麻豆传媒社区

Franchising is a common and important business form in the restaurant industry and a major contributor to economic activity worldwide. Prior research has examined broad issues such as franchise fees, brand reputation, and expansion strategies. This project builds on that body of work by offering a fine-grained analysis of franchisor support mechanisms and their relationship to profitability. Rather than focusing on overall patterns of chain performance, the study will concentrate on the specific types of assistance franchisors provide to franchisees and evaluate how these practices influence financial outcomes.

The observation period will cover 2017 through 2019. Focusing on this pre-pandemic window helps avoid the disruptions caused by Covid-19 and provides a clear perspective on franchisor operations under normal market conditions. The primary data source will be Franchise Disclosure Documents (FDDs) of restaurant chains, which franchisors in the United States are legally required to provide. These documents contain detailed descriptions of support systems such as training programs, marketing resources, site selection assistance, and operational guidance. Where possible, these materials will be supplemented with income statements and industry data to link support practices more directly with profitability.

The analysis will proceed in two stages. First, thematic text analysis will identify recurring patterns in franchisor support practices. This will highlight how chains emphasize different forms of assistance and whether certain practices are more prevalent among stronger performers. Second, Qualitative Comparative Analysis (QCA) will be applied to code and evaluate how combinations of support mechanisms are associated with profitability. To enhance the credibility of the results, a robustness test will also be conducted using data from 2022 and 2023, allowing comparison between pre-pandemic and more recent conditions. This approach will reveal which configurations of support appear necessary or sufficient for financial success across different contexts.

By combining thematic and comparative methods, this project will provide a more detailed understanding of how franchisor support contributes to chain-level profitability. The findings will generate insights useful to franchisors, franchisees, and policymakers seeking to strengthen performance and long-term success in franchising.

By participating in this project, first-year students will gain an introduction to research and begin developing skills that will help them in future academic and professional work. Expected outcomes include:

1. Exposure to academic research writing: Students will learn the basics of how research papers are organized and written, giving them early experience with academic communication.
2. Introduction to thematic text analysis and Qualitative Comparative Analysis (QCA): Students will be introduced to simple coding and comparison techniques, helping them see how researchers make sense of complex information.
3. Hands-on practice with document analysis: By working with real Franchise Disclosure Documents (FDDs), students will practice organizing, reading, and summarizing large amounts of information.
4. Growth in writing confidence: Students will practice writing short pieces such as notes, summaries, and parts of abstracts that could be used for conference or class presentations.
5. Experience preparing and sharing research: Students will take part in preparing research results for presentation, giving them an early look at how scholars share their work at conferences.
6. Understanding franchising and the restaurant business: Students will gain a beginner鈥檚 understanding of franchising as a business model, including how it works in restaurants and why it matters for company success.
7. Practice in teamwork and project skills: Students will gain experience working with peers on a shared project, learning how to divide tasks and meet deadlines.

• Reading and summarizing sections of Franchise Disclosure Documents (FDDs) to identify examples of franchisor support.
• Learning how to record findings in simple coding sheets and applying basic coding rules for thematic analysis.
• Assisting with data entry, organization, and cleaning to prepare material for analysis.
• Participating in group discussions to compare findings and practice drawing early insights from the data.
• Preparing small pieces of content (such as notes, figures, or draft text) that may be used later in abstract writing and presentations.
• Meeting regularly (bi-weekly or monthly) with the faculty mentor to review progress, receive feedback, and set goals for the upcoming  periods.

Online

Dr. Melih Madanoglu, mmadano1@kennesaw.edu 

Artificial Intelligence (AI) is transforming the way universities operate鈥攆rom how they recruit students to how they manage administrative tasks and develop academic programs. In recent years, some public universities have begun hiring senior-level administrators with titles like 鈥淐hief AI Officer鈥� or similar roles focused on leading AI strategy. This project explores the emergence of these AI-focused leadership roles and how they may influence key university outcomes.

As a student researcher on this project, you鈥檒l help investigate big questions: What types of universities are hiring AI officers? What are these officers responsible for? And does their presence make a difference in things like enrollment numbers, fundraising success, or new academic programs? We鈥檒l use publicly available data to look at trends in areas such as student enrollment, endowment growth, research funding, job placement outcomes, and national university rankings. We鈥檒l also explore whether these institutions are developing new partnerships with tech companies or offering more AI-focused courses and degrees.

This is a great opportunity for students who are curious about the future of higher education, interested in leadership and innovation, or excited to explore how AI is reshaping institutions beyond just the tech world. You do not need to have any technical background or coding experience鈥攋ust a willingness to learn, think critically, and work with data and ideas.

Students will assist with data collection, identifying relevant university officials and their roles, gathering university-level statistics, and possibly helping with qualitative research such as reading press releases or policy documents. There may also be opportunities to explore how media and public opinion view AI leadership in universities.

By the end of the project, you鈥檒l have a stronger understanding of how large institutions make strategic decisions around technology, and you鈥檒l gain valuable experience in research, critical thinking, and teamwork. You鈥檒l also contribute to a timely and important topic that could influence how universities prepare for the future.

This project offers first-year students a valuable opportunity to develop both academic and professional skills while working on a timely and impactful research topic.

Research and Data Analysis Skills:
Students will learn how to gather and organize data from public sources such as university websites, leadership directories, and national databases. They will practice analyzing trends related to enrollment, fundraising, academic innovation, and leadership structures.

Critical Thinking and Problem-Solving:
Students will be challenged to think about big-picture questions鈥攍ike how AI leadership might influence a university鈥檚 success鈥攁nd will learn how to interpret real-world information to draw meaningful conclusions.

Written and Visual Communication:
Students will have the chance to write brief reports, summaries, or visual presentations (such as charts and infographics) that clearly communicate their findings. These skills are essential in research, business, and beyond.

Collaboration and Professionalism:
Students will work closely with a faculty mentor and possibly other student researchers, gaining experience in team-based research and professional communication.

Understanding of Higher Education and Leadership:
Students will build a behind-the-scenes understanding of how universities function strategically and how innovation through AI leadership is reshaping higher education.

Preparation for Future Opportunities:
The project is especially beneficial for students interested in marketing, education, public policy, data analysis, or technology leadership. No prior research or technical experience is needed鈥攋ust a curious mind and willingness to learn.

By the end of the project, students will be better prepared to take on future research, internships, or leadership roles鈥攁nd they鈥檒l gain hands-on experience that strengthens both their resumes and their academic confidence.

By participating in this research project, students will gain valuable skills that apply to many fields, including business, education, public policy, and technology.

Research and Analytical Skills:
Students will learn how to collect, organize, and analyze real-world data from publicly available sources, including university websites, databases, and media reports. They鈥檒l also practice identifying patterns, asking meaningful research questions, and interpreting findings.

Critical Thinking:
Students will develop the ability to think critically about how leadership decisions鈥攕uch as hiring a Chief AI Officer鈥攃an influence major outcomes for universities. They鈥檒l explore the connections between leadership, technology, and institutional success.

Communication and Writing:
As part of the project, students may help draft summaries of their findings, create data visualizations, or contribute to research presentations. These activities will improve their ability to communicate complex ideas clearly and professionally.

Teamwork and Collaboration:
Students will work closely with a faculty mentor and possibly other student researchers. This will help them build teamwork skills, learn how to share tasks effectively, and contribute to group discussions.

Professional Awareness:
Students will gain insight into how universities operate at a strategic level and how roles focused on innovation and AI are becoming more common. This can be especially helpful for students interested in careers in higher education, administration, or the business of tech.

No prior research experience is required鈥攋ust curiosity, commitment, and a willingness to learn. Students will leave the project with a deeper understanding of the research process and stronger skills that will serve them in future academic or professional settings.

Online

Dr. Prachi Gala, pgala4@kennesaw.edu 

This project explores how fashion brands are perceived when celebrities wear them in court while facing criminal charges. Although many academic studies acknowledge the influence of celebrities as aspirational reference groups, particularly in shaping consumers' brand preferences, little is known about how such brand associations are affected when celebrities are seen in a negative or controversial context, such as a courtroom appearance with visible brand logos. Some questions may arise:

• How does seeing a celebrity wearing a branded item in court affect audience perceptions of the brand?
• Does this influence brand preference positively or negatively, and what explains that effect?
• Are audience evaluations shaped by the degree to which they identify with the celebrity (e.g., someone they look up to or aspire to be like vs. someone they do not)?
• Does the nature of the crime 鈥� such as moral (e.g., shoplifting, DUI, sex solicitation) versus non-moral (e.g., tax evasion, fraud), or the perceived severity (e.g., light vs. severe) 鈥� impact brand perception differently?

The examination may involve secondary and primary data collection. This study aims to contribute to the marketing literature by deepening our understanding of the celebrity effect on brand evaluation. 

The first-year undergraduate scholar will gain valuable research experience through active participation in this project. First, they will learn the full process of academic research, including conducting a literature review, designing a study, collecting and analyzing data, and generating insights that contribute to both academic literature and marketing practice. Second, the student will have the opportunity to present their findings at a research symposium or academic marketing conference, enhancing their communication skills and learning how to prepare professional presentation materials such as posters and slide decks. Finally, the student will gain first-hand experience in research collaboration and develop an appreciation for the value of faculty mentorship in the research process.

We will first set a goal for this research project and agree on the deadlines for each research activity. A regular online meeting is expected, and a student will brief their progress in an email prior to each research meeting with the faculty mentor. Students will be encouraged to contact the faculty mentor with any questions at any time. 

Online

Dr. Hyunju Shin, hshin13@kennesaw.edu,