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This case study outlined the strategic and organizational issues faced by an entrepreneurial firm operating in an emerging economy. While the traditional view is “more for more” and “less for less” with respect to quality and price, the medical devices sector demands “more for less” in an emerging economy such as India, i.e. the market demands quality products at affordable prices. This case was written to equip students with the knowledge of how entrepreneurs can overcome certain barriers and use technology to recognize and exploit an opportunity, using the Indian health-care industry as an example. The key learning outcomes for the case include the following:

• Entrepreneurs define their own market, come up with innovations and create a completely new market with suitable customer value proposition.

• Entrepreneurial opportunity recognition comes from being prepared, having prior knowledge of customers and the market and having a strong network.

• An entrepreneurial preference for error of omission or commission is the determining factor when deciding whether to exploit a recognized opportunity or not.

• Entrepreneurs exploit an opportunity by giving special emphasis on their entry and risk reduction strategy.

• A technology-based product with a combination of services that will create its own product ecosystem with data is the primary goal.

The Indian health-care sector is one of the largest sectors in India and incorporates the medical devices sector, and the heart monitor segment especially represents a huge untapped opportunity. India has the highest number of deaths because of heart disease in the world, yet there is no mechanism for affordable heart monitoring, which results in large number of deaths. As existing products are either B2B or unaffordable, there is an opportunity to leverage technology to come up with cgiq products similar to blood pressure and sugar monitors. However, there are certain challenges unique to the market and product. The case described how two young entrepreneurs founded a company called Agatsa and overcame certain challenges to create a credit card-sized ECG device and the importance of building an ecosystem in a new market. Some specific issues that the case posed included the following: will it be possible for Agatsa to come up with an ecosystem to monitor heart functioning and will that be accepted by the stakeholders in an emerging market such as India? Should Agatsa have a product-driven strategy or a data-driven strategy? Will Agatsa be able to find the right business model to create and capture value?

MBA in courses such as entrepreneurship development, new venture creation and entrepreneurship in emerging markets.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

This study aims to examine how perceived brand credibility (PBC) moderates the adoption of the Internet of Things (IoT) and identifies the influencing variables that consumers consider while adopting IoT products and services. The study uses the technology acceptance model (TAM) and extends its constructs by investigating the role of PBC to measure the intention to use IoT.

To test the proposed relationships, data was gathered using the survey method, from respondents in India, an emerging market. The data was analyzed using partial least square based structural equation modeling (PLS-SEM). Moreover, the study measured the moderating effect of PBC and evaluated the effect of control variables – gender and degree of exposure to IoT.

The study found that perceived usefulness (PU) and perceived ease of use (PEOU) have a significant influence on customers’ attitudes towards using IoT devices and services. Further, PBC moderates the relationship between attitude and behavioral intention to utilize IoT devices and services. Both components of PBC – brand trustworthiness and trust – have significant moderating effect on the adoption of IoT-based services and devices.

The study tests TAM empirically in a new setting and extends it further. Introducing PBC as a moderating variable improves the understanding of the way consumers adopt IoT technology and hence strengthens the predictive power of TAM. Thus, the study provides rich insights for businesses to effectively position their IoT devices and services among their target users.

Considering the ubiquity of FinTech services, the study proposes a research framework to examine FinTech adoption and use from the technology acceptance perspective by adding sub-constructs of technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), ServPerf and WebQual 4.0. This study broadly classified these sub-constructs in three dimensions: adoption, behavior and technological and explores the relationship between these attributes. It also proposes that digital behavior (Internet experience and level of awareness) and demographic characteristics (age and gender) moderate the main relationships.

The measurement scale for the study is developed through iterative discussion with domain experts. The data are collected from 439 active Internet users though a digital survey and analysis were done by applying structural equation modeling and multi-group analysis.

Perceived usefulness and social influence are found to be the key determinant for behavior intention to use FinTech services, with social influence having significant negative influence. Actual use is significantly influenced by ease of use and social influence but is not determined by behavior intention and perceived usefulness. Behavioral attributes are significantly impacted by technological attributes and digital behavior. Also, age significantly affects the perception of security among older users.

This study will help FinTech service providers to design FinTech services considering a wide spectrum of users. More consideration should be on enhancing the usefulness and security features to create social affirmations for the use of FinTech services. This will entice users for frequent use and attract nonusers to do their first online financial transaction.

The study adds to the technology acceptance literature by incorporating relevant technological and behavioral attributes and investigating the moderating effect of digital behavior and demographic characteristics. It contributes to the understanding of user beliefs and perceptions about actual use of FinTech services.