Module BUSI4N630: Advanced Business Data Analysis and Consultancy (Fudan DBA)

Department: Business School (Business)

BUSI4N630: Advanced Business Data Analysis and Consultancy (Fudan DBA)

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• provide students with the necessary training to undertake advanced level research in the area of business
• provide students with an advanced understanding of the relevance and importance of alternative epistemological positions in the social sciences and the nature of both qualitative and quantitative approaches to research
• provide students with opportunities to be familiar with the frontier empirical and theoretical research in business
• build upon students’ knowledge of business methods and provide them with the specific advanced technical skills necessary to pursue empirical research in business
• provide students with the tools required analyse business issues

Content

• Part I • The characteristics of the qualitative or phenomenological approach and its roots in the interpretive paradigm. Its advantages and disadvantages in relation to positivism. • Designing qualitative research, Case study research, Generating qualitative data: interviewing, observation, documents. Sampling and selecting. • Sorting organizing and indexing qualitative data. • Data analysis USING Nvivo and results interpretation
• Part II • Review of the basic statistical concepts • Cleaning, labeling, transforming and describing data • Crosstabs & hypothesis testing • Distributional assumptions and tests of two means • One way and two-way ANOVA • Correlation and bivariate regression • Multiple regressions • Hierarchical Multiple Regression • Logistic regression • Exploratory factor analysis • Structural equation modeling using AMOS

Learning Outcomes

• By the end of this module, students should:
• have a critical awareness and understanding of the nature and range of empirical techniques available to practitioner-researchers in business and management;
• have a critical appreciation of the distinctions between quantitative and qualitative methods of inquiry, together with the challenges inherit in selecting those techniques appropriate to the current research objectives;
• understand when to use various statistical applications that are commonly used in management and in academic papers;
• formulate a strategy for analyzing a particular data set;
• use the SPSS, AMOS and Nvivo software programs to analyze different types of data to answer a broad range of research questions;
• apply statistical analysis techniques in course assignments, research and corporate reports;
• have further enhanced their acquisition of the advanced skills needed to plan, implement, report, and manage a comprehensive programme of research during the thesis stage of the DBA.

• By the end of this module, students should:
• be able to apply core statistical and qualitative data analysis skills in business studies;
• be able to effectively organise, structure and manage a research project within a business context, including undertaking critical appraisal of relevant literature, and apply critical judgement and discrimination;
• have further developed the skill of inquiry, quantitative and qualitative research design, experimental research, data collection and information retrieval, measurement and analysis, interpretation and presentation, self-discipline and time-management and the ability to work autonomously;
• have further practised problem solving skills at an advanced level and the use of SPSS, Nvivo, AMOS software.

• Ability to make an initial formulation and articulation of a potential scheme of research
• Ability to understand and resolve the problems and issues in undertaking doctoral research
• Computer literacy
• Transferring academic knowledge into practice

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• The module will be delivered in a workshop format over two intensive two-day teaching blocks. Workshops will comprise a balanced mix of lecture- and seminar-type delivery combined with small group discussions, reinforced by IT-based practical classes in the use of both quantitative and qualitative software packages (e.g. SPSS, Nvivo), and other activities as appropriate to the nature of the material.
• Learning will also occur through tutor-supported, as well as self-supported learning groups. In addition, guided reading will address key topics. This range of methods will ensure that students will acquire the advanced skills and knowledge to enable them to develop a thorough understanding of this specialist field of study.
• The summative assessment is a 5000-word written assignment, designed to prepare students for subsequent stages of the programme – ultimately the doctoral thesis/viva.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Individual oral examination via a poster-style presentation with individual feedback

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University