This case details the evolution of the Hyperlocal Grocery Delivery Industry in India and a comparative analysis between Dunzo and Blinkit. The case describes the macro and industry level imperatives, growth drivers and competitive dynamics, and the resultant evolution of alternate business models. In an emerging economy context traditionally characterized by institutional voids, technological and infrastructural challenges, and a lack of entrepreneurial resources, the evolution, proliferation, and growth of the Hyperlocal Delivery business model makes for an intriguing story. We intend to make readers aware of the industry dynamics and allow them to use strategy, technological innovation, and the fundamentals of platform businesses frameworks from strategy, innovation, and platform businesses domains to evaluate the value proposition and offering that these firms have for consumers and the operational model to craft winning strategies in this emerging industry.

Adoption of Artificial Intelligence (AI) in organizations is getting popular due to the impact it is creating in business and society. While AI as a technology has made progress due to advances in various research areas, there is limited study on the adoption of AI in organizations. This article intends to develop a model for identifying the factors influencing AI adoption in organizations. We developed the model using Diffusion of Innovation and Technology-Organization-Environment theories, adopted from the field of Information Systems. In this article, we provide an analysis of application of theories toward AI adoption and provide a model at organization level. We collected data by designing a survey on 7-point Likert scale to validate our proposed model using regression-based approach and structural equation modelling. The results suggest that the change capability of an organization and leadership positively impact the AI adoption in organizations. Further, our study reflects that AI readiness by the organizations and AI adoption by trading partners of an organization also impact AI adoption positively.

This paper proposes a framework to understand organizations' perspectives while safeguarding customers' information privacy. Following a detailed literature review, a broad conceptual model was developed to build a theory based on a multi-site, multi-case study approach. The current manuscript treats information privacy as distinct from information security. From an organizational standpoint, this research reveals that legal policy, technology, and industry standards drive privacy assimilation. At a detailed level, adherence to compliance, competitive best practices, and data management controls significantly impact an organization's opportunistic perspective, resulting in higher-order assimilation (infusion) of organizational privacy practices. Resistance to compliance, investment cost, and reactive approach results in lower-order assimilation (adaptation) of organizational privacy practices. This study delivers practical implications related to how businesses perceive privacy practices while maintaining the right balance of privacy risks and opportunities.