CCII Research Products

CCII Research Products

Industry partners are welcome to collaborate with our research center for the following types of research projects:

1. Research Insights facilitates greater understanding of an industry situation or environment. A review of relevant industry and empirical literature is organized into brief segments under distinctive categories such as state of the industry, trending now, future trends, opportunities, and areas to watch.

2. White Papers apply academic rigor to create a detailed report on a specific and often complex problem or situation. Its purpose is to facilitate problem solving and decision making regarding the context researched.

3. Secret Shopper uses a real-world consumer experience with a company or brand and its products, services, and/or regulatory compliance. Data may be collected in either a physical or digital environment or in both. A research team member(s) serves as an actor engaging in the consumer experience scenario. Data are gathered as responses to specific questions, actions, interactions, or observations in the scenario and summarized as a descriptive narrative.

4. Qualitative Research – Field, Digital or Virtual Studies develops deep descriptive understanding of consumer phenomena by direct observation in physical, digital, and virtual environments. Research may use observation techniques, unstructured interviews, or a mixed method approach. In physical environments, data is collected as written field notes and by recordings, photographs, or videos. In digital or virtual environments, data is collected through visual observations of written and graphic information and/or physical interactions on a digital website or within a virtual experience. Content analysis reveals universals and interprets distinctive consumer behaviors.

5. Qualitative Research – Case History or Case Studies provides a rigorous descriptive analysis of a distinct problem within a specific situation. In a case history, an investigation is conducted across several cases of that situation (e.g., several sites where branded product is offered) to detect related variables, identify shared attributes, and frame how they impact the problem or situation. A case study offers a singular focus on one aspect of a situation with insights for decision processes. Data may be gathered by reviewing records and reports, observing key variables, and interviews.

6. Experimental Research uses controlled testing of fundamental processes to determine cause and effect. Sample selection requires subjects (participants) to be similar to each other. Subjects are randomly assigned to experimental or control groups. Both groups participate in pre-testing; only the experimental group is exposed to an experimental (casual) stimulus on a dependent variable. Both groups participate in post-testing. This method offers ease of replication, smaller samples, and quicker data turn-around time.

7. Survey Research uses questionnaires to solicit responses from a representative sample of respondents from a defined population. Surveys can be self-administered, completed in a face-to-face interview, online, or by a phone interview. This method is useful for descriptive studies, especially with larger populations. It may also be used for explanatory studies which investigate cause and effect.

8. Big Data Implementation through Network Analysis Visualization uses massive data extracted from activities left by social media users to reveal new knowledge about consumer behavior, social relationships, and community efficacy. This descriptive method is based on Social Network Analysis (SNA) concepts as it is applied to social media interaction. It capitalizes on consumer big data by articulating the challenges in understanding network big-data sets. Implications are drawn for evolving digital branding, social media promotion, consumer studies, social retailing, and global supply chain management.

9. Predictive Modeling applies regression models to predicting online product sales and market share, clustering models for studying customer segmentation and brand equity, association models for analyzing positively/negatively paired products and online purchase patterns, similarity models for personalizing sequential product recommendation, and NLP (natural language processing) models for sentiment analysis.

*Time to execute is dependent upon the complexity of the study, data analysis, implications drawn, presentation format, and research team organization (e.g., academic researchers, student teams, industry- academic partnerships, etc.).

*Visualization techniques vary by content and data. Examples might include concept maps, data flow diagrams, ER diagrams, line/bar graphs, org charts, process maps, photos, social network diagrams, system flowcharts, tables, value stream maps, and wireframes.