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  • Berlin International  (2)
  • Stasi-Unterlagen-Archiv
  • SB Oranienburg
  • Feministisches Archiv
  • Handbooks and manuals  (2)
Type of Medium
Language
Region
Library
  • Berlin International  (2)
  • Stasi-Unterlagen-Archiv
  • SB Oranienburg
  • Feministisches Archiv
Years
  • 1
    Online Resource
    Online Resource
    Cham, Switzerland :Palgrave Macmillan,
    UID:
    kobvindex_INT0004436
    Format: 1 electronic resource (xxiii, 253 pages) : , illustrations (black and white).
    ISBN: 9783319919706 , 3319919709 , 9783030063382 , 3030063380 , 9783319919713 , 3319919717
    Series Statement: Palgrave studies in sustainable business in association with Future Earth
    Content: MACHINE-GENERATED SUMMARY NOTE: "Taking the business model as point of departure, this open access book explores how companies and organizations can contribute to a more sustainable future by designing innovative models that are both sustainable and profitable. Based upon years of research, it draws together theoretical foundations and existing literature on the topic of sustainable business alongside case studies and practical solutions. After examining the theoretical foundations of sustainable business model innovation, the authors present their own framework - RESTART. Consisting of seven factors, this framework can be the basis for restarting any business model. The final section outlines a research agenda for sustainable business informed by the perspectives and frameworks put forward in this book."
    Note: EDITORIAL NOTE: hardback and e-book editions published 2018, paperback edition published 2019. , MACHINE-GENERATED CONTENTS NOTE: PART I: WHAT'S THE PROBLEM? Chapter 1: Why sustainable business model innovation? Chapter 2: The seven steps of the RESTART framework Chapter 3: RESTART: what, why, how and so what? 3.1 Responsibility and opportunity 3.2 Sustainable and profitable 3.3 The next step: aligning financial, social and environmental bottom-lines PART II: THE RESTART FRAMEWORK Chapter 4: Roadmap to a RESTART Chapter 5: Redesign rather than standstill 5.1 The business model as the story of how the company works 5.2 Redesigning business models Chapter 6: Experimentation rather than turnaround 6.1 The science of profitability 6.2 Asking the right questions Chapter 7: Service-logic rather than product-logic 7.1 At your service 7.2 Access to everything Chapter 8: The circular rather than the linear economy 8.1 The future goes in circles 8.2 Resources astray Chapter 9: Alliances rather than solo-runs 9.1 Unite and collaborate! 9.2 Creating and sharing value Chapter 10: Results rather than indulgences 10.1 With an eye on the ball 10.2 Prioritize what matters Chapter 11: Three-dimensionality rather than one-dimensionality 11.1 Take the lead 11.2. Building a better world Chapter 12: RESTART before it is too late PART III: IMPLICATIONS AND FUTURE RESEARCH Chapter 13: A recap of the RESTART framework Chapter 14: A process model for sustainable business model innovation Chapter 15: Avenues for future research Chapter 16: Case study: A RESTART for Scanship Chapter 17: Case study: A circular business model for Orkla and BIR?.
    Language: English
    Keywords: Handbooks and manuals
    URL: FULL
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Image
    Image
    Sebastopol, CA, USA : O'Reilly
    UID:
    kobvindex_INT0003044
    Format: xvi, 529 pages , illustrations, maps , 23.5 x 18 cm
    Edition: 1st edition, 1st release
    ISBN: 9781491912058 , 1491912057
    Content: "For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you'll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms."
    Note: INDEX NOTE: includes index. , Preface -- IPython: beyond normal Python -- Introduction to NumPy -- Data manipulation with Pandas -- Visualization with Matplotlib -- Machine learning - Index
    Language: English
    Keywords: Handbooks and manuals
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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