Analyzing the boundaries of balance theory in evaluating cause-related marketing compatibility

The phenomenon of brands partnering with causes is referred to as cause-related marketing (CRM). This dissertation provides numerous steps forward within the realm of CRM research, as well as balance theory research. Some CRM partnerships may seem less compatible than others, but the level of perceived compatibility (also referred to as “fit”) differs from consumer to consumer. I analyzed CRM compatibility through the lens of balance theory both via a survey-based approach, as well as a social media analytics approach. My contributions to CRM and balance theory are as follows: I found that a consumer’s attitude towards a brand, along with their attitude towards a cause, predicts their perceptions of CRM compatibility. I also show that adding continuous measures of attitude and attitude strength enabled the prediction of balanced and unbalanced consumer evaluations of perceived CRM compatibility. This is the first time that attitude strength has been incorporated into balance theory. I found evidence that a consumer’s attitude towards a brand (or towards a cause), and the strength of that attitude, can spill from one organization to another when brands and causes enter into CRM partnerships. Methodologically, I present a novel way to indirectly measure the strength of attitudes towards brands and towards causes through analyzing perceived conversation topic similarity via a self-reported survey measure, but I was not able to provide evidence that attitude strength could be measured via a social media analytics approach to conversation topic similarity. To dig deeper into this lack of social media analytics results, I provide some considerations with regards to research conducted using a hybridization of a survey-based approach tied to a social media analytics approach. Practically, I share recommendations as to how to choose CRM partners for future CRM partnerships, which should prove beneficial to CRM researchers, practitioners, and advertisers.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Informatics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Yun, Joseph T.

Contributors dc:contributor

• Duff, Brittany R.L.
• Himelboim, Itai
• Sundaram, Hari
• Vargas, Patrick

• cause-related marketing
• social media analytics
• fit
• compatibility
• brands
• machine-learning
• balance theory
• attitude strength

Statement dc:rights

• Copyright 2018 Joseph Yun

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101522

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101522