A central mission for universities is to conduct research that both advances a scientific discipline and enlightens practice in a professional domain. To make research not being a solitary exercise but instead a collective achievement it should be carefully designed and implemented. Different research approaches are available for social scientists: quantitative and qualitative research methods. For each of them there are different research tools that should be implemented. The overall objective of this course is to present the main steps to develop a rigorous and relevant research for academics and managers.

The course will examine the specific issues involved in developing and implementing research methods to solve a managerial decision problem. Students will obtain computer skills such as SPSS for Statistics. The course aims at enabling the students to: • Develop research for evidence-based managerial problem solving • Compare strengths and weaknesses of different statistical procedures • Illustrate findings from statistical analyses effectively • Perform different types of data-analyses such as OLS regressions • Interpret results of multivariate data-analysis techniques (e.g., regression, factor analysis, ANOVA) • Identify advantages and drawbacks of different statistical methods Knowledge and understanding: By the end of the course, students should be able to: • read and interpret scientific papers and reports; • understand and develop knowldege of research methodology; • able to evaluate research done and to design a research project; • able to evaluate and discuss papers. Applying knowledge and understanding: Upon completing the study program, students will be able to: • apply the concepts taught in the course to the different research methodologies; • diagnose research methodology advantages and drawbacks. • to implement statistical models to analyze data; • design, interpret and carry out evidence-based research for decision making in businesses. Making judgements: Upon completing the study program, students will be able to: • define the right statistical technique to use given the nature of the data available • derive theoretical and managerial implications from statistical data. Communications Skills: Upon completing the study program, students will be able to: • communicate and interpret, process and synthesize data relating to the problems under study; • acquire the appropriate terminology; • Communicate evidence-based findings to different audiences. Learning skills: Upon completing the study program, students will be able to: • interpret and understand the various research methodologies and the structure of scientific papers and reports

The course deals with the concept of engaged scholarship, evidencing the crucial step to develop a rigorous and relevant research: formulating the research problem and research question based on an accurate literature review and on the current empirical need; the need for theory building; the choice of the research design; how to collect data and how conduct empirical analyses; and how to communicate the outcomes. Concerning the research design phase, students will be exposed to quantitative and qualitative methods with empirical application.

For a reflection on the various steps in the research process, refer to: • Van de Ven, A. 2011. Engaged Scholarship. Oxford University Press. For guidance on statistical procedures • Field, A. (2017). Discovering statistics using IBM SPSS statistics. London: Sage. • Hinton, P., McMurray, I., & Brownlow, C. (2014). SPSS explained. Routledge. (available online through perlego)

Frontal classes, scientific articles reading, case discussion, individual assignments, group work.

For attending students: Individual assignment exercises (10% of the final grade) Group assignment (50%) Class participation (10%) Exam (30%) For non-attending students: Individual assignment (70%) Exam 30% Note: The individual assignment mark cannot be rejected. Non-attending students will have to study an extended program which will be communicated on the LuissLearn platform.

Upon request.

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