This article was downloaded by: [University of Auckland Library] On: 17 December 2014, At: 18:47 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

The Journal of Social Psychology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vsoc20

Maximizing Relationship Possibilities: Relational Maximization in Romantic Relationships a

Alan C. Mikkelson & Perry M. Pauley a

b

Whitworth University

b

San Diego State University Accepted author version posted online: 12 Feb 2013.Published online: 13 May 2013.

To cite this article: Alan C. Mikkelson & Perry M. Pauley (2013) Maximizing Relationship Possibilities: Relational Maximization in Romantic Relationships, The Journal of Social Psychology, 153:4, 467-485, DOI: 10.1080/00224545.2013.767776 To link to this article: http://dx.doi.org/10.1080/00224545.2013.767776

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or

indirectly in connection with, in relation to or arising out of the use of the Content.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

The Journal of Social Psychology, 2013, 153(4), 467–485 Copyright © Taylor & Francis Group, LLC

Maximizing Relationship Possibilities: Relational Maximization in Romantic Relationships ALAN C. MIKKELSON Whitworth University PERRY M. PAULEY San Diego State University

ABSTRACT. Using Rusbult’s (1980) investment model and Schwartz’s (2000) conceptualization of decision maximization, we sought to understand how an individual’s propensity to maximize his or her decisions factored into investment, satisfaction, and awareness of alternatives in romantic relationships. In study one, 275 participants currently involved in romantic relationships completed measures of maximization, satisfaction, investment size, quality of alternatives, and commitment. In study two, 343 participants were surveyed as part of the creation of a scale of relational maximization. Results from both studies revealed that the tendency to maximize (in general and in relationships specifically) was negatively correlated with satisfaction, investment, and commitment, and positively correlated with quality of alternatives. Furthermore, we found that satisfaction and investments mediated the relationship between maximization and relationship commitment. Keywords: commitment, investment model, maximization, romantic relationships

SIMON (1957) PROPOSED THAT EXPLAINING human choice was about understanding cognitive limitations. Simon suggested that the optimization of choices (that is, maximization, or making the best choice possible) was essentially impossible due to the complexity of life and the limits of information processing; as such, he suggested that people “satisfice.” Satisficing, according to Simon, occurs when individuals search for an alternative that meets a predetermined set of criteria. The primary difference between “maximizers” and “satisficers” then is the level of acceptability of alternatives—people who habitually maximize search for and actively desire the best alternative variable, whereas people who satisfice Address correspondence to Alan C. Mikkelson, Whitworth University, Department of Communication Studies, 300 W. Hawthorne Rd., Spokane, WA 99251, USA; [email protected] (e-mail). 467

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

468

The Journal of Social Psychology

are content with any alternative so long as it meets their pre-determined threshold of acceptability. Although the study of maximization as an individual personality trait has gained much traction in consumer behavior research (e.g., Schwartz, 2000; Schwartz et al., 2002), relatively few studies have examined the effects of maximization in other decision-making domains. The purpose of this study is to examine how people make and understand their choices (i.e., maximizers or satisficers) and how this decision-making process ultimately influences romantic relationships. Specifically, we will examine maximization as it relates to the investment model in romantic relationships. First we will review the investment model and relevant research that supports the model. Then we will explore how people understand their choices and the specific concept of maximization. The third section will explore how maximization may relate to the components of the investment model. Investment Model The investment model (Rusbult, 1980, 1983) extends upon the logic of interdependence theory (Kelley, 1979; Kelley & Thibaut, 1978) by asserting that the decision to stay in a relationship or leave a relationship is based on feelings of commitment (Rusbult & Buunk, 1993). Commitment is defined as a “psychological state that globally represents the experience of dependence on a relationship” (Rusbult & Buunk, 1993, p. 180). The investment model offers three variables that affect feelings of commitment: satisfaction, quality of alternatives, and investment in the relationship. Satisfaction level is the favorable or unfavorable evaluation of the relationship and is derived from the comparison of positive and negative feelings experienced in the relationship (Rusbult & Buunk, 1993). Quality of alternatives is the second variable proposed to influence commitment levels. Quality of alternatives refers to the desirability of alternatives outside of the current relationship, including (but not limited to) another romantic relationship, spending time with friends or family, or pursuing other hobbies and interests. Finally, investment size refers to the resources bound to the relationship. These are resources that would be lost or would decline in value if the relationship were to end such as time, emotional energy, mutual friends, social status, shared possessions, and even identity (Rusbult, Dirgotas, & Verette, 1994). In sum, the investment model concludes that commitment is highest when individuals are highly satisfied, have poor alternatives, and have a high investment in the relationship. A meta-analysis of this model demonstrates that across studies, these three variables account for an average of 60% of the variance in commitment (Le & Agnew, 2003). Satisfaction appears to be the crucial component in determining relationship outcomes, as it explains the greatest amount of unique variance in commitment; however, regression analyses also demonstrate the importance of alternatives and investments in predicting commitment as both of these variables account for unique variance above and beyond satisfaction.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

469

Although there is a great deal of empirical support for the investment model, there has been criticism of the fact that little scholarly attention has been paid to cognitive contributors to commitment (Agnew, Van Lange, Rusbult, & Langston, 1998). Specifically, Rusbult and Arriaga (1997) argued that cognitive processes could be important because they could influence the components of the investment model and thus affect the quality of the relationship. More recently, there have been several attempts to examine some of these cognitive elements. For example, Rusbult, Martz, and Agnew (1998) examined several factors that could contribute to the model such as need for cognition, self-esteem, and impression management; however, their results revealed that these factors did not influence the predictions of the investment model. Fitzpatrick and Sollie (1999) found that both gendered and relationship-specific beliefs were related to various elements in the investment model. Specifically, unrealistic beliefs were related to greater alternatives, lower satisfaction, and lower commitment. Furthermore, in a review of literature on attachment styles and adult relationships, Morgan and Shaver (1999) found that attachment styles were related to both commitment and relationship longevity. In that analysis, individuals with secure attachment styles (and secure-secure pairs) exhibited better relationship functioning than did pairings in which one or both partners experienced insecure attachment. Although these studies represent a good start to understanding some of the individual differences that could influence the investment model, the possibility that other individual-level traits might influence the relationships between satisfaction, investment, quality of alternatives, and commitment remains largely untested. We propose that one trait difference among individuals that may influence the investment model in romantic relationships is how people make and understand their choices. In the next section, we will elaborate upon the principles of maximization as one potential factor that could influence the investment model’s predictions. Maximizers and Satisficers Schwartz (2000; Schwartz et al., 2002) argued that even though people essentially cannot maximize their choices, some attempt to do so. For these individuals, identified as maximizers, added choices can pose problems for two primary reasons: First, Schwartz recognizes that one cannot truly maximize without examining all the alternatives, and second, when it is impossible to examine all the alternatives, maximizers are prone to “lingering doubt that he or she could have done better by searching a bit more” (Schwartz et al., 2002, p. 1179). By contrast, satisficers deal with added choices in a different way. Satisficers look for an option that satisfies a pre-determined level of acceptability. According to Schwartz, added options have little effect on satisficers as long as their initial choice satisfies their criteria. Further, since “good enough” is the accepted standard instead of “best,” satisficers are less likely to experience regret than maximizers.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

470

The Journal of Social Psychology

Schwartz conceptualized maximization as a trait-level variable that occurs on a continuum with maximization at one extreme and satisficing (or nonmaximization) on the other. Further, Gillham, Ward, and Schwartz (2001; as cited in Schwartz et al., 2002) measured maximization over a period of nine months and found that maximization orientation is relatively stable despite the fact that the importance of the decision might affect the extent to which individuals are willing to engage in the process of careful maximization. In the discussion of personal relationships, the importance typically given to personal relationships might increase the probability that all people—regardless of their general tendency to maximize—might choose to seek the best possible alternative. Indeed, previous studies have demonstrated that people tend to demonstrate great care and choose more conservative options when selecting a potential dating partner (Beisswanger, Stone, Hupp, Allgaier, 2003), so we anticipate that the effects of maximization might be particularly salient in decisions involving commitment to personal relationships. Maximization and the Investment Model Maximizers want to make the best possible choice. With respect to romantic relationships, we propose that maximization (as a trait) has a direct effect on the elements of the investment model and an indirect effect on commitment (the theoretical model appears in Figure 1). The model presented is based on

FIGURE 1. Theoretical model of maximization and the investment model.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

471

the following rationale. First, maximization should be negatively associated with satisfaction because of the persistent doubts and feelings of regret that typify maximizers’ decision-making process (Hypothesis 1 [H1], path A). Second, maximizers are also more acutely of alternatives because they want to make the best choice; therefore, trait maximization and awareness of alternatives are positively correlated (H2, path B). Third, since investments tied to relationships are often lost or devalued when relationships end, maximizers might be hesitant to invest a great deal in a relationship if they are not sure it is the best choice. Consequently, as maximization increases, investments in romantic relationships should decrease (H3, path C). Finally, given that the model proposes relationships with each individual element of the investment model that would ultimately result in relational instability, we propose that maximization itself is negatively related to commitment (H4, path D). In addition to these direct paths, it is important to understand how elements of the investment model might temper the effects of maximization. Given that maximization is understood as an individual level trait variable that is relatively stable over time, we have argued that maximization should influence satisfaction, alternatives, investments, and commitment. It is also possible that these relational characteristics might mediate the effects of trait-level maximization (Research Question 1 [RQ1]). Study 1 Method Participants The participants (N = 275) were 116 (42.2%) male and 157 (57.1%) female undergraduate students in communication courses (two students did not report their biological sex) who were involved in ongoing romantic relationships. Participants ranged in age from 18 to 54 years (M = 21.38 years, SD = 3.94). The length of participants’ dating relationships ranged from one month to nine years (M = 1.70 years, SD = 1.51). The majority (72.0) was Caucasian, 8.0% were Asian/Pacific Islander, 14.3% were Hispanic, 4.4% were Black/AfricanAmerican, 1.8% were Native American, and 4.0% were of other ethnic origins. These percentages add up to more than 100% because participants were instructed to check all applicable ethnicities. Procedure Participation in the study consisted of a brief questionnaire designed to assess “communication in romantic relationships.” The study was in compliance

472

The Journal of Social Psychology

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

with the university’s Institutional Review Boards (IRB) policies. In exchange for participation, students who completed any part of the questionnaire were awarded extra course credit by their instructors. The questionnaire itself contained a series of close-ended, Likert-type questions along with important relational and personal demographic information.

Measures Investment Model. Satisfaction, quality of alternatives, investment, and commitment within relationships were assessed with Rusbult and colleagues’ (1998) Investment Model Scale (IMS). The satisfaction, alternatives, and investment scales are all 10-items each, whereas the measure of commitment is seven items. In accordance with Rusbult and colleagues, all items were measured on a ninepoint scale and only the first five items from the investment, alternatives, and satisfaction measures were used in analysis. Although various scales have been used to measure these constructs, the IMS represents a conceptual fit with the rationale of the present study.

Maximization. Maximization was measured using Schwartz and colleagues’ (2002) 13-item scale. The scale represents a global or trait level of maximization and thus is not specific to one choice or one set of choices. Example items include, “No matter how satisfied I am with my job, it’s only right for me to be on the lookout for better opportunities” and “I treat relationships like clothing: I expect to try a lot on before I get the perfect fit.” Maxmimization was measured on a seven-point scale. Internal reliabilities, means, and standard deviations for all measures appear in Table 1.

Results H1 through H4 stated that maximization would be negatively related to satisfaction, investment size, and commitment and positively related to quality of alternatives, respectively. To test these predictions, we entered these variables into a full structural model using AMOS 18.0 (Arbuckle, 2009). For all tests, model fit was estimated using maximum likelihood (ML) techniques and assessed using the chi-square statistic as well as the comparative fit index (CFI) and root-mean square error of approximation (RMSEA). Hu and Bentler (1999) have argued that models with a CFI of .90 or greater demonstrate good fit to the data (a CFI of greater than .95 is indicative of excellent fit) and Browne and Cudeck (1993) have suggested that an RMSEA in which the entire 90% confidence interval (90% CI) is less than .10 indicates good fit (an RMSEA less than or equal to .05 is indicative

Mikkelson & Pauley

473

TABLE 1. Intercorrelations, Internal Reliability Estimates, Means, and Standard Deviations for Study 1 Variables (N = 275)

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Variable 1. Satisfaction2 2. Quality of alternatives2 3. Investments2 4. Commitment2 5. General maximization3

Alpha1 .94 .89 .86 .87 .78

M/SD

1

2

3

4

5

6.87/1.67 5.01/2.00 −.44∗ 6.01/1.81 .51∗ −.39∗ 6.49/1.71 .70∗ −.52∗ .68∗ 4.37/.92 −.26∗ .42∗ −.15∗ −.32∗

Notes. 1 Internal reliability estimates are based on Cronbach’s alpha. 2 Variables were measured on nine-point scales wherein higher values indicate a greater frequency or intensity of the variable. 3 Variable was measured on a seven-point scale wherein higher values indicate a greater frequency or intensity of the variable.

of excellent fit). Each full structural model was examined utilizing 1,000 bootstrapped samples drawn at random (with replacement) from the data to determine the 95% confidence intervals associated with each parameter estimate. Measurement Model Analyses were conducted in two phases. In the first phase, the fit of latent constructs was assessed using a confirmatory factor analysis (CFA), commonly referred to as a measurement model. The measurement model contained five latent factors: maximization (three indicators); satisfaction, alternatives, and investments (five indicators each); and commitment (seven indicators). Results of the CFA revealed that the underlying factor structure demonstrated modest fit to the data, χ 2 (265, N = 262) = 724.87, p < .001, CFI = .905, RMSEA = .082 (90% CI: .074–.089). Model specification searches did not reveal any items that displayed cross-loadings on multiple factors. However, two items from the commitment factor were strongly correlated (r (272) = .92, p < .001). Given the strong correlation between these items and the fact that they dealt with a similar aspect of commitment, making future plans, we allowed the error terms of these items to correlate. This change produced a significant improvement in model fit, χ 2 (1) = 173.23, p < .01, and the improved model demonstrated a good degree of fit to the data, χ 2 (264, N = 262) = 551.64, p < .001, CFI = .941, RMSEA = .065 (90% CI: .057–.072). Hypotheses Tests To test the predictions of H1 through H4, we analyzed a full structural model including the direct paths between trait maximization and satisfaction (H1), quality of alternatives (H2), investments (H3), and commitment (H4). Results

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

474

The Journal of Social Psychology

from the full model demonstrated an acceptable degree of fit to the data, χ 2 (270, N = 262) = 642.48, p < .001, CFI = .923, RMSEA = .073 (90% CI: .065–.080). H1 predicted a negative relationship between maximization and satisfaction, and such an effect occurred, β = –.79, 95% CI: –.845 to –.726, p = .003. H2 predicted a positive relationship between maximization and awareness of alternatives, and such an effect occurred, β = .58, 95% CI: .464 to .671, p = .004. H3 predicted a negative relationship between maximization and investments, such an effect occurred, β = –.79, 95% CI: –.838 to –.716, p = .003. H4 predicted a negative relationship between maximization and commitment, and such an effect occurred, β = –1.00, 95% CI: –1.048 to –.962, p = .002. H1 through H4 were supported. RQ1 inquired about the potential mediating effect of the elements of the investment model, satisfaction, quality of alternatives, and investment, on the relationship between maximization and commitment. To test RQ1, we added three direct paths to the proposed structural model: the path from investment to commitment, the path from alternatives to commitment, and the path from satisfaction to commitment. Results from the full structural model indicated an acceptable degree of fit to the data, χ 2 (267, N = 262) = 619.19, p < .001, CFI = .927, RMSEA = .071 (90% CI: .064 − .078), and represented a significant improvement in model fit compared to the previous model that did not include these direct paths, χ 2 (5) = 23.29, p < .01. To test for mediating effects, we employed a procedure identified by Shrout and Bolger (2002) that analyzes the direct and indirect effects of the paths of interest. According to this procedure, two values are of particular interest. First, the total of the indirect effects in the relationship between the antecedent variable and the outcome (that is, the total of all the mediated pathways) must be significantly different from zero. Second, evidence of complete mediation can be determined from a relationship between the antecedent and outcome variables that is not significantly different from zero. The data indicated that, in this sample, each of these conditions was met. The direct effect of maximization on commitment was not significant, β = –.26, 95% CI: –.976 to .116, p = .135; however, the combined indirect effect of all mediated pathways originating at maximization and leading to commitment was significant, β = –.54, 95% CI: –.896 to –.119, p = .031. Direct, indirect, and total effects for the mediated model appear in Table 2. Discussion One of the limitations of the existing approach to maximization is that it has primarily been framed in the language of consumer choice. Previous studies analyzing choice as it relates to personal relationships have revealed mixed results that call the validity of such an approach into question. Tayler, Arantes, and Grace (2009) asked participants to discount the value of rewards received today when compared to future rewards in two domains: monetary income and romantic relationships. Regardless of the reward value associated with waiting, participants in

Mikkelson & Pauley

475

TABLE 2. Predicting Commitment From Maximization and Investment Model Components: Direct, Indirect, and Total Effects

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Antecedent Maximization Satisfaction Quality of alternatives Investment

Direct

Indirect

Total

−.26 (–.98 to .12) .40 (–.04 to .56) .01 (–.18 to .28)

−.54∗ (–.90 to –.12)

−.80∗∗ (–.99 to –.65) .40 (–.04 to .56) .01 (–.18 to .28)

.42∗ (.14 to .54)

.42∗ (.14 to .54)

Note. ∗ = p < .05, ∗∗ = p < .01. Reported values are the standardized coefficient with 95% confidence interval.

the study showed much less restraint for potential romantic relationships than for monetary rewards. The authors argue that one possible implication of this effect is a sort of “relationship myopia” wherein people are willing to trade in long-term rewards for a short-term benefit. Other studies have determined that when it comes to making choices about relationship partners, individuals tend to be conservative in their decision-making processes. Although their study did not involve a comparison with monetary outcomes, Beisswanger and colleagues (2003) concluded that participants tend to be risk averse when making decisions about their own relationship future. Results from these studies inform the present analysis in at least two domains. First, evidence from Tayler and colleagues (2009) demonstrates appreciable differences in the way that people think about short-term rewards derived from relationships compared with financial rewards. Second, when it comes to making decisions about long-term romantic relationships, Beisswanger and colleagues (2003) demonstrated that people tend to show caution when making decisions about their personal relationships. Taken together, these findings suggest that people might not think about relationship rewards in rational, economic terms and that people exercise great care and caution when selecting relational partners. As a result of these conclusions, we decided to proceed with the study of decision making in personal relationships by creating a relationship-specific maximization scale. Study 2 Method Participants Participants (N = 343) were 127 (37.8%) male and 209 (60.9%) female undergraduate students in communication courses (seven students did not report their biological sex). Participants ranged in age from 18 to 33 years

476

The Journal of Social Psychology

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

(M = 21.00 years, SD = 2.42). Participants were asked to recall either their present or most recent dating relationship. The length of participants’ dating relationships ranged from one month to ten years (M = 1.59 years, SD = 1.48). The majority (79.6%) was Caucasian, 5.2% were Asian/Pacific Islander, 9.9% were Hispanic, 5.0% were Black/African-American, 2.9% were Native American, and 3.2% were of other ethnic origins. These percentages add up to more than 100% because participants were instructed to check all applicable ethnicities. Measures The Investment Model Scale and the Maximization scale were the same scales as used in Study 1. For the purpose of this study, the Relational Maximization Scale was created. To test the concurrent validity of the scale we predicted that the Relational Maximization Scale and its factors would be related to trait level maximization (Schwartz et al., 2002). We also assessed convergent and discriminant validity by having participants complete measures of regret (Schwartz et al., 2002) and life satisfaction (Diener, Emmons, 1985) similar to Nenkov, Morrin, Ward, and Schwartz (2008) assessment of the short form of the maximization scale. We predicted that relational maximization would be positively related to regret but negatively related to life satisfaction. Further, we included the relational measures of closeness (Aron, Aron, & Smollan, 1992), and the investment model scale (satisfaction, alternatives, investments, and commitment) to further test the validity of the scale. Procedure: Scale Creation The creation of the Relational Maximization Scale (RMS) was conducted in four distinct steps. In the first phase our goal was to generate a pool of descriptors for relational maximization to serve as possible items for the scale. Participants (N = 51) at a large Southwestern university were given a definition of maximization as it related to relationships and asked to “provide examples of behaviors, thoughts, and/or emotions, which may be indicative of maximizing in romantic relationships.” This resulted in participants producing 248 items. The investigators reviewed each participant’s questionnaire and every item that represented some form of maximization was entered into a master list. After eliminating duplicate answers, 65 unique items remained. The second phase of scale creation consisted of a data reduction technique in which we assessed the remaining items for face validity. Eight upper-division communication majors (five females and three males) enrolled in a relational communication course were enlisted in a focus-group to review the items in the list and to decide which items they believed were true examples of behaviors, thoughts, or emotions indicative of relational maximization. First, the members of the focus group individually voted on each of the items. Each member voted

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

477

either to include the item, to eliminate the item, or to include the item but reword it. A conservative approach to eliminating items was utilized as only items with at least half of the group voting yes were retained. This process eliminated 39 of the items, leaving 26 for inclusion in the scale. The third step in the process involved ten different upper-division communication majors (six females and four males) who served as judges of the remaining 26 relational maximization items. This procedure was similar to Schwartz and colleagues (2002) who used judges to help ensure the validity of their general maximization scale. Judges were given a definition of maximization as it pertained to romantic relationships. These judges then voted on each of the 26 items on whether they believed it was an example of maximization in romantic relationships. Only three of the items did not receive at least eight out of ten votes and were subsequently eliminated. For the fourth and final phase of scale construction, we tested the predictive and concurrent validity of the Relational Maximization Scale (RMS). During this phase 343 participants completed the 23-item version of the RMS along with other scales. All participants were involved in a romantic relationship at the time the questionnaire was completed. We then conducted a principal components factor analysis using the 23-items in the RMS. We tried several different factor solutions that met the following criteria: a) all factors had to have eigenvalues exceeding 1.0; b) the Scree Test had to indicate a reasonable improvement in the variance account for by the additional factor; and c) all factors had to contain at least three items with primary loadings of .50 or better. With respect to the factor solution that met these requirements, we chose the factor solution that accounted for the most variance. The initial solution produced five factors with Eigenvalues exceeding 1.0. However, after rotating the factor loadings there were several factors with less than three items. Further, the five-factor solution was difficult to interpret from a theoretical standpoint. By extracting three factors, a more conceptually acceptable factor solution was produced. This factor solution was obtained using an Equamax rotation with 16-items accounting for 56.59% of the variance. KMO test of sampling adequacy was .85 and the Bartlett test for sphericity was significant at p < .001. See Table 3. The first factor included items about comparing the current relationship to past relationships or other potential relationships, and was labeled alternative search. The second factor included items about not wanting to settle, wanting the best, and not compromising in romantic relationships, and was labeled high standards. The third factor included items about difficulty choosing the right romantic partner, and was labeled decision difficulty. Conceptually these three factors mirror the factors that Nenkov and colleagues (2008) proposed in their creation of a short form of the Maximization scale; however, the language of all items in the present scale was clearly focused on relational processes. Tests of concurrent and discriminant validity for the measure are available from the authors on request.

478

The Journal of Social Psychology

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

TABLE 3. Factor Structure for 16-item Relational Maximization Scale Variable label

1

I constantly compare my current relationship to other potential relationships. No matter how satisfied I am in my current relationship, I am always on the lookout for a better relationship. I wonder if I would be happier in another relationship. I always like to keep my relational options open. I compare my current relationship to my past relationships to see if my current relationship is better. I won’t settle for second best in my romantic relationships. I don’t want to settle for a relationship that is “good enough.” I know what I want in a relationship and I won’t compromise. I believe I can find the best relationship for me and I won’t settle. In relationships, I am unwilling to settle for less than I feel I deserve. Finding a relational partner is difficult because I want to choose the perfect person for me. I have a hard time choosing a relational partner. I always struggle to pick the right relational partner. I have a hard time finding a relational partner that I really like. I only commit to a relationship when I know all my expectations are going to be met. I am more selective about my choice of partner than most. Eigenvalues Coefficient alphas

.85

2

3

.78 .77 .73 .71 .76 .74 .72 .63 .61 .56 .77 .74 .70 .56 .51 4.67 .85

3.02 .77

1.36 .76

Notes. Factor 1 = alternative search, Factor 2 = high standards, Factor 3 = decision difficulty.

Results We tested the same hypotheses proposed in Study 1 using the new RMS. All analyses were conducted using the same two-step plan (Anderson & Gerbing, 1988). Results obtained from the CFA measurement model demonstrated a good degree of fit to the data, χ 2 (264, N = 305) = 591.74, p < .001, CFI = .946,

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

479

RMSEA = .064 (90% CI: .057 to .071), and we proceeded to examine the predictions of H1 through H4 from Study 1. We analyzed a full structural model consisting of the direct paths leading from relational maximization to satisfaction (H1), quality of alternatives (H2), investment (H3), and commitment (H4). Results demonstrated an acceptable degree of fit between the specified model and the data, χ 2 (270, N = 305) = 666.32, CFI = .93, RMSEA = .07 (.063 to .076). H1 predicted a negative relationship between relational maximization and satisfaction, and such an effect occurred, β = –.73, CI: –.78 to –.65, z = –9.60, p < .001. H2 predicted a positive relationship between relational maximization and quality of alternatives, and such an effect occurred, β = .54, CI: .44 to .63, z = 7.42, p < .001. H3 predicted a negative relationship between relational maximization and investment, and such an effect occurred, β = –.85, CI: –.89 to –.80, z = –10.28, p < .001. H4 predicted a negative relationship between relational maximization and commitment, and such an effect occurred, β = –.99, CI: –1.03 to –.96, z = –11.29, p < .001. RQ1 inquired about the potential mediating effects of the elements of the investment model, investment, satisfaction, and quality of alternatives, on the relationship between relational maximization and commitment. Results demonstrated an acceptable degree of fit between the model and the data, χ 2 (267, N = 305) = 640.70, CFI = .94, RMSEA = .07 (90% CI: .061 to .075), and demonstrated a significant improvement in model fit, χ 2 (3) = 25.62, p < .01, when compared to the non-mediated model. Results revealed evidence of partial mediation as the cumulative indirect effect of all mediated pathways originating at relational maximization and leading to commitment was significantly different from zero, β = –.40, CI: –.58 to –.05; however, unlike Study 1, the direct path leading from relational maximization to commitment remained significant, β = −.79, CI: –.95 to –.22. One element of relational maximization in particular, quality of alternatives, was strongly correlated with all three aspects of investment model (absolute value of average r = .47). Direct, indirect, and total affects for this model appear in Table 4. Additional Analyses One of the leading justifications for the creation of a maximization scale in the language of relational decision-making processes is that people often evaluate relational outcomes differently from financial outcomes. To examine the merits of this claim, we conducted a hierarchical regression to explore the effects of relational maximization while controlling for effects obtained from the general maximization scale alone. Participants’ scores on the general maximization scale were entered into the first block of the model, scores from the RMS were entered into the second block of the model, and relational commitment was entered as the criterion variable. Results of this analysis revealed that the RMS was indeed a stronger predictor of relational commitment than the general maximization scale.

480

The Journal of Social Psychology

TABLE 4. Predicting Commitment From the Relational Maximization Scale and the Elements of the Investment Model: Direct, Indirect, and Total Effects

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Antecedent

Direct

Indirect

Total

Relational −.46∗∗ (–.95 to −.40∗ (–.58 to –.05) −.86∗∗ (–.99 to –.73) maximization –.22) Satisfaction .17 (–.07 to .30) .17 (–.07 to .30) Quality of .07 (–.06 to .23) .07 (–.06 to .23) alternatives Investment .47∗ (.19 to .61) .47∗ (.19 to .61) Note. ∗ = p < .05 ∗∗ = p < .01. Reported values are the standardized coefficient with 95% confidence interval.

TABLE 5. Hierarchical Regression Predicting Commitment (N = 305) Predictor variables Step 1 General maximization Step 2 General maximization Relationship maximization

B

SE B

β

−.37

.13

−.16∗

R2 .03∗ .12∗∗

.04 −.80

.13 .12

.02 −.39∗∗

Notes. Total R2 = .15, adjusted R2 = .14, F (2, 302) = 26.24, p < .001. ∗ p < .01, ∗∗ p < .001.

The RMS accounted for approximately 12% of the variance in commitment above and beyond what was accounted for by general maximization alone, R2 = .12, F (1, 302) = 42.90, p < .001. Full results for the regression analysis appear in Table 5. General Discussion The present study investigated maximization, an individual trait affecting how people make choices, as it relates to relationships, specifically, the components of the investment model. The predictions in the study were derived from the general nature of maximizers and satisficers in the context of personal relationships. Whereas maximizers work diligently to seek the best possible outcomes, satisficers tend to be content with their choices (so long as their decision meets a predetermined set of criteria). Given that personal relationships often require significant resource investment, we predicted that the same behaviors would be evident in the ways that maximizers and satisficers seek relationship alternatives.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

481

In the first study, we examined the effects of general maximization on individuals’ relationship choices in accordance with the elements of the investment model. We predicted that general maximization would be negatively correlated with satisfaction, investment, and commitment in relationships. Furthermore, in accordance with maximizers’ desire to assess as many alternatives as possible, we predicted that maximization would be positively correlated with awareness of relationship alternatives. All four of these hypotheses were supported. In addition to these preliminary hypotheses, we were also interested in the mediating effects of the investment model on the relationship between maximization and commitment. A full structural model containing maximization and the elements of the investment model revealed that satisfaction and investment together fully mediated the effects of maximization on commitment. Although the findings from Study 1 indicated that maximization was useful in predicting relational outcomes like satisfaction and commitment, we believed that the tendency to exercise care when making relationship decisions might motivate some individuals to practice even greater vigilance when selecting a relational partner (Beisswanger et al., 2003). In accordance with this belief, the primary goal of Study 2 was to determine whether or not a relationship-specific maximization instrument would produce results consistent with those from the first study. We created a 16-item Relationship Maximization Scale (RMS) that specified three maximization behaviors (consistent with Nenkov et al., 2008 and Schwartz et al., 2002): alternative search, high standards, and decision difficulty. As with the first study, we found that maximization (this time assessed in the language of relational decision making) was positively associated with awareness of alternatives and negatively associated with satisfaction, investment, and commitment in relationships. Two other features of Study 2 are also worth noting. First, when analyzing the effects of maximization utilizing the RMS, the elements of the investment model only partially mediated the effects of maximization on commitment. Second, results of a simple hierarchical regression analysis confirmed that, when the outcome of the study was an element of personal relationships, the RMS proved a more robust predictor than the general maximization scale utilized in Study 1. Implications The overarching goal of the studies presented in this article was to determine whether or not maximization, a trait that has recently been found to affect consumer behavior, exerts a similar influence on individuals’ decisions about their romantic relationships. In particular, we examined the interplay between maximization and the elements of the investment model, factors that have reliably predicted commitment in romantic relationships (Le & Agnew, 2003). Results from the present study extend our understanding of each of these theoretic perspectives, while simultaneously informing how the trait of maximization factors

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

482

The Journal of Social Psychology

into the interdependence perspective (Kelley & Thibaut, 1978) upon which the investment model is based (Rusbult, Drigotas, & Verette, 1994). Overall, it seems that individuals’ tendency to maximize their decisions is tied closely to the comparison levels defined with interdependence theory. Furthermore, the concept of relational investment seems to mitigate the effect of maximization on relational commitment, one of the key predictions of the investment model. In this section, we will discuss the intersections between the tendency to maximize and the components of the investment model in turn. In each of the studies presented here, the element of the investment model most closely tied to the concept of maximization was awareness of alternatives. Indeed, the relationship between these concepts was so strong that awareness of alternatives was actually positively (albeit nonsignificantly) associated with commitment in each of the full structural models analyzed. This suggests that the awareness of alternatives components (as measured with the IMS and RMS) were almost perfectly positively correlated in the comprehensive models. Given that awareness of alternatives is a significant factor in both of the models we analyzed, we were not surprised by these findings. One of the primary claims advanced by Schwartz and colleagues (2002) is that maximizers actively seek out information about all available choices in an effort to make the best choice possible. In terms of interdependence theory, this active assessment of other potential relationship partners likely coincides with an increase in individuals’ comparison level for alternatives (CLalt ), their subjective assessment of the potential satisfaction that could be derived from other relationship possibilities (Kelley & Thibaut, 1978). As Thibaut and Kelley (1956) proposed CLalt , the calculations involved in this standard of satisfaction are primarily related to the ability of relational partners to keep one anothers’ experience within the relationship relatively satisfying. Although dyadic processes within a given relationship unquestionably influence partners’ CLalt , results from the present study suggest that some individuals might be more attuned to external relationship possibilities regardless of the nature of their romantic relationships. Future studies could examine this claim through dyadic analyses involving each partner’s maximization tendencies and the communication within their relationships. The second element of the investment model that shares a direct interdependence theory corollary is satisfaction. In the language of interdependence theory, satisfaction is based on a favorable comparison level, that is, individuals’ expectations for the outcomes they should be able to obtain from their ideal relationship. Within the maximization literature, a similar concept could be the “high standards” component (Nenkov et al., 2008). Generally speaking, the high standards component of maximization refers to a desire to avoid settling for “second best” in any decision. Emotionally, these high standards often present themselves as persistent regret with previous decisions (Diab, Gillespie, & Highhouse, 2008). Although perhaps not as direct as the similarity between the evaluationof-potential-alternatives components of each perspective, the similarity between

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

483

satisfaction and high standards is still clear. Interestingly, satisfaction was the one element of the investment model that did not present a consistent pattern of results across studies; indeed, in might be that satisfaction with relationships has a slight mediating effect on the relationship between maximization and commitment (Study 1). It is also possible that satisfaction does not exert a unique effect on commitment above and beyond the effects of maximization alone (Study 2). This presents an interesting area for future investigation: Does a trait-level tendency to hold high standards exert a clear and consistent effect on relational outcomes, or is it possible that the satisfaction derived from romantic relationships might in some way relax individuals’ need to maximize? In each of the analyses presented here, investment in relationships consistently mediated the effect of maximization on relational commitment. Rusbult and colleagues (1994) noted that examining the effects of investment on individuals’ willingness to maintain their relationships was initially the unique contribution of the investment model to the interdependence literature. As these authors note, “some relationships survive even when an attractive alternative is available, and even when outcomes in the relationship fall below what partners feel they deserve” (Rusbult et al., 1994, p. 119). In the present study, investment in a romantic relationship served as the strongest and most consistent mediator of the relationship between maximization and commitment. Furthermore, in both of the full structural models we analyzed, relational investment was the only component of the investment model to exert a significant direct effect on commitment despite the effect of maximization. The results of these analyses suggest that investment in romantic relationships might mitigate the negative relational outcomes associated with trait maximization. Said another way, the extent to which individuals feel they have developed meaningful relationship-specific resources might reduce their desire to seek alternative relationship possibilities and maintain high standards. Future studies interested in examining this possible causal model could longitudinally examine how increasing levels of investments in developing romantic relationships affect individuals’ willingness to maximize their relational outcomes. Conclusions, Limitations, and Future Directions Although the present study explores one trait variable and its relationship to the investment model, these findings require careful interpretation. Because of the cross-sectional data collection, it is not possible to establish a causal connection between the predictor and criterion variables in this study. Although the model tested in the present study is consistent with theoretic conceptualizations of both maximization (as an antecedent trait-level variable) and the components of the investment model (as relationship-specific predictors of commitment), it is possible that models with reverse causal pathways might be empirically supported. Further, our sample was homogenous with respect to age, with most

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

484

The Journal of Social Psychology

of the sample consisting of college-aged students. Although we did not find any significant relationship between age and the study variables, the lack of variance could be the cause. Despite these limitations, we have reason to believe that maximization operates as an antecedent to decisions about relationships (and decisions in general). Given the fact that relationship choices are among the most important choices people make, it seems plausible to assume that those who are high in maximization in general are also probably likely to maximize in their relationships. The results of our studies indicate that this is probably the case. However, as Schwartz and colleagues (2002) noted, it also might be important to study specific forms of maximization, such as maximization in personal relationships. The results of the present study confirm this hypothesis—we were able to determine that general maximization did affect levels of investment in personal relationships. Although the test of maximization in relationships is limited, we believe it demonstrates that future investigation in this area would be beneficial. AUTHOR NOTES Alan C. Mikkelson (PhD, Arizona State University, 2006) is an Associate Professor of communication studies at Whitworth University. Perry M. Pauley ( PhD, Arizona State University, 2009) is an Assistant Professor of communication at San Diego State University.

REFERENCES Agnew, C. R., Van Lange, P. A. M., Rusbult, C. E., & Langston, C. A. (1998). Cognitive interdependence: Commitment and the mental representation of close relationships. Journal of Personality and Social Psychology, 74, 939–954. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411–423. Arbuckle, J. L. (2009). AMOS (version 18.0) [Computer program]. Chicago, IL: SPSS. Aron, A., Aron, E. N., & Smollan, D. (1992). Inclusion of other in the self scale and the structure of interpersonal closeness. Journal of Personality and Social Psychology, 63, 596–612. Beisswanger, A. H., Stone, E. R., Hupp, J. M., & Allgaier, L. (2003). Risk taking in relationships: Differences in deciding for oneself versus for a friend. Basic and Applied Social Psychology, 25, 121–135. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural models (pp. 136–162). Newbury Park, CA: Sage. Diab, D. L., Gillespie, M. A., & Highhouse, S. (2008). Are maximizers really unhappy? The measurement of maximizing tendency. Judgment and Decision Making, 3, 364–370. Diener, E., Emmons, R. A., Laren, R. J., & Griffin, S. (2000). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75. Fitzpatrick, J., & Sollie, D. L. (1999). Unrealistic gendered and relationship-specific beliefs: Contributions to investments and commitment in dating relationships. Journal of Social and Personal Relationships, 16, 852–867.

Downloaded by [University of Auckland Library] at 18:47 17 December 2014

Mikkelson & Pauley

485

Gillham, J., Ward, A., & Schwatz, B. (2001). [Maximizing and depressed mood in college students and young adolescents.] Unpublished raw data. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. Kelley, H. H. (1979). Personal relationships: Their structures and process. Hillsdale, NJ: Erlbaum. Kelley, H. H., & Thibaut, J. W. (1978). Interpersonal relations: A theory of interdependence. New York, NY: Wiley. Le, B., & Agnew, C. R. (2003). Commitment and its theorized determinants: A metaanalysis of the investment model. Personal Relationships, 10, 37–52. Morgan, H. J., & Shaver, P. R. (1999). Attachment processes and commitment to romantic relationships. In W. H. Jones & J. M. Adams (Eds.), Handbook of interpersonal commitment and relationship stability (pp. 109–124). New York, NY: Plenum. Nenkov, G. Y., Morrin, M., Ward, A., Schwartz, B., & Hulland, J. (2008). A short form of the Maximization Scale: Factor structure, reliability and validity studies. Judgment and Decision Making, 3, 371–388. Rusbult, C. E. (1980). Commitment and satisfaction in romantic associations: A test of the investment model. Journal of Experimental Social Psychology, 16, 172–186. Rusbult, C. E. (1983). A longitudinal test of the investment model: The development (and deterioration) of satisfaction and commitment in heterosexual involvements. Journal of Personality and Social Psychology, 45, 101–117. Rusbult, C. E., & Arriaga, X. (1997). Interdependence theory. In S. Duck (Ed.), Handbook of personal relationships: Theory, research and interventions (pp. 221–250). Chichester, UK: Wiley. Rusbult, C. E., & Buunk, B. P. (1993). Commitment processes in close relationships: An interdependence analysis. Journal of Social and Personal Relationships, 10, 175–204. Rusbult, C. E., Drigotas, S. M., & Verette, J. (1994) The investment model: An interdependence analysis of commitment process and relationship maintenance phenomena. In D. J. Canary & L. Stafford (Eds), Communication and relational maintenance (pp. 115–139). San Diego, CA: Academic Press. Rusbult, C. E., Martz, J. M., & Agnew, C. R. (1998). The investment model scale: Measuring commitment level, satisfaction levels, quality of alternatives, and investment size. Personal Relationships, 5, 357–391. Schwartz, B. (2000). Self-determination: The tyranny of freedom. American Psychologist, 55, 79–88. Schwartz, B., Ward, A., Lyubomirsky, S., Monterosso, J., White, K., & Lehman, D. R. (2002). Maximizing versus satisficing: Happiness is a matter of choice. Journal of Personality and Social Psychology, 83, 1178–1197. Simon, H. A. (1957). Models of man, social and rational: Mathematical essays on rational human behavior. New York, NY: Wiley. Tayler, S., Arantes, J., & Grace, R. C. (2009). Temporal discounting for monetary and close relationship outcomes. Personal Relationships, 16, 385–400. Thibaut, J. W., & Kelley, H. H. (1956). The social psychology of groups. New Brunswick, NJ: John Wiley & Sons.

Received May 24, 2012 Accepted Dec 25, 2012