Business Analytics - MSc

Overview

Gain in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills. To meet the growing demand for graduates with analytics capabilities, the MSc in Business Analytics equips you with the latest analytics tools to analyse and interpret data, forecast future trends, automate and streamline decisions, and optimise courses of action.

In the era of Big Data, analytics is becoming a strategic necessity in virtually all areas of business and is an essential tool to drive real-time decisions, foster evidence-based decision-making and sustain competitive advantage. According to a recent ranking by Glassdoor.com, one of the world’s largest job and recruiting sites, Data Scientist has been named as the best job in the US for three years running. Harvard Business Review claims the 'sexiest job of the 21st century' with practitioners having rare and highly sought-after skills.

Learn how to apply descriptive, predictive and prescriptive modelling techniques to help organisations improve performance, explore alternatives, and anticipate and shape business outcomes in a rapidly changing environment. You also develop an understanding of fundamental analytics techniques, such as statistical analysis, machine learning, optimisation, simulation, and spreadsheet modelling. 

This programme is ideal for graduates with a quantitative background who are seeking to gain an in-depth knowledge of quantitative and analytical skills as well as management, communication and research skills. Upon graduation, you will be ready to start a career in a variety of industries and sectors including airline, manufacturing, energy, healthcare, banking, marketing and government.

While enrolled on the programme you have the opportunity to work for real organisations, improve your consultancy skills and enhance your employability through the Student In-company Scheme, which bridges the gap between classroom learning and workplace experience. As part of the Student In-company Scheme, students undertook a project to aid BMI The Chaucer Hospital in improving efficiency - read the full blog post to learn more.

Students are also involved in a variety of activities, including case studies, team project work, guest lectures and industry visits.

The state-of-the-art analytics packages including R, SPSS, Weka, and MS Excel, as well as optimisation packages (IBM ILOG CPLEX and OPL), simulation packages (SIMUL8) and programming languages (VBA), are taught in the programme.

Optional Pathways

Students have the option to undertake the MSc Business Analytics programme in two further specialist pathways - Business Analytics (Smart Logistics) or Business Analytics (Finance). Students can choose either pathway or remain on the main MSc Business Analytics programme following enrolment in September. Details of the specialist modules to be undertaken for either pathway are listed under the course structure section.

Funding opportunities

Kent Business School has a wide range of funding opportunities for postgraduate students, which include Scholarships, Bursaries, Kent Business School Loyalty Award for University of Kent undergraduates and the KBS Early Bird Scheme. The Early Bird equates to a 10% discount on tuition fees.

For more information on funding available from the University of Kent, please visit the Student Funding page.

KBS - Open for Business Summer Webinar Series

We are delighted to announce our Open for Business Summer Webinar Series - a free programme of Zoom webinars hosted by Kent Business School academics and professional services staff. 

You are welcome to register for one or two, or for the whole series! Each event will feature a Q&A session so be sure to submit your questions in the chat function. Click here for the full schedule.

About Kent Business School

With over 25 years’ experience delivering business education, Kent Business School is a leading UK business school, both for the standard of our teaching and student satisfaction. Our portfolio of postgraduate programmes demonstrates the breadth and depth of our expertise. Academic research and links with global business inform our teaching, ensuring a curriculum that is relevant and current. We also hold a number of accreditations by professional bodies.

Studying at Kent Business School (KBS) gives you the opportunity to increase your employability with real-life case studies, a student council and a business society. We have strong links to local and national organisations providing opportunities for projects, internships and graduate placements. The School attracts many high-profile speakers from industry and last year included visits and lectures from staff of the Bank of England, BAE Systems, Barclays, Lloyds Insurance, Cummins, Delphi and Kent County Council.

The School currently has 60 PhD students, who form a dynamic and close-knit research community.

Entry requirements

Qualification Requirements

A good honours degree (minimum 2:2) from the UK or an equivalent internationally recognised qualification in a quantitative discipline, such as statistics, logistics, mathematics, engineering or any other mathematically based natural science discipline.

All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications. 

International students

Please see our International website for entry requirements by country and other relevant information. Due to visa restrictions, international fee-paying students cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.

English language entry requirements

The University requires all non-native speakers of English to reach a minimum standard of proficiency in written and spoken English before beginning a postgraduate degree. 

For detailed information see our English language requirements web pages. 

Need help with English?

Applicants who are required to meet an English language condition may be able to study a pre-sessional course in English for Academic Purposes through Kent International Pathways.

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Course structure

Duration: 1 year full-time

The course structure provides a sample of the modules available for this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.  Most programmes require you to study a combination of compulsory and optional modules. You may also have the option to take ‘wild’ modules from other programmes offered by the University so that you may customise your programme, explore other subject areas that interest you and further enhance your employability.

Listed below are the modules required to be undertaken for the main MSc Business Analytics programme. Students also have the opportunity to transfer onto a specialist pathway within Business Analytics or remain with the overarching MSc Business Analytics degree. The pathway choices available are MSc Business Analytics (Smart Logistics) or MSc Business Analytics (Finance). Students can transfer to either of these in the autumn term. Details of the compulsory modules for these pathways are listed below. 

Pathway: MSc Business Analytics (Smart Logistics) compulsory modules may include:

CB921 - Advanced Spreadsheets and Decision Support Systems (15 credits)

CB969 - Business Statistics with R (15 credits)

CB996 - Logistics and Supply Chain Planning (15 credits)

CB932 - Operations Management and Digital Transformation (15 credits)

CB9165 - Big Data Analytics and Visualisation (15 credits)

CB9040 - Machine Learning and Forecasting (15 credits)

CB9058 - Warehousing and Global Transportation Management (15 credits)

CB966 - Simulation Modelling (15 credits)

CB8005* - Consultancy, Negotiation, and Research Skills* (15 credits)

* Note: all modules where an asterisk is placed beside the module code in the modules table below cannot be compensated.

Pathway: MSc Business Analytics (Finance) compulsory modules may include: 

CB8011 - Essentials of Financial Risk Management (15 credits)

CB969 - Business Statistics with R (15 credits)

CB997 - Prescriptive Analytics for Decision Making (15 credits)

CB8021 - Foundation of Finance (15 credits)

CB9060 - Finance with Excel (15 credits)

CB9040 - Machine Learning and Forecasting (15 credits)

CB9165 - Big Data Analytics and Visualisation (15 credits)

CB8005*- Consultancy, Negotiation, and Research Skills* (15 credits)

* Note: all modules where an asterisk is placed beside the module code in the modules table below cannot be compensated.

Modules

The MSc Business Analytics programme is studied over one year full-time. It consists of nine compulsory modules and two optional modules. The optional modules allow students to further specialise in a business analytics application area of their choice, such as marketing, or choose to undertake one of the two new pathways options: Smart Logistics or Finance.

The following modules are offered to our current students. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.

Compulsory modules currently include

Employers are in search for individuals who possess logical thinking, analytical capability, leadership, communication and negotiation skills and the ability to work under pressure. This module will equip you with skills of consultancy, negotiation and fundamentals of research methodology. Experts from the industry will be invited to share their real-world experiences and to inspire with their success stories.

The module covers three main areas. Indicative topics include:

- . Consultancy skills: Approaches to analyse a series of real-world problems in a structured manner and then develop solution diagnosis to such problems will be taught. Consultancy and report writing skills will also be taught.

- Negotiation skills: Approaches to manage conflict, optimise beneficial compromise, fair play and improve people management skills.

- Research methodology: Fundamentals of research methodology, such as data gathering, preparation and analysis and project management skills.

Find out more about CB8005

In this module, students will learn about the fundamentals of machine learning and forecasting techniques and gain hands-on experience with analysing and solving a variety of problems encountered in business and management.

Three indicative areas of the module could include:

- Machine learning: The introduction of modern machine learning techniques used in business data analysis, including both supervised learning (e.g. regression, classification, and artificial neural networks) and unsupervised learning (e.g. association rule discovery and cluster analysis).

- Forecasting: Students will learn about various forecasting methods, including exponential smoothing methods and the Box-Jenkins method (i.e. the ARIMA model and variants).

- Data analysis report writing. Students will systematically carry out a data analysis project and write a data analysis report.

The data analysis packages such as R, SPSS, and Weka may be used in this module.

Find out more about CB9040

This module aims to introduce students to the power of big data analytics and data visualisation techniques in contributing to business value creation. The module will also enable students to solve a variety of complex data centred business problems using computer software tools like R and Gephi.

The module covers two main themes as follows.

- Theoretical understanding of big data analytics: This part involves learning about the theoretical foundations of big data analytics, text mining, and social media data mining. It also introduces the effective use of data visualisation and database management concepts and their links with big data analytics. Example applications of big data analytics and visualisation techniques discussed within the module will focus on addressing contemporary challenges faced by industry.

- Building practical skills and managerial insights: In this part of the module, students will learn how to solve business problems using advanced functions within the R and Gephi software platforms. Students will be guided through demonstrations involving a variety of exercises that will prepare them to be data-driven managers and executives capable of utilising big data analytics for business value creation.

Find out more about CB9165

The aim of this module is to enable students to use spreadsheets (Microsoft Excel) to structure, analyse and solve a variety of business problems. It will also provide the students with a basic knowledge of Visual Basic for Applications (VBA) as a means to automate Excel functionalities and create user-friendly applications.

The module will cover two main topics:

- Spreadsheet Modelling. This part will involve learning about modelling techniques to represent the real world in a structured and logical way; how to use basic and advanced spreadsheet facilities to organize, visualise, query and summarise data; how to use spreadsheets to analyse and solve managerial problems in a variety of organisations (e.g. scheduling, forecasting, inventory, optimisation, financial analysis, and project management problems).

- Visual Basic for Applications. In this part of the module, students will learn how to take their Excel abilities to the next level by wrapping their spreadsheet models into friendly applications for the end users. Through guided demonstrations, students will develop a variety of applications, including financial, logistics and business management applications.

The module will be subject to continual refinement to ensure the content is kept relevant to industry's usage of spreadsheets.

Find out more about CB921

The aim of the module is to give students hands-on experience in using industry-standard simulation modelling software in order to structure and solve complex and large-scale managerial decision problems.

The module will cover the following topics:

- Queuing theory: Students will be introduced to the basic underpinnings of queuing theory, including key assumptions, benefits, and limitations.

- Discrete-event simulation: Core theory of discrete-event simulation will be covered, including a review of simulation mechanics, how to incorporate randomness into a simulation, and the systematic analysis of simulation model results. This will be supplemented with practical training in how to build and run simulation models using commercial software. Example applications will be drawn from a variety of sectors, such as manufacturing/production, transportation, healthcare, and other service industries (e.g., banking, retail, customer service).

Find out more about CB966

The aim of this module is to enable students to apply basic statistical inference methods for tackling real-world business questions and equip them with basic knowledge of the R statistical programming package.

The module covers two indicative areas:

- Business Statistics: Students will learn about descriptive analysis of quantitative data, focusing mainly on how to effectively summarise data, and inferential analysis of quantitative data, which includes identifying key properties of a given dataset, deriving point and interval estimates, hypothesis testing, correlation analysis, and simple linear regression.

- R programming package: This will cover the R statistical programming language and introduce students to basic and more advanced concepts within R, as well as how to use R for performing statistical data analyses.

Find out more about CB969

The aim of this module is to introduce students to optimisation modelling and solution techniques, typical applications areas within strategic/operation business planning, and the use of commercial optimisation software.

The module covers the following topics:

- Linear Programming: Students will be introduced to the building blocks of optimisation (i.e. decision variables, objectives, constraints), how to mathematically formulate linear programming (LP) models, LP solution techniques, sensitivity analysis (e.g. range of optimality reduced costs, dual prices), and typical applications like production planning, scheduling, and portfolio selection.

- Network Models: This topic includes a range of concepts and modelling techniques for formulating classic network models, including transportation and assignment, shortest path, maximum flow, and minimum spanning tree problems, and common solution approaches.

- Integer Programming: This will cover integer linear programming (ILP) models, including binary integer models, classic exact and heuristic solution methods (e.g. branch and bound, greedy heuristics), and typical application areas of ILP, including capital budgeting, fixed charge production, and facility location.

Find out more about CB997

Optional modules may include

This module will cover the design, planning, execution, control, and monitoring of supply chain activities, such as supplier relationship, production, inventory, transportation and demand management. Strategic questions regarding efficiency versus responsiveness will be addressed with the objective of creating net value, building competitive strategies, leveraging worldwide logistics and synchronizing supply with demand. The module will equip students with appropriate methods that are adopted in practice.

The module will be given in two parts with indicative topics to include:

- An overview of logistic systems and supply chain management, the various activities involved, the main supply chain drivers, responsiveness vs. efficiency, pull versus push strategies and global supply chain management strategies.

- Appropriate techniques to enhance the efficiency and responsiveness of supply chain activities, including the distribution design and planning (e.g., where to locate facilities and how to transport goods), the inventory control (to guarantee high customer service levels) and the forecasting activity (to plan operations capacity levels).

Find out more about CB996

The operations management function has always been of vital importance in a wide variety of organisations and industries whether manufacturing- or service-oriented, public or private, small or large. With the rise of Industry 4.0, managers are expected to continuously optimise operations to enable even faster, more flexible, and more efficient processes to create and deliver higher-quality goods and services at reduced costs. This digital revolution means that operations managers need to be prepared to face extraordinary levels of complexity and competitive pressures. Indicative topics include:

1. Provide with fundamental knowledge in operations management and understanding of how operations are being transformed by digital technologies, such as Blockchain, IoT, Big data, Cloud computing, driverless vehicles and 3D printing.

2. Inform and debate how operations management can deliver real competitive advantage by managing and leading digital transformation in businesses

3. Discuss the challenges of operations management to leverage the principles of Industry 4.0 to drive efficiency into the creation and delivery of products and services

Find out more about CB932

Topics are:

- The communications process

- Advertising

- Strategy and media planning

- Image, brand management and packaging

- Direct marketing

- Digital and interactive media

- Sales promotion, merchandising and point of sale

- Public relations and corporate identity

- Exhibitions, trade shows, product placement and sponsorship

- Personal selling and sales management

Find out more about CB952

In today's competitive and global economy, companies are turning to project management to consistently deliver business results. Increased number of international and complex projects brings with it a growing demand for project management specialists, according to Project Management Institute (PMI). This module introduces the principles and practice of project management in a global context. The module aims to:

Equip you with project management tools, techniques and management issues, focusing on key challenges that arise from managing complex projects, such as with regards to project time, quality and cost, resource constraints, stakeholder analysis, cultural diversity and teamwork.

Analyse contemporary project management issues and employ a range of established and innovative methodologies for adequate project plan, execution and control;

Critically analyse risks in projects, develop sustainable contingency plans and demonstrate ability to set reasonable and achievable deadlines and milestones across different project tasks with due consideration to economic, social, and environmental aspects surrounding a project.

Find out more about CB9173

As global supply chains stretch across the globe with buyers from numerous countries on one side and multinational suppliers on the other, corporations are under pressure to unlock the working capital trapped in their supply chains. In this module, we will explore a set of traditional and technology-driven solutions that optimise cash flow by allowing businesses to lengthen their payment terms to their suppliers while providing the option for their suppliers to get paid early, resulting in a win-win outcomes and risk minimisation across the supply chain. The module will cover the following indicative topics:

- Working capital and cash-to-cash cycle approaches as indicators of supply chain efficiency and methods for improving cash flow

- Transitional stages of supply chain finance, its barriers, challenges and opportunities, the new role of financial service providers, supply chain finance options, platforms, costs, benefits and risks

- Blockchain technology and its application in supply chain financing and traceability, through smart contracts, peer-to-peer value exchange, transparent private and public distributed validation.

Find out more about CB9174

The aim of this module is to enable students to critically evaluate the roles warehouses, transportation centres and the different modes of transport have on the logistic and supply chain systems. It will also provide the student with an understanding of warehouse management activities, such as picking strategies and warehouse layout, packaging, etc and of distribution decisions, such as transport modes and single-, multi- or omni-channel planning. Students will be able to appreciate the use of appropriate methods that are used in practice and their impact in generating the company competitive advantage.

Indicative topics are as follows:

- Warehousing/Storage (the warehouse location, layout problem, storage equipment, picking strategies, packaging, labelling, etc)

- Inventory management (how much you need to stock to minimise your cost and retain your competitive advantage)

- Distribution & Global Transportation

* Global transportation and techniques adopted in practice (air, sea, railroads, trucks, motorbikes/bicycles, pipelines, others)

* Transport/road technology including software and hardware (trucking devices, software used, etc)

* Transport modelling and its impact on the environment and safety.

Find out more about CB9058

Buyer Decision Making has its theoretical underpinning in a number of disciplines emanating from the social sciences, psychology and also economics. We will explore how complex the decision making process can be, how we learn, and what factors influence behaviour, such as situational, personal, societal, cultural and psychological. We will examine individual versus group/organization decision making.

Topics are:

- Introduction to Buying behaviour

- Decision Making Theories

- Motivation and Involvement

- Learning Theories and Perception

- Attitude Theories and Consumption

- Segmentation, Targeting, and Positioning

- Organizational Buying Behaviour

- Impression Management

- Affect, Perceived Risk and Buying Behaviour

Find out more about CB9065

This module provides an overview of key topics within the domain of marketing research and will provide students the platform to understand the importance and use of information for making marketing decisions. While this module will cover concepts in marketing research, its focus will be on i) providing students with an understanding of how marketing research fits into the contemporary marketing framework, and ii) understanding and interpreting the use of marketing research information and tools for the purposes of understanding information use.

Topics are:

- What is marketing research

- Buyers and sellers in the research process

- The marketing research industry

- Qualitative and quantitative techniques in marketing research

- Secondary data and marketing intelligence

- Observational techniques in marketing research

- Experiments and test marketing

- Questionnaire design and implementation

- Cross cultural issues in marketing research

- Communicating marketing research results

Find out more about CB9066

This module deals with the interpretation of financial statements, valuation models and implications of market based accounting research.

Indicative topics are:

- A framework for business analysis and valuation;

- Financial analysis/ratio analysis;

- Valuation theory and concepts;

- Quality of earnings;

- Security analysis;

- Credit analysis and financial distress prediction;

- Mergers and acquisitions.

Find out more about CB8006

Topics covered by the module are:

The Risk-Return Relationship

The Arbitrage Pricing Theory

Multifactor Asset Pricing Models

Dividend Policy

Mergers and Acquisitions

Find out more about CB8020

This module will cover the following topics:

• Investment appraisal techniques and decisions

• Stock market efficiency – capital market behaviour

• Portfolio theory

• The Capital Asset Pricing Model

• Sources of finance

• Capital Structure

Find out more about CB8021

Compulsory modules currently include

This module allows students to put into practice the knowledge and skills gained in the other modules on the MSc Business Analytics. Working under the guidance of an academic supervisor and possibly with a company, students solve practical problems that require an application-oriented thinking. The problems are varied and interesting, such as analysing marketing campaigns, ranking credit risks, optimising capital investments, forecasting sales trends, simulating patient flow through hospitals and extracting patterns from large datasets.

Find out more about CB986

Teaching and assessment

The programme involves a taught and a project component. The taught programme is assessed by a mixture of coursework assignments throughout the year, and by examinations in May and June.

Once these are completed, you then work full-time on the project and write a dissertation based on this. This 8,000 to 10,000 word dissertation is an opportunity to apply the techniques and insights presented in the programme and apply them to a particular problem area.

Industrial Placement

For students who wish to enhance their employability further, this programme offers the opportunity to undertake work experience in the UK or overseas, through the option to undertake the programme with an additional industrial placement. Placements are self-sought and can range from an additional 12 to 50 weeks. This would extend the normal 12 month Masters programme to a maximum of 24 months.

The School offers support to those students seeking the industrial placement option, through extra-curricular engagement with our dedicated placements team. Our dedicated placement team can help you gain a suitable paid position and provide support throughout your placement. Students considering this option should be aware that they will be required to successfully complete all stage 1 modules and that there may be additional costs for students in terms of visa extensions, Immigration Health Surcharge (IHS) and accommodation, for example.

Programme aims

The programme aims to:

  • educate you to become business analytics specialists, improving the quality of the business analytics profession
  • prepare you to be operationally effective in business analytics and/or for further study or an academic career in the area
  • provide in-depth study in business analytics, including a strong theoretical base and a range of skills relevant to practice
  • add value to a first degree by offering theoretical and practical exposure to problem-solving techniques for effective decision making in a range of complex strategic, operational and managerial situations
  • provide career development opportunities for individuals who are already experienced managers  wishing to enhance their knowledge and understanding through a structured course of study
  • enhance lifelong learning skills and personal development, enabling you to contribute to business and society at large
  • develop a range of cognitive, critical and intellectual skills, together with research and personal/interpersonal skills
  • develop the ability to conduct research into business and management issues, either individual or as part of a team, through research design, data collection, analysis, synthesis and reporting
  • develop effective oral and written communication of complex ideas and arguments, using a range of media, including the preparation of business reports and professional presentations
  • develop effective performance within team environments and the ability to recognise and use individuals' contributions in group processes and to negotiate and persuade or influence others
  • provide teaching and learning opportunities informed by high-quality research and scholarship
  • develop new areas and methods of teaching in response to the advance of knowledge, changes in technology and the needs of students
  • meet the growing market demand for highly skilled analytics workers.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

  • organisations, their external context and how they are managed
  • the application of business analytics knowledge to a range of complex situations
  • current issues in business analytics, which is informed by leading-edge research and practice in the field.

Intellectual skills

You gain the ability to:

  • creatively apply knowledge of business analytics and understand in practical terms how established techniques of research and enquiry are used to develop and interpret knowledge in business and management
  • evaluate the rigour and validity of published research, assessing its relevance to new situations
  • extrapolate from existing research and scholarship to identify new or revised approached to practice
  • be adaptable and demonstrate originality, insight, critical and reflective abilities, which can be applied to problem situations
  • evaluate and integrate theory and practice in a wider range of situations
  • take responsibility for continuing to develop your own knowledge and skills.

Subject-specific skills

You gain the ability to:

  • understand appropriate techniques sufficient to allow detailed investigation into relevant business and management issues
  • acquire and analyse data and information, evaluate their relevance and validity, and synthesise a range of information in the context of new situations
  • conduct research into business analytics issues that requires familiarity with a range of business data, research sources and appropriate methodologies, informing the overall learning process

Once you have graduated and are in professional practice you should be able to:

  • consistently apply knowledge and subject-specific and wider intellectual skills
  • deal with complex issues both systematically and creatively, and communicate their conclusions clearly to a range of audiences.

Transferable skills

You gain the ability to:

  • creatively apply knowledge of business analytics and understand in  practical terms how established techniques of research and enquiry are used to develop and interpret knowledge in business and management
  • communicate effectively, both orally and in writing, using a range of media
  • operate effectively in a variety of team roles and take leadership roles, where appropriate

Once you have graduated and are in professional practice you should be able to:

  • deal with complex issues both systematically and creatively, and communicate their conclusions clearly to a range of audiences
  • be proactive in recognising the need for change and have the ability to manage change
  • make decisions in complex and unpredictable situations
  • be self-directed and able to act autonomously in planning and implementing projects at professional levels.

Fees

The 2020/21 annual tuition fees for this programme are:

  • Home/EU full-time £10740
  • International full-time £19800

For details of when and how to pay fees and charges, please see our Student Finance Guide.

For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact information@kent.ac.uk

Additional costs

General additional costs

Find out more about general additional costs that you may pay when studying at Kent. 

Funding

Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:

The Complete University Guide

In The Complete University Guide 2020, the University of Kent was ranked in the top 10 for research intensity. This is a measure of the proportion of staff involved in high-quality research in the university.

Please see the University League Tables 2020 for more information.

Independent rankings

In the Research Excellence Framework (REF) 2014, we were placed 25th (out of 101 institutions) in the UK for research intensity in business and management studies and 98% of our research was judged to be of international quality. The School’s environment was judged to be conducive to supporting the development of research of international excellence.

The School was also ranked 24th for its breadth and depth of research across the whole community of research active staff by the Association of Business Schools.

Research areas

Research activities at Kent Business School are broadly organised into six areas;

Our Management Science group covers a wide range of research areas in Operational Research and Systems Thinking. These include research in the area of logistics including green logistics and network security with a special emphasis on the innovative design and analysis of heuristic and exact optimisation, DEA, operation management, multi-variate analysis, biometrics, multi-methodology and Soft OR/Systems. The group is now a member of NATCOR.

For more information, see our Applied Research Centres:

Staff research interests

Full details of staff research interests can be found on the School's website.

Dr Adolf Acquaye : Reader in Sustainability

Development and application of sustainability frameworks and models used to inform business practice, sustainability research and policies for a sustainable and low carbon society.

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Professor Steve Wenbin Liu : Professor of Management Science and Computational Mathematics

Global and parallel optimisation methods, numerical simulation and modelling, simulation and optimisation of highly complex systems, production and operations management, productivity analysis.

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Professor John Mingers : Professor of Operational Research and Systems

Multimethodology, critical realism, evaluating research performance.

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Dr Gabor Nagy : Senior Lecturer in Management Science

Logistics problems such as facility location and vehicle routing (and combined location-routing problems).

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Professor Jesse O'Hanley : Professor of Environmental Systems Management

Development of optimisation and simulation techniques for environmental management, facility location, transportation, and logistics.

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Professor Said Salhi : Professor of Management Science and Operational Research

Heuristic optimisation (with a focus on routing and location including green aspects of logistic research), logistics, routing, location.

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Dr Maria Paola Scaparra : Professor in Management Science

Social partnerships between business and non-profit organisations. Sustainability and corporate social responsibility, the functional role of conflict in achieving sustainable social outcomes.

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Dr Niaz Ahmed Wassan : Reader in Management Science

Optimisation techniques, in particular, heuristic optimisation modelling and intelligent decision support systems for logistics and supply chain management.

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Dr Shaomin Wu : Reader in Business-Applied Statistics

Applied Stochastic Processes, Statistical Data Analysis, Data Mining, and Risk Management.

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Mr Tuan Yu : Lecturer in Organisational Management and E-Commerce

The challenges of digital transformation, innovative technology organisation and management, technology and people.

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Careers

You gain much more than an academic qualification when you graduate from Kent Business School – we enhance your student experience and accelerate your career prospects.

From the moment you start with us, our efforts are focused on helping you gain the knowledge, skills and experience you need to thrive in an increasingly competitive workplace.

In today’s business climate employers are increasingly demanding more from new employees, we are therefore proud that they continually target our graduates for their organisations across the globe. Employers respect our robust teaching and reputation for delivering international business expertise, leading global research and an outstanding international learning experience.

Recent graduates have gone on to work for Barclays Capital, British Embassy, Gray Robinson PA and Holiday Extras.

To find out more about business analytics and future career prospects, see:

Professional recognition

Kent Business School is a member of the European Foundation for Management Development (EFMD) and the Chartered Association of Business Schools (CABS); and the Kent MBA is an Association of MBAs (AMBA) accredited programme.

In addition, KBS has accredited programmes with the following professional bodies:

  • The Chartered Institute of Personnel and Development (CIPD)
  • The Chartered Institute of Logistics and Transport (CILT)
  • The Chartered Institute of Procurement and Supply (CIPS)
  • The Chartered Institute of Marketing (CIM)
  • The Chartered Management Institute (CMI)
  • The Professional Risk Managers’ International Association (PRMIA)
  • The Global Association of Risk Professionals (GARP)
  • The Association of Chartered Certified Accountants (ACCA)
  • CFA Institute

KBS is a signatory of the United Nation's Principles for Responsible Management Education (PRME), which provides a global network for academic institutions to advance corporate sustainability and social responsibility.

Study support

Postgraduate resources

Kent Business School currently occupies a purpose-designed building consisting of executive learning facilities with wireless provision throughout. Each postgraduate student is assigned a specific member of academic staff who acts as your first point of contact throughout your studies. There is a lively postgraduate community at the School, with plenty of space to relax and interact with your fellow students and our academic staff.

On the Canterbury Campus, Kent Business School will soon be moving into a new academic building, known as The Sibson Building, a vibrant new campus destination.New academic facilities and social spaces for Kent Business School at Medway have also recently opened. The Sail and Colour Loft features six seminar rooms, a group learning room, a computer suite, quiet study areas, student social spaces and a special reference collection of core text books. Kent’s libraries offer over a million books, periodicals and journals, and we have subject-specific librarians to help you secure access to the information you need.

We also offer excellent teaching facilities with tailor-made specialist resources. Postgraduate students can access a range of specialist software packages used in quantitative analysis and in finance. Most academic schools have specific study areas for postgraduates and there is also a general postgraduate common room with work area.

An international focus

Kent Business School has more than 60 internationally recognised academics from 22 different countries. Most of our teaching faculty are involved with researching the latest issues in business and management, working with organisations to provide new insight for business leaders and policymakers. Their knowledge and findings feed into the programmes to ensure they are both cutting-edge and globally relevant.

Worldwide partnerships

Kent Business School has close links with: ifs (Institute of Financial Services); dunnhumby, who partners the Consumer Insight Service in the Centre for Value Chain Research; Hong Kong Baptist University, with whom we offer a joint Master’s programme in Operational Research and Finance Business Statistics; University of Castellanza (Italy); Audencia Nantes Business School (France); Aarhus School of Business and Social Sciences (Denmark); Universiti Teknologi Malaysia; University of Ingolstadt, Bayern (Germany); City University of Hong Kong; Renmin University of China, School of Business.

Dynamic publishing culture

Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Critical Perspectives on Accounting; Quantitative Finance; Human Resource Management Journal; Journal of Product Innovation Management; European Journal of Operational Research; and Psychology & Marketing.

Global skills

All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.

Global Skills Award

All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.  

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Learn more about the applications process or begin your application by clicking on a link below.

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T: +44 (0)1227 768896

E: information@kent.ac.uk

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F: +44 (0)1227 761187

E: kbsadmissions@kent.ac.uk

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T: +44 (0)1227 823254
E: internationalstudent@kent.ac.uk

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Kent Business School