursuit of pleasant arousal in novel ways according to one’s personal preference, while “Stimulation” and “Self-direction” involve intrinsic motivations for reaching specific levels of self-mastery. Consequently, individuals attribute greater importance to “Openness to Change” if they value contact with others in society. Contact with others provides not only exposure to new and varied ways of life and opportunities of learning (“Self-Direction” value), but through such contacts, there arises new opportunities to experience novelties and excitements (“Stimulation” value).

Given the associations among ‘Self-Direction’, ‘Stimulation’, and ‘Hedonism’ values, we proposed that these values can be reflected in an individual’s orientation toward self-fulfillment, self-reliance, self-gratification, and self-excitement where “self” occupies the center of one’s life. That is, those who value “Stimulation”, “Self-Direction”, and “Hedonism”, will accentuate the importance of fulfilling personal goals, and will be more individualistically and materialistically oriented (Burroughs & Rindfleisch, 2002). Interestingly, individualism predominates not only in the case of these values, but it also appears in compulsive buying, which prevails in western cultures (Harding & Philips, 1986; Horváth et al., 2013). As Wong and Ahuvia (1998) stated, cultural differences between collectivistic and individualistic cultures reflect different conceptions of self – that is, the independent construal of self (dominant in western cultures) and the interdependent construal of self (commonly found in collectivistic cultures; see also Henry, 1976; Hofstede, 2001). Thus, people’s cultural backgrounds shape not only their needs, but it also influences their values and compulsive buying behavior (Abraham & Dameyasani, 2013; Firat & Venkatesh, 1995). Young individuals, in order to profit from a variety of available products or to pursue their own goals, must live and grow in specific cultural and economic conditions that are characteristic of developed countries (S. Miles, 1998; Zhong & Mitchell, 2012). Such cultures and rich economies provide stimulus for new activities and ways of fulfilling desires. However, there is a risk that the more an individual wishes to develop and appease their life/personal goals or aspirations (and the more they are provided with such opportunities), the more likely they will become compulsive buyers. That is, those who attach greater meaning to values such as ‘Self-Direction’, ‘Stimulation’, and ‘Hedonism’ will be more prone to compulsive buying tendencies. More specifically, it was postulated that:

H1a–b: A high level of Self-Direction (a) is positively related to compulsive buying behavior in a group of young adult buyers, who possess a compulsive orientation and (b) is not related to this type of behavior in a group of young adult non-compulsive buyers.

H2a–b: A high level of Stimulation (a) is positively associated with compulsive buying behavior in a group of young adult buyers who have a compulsive orientation and (b) is not related to this type of behavior in a group of young adult non-compulsive buyers.

H3a–b: Hedonism (a) has a positive relationship with compulsive buying behavior among young adult buyers, who exhibit a compulsive orientation, and (b) has no relationship with this behavior in a group of young adult non-compulsive buyers.

Achievement and power—Self-enhancement dimension

In regard to the value types of “Achievement” and “Power” (which are related to the “Self-Enhancement” dimension), we argue these values also are related to compulsive buying, especially in countries with rich economies, which offer numerous opportunities for individuals to raise their socio-economic status and to spend more money. When income levels increase, there appears a greater likelihood of becoming addicted to compulsive buying (Becker & Murphy, 1988). As Dittmar (2005a) reported, increased individual incomes, particularly in matured and developing economies, make it easier for individuals to over-spend, which results in excessive consumerism. In this context, “Achievement” as a value stresses the importance of competition and its effect, (i.e., financial and/or nonfinancial rewards defined in terms of a desirable social position, and the acquisition of money and resources). “Achievement” is largely based on the personal beliefs of individuals who believe success and money is the only goal in life, which can be obtained through demonstrating a higher competence in comparison to others (Kajonius et al., 2015; Maio & Olson, 1995). As a consequence, the required competences for these individuals constantly raise demands for increased performance of professional and personal goals, which further leads to permanent stress, restlessness, and anxiety. In order to mitigate the negative affective states increased performance of professional and personal goals produce, more frequent buying occurs (Roberts & Pirog, 2004). Among young adults, the glorification of “Achievement” values is often associated with their material consumption and desires for possessions in order to project to others high status (Moon et al., 2015; Richins & Dawson, 1992). Such a materialistic orientation can further evoke compulsive buying behavior (Dittmar et al., 1996). According to Schwartz (2015), those who hold “Achievement” values can be perceived as too ambitious, always greedy of success, exceedingly avaricious, and vulnerable to the influence of others. Interestingly, these characteristics are closely related with “Power” values; those who strive for success tend to acquire greater power to manage or control societies. Thus, such individuals who hold “Power” values are often unable to control their own life, and are unable to face their personal problems (Sagiv, Sverdlik et al., 2011).

As related to compulsive buying, “Achievement” and “Power” values, (as being part of the “Self-enhancement” dimension of values) likely bring negative consequences for young adults, particularly those who, display strong compulsive buying symptoms. These negative consequences can include lower self-esteem, greater stress and anxiety, as well as a lack of confidence within one’s own capabilities and competences. Because of this, the following was hypothesized.

H4a–b: A high level of Achievement (a) is positively related to compulsive buying behavior in a group of young adult buyers, who possess a compulsive orientation and (b) is not related to compulsive buying in a group of young adult buyers identified as non-compulsive buyers.

H5a–b: A high level of Power (a) is positively related to compulsive buying behavior in a group of young adult buyers, who hold a compulsive orientation and (b) is not related to compulsive buying in a group of young adult buyers identified as non-compulsive buyers.

Security, conformity and tradition—Conservation dimension

In contrast to values comprising the constructs of “Self-Enhancement” and “Openness to Change,” which accentuate one’s self focus in life, values related to “Conservation” (i.e., values of “Security”, “Tradition”, and “Conformity”) stress the importance of a social focus. “Conservation” conflicts with a personal focus that emphasizes one’s own independent thoughts and egoistic motives (Schwartz, 2015). Rather, “Conservation” is associated with submission, self-restriction, stability and the preservation of traditional practices. For instance, “Security” compounds social harmony (i.e., interpersonal relations), and social order. “Security” as Schwartz (2012) explained, is derived from individual and group requirements (see also Kluckhohn, 1951; Maslow, 1965; Zwetsloot et al., 2013), and consequently serves both the individual’s basic interests (e.g., order), and the wider group’s interests (e.g., national security). In a similar context, “Conformity” represents respect for social norms. Thus, those young adults who value “Conformity” will restrain from actions and impulses that harm others or violate social expectations or norms (Simpson & Willer, 2008). “Conformity” will be most important for those who show obedience to authority, self-discipline, and politeness (i.e., follow social norms of appropriate behavior). Such individuals should be much more responsible than individuals who lack this value (Boer & Fischer, 2013).

Also note that “Conformity” and “Security” values are associated with “Tradition” which expresses group solidarity and uniqueness (Boer & Fischer, 2013). Similar to “Conformity,” “Tradition” represents respect and commitment to the customs and ideas of a culture or religion (Inglehart & Baker, 2000). Young adults by valuing “Tradition” typically have grown up with practices, symbols, ideas, and beliefs that represent a shared experience and fate. These become sanctioned as valued group customs and traditions that symbolize group solidarity, allowing the expression of the group’s unique worth (Campbell, 2018; Durkheim,1912/1954; Parsons, 1951). Such customs and traditions often take the form of religious rites, beliefs, and norms of behavior. As Schwartz (2015) remarked, “Tradition” is associated with a moderate, spiritual life, and is respected by those who are “accepting of their position in life,” and are humble and devout. Schwartz (2005, 2015) also claimed that both, “Tradition” and “Conformity” are especially closely positioned because they share the goal of submitting “the self” to socially imposed expectations. These values differ only in the objects to which one subordinates “the self;” “Conformity” entails complying to others requests with whom one frequently interacts (e.g., parents, teachers), while “Tradition” entails subordination to more abstract objects like religious and cultural customs, and ideas (Sagiv et al., 2011).

Overall, the importance of ‘Conservation’ values in young adults’ life should insulate them from compulsive buying tendencies, provided they have developed self-control. Self-control aids such individuals from engaging in excessive and uncontrollable consumption (Faber, 2004). Thus, young adults who hold “Conformity,” “Tradition” and “Security” values should be protected from compulsive buying tendencies. Conversely, as levels of “Security”, “Conformity,” and “Tradition” decrease, compulsive buying should increase. Based on these assumptions, the following hypotheses were formulated.

H6a–b: Security is (a) not related to compulsive buying in a group of young adult compulsive buyers, and (b) is negatively related to compulsive buying in a group of young adult non-compulsive buyers.

H7a–b: Conformity (a) in a group of young adult compulsive buyers is not related to compulsive buying behavior, and (b) is negatively related to this type of behavior in a group of young adult non-compulsive buyers.

H8a–b: Tradition (a) in a group of young adult compulsive buyers is not related to compulsive buying behavior, and (b) is negatively related to this type of behavior in a group of young adult non-compulsive buyers.

Benevolence and universalism—Self-transcendence dimension

Finally, the value types, “Benevolence” and “Universalism” (as being part of the “Self-Transcendence” dimension), accentuate a social focus; consequently, young adults by the fact of possessing these values, will be less prone to compulsive buying behavior. This is because those who score high in “Benevolence” have a sense of belonging, have meaning in their life, and have a spiritual life, which immunes them from absorbing harmful social trends (Chernev & Blair, 2015). “Benevolence” as a value strikes a moral undertone emphasizing less harmful behaviors (Benoit & Jordan, 2009; Lawrence, 1981). “Benevolence” is mainly valued by those who are helpful, honest, forgiving, and responsible. Such individuals value true and close friendships. Similarly, “Universalism” stresses the importance of social needs to ensure the survival of individuals and other groups (not only those closely related), particularly in situations where the resources on which life depends are scarce and should be shared equally across the entire society (Schwartz, 1994, 2015). The chief postulates of “Universalism” can be defined on the ground of mutual understanding and appreciation, tolerance, and protection for the welfare of all people and for nature (Collins et al., 2007; Karp, 1996; Katz-Gerro et al., 2017). Young consumers who value “Universalism” will not recognize these needs until they encounter others beyond the extended primary group (i.e., family) and until they become aware of the scarcity of natural resources. Thus, “Universalism” combines two subtypes of concerns – the welfare of society and nature. Schwartz (2015) has attributed “Universalism” to broad-minded people, who are capable of showing social justice and equality, as well as preferring a world at harmony, peace, and unity with nature.

Thus, we postulate that as long as young adults have a sense of belonging, have meaning in their life, and have a spiritual life, they should be less susceptible to compulsive buying tendencies. Note that in this context, compulsive buying is regarded as behavior that reflects a chronic, repetitive and uncontrollable urge to purchase goods (Flight et al., 2012), and is triggered by negative events or human feelings that have roots in psychological and/or societal problems (Faber & O’Guinn, 1992; Lo & Harvey, 2011; Maraz et al., 2016). Thus, those who hold “Benevolence” and “Universalism” values should be resistant to compulsive buying tendencies. In contrast, those who do not hold “Benevolence” and “Universalism” values should be more susceptible to compulsive buying tendencies. Given this, the following hypotheses are posited.

H9a–b: Benevolence (a) in a group of young adult compulsive buyers is not related to compulsive buying behavior, and (b) is negatively related to this type of behavior in a group of young adult non-compulsive buyers.

H10a–b: Universalism (a) in a group of young adult compulsive buyers is not related to compulsive buying behavior, and (b) is negatively related to this type of behavior in a group of young adult non-compulsive buyers.

Methodology

Sample and procedure

A large-scale survey of young Polish adults was conducted. The sample included students enrolled at universities, high schools and professional schools. University students were recruited randomly from a database containing all registered students at a particular level of study, including first through third year for a bachelor’s degree and fourth to fifth year for a master’s degree. High school students were recruited from the highest three class levels, while for professional schools, participants from the two highest levels were selected. The schools and universities were spread across Poland. To select the respondents, we first initiated contact with a respective school/university representative. After obtaining appropriate institutional, parental and personal permissions, we administered the questionnaires to a random group of students. Note that the consent procedure assumed informing parents and respondents of the researcher’s intent, type of research, forms of posed questions, and the ways of collecting data from youth in a given location (e.g., a school). Thus, we presented the project details both to parents and the young adults who were our target. Naturally, we respected the wishes of those parents who did not want to have their young adults participate in the project. For those parents and young adults, who agreed to participate in research, we obtained informed consent in writing at the time of data collection. Also note that all procedures involving human participants were in accordance with the ethical standards set forth by, and approved by, the Commission of Research Ethics at University of Economics.

Finally, to ensure high data quality, the researchers were present in classroom/lecture room to explain one more time the procedure and answer any questions. Out of 830 potential respondents, 804 agreed to participate in the study and provided responses to the questionnaire, resulting in a 96% response rate. As an incentive, for those who agreed to participate in research, we provided minor gifts (e.g., pens, stickers, mugs, etc.). The time of data collection ranged from September to October 2018.

The structure of the sample is as follows. As presented in Table 1, nearly two-thirds (65%) of the respondents were women while 35% were men. The two-to-one difference in the number of women and men in the sample is due to the proportion of women and men enrolled at professional and high schools, and at universities in Poland (Central Statistical Office in Poland, 2018). The mean age of the respondents was 20 years-old, with the youngest being 17 years-old and the oldest 25 years-old. Less than half of the respondents (40%) were in the course of their professional education; while the other respondents were learning at the high school (34%) or university (26%) level. Other demographic information is presented in Table 1.

Table 1.

Percentage of participants according to selected demographics and family traits [N = 804].

Trait		Percentage
Gender	Female	65%
	Male	35%
	Total	100%
Age	Min (17) Mean (20) Max (25)
Respondents’ education	Professional school	40%
	High school	34%
	University (bachelor- master level)	26%
	Total	100%
Number of siblings in family	No siblings/living alone	20%
	1 brother/sister	43%
	2 brothers/sisters	27%
	3 brothers/sisters	6%
	More than 3 brothers/sisters	4%
	Total	100%
Place of permanent residence	Flat in big house	58%
	Single-family house	36%
	Other	6%
	Total	100%

Note: Students recruited from universities, represented various fields: economics and management, medical, agriculture, pedagogy, sociology and psychology, law, arts, mathematics across 16 voivodships from the following universities: Warsaw University, University of Physical Education in Wroclaw, University of Life Sciences in Lublin, Poznan University of Economics, Technical University of Lodz, Jagiellonian University in Cracow, Opole University, Gdansk University of Technology, University of Life Sciences.

Students recruited at high- and professional schools represented: comprehensive high schools, technical colleges; and vocational schools. The list includes the following randomly selected schools across 16 voivodeships: (1 – Greater Poland region): High School in Krzyż Wielkopolski; Technical College of Stefan Wyszynski; Technical College; (2 – West Pomeranian region): Technical College of Economics; Special School No. 2; (3 – Warmian-Masurian region) High School of Stefan Żeromski; Technical College in Bartoszyce; Vocational School of Jan Liszewski; (4 – Świętokrzyskie region): V High School in Busko-Zdrój; Vocational Training Center in Kielce; (5 – Silesian region): II High School of Stanisław Wyspiański; Technical College No. 2 Danuta Sitikówna "INKA"; (6 – Pomerania region): High School of Sports in Bytow; Technical School of the Bydgoszcz Training Center; (7 – Podlaskie region): Vocational school in Bielsk Podlaski; Vocational Training Center in Bialystok; (8 – Subcarpatian region): Technical college No. 3 in Debica; Vocational School in Jarosław; (9 – Opole region): I High School in Brzeg; Profectus vocational training center in Kędzierzyn Koźle; (10 – Masovia region): I High School in Ciechanów; Technical College No. 2 in Garwolin; (11 – Lesser Poland region): XXVI High School; Technical College I Degree No. 33 in Krakow; (12 – Łodzkie region): Technical College No. 3 in Łódź; Study of Medical and Social Workers; (13 – Lubusz region): Technical College in Witnica; European Center for Vocational Education in Gubin; (14–Lubelin region): High School "LIDER" in Lublin; "Omega" Center for Vocational Development; (15–Kuyavia-Pomerania region): Technical College in Brodnica; Vocational School of Gen. Stanisław Maczek in Koronów; (16–Lower Silesia region): Technical College No. 4 in Głógów; Vocational School in Złotoryja.

It is noteworthy that when designing the study, we strove to obtain a highly representative sample of young Polish consumers (calculated on the basis of 4.23 million consumers aged 17–25 years; see Central Statistical Office in Poland, 2018; European Social Survey Report, 2019) that assumed a 95% confidence level and 4.36 margin of error.

Classification for compulsive and non-compulsive buyers

To classify respondents as compulsive or non-compulsive buyers, total scores on the Polish version of the Richmond Compulsive Buying Scale (P-RCBS; Tarka & Kukar-Kinney, 2020) were calculated. Using Tarka and Kukar-Kinney’s (2020) recommendation of classifying individuals who scored 25 or higher on the P-RCBS as compulsive buyers, we identified 16% of the respondents as compulsive buyers, while 84% were categorized as non-compulsive buyers. If extrapolated, the observed prevalence rate to the 4,227,474 Polish youth between the ages of 17 and 25 (Central Statistical Office in Poland, 2018), there could potentially be 676,396 young Poles between the ages of 17 and 25 who are compulsive buyers.

Measures applied

Two scales were used in the study: The P-RCBS (Tarka & Kukar-Kinney, 2020) and the Polish version of the Portrait Values Questionnaire (P-PVQ-40; Cieciuch & Zaleski, 2011). The simple correlations of respective theoretical constructs (i.e., between personal values and compulsive buying), derived from both scales, are shown in the Appendix 2.

Compulsive buying

The P-RCBS (Tarka & Kukar-Kinney, 2020) consists of the 6 items comprising the Richmond Compulsive Buying Scale (Ridgway et al., 2008). Three items assessed obsessive-compulsive behavior (OCB) and three measured impulse control (IC). Rather than focusing on impulse-control or obsessive-compulsive tendencies, the P-RCBS includes both dimensions. Thus, the P-RCBS surmounts shortcomings associated with older measures of compulsive buying that focus on only one dimension (see Ridgway et al., 2008). Like the original (US) version of the RCBS (Ridgway et al., 2008), the use of the P-RCBS is not limited to those identified with a psychiatric buying disorder, but is suitable for use in a nonclinical population. Thus, the P-RCBS allows for a wider extension and in-depth analysis of an inappropriate behavior related to the acquisition of goods by individuals who do not have a history or a previous diagnosis of pathological compulsive buying. As an additional advantage, the P-RCBS measures consequences of compulsive buying independently of the compulsive buying tendency itself. That is, the P-RCBS, like the RCBS, considers harmful effects of compulsive buying more broadly than financial debt, to include behaviors such as hiding and returning purchases, and engaging in family arguments related to excessive buying (Ridgway et al., 2008).

Using a 7-point scale where 1 = strongly disagree and 7 = strongly agree, respondents indicated their agreement on the three obsessive-compulsive buying items (e.g., “My closet has unopened shopping bags in it”) and the three impulse control buying items (e.g., “I buy things I don’t need”).

Schwartz’s portrait of values questionnaire

The Portrait Values Questionnaire (PVQ-40; Schwartz et al., 2001) was applied to assess values. The PVQ-40 was selected over the Schwartz Value Scale (SVS; Schwartz et al., 2001) because it is less time-consuming for respondents to complete compared to the SVS, and is based on a 40-item typology (in contrast, the SVS was based on set of 56 items) that includes short portraits of 40 different – hypothetical – people (Cieciuch & Schwartz, 2012; Schwartz et al., 2001). The 40 items are defined in terms of short verbal portraits that are described in simple language so that respondents, regardless of their educational or status level, can respond easily to the posed portrait (see Cieciuch & Schwartz, 2012). Each portrait describes a person’s goals, aspirations, or desires that point implicitly to one of the ten basic personal values proposed by Schwartz (1992, 1994). As an example, the following portrait that reads: “He/she really wants to enjoy life. Having a good time is important to him/her”, describes a person to whom hedonic values are important. Note that for all portraits, respondents are asked to indicate “How much like you is this person?” using a 6-point scale where 6 = very much like me, 5 = like me, 4 = somewhat like me, 3 = a little like me, 2 = not like me, and 1 = not like me at all.

Overall, the PVQ-40 assesses 10 value dimensions: “Universalism” (measured by six portraits); “Security” (measured by five portraits); “Tradition” (measured by four portraits); “Conformity” (measured by four portraits); “Benevolence” (measured by four portraits); “Self-Direction” (measured by four portraits); “Achievement” (measured by four portraits); “Stimulation” (measured by three portraits); “Hedonism” (measured by three portraits); and “Power” (measured by three portraits; Vecchione et al., 2009).

A two-stage strategy in data analysis

Given the nature of the theoretical constructs (both the causes and the effects within the stated research hypotheses), Structural Equation Modeling (SEM; Bollen, 1989; Jöreskog & Sörbom, 1979; Kaplan, 2000) was employed. The first phase of analysis, due to unequal size proportions of two examined groups (especially observable among compulsive buyers), was conducted separately, on the basis of a two-stage strategy (Anderson & Gerbing, 1988). According to this strategy, we first tested the quality of particular measurement parts (CFA models,) and after having obtained a level of quality within all investigated constructs, we proceeded with SEM. Note that quality of each latent variable was investigated with: Composite reliability (CR; Jöreskog, 1971), Average Variance Extracted (AVE; Fornell & Larcker, 1981), and Cronbach’s Alpha (Cronbach,1951). That is, each coefficient was calculated for each latent variable.

Both CFA and SEM analyses were based on ML (Maximum Likelihood) estimator and conducted in Mplus 8.0 software (Muthén & Muthén, 2014). The level of fit of the models was assessed by root-mean-square error of approximation (RMSEA) and its 90% confidence interval (90% CI), standardized root-mean-square residual (SRMR), comparative fit index (CFI), and Tucker–Lewis Fit Index (TLI). For comparing the structural path coefficients, obtained in Structural Equation Modeling, Wald tests were calculated to detect prospective statistical differences between groups (i.e., the compulsive, and non-compulsive buyers) about the equality of coefficients. In this regard, we followed recommendations provided by Kwan and Chan (2011).

In the final stage of the analysis, we implemented an integrated SEM model to investigate the postulated relationships between four main, broader value dimensions (i.e., “Openness to Change”, “Self-enhancement”, “Conservation”, “Self-transcendence”) and compulsive buying. However, to make this model realistic, due to the large number of measured items and latent variables (i.e., the PVQ-40, and P-RCBS), they were examined as single-composite measures (Landis et al., 2000). That is, if we were to configure the SEM model with 11 constructs (i.e., SD, ST, HE, AC, PO, SE, CO, TR, BE, UN, P-RCBS) as latent variables, by including 46 items altogether (with an anticipated effect size of 0.1 and the desired statistical power equal to 0.8 with a probability level of 0.05), we would need a sample size of 2,078 respondents. This was the main reason why we decided to aggregate items within respective constructs using rules derived from ‘parceling strategy’ (Bandalos, 2008; Little et al., 2002). Thus, all four general values (i.e., “Openness to Change”, “Self-enhancement”, “Conservation”, “Self-transcendence”), were treated as ‘broader value constellations’ (see Cieciuch & Schwartz, 2012). Namely, the “Openness to Change” dimension comprised of items identified as: Self-Direction (SD), Stimulation (ST), and Hedonism (HE). “Self-Enhancement dimension” contained Achievement (AC), and Power (PO) items. The “Conservation” dimension included Security (SE), Conformity (CO), and Tradition (TR) items, while the “Self-Transcendence” dimension contained Benevolence (BE), and Universalism (UN) items. The same strategy was applied to the ‘Compulsive Buying’ variable, according to which the two components, Obsessive-Compulsive Buying and Impulsive Buying were parceled.

Results

Examination of theoretical constructs

The factor structure of the P-RCBS construct tested with CFA indicated a better model fit in the group of compulsive buyers ( $χ^{2}$ = 6.105, df = 8, p = 0.635; CFI = 0.993; TLI = 0.989; SRMR = 0.019; RMSEA = 0.000 [CI, 90%: 0.000–0.049]), as compared to non-compulsive buyers for which the model was slightly worse, but was still acceptable ( $χ^{2}$ = 14.627, df = 8, p = 0.066; CFI = 0.941; TLI = 0.916; SRMR = 0.048; RMSEA = 0.086 [CI, 90%: 0.000–0.155]).

Examining the dimensions of the PVQ-40, specifically the “Openness to Change” dimension (which comprised of values related to “Self-Direction” – SD, “Stimulation” – ST, and “Hedonism” – HE), the CFA model again indicated a better fit for compulsive buyers ( $χ^{2}$ = 49.302, df = 31, p = 0.039; CFI = 0.950; TLI = 0.927; SRMR = 0.050; RMSEA = 0.058 [CI, 90%: 0.040–0.075]) as compared to the CFA model for non-compulsive buyers ( $χ^{2}$ = 85.999, df = 31, p = 0.000; CFI = 0.888; TLI = 0.838; SRMR = 0.088; RMSEA = 0.073 [CI, 90%: 0.030–0.110]). Similarly, for the “Self-Enhancement” dimension (values related to “Achievement” – AC, and “Power” – PO), the CFA model for compulsive buyers reached better fit indices ( $χ^{2}$ = 47.886, df = 31, p = 0.083; CFI = 0.969; TLI = 0.956; SRMR = 0.023; RMSEA = 0.037 [CI, 90%: 0.024–0.089]), as compared to non-compulsive buyers ( $χ^{2}$ = 76.615, df = 31, p = 0.073; CFI = 0.934; TLI = 0.904; SRMR = 0.052; RMSEA = 0.067 [CI, 90%: 0.035–0.084]).

In contrast, for the “Conservation” dimension (comprised of “Security” – SE, “Conformity” – CO, and “Tradition” – TR values) and the “Self-Transcendence” dimension (comprised of “Benevolence” – BE, and “Universalism” – UN values), inverse scores within the model fit indices across the two compared groups were observed. Namely, the model fit statistics for values such as SE, CO and TR (being part of the “Conservation” dimension) showed a worse fit for compulsive buyers ( $χ^{2}$ = 96.828, df = 49, p = 0.000; CFI = 0.923; TLI = 0.915; SRMR = 0.076; RMSEA = 0.050 [CI, 90%: 0.035–0.064]) as compared to non-compulsive buyers ( $χ^{2}$ = 76.639, df = 49, p = 0.071; CFI = 0.963; TLI = 0.955; SRMR = 0.047; RMSEA = 0.041 [CI, 90%: 0.038–0.101]). A similar pattern in the model fit statistics was observed for the theoretical construct “Self-Transcendence” and its related values (BE and UN); the model fit statistics revealed a worse fit for compulsive buyers ( $χ^{2}$ = 45.660, df = 33, p = 0.093; CFI = 0.946; TLI = 0.927; SRMR = 0.068; RMSEA = 0.049 [CI, 90%: 0.010–0.068]), as compared to non-compulsive buyers ( $χ^{2}$ = 41.910, df = 33, p = 0.137; CFI = 0.984; TLI = 0.978; SRMR = 0.036; RMSEA = 0.031 [CI, 90%: 0.000–0.052]).

Finally, to ensure the factorial validity and reliability of the measures, size of the factor loadings measuring the respective constructs were examined, as well as AVE, Cronbach’s Alpha, and Composite Reliability (CR) coefficients were calculated. Results revealed that no item loading was lower than 0.50; therefore, no items were removed (Bagozzi & Yi, 1988; Wieland et al., 2017). See Tables 2 to 4. However, factor loadings were significantly higher among the following constructs: Compulsive Buying (i.e., the “Obsessive-Compulsive Buying” – OCB, “Impulsive Buying” – IB); and values SD, ST, HE (comprising the “Openness to Change” dimension); and AC, PO (encompassing the “Self-Enhancement” dimension) among compulsive buyers compared to non-compulsive buyers. Conversely, factor loadings analyzed among non-compulsive buyers were on average higher on values SE, CO, TR (comprising the “Conservation” dimension); BE and UN (encompassing the “Self-Transcendence” dimension) compared to compulsive buyers.

Table 2.

Parameters on examined components as part of P-RCBS (Compulsive Buying) construct in CFA analysis across compulsive and non-compulsive buyers.

	Value type	Factor loadings		AVE	Alpha/Composite Reliability
	Value type	Item	Estimate	AVE	Alpha/Composite Reliability
General	Obsessive-Compulsive Buying (OCB)	P-RCBS1	0.597/0.541*	0.7500.673*	0.789/0.7910.694/ 0.713
		P-RCBS2	0.863/0.792*
		P-RCBS3	0.789/0.687*
	Impulsive Buying (IB)	P-RCBS5	0.906/0.692*	0.7800.597*	0.825/0.8550.652/0.691
		P-RCBS6	0.690/0.575*
		P-RCBS9	0.693/0.523*

Note: Groups: *Compulsive buyers, **Non-compulsive buyers. Meaning of symbols P-RCBS1-P-RCBS9 (see Appendix 1).

Model fit statistics for set of values: Group*: $χ^{2}$ = 6.105, df = 8, Prob. ≤0.05 = 0.635; CFI = 0.993, TLI = 0.989; SRMR = 0.019; RMSEA = 0.000 (90 percent C.I.: 0.000–0.049). Group**: $χ^{2}$ = 14.627, df = 8, Prob. ≤0.05 = 0.066; CFI = 0.941, TLI = 0.916; SRMR = 0.048; RMSEA = 0.086 (90 percent C.I.: 0.000–0.155).

Table 3.

Parameters on examined value as part of ‘Openness to Change’ and ‘Self-Enhancement’ in CFA analysis across compulsive and non-compulsive buyers.

Dimension	Value type	Factor loadings		AVE	Alpha/Composite Reliability
Dimension	Value type	Item	Estimate	AVE	Alpha/Composite Reliability
Openness to Change	Self-Direction (SD)	SD1	0.708/0.622*	0.7020.560*	0.822/0.8410.621/0.639
		SD11	0.586/0.515*
		SD22	0.807/0.585*
		SD34	0.707/0.516*
	Stimulation (ST)	ST6	0.708/0.622*	0.6690.581*	0.783/0.8120.616*/0.631
		ST15	0.685/0.529*
		ST30	0.615/0.593*
	Hedonism (HE)	HE10	0.767/0.539*	0.7480.557*	0.802/0.8140.621/0.645
		HE26	0.631/0.591*
		HE37	0.847/0.541*
Self-Enhancement	Achievement (AC)	AC4	0.628/0.516*	0.7030.621*	0.822/0.8540.663/0.692**
		AC13	0.817/0.694*
		AC24	0.655/0.579*
		AC32	0.713/0.694*
	Power (PO)	PO2	0.591/0.541*	0.8030.608*	0.846/0.8650.648/0.721
		PO17	0.921/0.565*
		PO39	0.896/0.718*

Note for respective Groups is the same as in Table 2. Meaning of particular items adhered to constructs SD, ST, HE, AC and PO (see Appendix 1).

Model fit statistics for set of values: SD, ST and HE: Group*: $χ^{2}$ = 49.302, df = 31, Prob. ≤0.05 = 0.039; RMSEA = 0.058 (90 percent C.I.: 0.040–0.075); CFI = 0.950, TLI = 0.927; SRMR = 0.050. Group**: $χ^{2}$ = 85.999, df = 31, Prob. ≤0.05 = 0.000; RMSEA = 0.073 (90 percent C.I.: 0.030–0.110); CFI = 0.888, TLI = 0.838; SRMR = 0.088.

Model fit statistics for set of values: AC and PO: Group*: $χ^{2}$ = 47.886, df = 31, Prob. ≤0.05 = 0.083; RMSEA = 0.037 (90 percent C.I.: 0.024–0.089); CFI = 0.969, TLI = 0.956; SRMR = 0.023. Group**: $χ^{2}$ = 76.615, df = 31, Prob. ≤0.05 = 0.073; RMSEA = 0.067 (90 percent C.I.: 0.0351–0.084); CFI = 0.934, TLI = 0.904; SRMR = 0.052.

Table 4.

Parameters on examined value as part of ‘Conservation’ and ‘Self-Transcendence’ in CFA analysis across compulsive and non-compulsive buyers.

Dimension	Value type	Factor loadings		AVE	Alpha/Composite Reliability
Dimension	Value type	Item	Estimate	AVE	Alpha/Composite Reliability
Conservation	Security (SE)	SE5	0.562/0.751*	0.5670.682*	0.632/0.7100.718/0.832
		SE14	0.673/0.676*
		SE21	0.527/0.578*
		SE31	0.528/0.593*
		SE15	0.542/0.811*
	Conformity (CO)	CO7	0.588/0.633*	0.5990.689*	0.648/0.6990.731/0.819
		CO16	0.599/0.753*
		CO28	0.524/0.589*
		CO36	0.686/0.781*
	Tradition (TR)	TR9	0.537/0.675*	0.6130.645*	0.634/0.7850.808/0.921
		TR20	0.613/0.705*
		TR25	0.739/0.606*
		TR38	0.564/0.593*
	Benevolence (BE)	BE12	0.686/0.757*	0.5940.762*	0.651/0.7920.853/0.912
Self-Transcendence		B18	0.547/0.637*
		BE27	0.589/0.797*
		BE33	0.552/0.856*
	Universalism (UN)	UN3	0.579/0.671*	0.5670.682*	0.624/0.6430.762/0.775
		UN8	0.509/0.584*
		UN19	0.534/0.688*
		UN23	0.536/0.690*
		UN29	0.708/0.779*
		UN40	0.536/0.677*

Note for respective Groups is the same as in Table 2. Meaning of particular items adhered to constructs SE, CO, TR, BE and UN (see Appendix 1).

Model fit statistics for set of values: SE, CO and TR: Group*: $χ^{2}$ = 96.828, df = 49, Prob. ≤0.05 = 0.000; RMSEA = 0.050 (90 percent C.I.: 0.035–0.064); CFI = 0.923, TLI = 0.915; SRMR = 0.076. Group**: $χ^{2}$ = 76.639, df = 49, Prob. ≤0.05 = 0.071; RMSEA = 0.041 (90 percent C.I.: 0.038–0.101); CFI = 0.963, TLI = 0.955; SRMR = 0.047.

Model fit statistics for set of values: BE and UN: Group*: $χ^{2}$ = 45.660, df = 33, Prob. ≤0.05 = 0.093; RMSEA = 0.031 (90 percent C.I.: 0.010–0.068); CFI = 0.946, TLI = 0.927; SRMR = 0.068. Group**: $χ^{2}$ = 41.910, df = 33, Prob. ≤0.05 = 0.137; RMSEA = 0.049 (90 percent C.I.: 0.000–0.052); CFI = 0.984, TLI = 0.978; SRMR = 0.03.

To conclude, as observed from Tables 2 to 4, all factors yielded acceptable results, but they were lower among non-compulsive consumers compared to compulsive buyers in the case of the following factors: OCB, IB, SD, ST, HE, AC and PO (see Figure 2). Conversely, AVE and Cronbach’s Alpha coefficients calculated for the SE, CO, TR, BE, and UN factors were larger among non-compulsive buyers than compulsive buyers. Finally, all CR coefficients calculated for the latent variables (see Tables 2 to 4) reached acceptable values across both compulsive and non-compulsive buyers (Fornell & Larcker, 1981; Jöreskog, 1971).

Figure 2.

AVE, CR and Alpha coefficients across measured latent variables and two groups: compulsive and non-compulsive consumers.

Testing hypothesized relationships

Table 5 summarizes the hypothesized and confirmed/rejected relationships based on expected effects between the group of compulsive and non-compulsive buyers (+/). The results were classified according to four structural models measuring distinct types of value sets such as: SD, ST, and HE (“Openness to Change” dimension); AC and PO (“Self-Enhancement” dimension); SE, CO, and TR (“Conservation” dimension); BE and UN (“Self-Transcendence” dimension) in relation to P-RCBS.

Table 5.

Structural parameters of SEM models diagnosing relationships between particular value types and compulsive buying in compulsive and non-compulsive group.

Structural path coefficients (SPC)	Standardized solution				Model fit information								Probability of Wald test on SPC differences	Hypothesis support based on theoretical and empirical findings
Structural path coefficients (SPC)	Estimate	S.E.	Est./S.E.	Probability	$χ^{2}$	Df	Prob.	RMSEA	90 percent C.I.	CFI	TLI	SRMR	Probability of Wald test on SPC differences
SD → P-RCBS	0.6190.012*	0.0770.014*	8.0240.857*	0.0000.981*	119.524152.940*	96/*	0.0450.000*	0.0390.048*	0.023–0.0530.027–0.061*	0.9480.908*	0.9340.873*	0.0480.088*	0.000^▪	H1aH1b	AcceptedAcceptedAcceptedAcceptedAcceptedRejected
ST → P-RCBS	0.5980.028*	0.0870.197*	6.8900.140*	0.0000.889*									0.034^▪	H2aH2b
HE → P-RCBS	0.8940.267*	0.0700.098*	12.7622.724*	0.0000.016*									0.000^▪	H3aH3b
AC → P-RCBS	0.6230.265*	0.1090.088*	5.7153.011*	0.0000.030*	79.897117.595*	60/*	0.0830.000*	0.0210.065*	0.012–0.0380.046–0.079*	0.9620.915*	0.9450.905*	0.0320.063*	0.069^▪	H4aH4b	AcceptedRejectedAcceptedAccepted
PO → P-RCBS	0.4980.051*	0.0730.100*	6.8290.510*	0.0000.610*	79.897117.595*	60/*	0.0830.000*	0.0210.065*	0.012–0.0380.046–0.079*	0.9620.915*	0.9450.905*	0.0320.063*	0.009^▪	H5aH5b	AcceptedRejectedAcceptedAccepted
SE → P-RCBS	−0.283−0.430*	0.0940.078*	−3.010−5.512*	0.0190.000*	121.62869.211*	127/*	0.0070.169*	0.0780.029*	0.065–0.0870.018–0.039	0.9040.971*	0.8920.941*	0.0790.031*	0.023^▪	H6aH6b	RejectedAcceptedRejectedAcceptedAcceptedAccepted
CO → P-RCBS	−0.239−0.610*	0.0980.078*	−2.438−7.820*	0.0130.000*									0.035^▪	H7aH7b
TR → P-RCBS	−0.012−0.757*	0.1390.093*	−0.086−8.139*	0.4480.000*									0.001^▪	H8aH8b
BE → P-RCBS	−0.098−0.676*	0.1260.089*	−0.767−7.595*	0.5460.018*	101.18445.015*	99/*	0.0340.291*	0.0690.018*	0.052–0.0790.000–0.023*	0.9030.988*	0.8970.986*	0.0650.039*	0.007^▪	H9aH9b	RejectedAcceptedAcceptedAccepted
UN → P-RCBS	−0.158−0.472*	0.0930.062*	−1.698−7.612*	0.0310.000*	101.18445.015*	99/*	0.0340.291*	0.0690.018*	0.052–0.0790.000–0.023*	0.9030.988*	0.8970.986*	0.0650.039*	0.043^▪	H10aH10b	RejectedAcceptedAcceptedAccepted

Note: Groups: *Compulsive buyers, **Non-compulsive buyers.

Note for respective Groups is the same as in Table 2, and for value types as in Tables 3 and 4.

^▪Results of Wald test were obtained between two groups on the basis of analysis conducted in Mplus 8.0. Tests between particular structural path coefficients (SPC) pertained to: SD → P-RCBS; ST → P-RCBS; HE → P-RCBS; AC → P-RCBS; PO → P-RCBS; SE → P-RCBS; CO → P-RCBS; TR → P-RCBS; BE → P-RCBS; UN → P-RCBS.

There were no statistical differences among the different types of schools (i.e., professional schools, high schools, and universities) when examining personal values and compulsive buying.

Model 1: SD, ST and HE values → P-RCBS

The fit indices for all structural models indicated a satisfactory fit. The path relations in these models, as obtained for the group of compulsive buyers were the following: SD→ P-RCBS (0.619); ST→ P-RCBS (0.598); HE→ P-RCBS (0.894) with model results as follows $χ^{2}$ = 119.524, df = 96, p = 0.045; CFI = 0.948; TLI = 0.934; SRMR = 0.048; RMSEA = 0.039 [CI, 90%: 0.023–0.053]. In contrast, the same path relations for non-compulsive buyers were only moderately acceptable ( $χ^{2}$ = 152.940, df = 96, p = 0.000; CFI = 0.908; TLI = 0.873; SRMR = 0.088; RMSEA = 0.048 [CI, 90%: 0.027–0.061]). Moreover, despite the fact the standardized path between HE→ P-RCBS (0.267) was positive and significant, it was lower as compared to the path measured for compulsive buyers. Additionally, two other coefficients, SD→ P-RCBS (0.012) and ST→ P-RCBS (0.028) indicated positive relationships, but were not significant.

The postulated hypotheses (H1a-b; H2a-b; H3a-b), which posited that those who would more strongly endorse SD, ST and HE values would be compulsive buyers was supported. Non-compulsive buyers did not show, in terms of statistical estimation, the same inclination toward these values as compared to compulsive buyers. They did not have the same orientation (see Table 5 and results of Wald tests conducted between particular structural path coefficients) as compulsive buyers, toward SD, ST and HE values and compulsive buying. As a result, we claim that the relationships between SD→ P-RCBS, ST→ P-RCBS do not exist, although in case of path HE→ P-RCBS, we observe that that relationship is significant and moderate. Overall, hypotheses H1a, H2a, H3a (related to compulsive buyers), as well as hypotheses H1b and H2b (concerning non-compulsive buyers) were supported, but hypothesis H3b received no support.

Model 2: AC, PO values → P-RCBS

Similarly, in the case of hypotheses H4a-b, H5a-b, in which it was postulated that as AC and PO values increase so will compulsive buying propensity. It was argued that the only noticeable difference within the examined relationships (i.e., AC→ P-RCBS and PO→ P-RCBS) will be the level of intensity of the calculated path coefficients between compulsive and non-compulsive buyers. That is, a higher orientation on AC and PO values should be associated with compulsive buying, whereas a lack of relationship or very low level should be associated with non-compulsive buying.

Results revealed substantive support for hypotheses H4a, H5a, and H5b, but no support for hypothesis H4b that concerned non-compulsive buyers. In other words, both paths were positive and significant among compulsive buyers: 0.623 (AC→ P-RCBS) and 0.498 (PO→ P-RCBS); whereas among non-compulsive buyers, the path coefficient (AC→ P-RCBS) was significant, although it obtained a lower value (0.265), while path coefficient (PO→ P-RCBS) was not significant at all. Also note that according to Wald test, calculated for both groups, the coefficient (AC→ P-RCBS) did not indicate a statistical difference (p = 0.069).

Finally, the SEM model calculated for compulsive buyers, diagnosing the relationships between AC→ P-RCBS and PO→ P-RCBS, yielded the following fit ( $χ^{2}$ = 79.897, df = 60, p = 0.083; CFI = 0.962; TLI = 0.945; SRMR = 0.032; RMSEA = 0.021 [CI, 90%: 0.012–0.038]), while for non-compulsive buyers, the following fit was obtained ( $χ^{2}$ = 117.595, df = 60, p = 0.000; CFI = 0.915; TLI = 0.905; SRMR = 0.063; RMSEA = 0.065 [CI, 90%: 0.046–0.079]).

Model 3: SE, CO and TR values → P-RCBS

Results associated with values such as SE, CO and TR (comprising the “Conservation” dimension) in the context of the postulated relationships with compulsive buying (P-RCBS), indicated the following effects across both compulsive and non-compulsive buyers. Namely, research findings obtained on the basis of SEM model ( $χ^{2}$ = 69.211, df = 127, p = 0.169; CFI = 0.971; TLI = 0.941; SRMR = 0.031; RMSEA = 0.029 [CI, 90%: 0.018–0.039]) showed a stronger negative influence of SE, CO and TR on the P-RCBS among non-compulsive buyers across all three tested paths (SE→ P-RCBS = −0.430; CO→ P-RCBS = −0.610; TR→ P-RCBS = −0.757). Given these results, hypotheses H6b, H7b, H8b, which claimed a negative direction of orientation between these types of values and compulsive buying, were supported.

In contrast, the SEM model ( $χ^{2}$ = 121.628, df = 127, p = 0.007; CFI = 0.903; TLI = 0.897; SRMR = 0.065; RMSEA = 0.078 [CI, 90%: 0.065–0.087]) calculated for compulsive buyers, yielded the following results (SE→ P-RCBS = −0.283; CO→ P-RCBS = −0.239). These relationships were statistically significant, but lower as compared to non-compulsive buyers. There was only one low and nonsignificant relationship (TR→ P-RCBS = −0.012). Therefore, we accepted hypothesis H8a, while hypotheses H6a and H7a were rejected although values of the respective structural paths (SE→ P-RCBS; CO→ P-RCBS) were significant, they were lower as compared to the group of compulsive buyers. This suggests that compulsive buyers have a very low orientation on values such as SE, CO and TR and because of this, they will be more vulnerable to compulsive buying tendencies. In contrast, because orientations among young non-compulsive buyers are higher on SE, CO, and TR, non-compulsive buyers can successfully oppose compulsive buying behavior. These research findings were supported by results of the Wald test obtained within each structural path coefficient. See Table 5.

Model 4: BE and UN values → P-RCBS

Examining the relationships between BE and UN values, the SEM model for non-compulsive buyers obtained the following fit ( $χ^{2}$ = 45.015, df = 99, p = 0.291; CFI = 0.988; TLI = 0.986; SRMR = 0.039; RMSEA = 0.018 [CI, 90%: 0.000–0.023]), whereas the model tested for compulsive buyers yielded the following results: $χ^{2}$ = 101.184, df = 99, p = 0.034; CFI = 0.903; TLI = 0.897; SRMR = 0.065; RMSEA = 0.069 [CI, 90%: 0.052–0.079]. See Table 5. For compulsive buyers, only one path coefficient was significant in the SEM model (UN→ P-RCBS = −0.158), whereas for non-compulsive buyers, all standardized path coefficients were significant and large (BE→ P-RCBS = −0.676; UN→ P-RCBS = −0.472). It appears that for non-compulsive buyers the higher their orientation on BE and UN values, the lower their propensity to compulsively buy. In the case of compulsive buyers, these relationships were low and nonsignificant (with the exception of the aforementioned path UN→ P-RCBS). Compulsive buyers simply attributed lower importance to values as BE and UN than do non-compulsive buyers (see Wald test results in Table 5). Thus, it seems that the greater focus one has on societal objectives in life, instead of focusing on individual interests, makes non-compulsive buyers more immune to compulsive buying. In contrast, compulsive buyers were more susceptible to compulsive buying tendencies due to their rejection of BE and UN values. To conclude, hypothesis H9b and H10b with regard to non-compulsive buyers was supported. For compulsive buyers, only hypothesis H10a was supported, while hypothesis H9a was rejected.

Diagnosis of integrated relationships based on four general values and compulsive buying

To explore the entire set of values in a global configuration that allowed us to assess the relative importance of the ‘value constellations’ relative to one another, we decided to investigate an integrated, single model. However, as mentioned earlier, due to unequal proportions of the two examined groups (especially given the compulsive buyers’ group), we used ‘parceling strategy’ (Bandalos, 2008; Little et al., 2002). The effect was value types were analyzed as ‘broader value constellations’ (see Cieciuch & Schwartz, 2012) in the following configuration: “Openness to Change”, “Self-enhancement”, “Conservation”, “Self-transcendence”. The same strategy was applied to construct ‘Compulsive Buying” (see Table 6). A major strength of this methodological approach was that four general personal values were included as potential drivers of compulsive buying behavior.

Table 6.

Structural parameters of integrated SEM model diagnosing relationships between four general value dimensions and compulsive buying in compulsive and non-compulsive group.

Structural path coefficients (SPC)	Standardized solution
Structural path coefficients (SPC)	Estimate	S.E.	Est./S.E.	Probability
Openness to Change (SD, ST, HE) → Compulsive Buying (OCB, IB)	0.7040.097*	0.0970.018	7.2570.538	0.0000.829
Self-Enhancement (AC, PO) → Compulsive Buying (OCB, IB)	0.5610.131*	0.1270.093	4.4171.401	0.0000.043
Conservation (SE, CO, TR) → Compulsive Buying (OCB, IB)	−0.108−0.599*	0.0700.089	−1.542−6.730	0.0690.000
Self-Transcendence (BE, UN) → Compulsive Buying (OCB, IB)	−0.092*−0.624	0.0320.124	−2.358−5.032	0.5910.000

Note: Groups: *Compulsive buyers, **Non-compulsive buyers.

Model fit results: $χ^{2}$ = 34.411, DF = 4, Prob. = 0.528, RMSEA = 0.036 (90 percent C.I.: 0.021 – 0.058, CFI = 0.978, TLI = 0.962, SRMR = 0.023.

Note: General values parceled as broader value constellations: “Openness to Change” dimension (SD = Self-Direction, ST = Stimulation, HE = Hedonism); “Self-Enhancement” (AC = Achievement, PO = Power); “Conservation” (SE = Security, CO = Conformity, TR = Tradition); “Self-Transcendence” (BE = Benevolence, UN = Universalism). “Compulsive Buying” construct parceled with two components (OCB = Obsessive-Compulsive Buying, IM = Impulsive Buying).

^▪Results of Wald test were obtained between two groups on the basis of analysis conducted in Mplus 8.0. They are significant on four tested paths at p < 0.05, p < 0.01.

Table 6 summarizes the encompassing values configuration, based on the integrated model, where the fit indices indicated a satisfactory fit ( $χ^{2}$ = 34.411, df = 4, p = 0.528; CFI = 0.978; TLI = 0.962; SRMR = 0.023; RMSEA = 0.036 [CI, 90%: 0.021–0.058]). Research findings indicated that “Self-Enhancement” (SD, ST, HE) and “Openness to Change” (AC, PO) value constellations were the most important motives that drive compulsive buying among young adults; that is, those who held these values were more likely to be compulsive buyers. In contrast, young adults who held values comprising “Self-Transcendence” (BE, UN) and “Conservation” (SE, CO, TR), were more likely to be non-compulsive buyers.

Discussion and conclusions

The goal of the current study was to explore how personal values may impact compulsive buying behavior in two contrasting groups of young adults. Results generally supported the hypotheses. That is, among those categorized as compulsive buyers, “Self-Direction”, “Stimulation”, “Hedonism”, “Achievement”, and “Power” were related positively to compulsive buying, while “Security”, “Conformity”, and “Universalism” were inversely and weakly associated with compulsive buying. For those classified as non-compulsive buyers, “Hedonism”, and “Achievement” were weakly related to compulsive buying, while “Security”, “Conformity”, “Tradition”, “Benevolence”, and “Universalism” were negatively associated with compulsive buying.

“Self-Direction”, “Stimulation”, “Hedonism”, “Achievement”, and “Power” values stress the importance of striving to fulfill individualistic goals at the expense of others (Burroughs & Rindfleisch, 2002). The result for compulsive buyers is they become more hedonistic and use goods (and services) to obtain the approval of others (Dittmar, 2000; Harnish et al., 2018a). The current findings suggest that compulsive buyers are more self-focused, power- and achievement-oriented than non-compulsive buyers. In other words, when consumers become more hedonistic, self-focused, and prone to social-market stimulations, such consumers may use an irrational approach to buying goods and services (see also Horváth & Adigüzel, 2018). Results also revealed that values comprising the constructs of “Self-Enhancement” and “Openness to Change” appear to motivate compulsive buyers’ purchasing behavior. These findings are consistent with research that suggests compulsive buyers use purchases to increase their social standing and self-esteem (Dittmar & Drury, 2000; Dittmar et al., 1996). That is, by using the symbolic qualities of the products (and services) purchased in a transaction with others (i.e., salespeople, others present for the sale), compulsive buyers improve their self-image and project a desirable image to others (Harnish et al., 2018a).

Because the values comprising the constructs of “Self-Enhancement” and “Openness to Change” motivate compulsive buyers’ purchasing behavior, compulsive buyers may feel better about themselves by demonstrating to others they have achieved material success resulting in higher social status illustrated by an extravagant lifestyle. As Burroughs and Rindfleisch (2002) noted, individuals who value “Achievement” and “Power” (components of the “Self-Enhancement” dimension) tend to seek out the approval of others, while those who value “Stimulation”, “Self-Direction”, and “Hedonism” (components of “Openness to Change” dimension) are more materialistically oriented. Thus, for compulsive buyers, “Self-Enhancement” and “Openness to Change” values are what motivates their maladaptive purchasing behavior. More specifically, for compulsive buyers, feeling better about themselves through the ostentatious display of symbolic goods reduces the anxiety, depression or negative affect they experience about themselves.

In contrast, the values comprising “Self-Transcendence” and “Conservation” emphasize the importance of communal rather than individualistic goals (Schwartz, 2015). The current findings suggest that these values appear to prevent compulsive buying. In other words, in order to meet communal goals, other-focus and self-restraint (i.e., self-regulation) are needed. Consequently, these values protect individuals not only from becoming a compulsive buyer, but also from becoming a person more oriented on “Hedonism”, “Stimulation”, “Power”, and “Achievement” values. As related to the current study, non-compulsive buyers do not have to self-enhance to increase their social status as they may have a sense of belonging and meaning in their life. Moreover, non-compulsive buyers value self-restraint; they may be humbler and prefer a lifestyle that emphasizes eudemonic well-being (see Ryan & Deci, 2001 for a review of hedonic and eudemonic well-being). Indeed, self-restraint or self-regulation has been identified as an important value that differentiates various maladaptive purchasing behaviors. For example, Harnish and Roster (2019) proposed that maladaptive purchasing behavior can be understood by understanding how self-regulation, pain of paying, and acquisitiveness (i.e., materialism) interact to guide purchasing behavior. In this context, we should infer that, compulsive buyers, in contrast to non-compulsive buyers, fail to self-regulate when faced with a purchasing decision (i.e., control spending) and experience little pain of paying when making a purchasing decision (Harnish et al., 2018a). It could be that “Self-Transcendence” and “Conservation” values underpin the ability to self-regulate thereby helping to “immunize” oneself from compulsively buying goods or services.

Implications

Theoretical

Personal value theory (Schwartz, 1992, 1994, 2012) can assist social science researchers, particularly consumer researchers, in many ways. The results of the current study suggest that with the proper understanding of an individuals’ interpersonal worlds and their adaptation to the external environment (Kahle, 1983), better insight into the underlying motives for maladaptive purchasing behavior may be obtained. This is because values serve as standards of conduct across cultures (Rokeach, 1973) that underlie human cognition and behaviors (Schwartz, 1992). Specifically, the centrality of values to an individual’s cognitive structure can explain the underpinnings of consumption behavior (Burgess, 1992; Krystallis et al., 2012).

Interestingly, despite the significance of values theory for understanding consumer behavior, insufficient attention has been paid to values. As noted earlier, most prior studies generally focused on materialistic aspects of consumption (e.g., Dittmar, 2005a, 2005b; Richins & Dawson, 1992; Mowen & Spears, 1999; O’Guinn & Faber, 1989); where materialists seemed to embody a hedonistic orientation toward consumption (Horváth & Adigüzel, 2018; Moen, 2016; O’Shaughnessy & O’Shaughnessy, 2002; Zhong & Mitchell, 2012), neglecting simultaneously relationships among other value types and compulsive buying behavior. Therefore, by developing a conceptual model of the relationships among value types and compulsive buying, we have provided important insight into both personal values theory and consumer behavior theory in the following ways. First, as Faber and O’Guinn (1992) noted, a deeper understanding of the antecedents bearing responsibility for compulsive buying behavior awaits investigation and until now, little attention has been given to how personal values motivate compulsive buying. The current research provides a more complete understanding of the underpinnings of compulsive buying by assessing the relative importance of different values, relative to one another, in driving compulsive buying behavior. As revealed, “Self-Enhancement” and “Openness to Change” values are the most important motives that motivate compulsive buying among young consumers. These motives place greater importance on personal rather than communal goals, and as such suggest that young compulsive buyers lack self-esteem and the ability (or motivation) to self-regulate. As a consequence, these deficiencies strongly affect their buying behaviors such that these individuals are more inclined to consume without deliberation relying on emotions to guide their behavior.

Second, the current findings imply that young adults who hold values comprising ‘Self-Transcendence’ and ‘Conservation’ dimensions, were more likely to be non-compulsive buyers. Recall those who held stronger values on the “Self-Enhancement” and “Openness to Change” dimension were more likely to be compulsive buyers; they were more self-focused, hedonistic, power- and achievement-oriented than non-compulsive buyers. By conducting a comprehensive diagnosis of the relationships between all value types with compulsive buying, as conducted across both groups, we were able to explain the extent to which a particular value fostered compulsive buying. In doing so, we gained insight into which values make consumers more prone toward compulsive buying, and which values make consumers less inclined to compulsively buy. To conclude, the current research findings make a useful contribution to understanding compulsive buying in a new theoretical context – personal values.

Practical

The current findings offer interesting implications for controlling excessive consumerism and uncontrolled spending (Campbell, 2018; S. Miles, 1998). For instance, marketers may emphasize the values that comprise both the “Conservation” and “Self-Transcendence” dimensions and/or contrast them with values that comprise the “Openness to Change” and “Self-Enhancement” dimensions. In particular, this strategy might be applied to advertising in order to help consumers restrain their purchasing. That is, by describing a good or service so that the consumer understands the benefits it provides to oneself, as well as to others, spending might be controlled. For example, Macy’s has a Thanks for Sharing program where a cardholder can donate (i.e., charge) $25 to their Macy’s card and receive in return 10% back in rewards. Such an approach that emphasizes the greater good (i.e., donating monies to charity) but receiving something in return (i.e., 10% off all purchases) provides an individual with dual motives. Namely, values that comprise the “Self-Enhancement” dimension (that typically serve a utilitarian function in which individuals seek to maximize rewards) are contrasted with values that comprise the “Self-Transcendence” dimension (that typically serve a value-expressive function which facilitates the expression of important values and self-concept). In fact, in a series of experiments conducted by Maio and Olson (1994, 1995), values that comprised both the “Self-Enhancement” and “Self-Transcendence” dimensions were shown to serve both a value-expressive and utilitarian function for an individual if they reflected specific motivational goals. Thus, by contrasting these values, a goal-expressive (both utilitarian and value-expressive) attitude may be expressed. This should not only reduce the likelihood of overspending, debt, or bankruptcy among compulsive buyers, but it also should result in favorable perceptions of the company’s marketing activity, meeting the norms of the social responsibility and generating good will toward the company itself.

In sum, by understanding how values underpin compulsive buying, preventative actions such as promoting ‘good’ values for consumers, compulsive buying behaviors may be reduced or kept under control. The effect of conscious and long-term processes of ‘accentuating’ good values should lead to the reduction of the overspending, which in turn should increase the well-being of individuals, families, and societies.

Limitations of the study and future research

Contributions of this research need to be interpreted in light of its limitations, which at the same time provide opportunities for further research. First, the current research examines compulsive buying in an educated, industrialized, economically fast-growing and democratic culture as Poland (see Central Statistical Office in Poland, 2018; Eurostat, 2020). Because of this, it would be interesting to explore values and compulsive buying in the context of the socio-economic-cultural differences in other mature and developing countries (e.g., Cleveland et al., 2013; Harding & Philips, 1986; Kim et al., 2002).

Another limitation of the current research is that the results are based on a cross-sectional design. Future research may employ alternative methodological approaches such as longitudinal designs that can enhance causal inferences. This is important because as particular societies change economically, demographically, and culturally (Steenkamp & Maydeu-Olivares, 2015), we should expect changes in the importance placed on particular values and consequently in the prevalence of compulsive buying behavior.

Finally, future studies should focus on experimental research and group comparison. Additional research is needed to explore how demographic characteristics impact compulsive buying. For instance, it would be interesting to investigate the moderating effect of gender on values and compulsive buying. Additionally, it might be interesting to explore compulsive buying in the context of group differences/similarities based on demographic traits beyond gender.

Appendix 1

Portraits (male version*)
Here we briefly describe some people. Please read each description and think about how much each person is or is not like you. Put an X in the box to the right that shows how much the person in the description is like you. For answers use the following scale, where: 6 – Very much like me; 5 – Like me; 4 – Somewhat like me; 3 – A little like me; 2 – Not like me; 1 – Not like me at all
SD1. Thinking up new ideas and being creative is important to him. He likes to do things in his own original way.
PO2. It is important to him to be rich. He wants to have a lot of money and expensive things.
UN3. He thinks it is important that every person in the world be treated equally. He believes everyone should have equal opportunities in life.
AC4. It’s very important to him to show his abilities. He wants people to admire what he does.
SC5. It is important to him to live in secure surroundings. He avoids anything that might endanger his safety.
ST6. He thinks it is important to do lots of different things in life. He always looks for new things to try.
CO7. He believes that people should do what they’re told. He thinks people should follow rules at all times, even when no one is watching.
UN8. It is important to him to listen to people who are different from him. Even when he disagrees with them, he still wants to understand them.
TR9. He thinks it’s important not to ask for more than what you have. He believes that people should be satisfied with what they have.
HE10. He seeks every chance he can to have fun. It is important to him to do things that give him pleasure.
SD11. It is important to him to make his own decisions about what he does. He likes to be free to plan and to choose his activities for himself.
BE12. It’s very important to him to help the people around him. He wants to care for their well-being.
AC13. Being very successful is important to him. He likes to impress other people.
SC14. It is very important to him that his country be safe. He thinks the state must be on watch against threats from within and without.
ST15. He likes to take risks. He is always looking for adventures.
CO16. It is important to him always to behave properly. He wants to avoid doing anything people would say is wrong.
PO17. It is important to him to be in charge and tell others what to do. He wants people to do what he says.
BE18. It is important to him to be loyal to his friends. He wants to devote himself to people close to him.
UN19. He strongly believes that people should care for nature. Looking after the environment is important to him.
TR20. Religious belief is important to him. He tries hard to do what his religion requires.
SC21. It is important to him that things be organized and clean. He really does not like things to be a mess.
SD22. He thinks it’s important to be interested in things. He likes to be curious and to try to understand all sorts of things.
UN23. He believes all the worlds’ people should live in harmony. Promoting peace among all groups in the world is important to him.
AC24. He thinks it is important to be ambitious. He wants to show how capable he is.
TR25. He thinks it is best to do things in traditional ways. It is important to him to keep up the customs he has learned.
HE26. Enjoying life’s pleasures is important to him. He likes to ‘spoil’ himself.
BE27. It is important to him to respond to the needs of others. He tries to support those he knows.
CO28. He believes he should always show respect to his parents and to older people. It is important to him to be obedient.
UN29. He wants everyone to be treated justly, even people he doesn’t know. It is important to him to protect the weak in society.
ST30. He likes surprises. It is important to him to have an exciting life.
SC31. He tries hard to avoid getting sick. Staying healthy is very important to him.
AC32. Getting ahead in life is important to him. He strives to do better than others.
BE33. Forgiving people who have hurt him is important to him. He tries to see what is good in them and not to hold a grudge.
SD34. It is important to him to be independent. He likes to rely on himself.
SC35. Having a stable government is important to him. He is concerned that the social order be protected
CO36. It is important to him to be polite to other people all the time. He tries never to disturb or irritate others.
HE37. He really wants to enjoy life. Having a good time is very important to him.
TR38. It is important to him to be humble and modest. He tries not to draw attention to himself.
PO39. He always wants to be the one who makes the decisions. He likes to be the leader.
UN40. It is important to him to adapt to nature and to fit into it. He believes that people should not change nature.

Conformity; TR = Tradition; BE = Benevolence; UN = Universalism; SD = Self-Direction; ST = Stimulation; HE = Hedonism; AC = Achievement; PO = Power; SC = Security.

The number next to the abbreviation of each value name corresponds to its order in the questionnaire.

*Both versions for males and female can be found in work of Cieciuch and Zaleski (2011), Schwartz et al. (2001).

P-RCBS scale
Please characterize with below statements, your buying behavior according to 7-point scale, where: 1 = strongly disagree; 3 = neither agree nor disagree 7 = strongly agree.
P-RCBS1. My closet has unopened shopping bags in it
P-RCBS2. Others might consider me a ‘shopaholic
P-RCBS3. Much of my life centers around buying things
P-RCBS5. I buy things I don’t need
P-RCBS6. I buy things I did not plan to buy
P-RCBS9. I consider myself an impulse purchaser

Source: Tarka and Kukar-Kinney (2020), Ridgway et al. (2008).

Appendix 2

Correlations between constructs	P-RCBS	SD	ST	HE	AC	PO	SE	CO	TR	BE	UN
P-RCBS	1.000
SD	0.519**	1.000
ST	0.637**	0.462**	1.000
HE	0.795**	0.260**	0.605**	1.000
AC	0.637**	0.481**	0.363**	0.397**	1.000
PO	0.497**	0.354**	0.251**	0.286**	0.565**	1.000
SE	−0.511**	0.133*	0.052	0.065	0.124*	0.178**	1.000
CO	−0.593**	0.069	0.082	0.029	0.112*	0.019	0.512**	1.000
TR	−0.279**	−0.016	0.069	−0.062	−0.003	−0.188**	0.398**	0.538**	1.000
BE	−0.393**	0.198**	0.073	0.118*	0.096*	−0.081	0.253**	0.392**	0.367**	1.000
UN	−0.459**	0.248**	0.104*	0.066	0.121**	−0.116*	0.339**	0.414**	0.317**	0.479**	1.000

**Correlation is significant at the 0.01 level (2-tailed); *Correlation is significant at the 0.05 level (2-tailed). Short-cuts see Tables 2 to 4, N = 804.

Supplemental Material

sj-pdf-1-prx-10.1177_0033294120959777 - Supplemental material for Toward the Extension of Antecedents of Compulsive Buying: The Influence of Personal Values Theory

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Supplemental Material

sj-pdf-2-prx-10.1177_0033294120959777 - Supplemental material for Toward the Extension of Antecedents of Compulsive Buying: The Influence of Personal Values Theory

Supplemental material, sj-pdf-2-prx-10.1177_0033294120959777 for Toward the Extension of Antecedents of Compulsive Buying: The Influence of Personal Values Theory by Piotr Tarka and Richard J. Harnish in Psychological Reports

Footnotes

Article Notes

ORCID iD

Piotr Tarka

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Structural path coefficients (SPC)	Standardized solution				Model fit information								Probability of Wald test on SPC differences	Hypothesis support based on theoretical and empirical findings
Structural path coefficients (SPC)	Estimate	S.E.	Est./S.E.	Probability	$χ^{2}$	Df	Prob.	RMSEA	90 percent C.I.	CFI	TLI	SRMR	Probability of Wald test on SPC differences
SD → P-RCBS	0.6190.012*	0.0770.014*	8.0240.857*	0.0000.981*	119.524152.940*	96/*	0.0450.000*	0.0390.048*	0.023–0.0530.027–0.061*	0.9480.908*	0.9340.873*	0.0480.088*	0.000^▪	H1aH1b	AcceptedAcceptedAcceptedAcceptedAcceptedRejected
ST → P-RCBS	0.5980.028*	0.0870.197*	6.8900.140*	0.0000.889*									0.034^▪	H2aH2b
HE → P-RCBS	0.8940.267*	0.0700.098*	12.7622.724*	0.0000.016*									0.000^▪	H3aH3b
AC → P-RCBS	0.6230.265*	0.1090.088*	5.7153.011*	0.0000.030*	79.897117.595*	60/*	0.0830.000*	0.0210.065*	0.012–0.0380.046–0.079*	0.9620.915*	0.9450.905*	0.0320.063*	0.069^▪	H4aH4b	AcceptedRejectedAcceptedAccepted
PO → P-RCBS	0.4980.051*	0.0730.100*	6.8290.510*	0.0000.610*	79.897117.595*	60/*	0.0830.000*	0.0210.065*	0.012–0.0380.046–0.079*	0.9620.915*	0.9450.905*	0.0320.063*	0.009^▪	H5aH5b	AcceptedRejectedAcceptedAccepted
SE → P-RCBS	−0.283−0.430*	0.0940.078*	−3.010−5.512*	0.0190.000*	121.62869.211*	127/*	0.0070.169*	0.0780.029*	0.065–0.0870.018–0.039	0.9040.971*	0.8920.941*	0.0790.031*	0.023^▪	H6aH6b	RejectedAcceptedRejectedAcceptedAcceptedAccepted
CO → P-RCBS	−0.239−0.610*	0.0980.078*	−2.438−7.820*	0.0130.000*									0.035^▪	H7aH7b
TR → P-RCBS	−0.012−0.757*	0.1390.093*	−0.086−8.139*	0.4480.000*									0.001^▪	H8aH8b
BE → P-RCBS	−0.098−0.676*	0.1260.089*	−0.767−7.595*	0.5460.018*	101.18445.015*	99/*	0.0340.291*	0.0690.018*	0.052–0.0790.000–0.023*	0.9030.988*	0.8970.986*	0.0650.039*	0.007^▪	H9aH9b	RejectedAcceptedAcceptedAccepted
UN → P-RCBS	−0.158−0.472*	0.0930.062*	−1.698−7.612*	0.0310.000*	101.18445.015*	99/*	0.0340.291*	0.0690.018*	0.052–0.0790.000–0.023*	0.9030.988*	0.8970.986*	0.0650.039*	0.043^▪	H10aH10b	RejectedAcceptedAcceptedAccepted