Running Head: CONSUMER COMMITMENT
Where do your loyalties lie?
An investigation of consumer commitment and the Investment Model
Elizabeth Cherson
Abstract
Every business needs customers that keep coming back no matter what, but how can businesses find those customers? Is there a manner of predicting a consumer’s commitment level? Using the Investment Model scale as a template, we wrote a scale to measure consumer commitment to local independently owned music stores. We administered the online survey to 59 participants. We found that the Investment Model scale does function well as a predictor of consumer behavior and retains the established and predictable relationships between commitment levels and the constructs of satisfaction level, quality of alternatives, and investment level. This study holds major implications for revolutionizing how businesses determine how well they are doing their jobs and for redefining customer service. Measuring customer commitment levels instead of customer satisfaction may be the customer service of the future, paving the way for corporate efficiency and large profits.
Where do your loyalties lie?
An investigation of consumer commitment and the Investment Model
At this point in time, it has never been easier to say that we are a part of a global economy. Consumers have never been freer to comparison shop, bargain hunt and search for the biggest and best steal. Products are continually being improved and refined while completely new innovations continue to be introduced and subsequently flood the market. Every industry is facing extreme competition. Every business, brand, company, store and mom-n-pop quickie-mart is asking itself the same question: how is it possible to become successful and profitable in such a cut throat environment? The answer: consumer commitment.
Consumer commitment has never been more important. The profit impact of having a loyal consumer base is amazing. “The net present value increase in profit that results from a 5% increase in consumer retention (i.e. a 5% increase in loyal, committed customers) varies between 25 and 95% over 14 industries,” (Reichheld (1996), Reichheld & Sasser (1990) as cited in Oliver, 1999). In addition, the relative costs of holding onto committed (i.e. loyal) current customers are considerably less than those of attempting to acquire new customers. But what are loyal customers? Where do they come from? Why are they loyal? Do they just fall from the sky, pockets full of money and completely loyal to the first business they lay eyes on?
Loyalty, within a consumer context, is defined as “a deeply held commitment to re-buy or re-patronize a product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts which have the potential to cause switching behavior.” (Oliver, 1999) In other words, loyal consumers are every business’s dream come true. They are committed to spending their money at a particular establishment, company or on a specific brand (Backman, 1991).
In light of how profitable committed consumers have been proven to be, many businesses and industries have invested both time and money into researching how to increase consumer commitment by way of increasing satisfaction (Oliver, 1999); especially since it has been established that repeat usage and buying alone are not all that constitute loyalty (Backman, 1991). But satisfaction is not the only construct variable that is involved in commitment. It has been shown, most often in the context of relationship commitment research, that in addition to satisfaction, investment and quality of alternatives have significant bearing on one’s commitment (Le & Agnew, 2003; Rusbult, Drigotas, & Verette, 1994; Rusbult, Martz & Agnew, 1998). Studies diverse in both methodology and participants have consistently found that commitment level is positively associated with satisfaction level and investment level, and negatively associated with quality of alternatives. The correlations between the constructs and commitment usually range from .30 to .70 and typically account for 50 to 90% of the variance found in commitment (Rusbult et al, 1994; Le & Agnew, 2003). An instrument was written, in the form of a survey, by Rusbult et al (1998) to measure the four constructs of commitment level, satisfaction level, quality of alternatives, and investment level. Up until the publication of the Rusbult et al (1998) survey, there was no instrument with which to measure commitment by way of its antecedents. The Investment Model scale that they devised set the foundation for many past studies, the study at hand, and will be the basis for many studies to come.
The current research study attempts to determine whether the Investment Model scale can be translated into an able predictor for consumer commitment levels from a predictor for commitment levels to romantic relationships. If the Investment Model scale can indeed be rendered into terms of consumer commitment, then one would expect that the strong positive correlation would still be found between the construct of satisfaction level and commitment level. In addition, the relationship between the construct of quality of alternatives would remain significantly inverse, while the correlation between the construct of investment level and commitment level would be significantly positive. This relationship is illustrated in Figure 1.
Figure 1.

We hypothesize that the Investment Model scale will translate well into a predictor of consumer commitment. The relationships between the constructs (satisfaction level, quality of alternatives, investment level) and commitment level will be retained and will remain accurate predictors of one’s commitment level.
Method
Participants
The
participants in this study were recruited by means of email, AOL Instant
Messenger chat, and word of mouth from friends and family of the experimenter. They
were not randomly selected. The participants included 31 females and 28 males. Their
ages fell between 18 and 30 years of age with the majority of participants
(42.4%) self-reporting 20 years of age. Most participants (95%) had at least
some college education. The majority of participants lived in the mid-Atlantic (18.6%)
and north-east (54.2%) areas of the
Materials
The
experimenter based the survey taken by the participants on the survey originally
designed by Rusbult et al (1998). The Rusbult et al survey was designed to
measure a participant’s investment in a romantic relationship. The Investment
Model Scale sought to measure and calculate one’s commitment through positive
correlations with satisfaction, investment and negative correlations with
quality of alternatives. The experimenter altered this survey to access one’s consumer
commitment to an independently owned music store, rather than one’s commitment
to a romantic relationship. The altered survey can be found in the appendix, or
at http://www.angelfire.com/punk4/biz/social_psych_survey.html.
Two types of items were included to measure satisfaction, alternatives and
investments: facet items, which measured exemplars of each construct, and
global items, which served as general measures of each construct. The facet
items were meant to prepare participants to answer the global items by
activating thoughts about each construct and by illustrating examples of each
construct. It was hoped that the facet items would enhance the reliability and
validity of the global items. The satisfaction level items assessed the degree
to which the music store met the needs of the consumer. The quality of
alternatives items assessed the extent to which the customer’s needs could be
fulfilled by another music store. The investment level items assessed the time,
money and emotional energy the consumer had expended in the context of the
music store (Rusbult et al, 1998).
Procedure
After
being recruited to participate in the study, the participants electronically
gave, by way of a check box, informed consent. They then read and completed the
survey. The scales “total facet satisfaction,” “total global satisfaction,”
“total facet quality of alternatives,” “total global quality of alternatives,”
“total facet investment,” “total global investment,” and “total commitment”
were devised to measure the constructs of satisfaction, quality of
alternatives, investment and commitment. Total facet satisfaction (a=0.8598)
was comprised of 6 items. Total global satisfaction (a=0.9430) was comprised of
4 items. Total facet quality of alternatives (a=0.7733) was comprised of
6 items. Total global quality of alternatives (a=0.6289) was comprised of
2 items. Total facet investment (a=0.8705) was comprised of 2 items. Total global
investment (a=0.8524)
was comprised of 2 items. Total commitment (a=.9288) was comprised of 4
items. The items that comprised the facet and global constructs were combined
into overall total constructs. Overall total satisfaction (a=0.9745)
was comprised of 5 items. Overall total quality of alternatives (a=0.7647)
was comprised of 6 items. Overall total investment (a=0.8670) was comprised of
5 items.
Results
Overall satisfaction level, overall total quality of alternatives, overall investment level and total commitment level were found to have means of 4.65, 3.91, 2.40 and 3.46, respectively. Overall satisfaction level, overall total quality of alternatives, overall investment level and total commitment level were found to have standard deviations of 1.76, 0.98, 1.10, and 1.95, respectively.
Overall total satisfaction level, overall total quality of alternatives, and overall total investment level were each highly correlated with commitment (r = .798, -.264, .738 respectively). Satisfaction and investment level were also determined to be significantly correlated with each other (r= .606). Satisfaction level was the most significantly correlated with commitment level.
Table 1.
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Correlations Between Investment Model Variables |
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1 |
2 |
3 |
4 |
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1. overall total quality of alternatives |
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-0.120 |
-0.055 |
-0.264
* |
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2. overall total investment |
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0.606
** |
0.738
** |
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3. overall total satisfaction |
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0.798
** |
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4. total commitment |
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-0.264
* |
0.738
** |
0.798
** |
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N = 59 |
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* p<.05 |
** p<.01 |
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Similar to the findings of the correlational analyses, satisfaction was the strongest predictor of commitment. While investment level and quality of alternatives were predictors of commitment as well, they were not as strong predictors as satisfaction level.
Table 2.
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Predicting Commitment with the Investment Model |
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b |
t |
R˛ |
F |
df |
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Model |
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0.767 |
59.348 |
3, 54 |
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overall total quality of alternatives |
-0.171 |
-2.585
* |
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overall total investment |
0.383 |
4.621
** |
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overall total satisfaction |
0.551 |
6.673
** |
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dependent variable: total commitment |
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* p<.05; **p<.01 |
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Discussion
This study provided evidence regarding the reliability and validity of the Investment Model Scale, an instrument developed to measure commitment level and three constructs with which commitment can be predicted: satisfaction level, quality of alternatives, and investment level, with regard to consumer commitment to an independently owned music store. The altered survey evidenced good internal structure, as the items designated to measure each construct were found to have good reliability, high correlations and good alpha coefficients. The relationships between satisfaction level, quality of alternatives and investment level were consistent with the findings of prior research and the hypotheses. Commitment was positively associated with satisfaction level and investment level, and was inversely associated with quality of alternatives. From this it can be determined that a customer’s high satisfaction and investment levels, when combined with a lack of alternatives, will bolster his or her commitment level. It can also be determined that a customer’s low satisfaction and investment levels, when combined with a plethora of alternatives, will depreciate his or her commitment level.
There are factors, though, that might affect a consumer’s commitment to a brand, business or particular store (e.g. an independently owned music store.) These factors are not accounted for in the Investment Model. If a business becomes embroiled in a lawsuit, is exposed for poor treatment of workers or illegal activities, regardless of a consumer’s preexisting commitment to that business, the consumer may not choose to shop there any longer. In addition, external influences, such as social pressure (e.g. the cool kids in high school don’t shop at that store) or changes in environment (e.g. moving to a new city) can affect a consumer’s desire and/or ability to commit to a particular store, business or brand (Le & Agnew, 2003).
Even though the desire to appear consistent and to present oneself favorably has been established as a pitfall of self report measures such as the one used in this study (Rusbult et al, 1998), these hazards are not particularly dangerous to the study at hand. Previous research has established that within the context of close relationships these difficulties are not of major concern. It is reasonable to assume that since the relationships between commitment’s antecedents translated so well to consumer behavior, the lack of a need for concern regarding such confounds would also translate. Also, as Rusbult et al (1998) point out, there is no other way than self report to measure a purely “in the head” phenomena such as commitment.
The major methodological failing of this study
is the extremely biased and small sample. The sample consisted solely of
friends of the experimenter and friends of the experimenter’s friends. As
evidenced by the descriptive statistics, the sample was limited to 18-30 year
olds, most with some college education and a significant amount from the
north-east and mid-Atlantic regions of the
The results of this study showed that the predictive power of the bases of commitment are not diminished in the context of consumer behavior (Le & Agnew, 2003), but is, in fact, proven to be just as strong, if not stronger than in the context of romantic relationships. The Investment Model scale and its ability to predict consumer commitment has the potential to revolutionize corporate and industrial approaches to measures of consumer satisfaction and measures of success in their own endeavors to create superior products and services.
References
Backman, S.J. (1991). An investigation of the relationship between activity loyalty and
perceived constraints. Journal of Leisure Research, 23, 332-344.
Le, B. & Agnew, C. (2003). Commitment and its theorized determinants: A meta-analysis of the
Investment Model. Personal Relationships, 10, 37-57.
Oliver, R.L., (1999). Section 1: How do customers and consumers really behave? Whence
Consumer Loyalty. Journal of Marketing, 63, 33-51.
Reichheld, F.F. (1996). The loyalty effect.
Reichheld, F.F. & Sasser, W. E.
(1990). Zero defections: Quality comes to services. Harvard
Business Review, 68 (September/October), 105-111.
Rusbult, C.E., Drigotas, S.M., & Verette, J. (1994). The Investment Model: An interdependence
analysis of
commitment processes and relationship maintenance phenomena. In D.J. Canary
& L Stafford (Eds.), Communication
and Relational Maintenance, (pp.115-139).
Rusbult, C.E., Martz, J.M., &
commitment level, satisfaction level, quality of alternatives, and investment size. Personal Relationships, 5, 357-391.