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Case study
Publication date: 1 April 2024

K.S. Ranjani, Sumi Jha and Neeraj Pandey

After reading this case study, the students will be able to identify the various choices available in social e-commerce using network marketing, interpret data-driven decisions in…

Abstract

Learning outcomes

After reading this case study, the students will be able to identify the various choices available in social e-commerce using network marketing, interpret data-driven decisions in social e-commerce and evaluate their role in scaling business, analyse cost and revenue management in value segments, evaluate technology adoption among the masses using appropriate communication structures and develop customer relationships and manage their sentiments in the era of social media.

Case overview/synopsis

DealShare became a unicorn in 2022 and targeted the rural and low-income groups. Based on a networking model for customer acquisition and a hyperlocal supply chain model, DealShare is increasing its customer base at a rapid pace. However, profitability was still a challenge, and converting high volume into high value continued to be a daunting task. This case study delves deep into the challenges co-founder Sourjyendu Medda and the DealShare team faced. It seeks to address key issues: how should DealShare leverage customer network for faster customer acquisition and how should they increase ticket size and profitability? As a data-driven business, what advantages does DealShare have in influencing customers’ buying behaviour using data? Dependence on social media could have a cascading effect on “word of mouth”. How can they manage customer complaints and increase engagement?

Complexity academic level

This case study has the potential to be used in different settings. In strategic cost management, this case study can demonstrate strategies for cost management in the value-conscious segment. This case study can be used in marketing management courses while teaching “positioning” in business-to-consumer markets and CRM. For second-year management students, this can be used in entrepreneurship and strategic management courses to demonstrate the network effect in social e-commerce start-up businesses. This case study is also relevant for various course modules in graduate management programmes to demonstrate the power of data-driven decision-making in business.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS 8: Marketing

Details

Emerald Emerging Markets Case Studies, vol. 14 no. 1
Type: Case Study
ISSN: 2045-0621

Keywords

Case study
Publication date: 13 December 2019

Kerryn Ayanda Malindi Krige, Verity Hawarden and Rose Cohen

This case study introduces students to the core characteristics of social entrepreneurship by teaching Santos (2012) positive theory. The case allows students to transition from…

Abstract

Learning outcomes

This case study introduces students to the core characteristics of social entrepreneurship by teaching Santos (2012) positive theory. The case allows students to transition from comprehension and application of what social entrepreneurship is, to considering how they operate. Druckers (2005) argument that social organisations will never have sufficient resources to do their work because they operate in an environment of infinite need is the catalyst for a conversation on resource dependency theory and the risks of mission drift. Students are introduced to the funding spectrum that can be used to understand the type of income that comes to an organisation, and to apply this to the case. By the end of their studies, students should be able to apply the Santos (2012) definition to social enterprises and social entrepreneurs, have insight into the complexity of operating in an environment of infinite need and able to apply the funding spectrum as a tool to manage to understanding financial sustainability.

Case overview/synopsis

The case tells the story of Sharanjeet Shan, a globally recognised social entrepreneur, and recipient of the Schwab Foundation’s Social Entrepreneur of the Year award in 2015. Shan moved to South Africa as the country moved into democracy, and has spent the past 20-plus years building the skills of Black African school children in mathematics and science through the organisation she leads, Maths Centre. But the country remains at the bottom of world rankings for the quality of its maths and science education, despite spending more per capita on education than any other country in Africa. Maths Centre has seen a dip in donations despite steady growth in the amount of money that businesses are investing in social change in South Africa through corporate social investment. But does Shan really need more donor income? Or are there other ways that she can build the financial sustainability of Maths Centre?

Complexity academic level

This case study is aimed at students of non-profit management, entrepreneurship, social entrepreneurship, women in leadership, corporate social investment, development studies and sustainable livelihoods. It is written at an Honours / Masters level and is therefore also appropriate for use in customised or short programmes. The case study is a good introduction for students with a background in business (e.g. Diploma in Business Administration / MBA / custom programmes) who are wanting to understand social enterprise and apply their learning's.

Supplementary materials

A list of supplementary materials is provided in the Teaching Note as Table I, which includes video's, radio interview recordings and a book chapter.

Subject code

CSS 3: Entrepreneurship.

Case study
Publication date: 9 January 2017

Margie Sutherland and Kerryn Krige

This case study focuses on social entrepreneurship in emerging markets, looking at what is social entrepreneurship, theories of market failure, opportunity generation through…

Abstract

Subject area

This case study focuses on social entrepreneurship in emerging markets, looking at what is social entrepreneurship, theories of market failure, opportunity generation through effectuation, social franchising and funding.

Study level/applicability

Students of social entrepreneurship, development studies, sustainable livelihoods and asset-based development. It is useful for customised or short programmes or for students with a background in business (e.g. Diploma in Business Administration/MBA/custom programmes) wanting to understand social enterprise and blended theories of social and economic change.

Case overview

The case tells the story of Unjani container clinics which are providing affordable, quality access to people who struggle to access South Africa’s crumbling public health system. Dr Iain Barton recognised the role that nurses can play to relieve pressure on the system, by providing primary healthcare. He piloted Unjani using shipping containers as clinics with support from his company, Imperial Health Sciences. The story of Unjani is therefore one of startup and sustainable growth, partnership and building independent, self-sustaining social enterprises in a franchising system. The theory explored includes the importance of context, the role of market failure in spotting opportunity, developing opportunity through effectuation, defining social entrepreneurship and funding and growing the organisation.

Expected learning outcomes

The teaching objectives are framed by Mair (2010) who finds that where social entrepreneurs operate affects what they do and how they do it. Objective 1: Explores the influence of context on social entrepreneurship helping students frame a definition of social entrepreneurship. Objective 2: Students are able to connect the theory of market failure to opportunity identification and effectuation for social entrepreneurs. Objective 3: Students apply the definition of social entrepreneurship based on Santos’ (2010) Positive Theory. Objective 4: Students will be able to apply knowledge of social franchising models, as an approach to scaling. Objective 5: Students understand the principles of resource dependency theory and are able to use the funding spectrum as a tool to identify funding types.

Supplementary materials

Links to two videos are provided in the case. Recommendations are also made for materials to be used in the class, e.g. Global Competitiveness Index and Gapminder World, which are excellent tools to demonstrate the social and economic growth divide.

Subject code

CSS 3: Entrepreneurship.

Details

Emerald Emerging Markets Case Studies, vol. 7 no. 1
Type: Case Study
ISSN: 2045-0621

Keywords

Case study
Publication date: 4 May 2023

Riyazahmed K.

The case is presented as descriptive in nature and primarily involves exploratory research.

Abstract

Research methodology

The case is presented as descriptive in nature and primarily involves exploratory research.

Case overview/synopsis

Ashraf, a young graduate from Bangalore, India, started a chain of lifestyle shops, his family business in Khartoum, Sudan. To modernize the shops, Ashraf approached a small finance bank for financial assistance. However, after submitting the required documents and with a good credit score, he was denied a loan. The bank officials had mentioned that the loan automation software did not approve the application. Hence, the bank personnel said that they could not do anything further. Disappointed, Ashraf sought the help of his professor, John, to understand why the software rejected his application. Professor John explained to Ashraf the advantages and disadvantages of automation. In the process, Ashraf understood the significance and compelling need to address “Algorithm Bias,” a situation in which specific attributes of an algorithm cause unfair outcomes. The case place students in Ashraf’s position to help them understand the advantages and issues of applying automation through artificial intelligence.

Complexity academic level

The case suits graduate-level courses like business analytics, financial analytics and business intelligence.

Learning objectives

Through the case, the students will be able to: Understand the role of algorithms in business and society. Understand the causes, effects and methods of reducing algorithm bias. Demonstrate the ability to detect algorithm bias. Define policies to mitigate algorithm bias.

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