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  • Courseware 
    BUS208: Principles of Management

    BUS208: Principles of Management

    Management is the organization and coordination of work to produce a desired result. A manager is a person who practices management by working with and through people in order to accomplish his or her organization's goals. When you think of the term manager, you may be imagining your supervisor as he or she hires and terminates employees and makes major decisions above your authority. However, although you may not view yourself in this way, you yourself may also be a manager. In fact, many of us practice management skills in the workplace every day. You may have a team of employees that you manage, or lead a project that requires management strategy, or demonstrate leadership qualities among your peers. These are all scenarios that require you to apply the principles of management. In this course, you will learn to recognize the characteristics of proper management by identifying what successful managers do and how they do it. Understanding how managers work is just as beneficial for the subordinate employee as it is for the manager. This course is designed to teach you the fundamentals of management as they are practiced today. This course will illustrate how management evolves as firms grow in size. It is based upon the idea that the essential purpose of a business is to produce products and services in order to meet the needs and wants of the marketplace. A manager marshals an organization's resources (its people, finances, facilities, and equipment) toward this fundamental goal. In this course, you will explore the tasks that today's managers perform and delve into the key knowledge areas that managers need to master in order to run successful and profitable businesses.

    Subjects:
    Management
    Keywords:
    Management
    Resource Type:
    Courseware
     
  • Courseware 
    Logistics and Supply Chain Management

    Logistics and Supply Chain Management

    This course surveys operations research models and techniques developed for a variety of problems arising in logistical planning of multi-echelon systems. There is a focus on planning models for production/inventory/distribution strategies in general multi-echelon multi-item systems. Topics include vehicle routing problems, dynamic lot sizing inventory models, stochastic and deterministic multi-echelon inventory systems, the bullwhip effect, pricing models, and integration problems arising in supply chain management. Probability and linear programming experience required.

    Subjects:
    Logistics and Industrial and Systems Engineering
    Keywords:
    Industrial management
    Resource Type:
    Courseware
     
  • Others 
    Agile Software Development: It’s Implication for AI products and Developers

    Agile Software Development: It’s Implication for AI products and Developers

    Software developments is advancing the technological world today. This changes have far more reaching implications in I.T industries such as Big data, Artificial intelligence and Agile Software development methodologies. Competition in the software development ecosystem has made developers to build software that are quick and reliable and often referred to as Agile development. Agile transformation is real and requires rethinking the business management, recruitment process and data strategy in a bid to stimulate disruptive solutions from within in-house development and deployment. AI product development would require rapid transformational changes within any organization. This can be accomplished by establishing specific operating models that permit development teams with the freedom of technology choice. This publication highlights some operating models that can be adopted to improve the success of AI products using Agile software development methodologies.

    Subjects:
    Computing, Data Science and Artificial Intelligence
    Keywords:
    Agile software development
    Resource Type:
    Others
     
  • Open (Access) Journal-Article 
    The Integration of Lean Management and Six Sigma Strategies to Improve the Performance of Production in Industrial Pharmaceutical, Vol. 13, No. 8 (2018) | International Journal of Business and Management | CCSE

    The Integration of Lean Management and Six Sigma Strategies to Improve the Performance of Production in Industrial Pharmaceutical, Vol. 13, No. 8 (2018) | International Journal of Business and Management | CCSE

    The aim of this paper is to identify the lean management and Six Sigma strategies to improve production performance in pharmaceutical companies through the ...

    Subjects:
    Management and Business Information Technology
    Keywords:
    Pharmaceutical industry -- Quality control Production management Six sigma (Quality control stard)
    Resource Type:
    Open (Access) Journal-Article
     
    OER
  • Presentation 
    OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation

    OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation

    This video was recorded at 7th International Semantic Web Conference (ISWC), Karlsruhe 2008. The documentation of Enterprise Research Planning (ERP) systems is usually (1) extremely large and (2) combines various views from the business and the technical implementation perspective. Also, a very specific vocabulary has evolved, in particular in the SAP domain (e.g. SAP Solution Maps or SAP software module names). This vocabulary is not clearly mapped to business management terminology and concepts. It is a well-known problem in practice that searching in SAP ERP documentation is difficult, because it requires in-depth knowledge of a large and proprietary terminology. We propose to use ontologies and automatic annotation of such large HTML software documentation in order to improve the usability and accessibility, namely of ERP help files. In order to achieve that, we have developed an ontology and prototype for SAP ERP 6.0. Our approach integrates concepts and lexical resources from (1) business management terminology, (2) SAP business terminology, (3) SAP system terminology, and (4) Wordnet synsets. We use standard GATE/KIM technology to annotate SAP help documentation with respective references to our ontology. Eventually, our approach consolidates the knowledge contained in the SAP help functionality at a conceptual level. This allows users to express their queries using a terminology they are familiar with, e.g. referring to general management terms. Despite a widely automated ontology construction process and a simplistic annotation strategy with minimal human intervention, we experienced convincing results. For an average query linked to an action and a topic, our technology returns more than 3 relevant resources, while a naïve term-based search returns on average only about 0.2 relevant resources.

    Subjects:
    Computing, Data Science and Artificial Intelligence and Management
    Keywords:
    Software documentation Enterprise resource planning Ontologies (Information retrieval)
    Resource Type:
    Presentation
     
    OER
  • Presentation 
    Linked Data at The New York Times: The First 161 Years

    Linked Data at The New York Times: The First 161 Years

    This video was recorded at 11th International Semantic Web Conference (ISWC), Boston 2012. The New York Times committment to Linked Data began over 160 years ago. Starting in 1851, The New York Times has always catalogued its archival articles using a controlled vocabulary of people, places, organizations and descriptors. In 2009 The New York Times started publishing this vocabulary as linked data using semantic web standards. In 2011 The Times announced the launch of several RESTful Semantic APIs. And in late 2012 and early 2013, The Times will migrate its entire process for vocabulary management to a system designed around the principles of Linked Data. In my remarks, I will survey the history of Semantic publishing at The New York Times, outline our semantic strategy, detail the business-case for linked data at The Times and provide an in-depth explanation of our new vocabulary management system.

    Subjects:
    Computing, Data Science and Artificial Intelligence and Management
    Keywords:
    New York times Linked data
    Resource Type:
    Presentation
     
    OER
  • Courseware 
    Big Data Strategies to Transform Your Business

    Big Data Strategies to Transform Your Business

    While big data infiltrates all walks of life, most firms have not changed sufficiently to meet the challenges that come with it. In this course, you will learn how to develop a big data strategy, transform your business model and your organization. This course will enable professionals to take their organization and their own career to the next level, regardless of their background and position. Professionals will learn how to be in charge of big data instead of being subject to it. In particular, they will become familiar with tools to: - assess their current situation regarding potential big data-induced changes of a disruptive nature, - identify their options for successfully integrating big data in their strategy, business model and organization, or if not possible, how to exit quickly with as little loss as possible, and - strengthen their own position and that of their organization in our digitalized knowledge economy The course will build on the concepts of product life cycles, the business model canvas, organizational theory and digitalized management jobs (such as Chief Digital Officer or Chief Informatics Officer) to help you find the best way to deal with and benefit from big data induced changes. During the course, your most pressing questions will be answered in our feedback videos with the lecturer. In the assignments of the course, you will choose a sector and a stakeholder. For this, you will develop your own strategy and business model. This will help you identify the appropriate organizational structure and potential contributions and positions for yourself.

    Subjects:
    Computing, Data Science and Artificial Intelligence and Management
    Keywords:
    Business -- Data processing Big data
    Resource Type:
    Courseware
     
  • Courseware 
    Introduction to Environmental Policy and Planning

    Introduction to Environmental Policy and Planning

    This course focuses on national environmental and energy policy-making; environmental ethics; the techniques of environmental analysis; and strategies for collaborative environmental decision-making. The primary objective of the course is to help students formulate a personal theory of environmental planning practice. The course is taught comparatively, with constant references to examples from around the world. It is required of all graduate students pursuing an environmental policy and planning specialization in the Department of Urban Studies and Planning at MIT. This course is the first subject in the Environmental Policy and Planning sequence. It reviews philosophical debates including growth vs. deep ecology, "command-and-control" vs. market-oriented approaches to regulation, and the importance of expertise vs. indigenous knowledge. Emphasis is placed on environmental planning techniques and strategies. Related topics include the management of sustainability, the politics of ecosystem management, environmental governance and the changing role of civil society, ecological economics, integrated assessment (combining environmental impact assessment (EIA) and risk assessment), joint fact finding in science-intensive policy disputes, environmental justice in poor communities of color, and environmental dispute resolution. Environmental Problem-Solving (Susskind et. al, 2017, Anthem Press), a video-enhanced eBook, provides students with full access to all the assigned readings, faculty commentary on the readings, and examples of the best student performance on course assignments in previous years.

    Subjects:
    Environmental Policy and Planning
    Keywords:
    Environmental protection Environmental policy
    Resource Type:
    Courseware