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Anwar Shaikh

    Anwar M. Shaikh est un économiste distingué, bien qu'hétérodoxe, dont le travail s'inspire de la tradition de l'économie politique classique. Ses recherches se concentrent sur les lois du mouvement et les modèles empiriques du capitalisme industrialisé, en développant une théorie de la concurrence indépendante de l'économie néoclassique. Ses analyses abordent un large éventail de sujets, de la théorie de la valeur-travail et du commerce international aux crises économiques mondiales. L'approche de Shaikh offre un aperçu pénétrant du fonctionnement et de l'évolution du capitalisme contemporain.

    People Analytics
    Artificial to Bionic and Cyborg Intelligence
    Capitalism
    Globalization and the Myths of Free Trade
    • Globalization and the Myths of Free Trade

      History, Theory and Empirical Evidence

      • 336pages
      • 12 heures de lecture
      4,4(9)Évaluer

      The book offers a critical analysis of neoliberalism, exploring its historical roots, theoretical foundations, and practical applications. It delves into the diverse outcomes of neoliberal policies, drawing insights from an international team of contributors to provide a comprehensive understanding of this influential economic and political framework.

      Globalization and the Myths of Free Trade
    • Capitalism

      • 1024pages
      • 36 heures de lecture

      In Capitalism, Anwar Shaikh demonstrates that most of the central propositions of economic analysis can be derived without any reference to hyperrationality, optimization, perfect competition, perfect information, representative agents or so-called rational expectations. These include the laws of demand and supply, the determination of wage and profit rates, technological change, relative prices, interest rates, bond and equity prices, exchange rates, terms and balance of trade, growth, unemployment, inflation, and long booms culminating in recurrent general crises.

      Capitalism
    • People analytics is a data-driven approach to improving people-related decisions for the purpose of advancing both individual and organizational success. While people have always been critical to the success of organizations, many business leaders still make key decisions about their workforce based on intuition, experience, advice, and guesswork. However, today leaders can improve their people decision-making based on the collection and systematic analysis of data. In this Monograph we will explore a number of strategies used to attract and retain top talent, and illustrate how these strategies are being designed and used at cutting-edge companies. In doing so, we will examine and discuss examples of organizations and company projects addressing key people-related issues, such as recruiting and hiring, performance evaluation, promotion and training opportunities, compensation, and organizational change. This book will understand you how and when “big data” can be used to make key employee decisions so that you can position yourself as a strategic partner in your company’s talent management.

      People Analytics