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We use community detection analysis to investigate the structure of Bengaluru's ICT cluster's inter-organizational network during the period 2015–2017. Building on the knowledge sourcing literature, we conjecture that cluster firms primarily build knowledge-seeking horizontal linkages with technologically similar companies, and that this splits the network into multiple technological communities within which firms are tightly connected, but between which linkages are scarce. We further propose that community-spanning firms which build horizontal linkages that bridge technological communities are more likely to conduct radical innovation than their peers. We finally argue that no relation exists between technological proximity and community formation in the network of vertical buyer-supplier relations. Using a voltage-based algorithm for community discovery, we draw empirical support for these predictions. We discuss the implications of our findings for Bengaluru's upgrading potential.
We provide strong support for the underappreciated expected earnings hypothesis of a negative correlation between aggregate stock returns and earnings. For 1970–2000, our powerful modeling strategy incorporating macroeconomic information reveals that aggregate returns are significantly and negatively correlated with expected aggregate earnings changes but uncorrelated with unexpected aggregate earnings changes. However, this negative correlation changes after 2000, perhaps from heightened volatility or accounting changes. We also show that underlying macroeconomic information explains the power of aggregate earnings to predict future gross domestic product growth.
India began the process of market liberalization that opened it to significant interactions with the world economy in 1991. In this essay, we provide an overarching view of the country's journey toward integration with the global innovation and entrepreneurship network. Major nodes in this global network have two major components that may be metaphorically referred to as ‘pillars and ivy’. Globally connected multinational enterprises (MNEs) form the pillars. Agile startups are the ivy, and their success (metaphorically, the height to which they can climb) depends on their symbiotic connections with the pillar MNEs. Both components are essential and reinforce each other. Without MNEs, the scaling of startups is hampered. Without a vibrant population of startups, MNEs’ interest in a location remains driven by cost, rather than capability and creativity. MNEs (mainly foreign) provided the initial sparks for the formation of the Indian innovation and entrepreneurship ecosystem. We chart the subsequent growth of India's startups. They began in the information technology (IT) sector but now cover a much wider range of industries. Today, India's innovation and entrepreneurship ecosystem is one of the largest in the world, with global integration in terms of technology, financing, human capital, and administration.
In Strategic Decisions, Planellas and Muni provide an invaluable tool for anyone facing the challenge of taking strategic decisions. Using their 'circle of strategic decisions' framework, they guide readers smoothly through the decision-making process. Following this, they present thirty of the most widely used strategic models, including Porter's Five Forces, Ansoff's Matrix, Blue Ocean Strategy, Open Innovation, and the 8-Step Change Model. For each model, they demonstrate the content, context, and application, using clear and eye-catching graphics. This is a must-have book for all M.B.A. students and business managers.
Promises of technological progress have always intrigued humankind. Throughout history, people have imagined what they could accomplish with stronger tools, faster machines and more advanced technologies. Such hopes about technological transformations continue to shape most domains of life, from economies and production over social relations to politics and knowledge. The hopes associated with contemporary digital transformations are no exception. The internet and mobile technologies make it easier than ever to find information and communicate. Big data gives us direct, precise insights into all aspects of human life. Right around the corner, artificial intelligence may lead to faster and smarter decision-making. While we often experience that the reality of such developments is more complicated, most technological revolutions are welcomed with the same kind of enthusiasm (Marvin, 1988). Likewise, many companies and other organizations scramble to stay up to speed and fear falling behind the pace of technology while they are busy attending to the core of their work. As a result, most organizations contain departments and people who are on completely different pages when it comes to understanding and working with digital transformations. That is, organizations are simultaneously doing some things in very handheld ways, relying on digital technologies for a wide range of activities and experimenting with big data or artificial intelligence in some parts.
Created in a dorm room at Harvard University, Facebook was a simple website set up to compare two pictures of female students at a time, inviting fellow students to mark them as hot or not. Since then, the scope and ambitions of Facebook have expanded considerably. Here is what Mark Zuckerberg said about the role of Facebook at a meeting on the financial results of the company ten years later: “Next, let’s talk about understanding the world. What I mean by this is that every day, people post billions of pieces of content and connections into the graph and in doing this, they’re helping to build the clearest model of everything there is to know in the world” (Facebook, 2013, italics added).