Problems, that is ‘questions’, drive research. Without research questions there would hardly be any research at all. Research problems are not ‘given’, however; they are detected and constructed. How research problems are captured and framed drives subsequent research activities. In normal research situations, we first select a topic and then formulate a research problem within that topic. The process of constructing a research problem is not straightforward and often involves a lot of back-and-forth adjustments and refinement. In this chapter we particularly focus on how to construct and adequately capture research problems. The role of reviewing past literature to identify weaknesses and gaps is also examined.

A huge array of statistical methods are available to the researcher, of variable levels of sophistication, and a comprehensive survey would be well beyond the scope of this textbook. Here we outline three methods which are widely used in business studies research, namely factor analysis, structural equation modelling, and event study analysis. In each case, we explain the key elements of each method, the underlying intuition, and how to interpret the results, and then provide an example from the business literature.

Medical devices and medical technology, with worldwide revenues of roughly $330 billion, comprise an important segment within healthcare. This broad set of products, ranging from extraordinarily complex implantable defibrillators to metal mesh stents to hip and knee implants, have truly advanced the practice of medicine and represent life-saving therapies to patients in need. Growth, in recent years, while slower than that of the 1990s when several entirely new therapeutic categories emerged, continues at a good pace. The industry is increasingly dominated by large companies such as Medtronic, Abbott, Johnson & Johnson, and Stryker which offer a broad mix of technologies in multiple anatomies and diseases. In as much as structural developments, including reimbursement and the containment of healthcare costs, they have made it more difficult for single product/single anatomy companies to flourish. Those that provide truly innovative products that are treatment-altering can succeed and remain independent. Indeed, there exist several examples – in areas such as diabetes, heart failure, and neurological diseases. Furthermore, the industry remains highly profitable – companies on average enjoy operating margins in the mid-twenties, considerably higher than nearly every other industry. We anticipate continued growth for the sector as devices and technology play an expanded role in healthcare. Of the US $3.6 trillion healthcare spend, medical technology represents less than 5 percent on a revenue basis.

The most commonly used technique for the analysis of quantitative data in business research is multiple regression analysis. This is a powerful technique for understanding the relationships between variables, which variables have the most impact, and for prediction. In this chapter, we consider how to specify regression models, how to estimate the models, and how to use the estimated models to undertake some simple hypothesis tests. We emphasize that the researcher has to exercise his/her judgement in deciding not only the specification of the initial model but also in how to adapt and interpret the model in response to the various statistical tests.

After completing the data collection and analysis, the research problem, the data collected, and the findings need to be presented in a logical, consistent, and persuasive report. This chapters outlines a typical format for such a research report, and describes the contents of each section. It also discusses oral presentations and writing for publication.

Problems, that is ‘questions’, drive research. Without research questions there would hardly be any research at all. Research problems are not ‘given’, however; they are detected and constructed. How research problems are captured and framed drives subsequent research activities. In normal research situations, we first select a topic and then formulate a research problem within that topic. The process of constructing a research problem is not straightforward and often involves a lot of back-and-forth adjustments and refinement. In this chapter we particularly focus on how to construct and adequately capture research problems. The role of reviewing past literature to identify weaknesses and gaps is also examined.

The appropriate method of data analysis depends upon a variety of factors that have been specified in the research question and as part of the research design. One key issue is whether the data are qualitative or quantitative, and this depends upon the underlying research approach. If the research approach is deductive, then most of the data are likely to be expressed as numbers and the key issue will be selecting the appropriate statistical techniques for describing and analysing the data. In this chapter, we will concentrate on techniques for describing quantitative data and for providing simple preliminary analyses.

This chapter outlines the purpose, scope, and structure of the book and introduces the scientific, data-driven approach to analysing and solving business problems and conducting business research.