This chapter deals with some conceptual (theoretical) foundations of research. Practical business research is often thought of as collecting data from various statistical publications, constructing questionnaires, and analysing data by using computers. Research, however, also comprises a variety of important, non-empirical tasks, such as finding/‘constructing’ a precise problem, and developing perspectives or models to represent the problem under scrutiny. In fact, such aspects of research are often the most crucial and skill demanding. The quality of the work done at the conceptual (theoretical) level largely determines the quality of the final empirical research. This is also the case in practical business research. Important topics focused on in this chapter are the research process and the role of concepts and theory.

The research design is the overall plan for relating the conceptual research problem to relevant and practicable empirical research. In other words, the research design provides a plan or a framework for data collection and its analysis. It reveals the type of research (e.g. exploratory, descriptive, or causal) and the priorities of the researcher. The research methods, on the other hand, refer to the techniques used to collect and analyse data. This chapter looks at a variety of research designs and methods, as well as at the concept of validity.

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.

The research design is the overall plan for relating the conceptual research problem to relevant and practicable empirical research. In other words, the research design provides a plan or a framework for data collection and its analysis. It reveals the type of research (e.g. exploratory, descriptive, or causal) and the priorities of the researcher. The research methods, on the other hand, refer to the techniques used to collect and analyse data. This chapter looks at a variety of research designs and methods, as well as at the concept of validity.

In this chapter, we first provide a detailed discussion of the advantages and disadvantages of collecting and using secondary data, and highlight some important secondary data sources. The next section then considers the advantages and disadvantages of collecting and using primary data. The following three sections are devoted to sampling. With secondary data, the researcher is obliged to accept the data that are publicly available, and is not able to influence how the data are collected or how much data are collected. In contrast, the researcher collecting primary data needs to decide whether to survey the entire population or just a sample, to choose an appropriate sampling procedure, and to determine the sample size that will assure a satisfactory level of precision in the subsequent empirical analysis. The final two sections are then devoted to undertaking the two most common methods of primary data collection, namely questionnaire surveys and experiments.

In this chapter, we first provide a detailed discussion of the advantages and disadvantages of collecting and using secondary data, and highlight some important secondary data sources. The next section then considers the advantages and disadvantages of collecting and using primary data. The following three sections are devoted to sampling. With secondary data, the researcher is obliged to accept the data that are publicly available, and is not able to influence how the data are collected or how much data are collected. In contrast, the researcher collecting primary data needs to decide whether to survey the entire population or just a sample, to choose an appropriate sampling procedure, and to determine the sample size that will assure a satisfactory level of precision in the subsequent empirical analysis. The final two sections are then devoted to undertaking the two most common methods of primary data collection, namely questionnaire surveys and experiments.

Information technology has played a substantial role in healthcare since the 1960s. Its adoption has rapidly progressed. In 2007, only 2.2 percent of American hospitals had mature electronic medical record systems, while by 2017, 73.1 percent had mature systems. This chapter aims to inform readers about the historical drivers of health information technology (IT) adoption, as well as about the status of the industry today. The chapter provides detailed explanations of how health IT is being used by healthcare providers, payers, and consumers. Multistakeholder products and services are discussed, and the health information technology services industry is explored. The chapter concludes with a discussion of international adoption of health information technology, the size and growth of the industry, and the future of the health IT industry.

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.

In this chapter, we focus on the role that innovation plays in the medtech ecosystem, including how innovation is financed by early-stage venture capital investors and valued by other stakeholders in the ecosystem. Using specific case studies and empirical data, we review the impact that innovation has on medical device companies’ revenue growth through market expansion and derivative product sales, and the ways in which medical device companies are valued by early-stage venture capital investors, public market investors, and strategic acquirers. In addition, there is a focus on the types of medtech product and service innovations that have driven the greatest value in the market, and the process of developing new technologies from ideation and invention to clinical evidence generation and regulatory approval, and then all of the way to widespread market adoption.

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.