ICT Management

Aims

The purpose of this course is to provide a broad understanding of the importance of ICT systems in the modern business environment so that the management makes the right decisions on issues relating to information systems. The course focuses on issues of information systems integration within the organization, information systems utilization according to the organization’s capabilities and its implications on processes and individuals, as well as information resources management. Topics covered include process analysis, project analysis, production planning and scheduling, ICT systems and new business models, quality management, supply chain management, capacity and facilities planning. The course also develops basic macroeconomic theory to enable managers to critically evaluate economic forecasts and policy recommendations and then applies these concepts in a series of case studies.

Learning Outcomes

Upon completing this course, students will:

• Develop analytical skills in planning, evaluating and supervising a project in ICT
• Develop skills in Evaluating and Sustaining Production Quality in ICT
• Understand some basic elements of Supply Chain Management
• Develop skills in Human Resource and Workforce allocation and management
• Broaden their experience through several case study examples

Content

• Process and Project Analysis
• Production Planning and Scheduling
• Quality Management
• ICT Systems and New Business Models; E-Commerce, Decision Making
• Capacity and Facilities planning
• Workforce Scheduling
• Project Valuation and Financing
• Case Studies

Reading

E. Turban, L. Volonino, Information Technology for Management, 8th Edition, 2010, John Wiley & Sons, Inc.

Oz E. Management Information Systems, Course Technology, 6th edition.

J. Laudon, K. Laudon, Essentials of Management Information Systems, Prentice Hall, 8th edition.

M.H. Sherif, Managing Projects in Telecommunication Services, Wiley-IEEE Press.

Digital Marketing

Learning Outcomes

• Understand digital marketing concepts, principles and strategies
• Learn the state-of-the-art in digital marketing practices
• Develop the knowledge to design a successful digital marketing strategy

Web Analytics

Learning Outcomes

• Understand web analytics concepts, principles and strategies
• Learn the state-of-the-art in web analytics tools and technologies
• Develop the knowledge to utilize web analytics to gain competitive advantage
• Recognise the role of web analytics within the digital marketing landscape
• Identify, define and interpret commonly used web metrics and KPIs

Gain a practical understanding of common monitoring or analysis tasks and techniques used in web analytics and how to effectively use the resulting insights to support website design decisions, campaign optimisation, search analytics, etc.

Data Science for Business: Theory and Practice

Instructor(s): Prof. V. Peristeras
Teaching Hours and Credit Allocation: 30 Hours, 6 Credits
Course Assessment: Exam Coursework

Aims

The course examines the impact of data science in modern private and public organisations and presents challenges, opportunities and trends in the field. The students will gain the necessary conceptual understanding of the uprising “data economy” with its underlying technological and business characteristics. Business cases will be presented and discussed, while specific business problems will be matched with new data technologies. Data/information management and interoperability topics will be also presented and discussed.

Learning Outcomes

On completing the course, students will be able to:

• Understand the scope of data science and the role/function of data scientists.
• Identify different types of data that are relevant in business environments.
• Know which data science solutions can address specific types of business problems.
• Be able to design a data governance policy.
• Understand challenges and opportunity in the data-driven economy and public policy.

Content

• Defining Data Science.
• Data-analytic thinking.
• Big/smart/open/linked/meta/reference/master data.
• Data interoperability.
• The data value chain.
• Business problems and data science solutions.
• Data governance.
• Data for policy.
• Data-driven economy.

Reading

• Data Science for Business, Foster Provost, Tom Fawcett, O'Reilly Media, 2013.

ICT Essentials

Aims

This course is intended for students with little or no background in computer technology. It offers a broad coverage of modern technology concepts, outlining the basic principles of computing. ICT Essentials is an introduction to a variety of technologies and their applications, such as:

• Computer Systems Architecture
• Operating Systems
• Software Architecture and Information Systems
• Databases and Storage Systems
• Computer Networks, the Internet & the World Wide Web
• Mobile Computing
• Data Science and Business Analytics
• Big Data and Cloud Computing
• Information and Network Security

Learning Outcomes

The overall goal is not to turn managers into computer specialists but to provide them with the technological background that will allow them to

• make informed business decisions based on the utilization of technology
• effectively interact with the technical staff

Recommended Reading

1. Brian Williams and Stacey Sawyer, Using Information Technology, 11th Ed., 2015, McGraw Hill
2. R. Kelly Rainer, Brad Prince, Casey G. Cegielski, Introduction to Information Systems, 5th Ed. Int’l Student Version, 2014, Wiley.
3. Carol V. Brown, Daniel W. DeHayes, Jeffrey A. Hoffer, Wainright E. Martin, William C. Perkins, Managing Information Technology, 7/E, 2012, Pearson.
4. Preston Gralla, “How the Internet works”, 8th edition, Que Publishing.
5. John Petersen, “Absolute beginner’s guide to databases”, Que Publishing.
6. V. Anton Spraul, “How software works: the magic behind encryption, CGI, search engines and other everyday technologies”, No Starch Press.

Digital Entrepreneurship: Developing and Financing an e-Business

Aims

The course aims at introducing the student to the reality of the entrepreneur and the central issues related to the preparation of an e-business entrepreneurial project. The focus is on the entrepreneurial process, from recognizing opportunities and generating ideas, through the enterprise formation and financing, to the international expansion of a new venture. Methods for assessing a business and for developing financial statements are discussed. Students will also be equipped with the required skill set for developing a business plan.

Learning Outcomes

Having successfully completed the course, students will:

§ Learn the basic principles of entrepreneurship and innovation

§ Learn to recognize business ideas and evaluate business opportunities

§ Learn how to build a team around the opportunity

§ Learn how to assess and gain control of the required resources (e.g. financial)

§ Have an overview of the major strategic and operational issues that typically confront young growing businesses

§ Become acquainted with writing a business plan

§ Learn through examples of successful and unsuccessful enterprises and case studies from high-technology ventures

§ Exit strategies

Content

§ Introduction to digital entrepreneurship and innovation

§ Opportunity exploration and exploitation

§ Methodologies for analysing, specifying, designing and launching digital businesses

§ Disciplined Entrepreneurship

§ Creativity and entrepreneurial problem solving

§ Business Plan

§ Financing an e-business

§ Exit strategies

Reading

Baron, R., & Shane, S. (2007). Entrepreneurship: A process perspective. Cengage Learning. Chicago.

Tidd, J., & Bessant, J (2005). Managing Innovation: Integrating Technological, Market and Organisational Change, John Wiley & Sons Ltd.

Barringer, B. R., & Ireland, D. Entrepreneurship: Successfully Launching New Ventures, 4th Ed., Pearson Education, 2012.

Mariotti, S., & Glackin, C. Entrepreneurship: Starting and Operating a Small Business, 2nd Ed., Prentice Hall, 2010.

Spinelli, S., & Adams, R. New Venture Creation: Entrepreneurship for the 21st Century, 9th Ed., McGraw-Hill, 2012.

Chaffey, D. e-Business and e-Commerce Management, 5th Edition. FT Prentice Hall, 2011.

Baron, R., & Shane, S. (2007). Entrepreneurship: A process perspective. Cengage Learning. Chicago.

Tidd, J., & Bessant, J (2005). Managing Innovation: Integrating Technological, Market and Organisational Change, John Wiley & Sons Ltd.

Aulet, B. (2013). Disciplined entrepreneurship: 24 steps to a successful startup. John Wiley & Sons.

Social Media and Online Community Management

Digital Organisations: eCommerce and eGovernment

Aims

The aim of this course is to broaden and expand knowledge of the concepts and techniques required for the design, operation and control of the modern upcoming e-commerce applications and e-government systems that are massively introduced by western governments to fight bureaucracy. The essential computing background to support such systems is presented, along with the individual requirements for a wide variety of modern life activities that can be performed online.

Learning Outcomes

On completing the course students will:

• Develop knowledge of the information and communication skills to support and develop this type of information systems
• Broaden their knowledge into e-commerce, covering business, marketing, organisational and payment security issues
• Explain the concepts, processes behind developing an e-learning facility
• Understand the technological, ethical, legal and practical requirements of an electronic government information system

Content

• Current and emerging business models
• The use of information and communications technology
• Mobile commerce
• E-marketing and e-business strategy
• E-consumer behaviour and advertisement
• Organisational and managerial challenges in the electronic environment
• E-Payment systems
• E-learning; security issues and the legal environment
• Understanding eGovernment
• eAdministration/G2G
• eCitizens/ eAccountability
• eDemocracy/eParticipation
• eServices/G2C & G2B
• Legislation for eGovernment
• Integrated eGovernment, Group Presentations

Reading

Laudon K., Guercio-Traver C. (2008) E-Commerce 2009: Business, Technology, Society, Prentice Hall, 5th edition.

Turban E., Lee J. K., King D., McKay J., Marshall P., (2008) Electronic Commerce 2008, Prentice Hall. Abramson M., Morin T. (2003) E-Government 2003, Rowman & Littlefield, Lanham, MD.

Heeks R. B. (2006) Implementing and Managing eGovernment: An International Text, Sage Publications, London

Big Data and Cloud Computing

Aims

The big data explosion has led to new computing paradigms, the most prevalent among them being cloud computing. Cloud computing is about vast computing resources on demand, that allow for centralized data storage and online access. Big data is a broad term that includes several concepts and tasks, such as data capture, storage, sharing, management and analysis. This course focuses mostly on the big data storage and management part, rather than the analysis as well as cloud service models, architectures and tools. Students will familiarize with modern big data and cloud technologies, understand the privacy and security concerns and learn about popular big data and cloud computing platforms.

Learning Outcomes

On completing the course students will be able to:

• Develop the knowledge, understanding and skills to work with Big data
• Deploy a structured lifecycle approach to data analytics problems
• Apply appropriate analytic techniques and tools to analyzing big data
• Understand Cloud Computing Concepts and Mechanisms
• Learn the concepts, principles, techniques and methodologies you need to manage cloud services and resources

Content

• Big data concepts, principles and practical applications
• Big data capture, storage, sharing, management and analysis
• Cloud Computing Concepts and Mechanisms
• Cloud Architectures
• Working with Clouds
• Managing Cloud Services and Resources
• Big data and cloud computing platforms

Reading

T. Erl, R. Puttini, Z. Mahmood, Cloud Computing: Concepts, Technology & Architecture, Pearson, 2013.

EMC Education Services (Editor), Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data, Wiley 2015.

Digital Business Strategy

Aims

The course provides students with the ability to analyze the drivers of competitive strategy and apply strategic management principles across a range of organization types. Additionally, the course presents frameworks for identifying the challenges of various competitive environments and discusses useful analytical approaches applied in widely different strategic problems. Students understand how to build a strategically responsive e-Business organization by tuning systems, structures and people to strategy, and how to effectively manage the process of strategizing.

Learning Outcomes

On completing the course students will:

• Demonstrate an understanding of the principles of strategic management
• Analyze the global business environment and critically discuss its impact on contemporary strategic thinking
• Prepare and deliver senior management reports and presentations
• Justify and promote strategic initiatives, such as adopting a new technology and contribute to strategic technical decisions
• Define and quantify the benefits, costs, risks and time-scales associated with new strategic initiatives
• Demonstrate an array of skills and techniques for evaluating emerging technologies in enterprise and e-Business applications
• Understand the key issues and frameworks that e-Business practitioners need to grapple with

Content

• The global business environment and the strategic context
• Business strategy and strategic management
• Strategy selection and formulation
• Corporate objectives, organizational analysis and environment scanning
• Strategic analysis: Internal and external analysis
• Financial and non-financial comparative measurement, PEST and market scanning
• Strategic planning: Optimization, co-ordination and negotiation approaches
• Appropriate tools and techniques: SWOT, TOWS, scenario planning, portfolio planning, value chain analysis and crafting strategy
• Managing and planning the transition to e-Business
• Emergent e-Business models

Reading

Campbell, D., Edgar, D., & Stonehouse, G. Business Strategy: An Introduction, 3rd Edition. Palgrave Macmillan, 2011.

Combe, C. Introduction to e-Business: Management and Strategy, Butterworth-Heinemann, 2006.

Jelassi, T., & Enders, A. Strategies for e-Business: Concepts and Cases, 2nd Edition. FT/Prentice Hall/Pearson Education, 2008.

Johnson, G., Scholes, K., & Whittingtoon, R. Exploring Corporate Strategy, 8th Edition. FT/Prentice Hall, 2008.

Data Mining

Aims

The course covers Knowledge Discovery in Databases (KDD) and Data Mining (DM) as a set of computational tools and technologies, which provide valuable assistance for business analysis and strategic business decision making. This is a hands-on course that provides an understanding of the key methods of data visualization, exploration, classification, prediction, and clustering. Students will learn how to apply various data mining techniques for solving practical problems and how to develop and use simple business analytics systems.

Learning Outcomes

By the end of this course you should be able to

• Organise and efficiently process any knowledge, either given a priori or extracted
• Understand the basic concepts of data mining
• Understand and apply various data mining approaches, including Classification, Clustering and Association Rules.
• Model complex problems
• Develop skills on a broad range of business intelligence problems
• Understand, evaluate and utilise knowledge extracted from large volumes of data.Identify the basic components and special characteristics of a business decision problem and develop a solution.

Content

• Introduction to Knowledge Discovery in Databases (KDD) and Data Mining (DM)
• Classification and Regression
• Clustering
• Association Rules
• Exploratory vs. Confirmatory analysis
• DM Systems, Data pre-processing and EvaluationBusiness use cases

Reading

J. Han and M. Kamber, Data Mining: Concepts and Techniques, 3rd ed., The Morgan Kaufmann Series in Data Management Systems, Morgan Kaufmann Publishers, 2011.

I. Witten, E. Frank, and M. Hall, “Data Mining: Practical Machine Learning Tools and Techniques”, 3rd Ed., Morgan Kaufmann, 2011.

J. Ledolter, Data Mining and Business Analytics with R, Wiley, 2013.

P.N. Tan, M. Steinbach, and V. Kumar, “Introduction to Data Mining” Int’l Ed., 1/e, Pearson Higher Education, 2006.

R. Sharda, D. Delen, E. Turban, Decision Support and Business Intelligence Systems Int’l Ed. 10/E, Pearson Higher Education, 2015.

M.H. Dunham, “Data Mining: Introductory and Advanced Topics”, Prentice Hall, 2003.

M.M. Gaber (ed.), Journeys to data mining: experiences from 15 renowned researchers, Springer, 2012

Human Computer Interaction, Design and User Experience

Computers have been a part of every aspect of human life for quite a while. A vast number of computing technologies, paradigms, architectures, solutions, applications etc. were born, evolved, matured and died, to give their place in new ones that can harness the ever growing potential of a continuously evolving landscape. Human creativity and ingenuity has played a crucial role in these developments. However, the software market has gone beyond discovering new technologies or improving the existing ones. Except from being operational, software has to be not just easy to use but also intuitive, engaging and pleasant. Human-Computer Interaction (HCI) is a field that addresses the need to create user interfaces that can improve user experience, increase productivity while at the same time providing an environment that is safe and comfortable. HCI involves a confluence of many different disciplines, such as graphic design, cognitive science and psychology, education etc. Therefore, a familiarization of basic concepts of non-computing fields is necessary.

Market Research and Analysis

One of the most popular quotes in statistic is “In God we trust, others must provide data”. In today’s globalized digital economy, it becomes more evident that data-driven decisions are gaining ground on the traditional approach that is based on experience, intuition and limited information. Business and marketing managers now rely on informative and market analyses to gain evidence-based insight οn the dynamics of the economic landscape. This requires a systematic research and analysis if the target market in order to evaluate their products and services against the competition. To achieve this, they should be able to conduct quantitative and qualitative research that involves tasks that expand from the correct formulation of the research question, the critical study of the available literature, the collection and analysis of relevant data and the delivery of the results in professional, well-structured and informative reports and presentations.

Learning Outcomes

• Foundations of marketing/management research
• Conducting a literature review
• Collecting data
• Quantitative and qualitative data analysis
• Formulating research questions
• Questionnaire design
• Business writing

Content

• Introduction to market research
• Review of market research concepts and definitions
• Research design formulation
• Data collection and preparation
• Quantitative analysis (hypothesis testing)
• Qualitative analysis
• Exploratory and descriptive analysis
• Market reporting and business writing

Reading

• Naresh Malhotra, Marketing Research: an Applied Orientation, Sixth Edition, ISBN 13: 978-0-13-608543-0, Pearson Prentice Hall
• Saunders, M., Lewis, P. and Thornhill, A. (2012). Research Methods for Business Students.
• Corbin, Juliet and Anselm Strauss (2008). Basics of Qualitative Research.
• Exploring Marketing Research, 8th edition, by William G. Zikmund, Thomson/South-Western, 2003.

Consulting Project

Credit Allocation:   6 Credits

Course Assessment:  Final deliverable

Aims

The Consulting Project will require students to apply knowledge gained in classroom into practice. Students will tackle real-life problems and challenges facing companies or organisations in order to provide actual business solutions. Following a procedure of specifications/requirements, design and implementation, students will prepare and present their concrete and practical solutions in a final deliverable report.

Learning Outcomes

On completing the course, students will be able to:

• Understand real-world problem faced by companies/firms and propose functional solutions.
• Develop critical thinking and ability to integrate data and information towards the optimal solution.
• Understand the structure, operational mode and challenges of real-world companies.

Content

• Understanding and recording a company’s needs and challenges.
• Project requirements.
• Data analysis, implementation and company feedback.
• Producing a deliverable.