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Learning objectives of this case is to understand the hairdressing industry and develop the sub-branding strategy. After reading this case and practicing in class, students should be able to understand this business and marketing terminology and apply them in the real world. Students will learn the branding strategies: brand extension, brand architecture and brand portfolio. Students will design (DS) the brand name for the new store.

Case synopsis Mr. Tai-Hua Teng (aka TR) was a hair artist and opened his first hair salon, vis-à-vis (VS), in 1989 using a high-end positioning strategy. VS focused on offering superb and diverse services to keep ahead of the competition rather than trying to undercut prices. VS hair salon had a solid foundation based mainly on the elite, celebrities and high-salary customers. In 2017, TR owned 16 stores (including one in Canada and two intern salons), 1 academy, 265 employees and 3 brand names. The three brand names were VS, DS and concept (CC). DS and CC were less known to the public, so now these two brands had been carried the parent name and were known as VS DS and VS CC. Quick cut hairdressing businesses were thriving because customers needed quick and cheap hairdressing services. Acknowledging the benefits of entering the highly competitive quick haircut market, TR began to contemplate the new brand name and services to offer. VS had adopted the brand house strategy but TR wondered if it was better to have an individual brand name when entering the quick haircut market. The sub-branding strategy carried the established quality assurance of VS but there was possible brand overlap. An individual new brand name might lack the well-established values from VS but it also showed the potential to reach different segments of customers. TR’s decision to make: a branded house or hybrid? This case showed a high-end hair salon facing the need for simplicity in the market and considered how to expand its business to the lower-end market. Keywords: hairdressing, brand extension and sub-branding strategy.

Level of difficulty: easy/middle level to undergraduate courses specific prerequisites: it is not necessary for students to prepare or read any marketing theory or chapters of the textbook. However, it would help a more in-depth discussion if students know the CCs of brand architecture, brand portfolio, brand extension and line extension.

Teaching Notes are available for educators only.

CSS 8: Marketing.

This case is designed to enable students to understand the role of women in artificial intelligence (AI); understand the importance of ethics and diversity in the AI field; discuss the ethical issues of AI; study the implications of unethical AI; examine the dark side of corporate-backed AI research and the difficult relationship between corporate interests and AI ethics research; understand the role played by Gebru in promoting diversity and ethics in AI; and explore how Gebru can attract more women researchers in AI and lead the movement toward inclusive and equitable technology.

The case discusses how Timnit Gebru (She), a prominent AI researcher and former co-lead of the Ethical AI research team at Google, is leading the way in promoting diversity, inclusion and ethics in AI. Gebru, one of the most high-profile black women researchers, is an influential voice in the emerging field of ethical AI, which identifies issues based on bias, fairness, and responsibility. Gebru was fired from Google in December 2020 after the company asked her to retract a research paper she had co-authored about the pitfalls of large language models and embedded racial and gender bias in AI. While Google maintained that Gebru had resigned, she said she had been fired from her job after she had raised issues of discrimination in the workplace and drawn attention to bias in AI. In early December 2021, a year after being ousted from Google, Gebru launched an independent community-driven AI research organization called Distributed Artificial Intelligence Research (DAIR) to develop ethical AI, counter the influence of Big Tech in research and development of AI and increase the presence and inclusion of black researchers in the field of AI. The case discusses Gebru’s journey in creating DAIR, the goals of the organization and some of the challenges she could face along the way. As Gebru seeks to increase diversity in the field of AI and reduce the negative impacts of bias in the training data used in AI models, the challenges before her would be to develop a sustainable revenue model for DAIR, influence AI policies and practices inside Big Tech companies from the outside, inspire and encourage more women to enter the AI field and build a decentralized base of AI expertise.

This case is meant for MBA students.

Teaching Notes are available for educators only.

CCS 11: Strategy