1.1 Introduction
Take any statement about aims and scope of top tier management journals (AM, 2019; AMJ, 2019; AMR, 2019), they all refer to rigor, novelty, and strong theoretical or empirical contribution, depending whether the outlet publishes conceptual or empirical papers. While sometimes posited to come at the expense of relevance, rigor has been defended as a cornerstone of management research in answering questions of relevance to managers (Gulati, 2007; Vermeulen, 2005). Research methods and construct measurement represent important aspects in assessing the quality of research during the peer review process. Accordingly, the Academy of Management Journal states that one reason for rejection might be a weakly validated measure or implementation of flawed research design. In a similar vein, the Academy of Management Review seeks carefully crafted conceptual articles. Pursuing a rigorous research is also in the code of ethics of the Academy of Management (https://aom.org/About-AOM/AOM-Code-of-Ethics.aspx) and its sister academic societies. In sum, whether an article is conceptual or empirical, constructs are the building blocks and construct measurement is a key task in any research endeavor.
The language of rigorous research revolves around key terms such as construct, measurement, validity, and reliability, just to mention a few. For each of these terms and corresponding activities, Ph.D. level courses are designed and a vast amount of textbooks and journal articles are available. In this chapter, we offer an overview of construct measurement and its key terms and analyze construct measurement practices in the management and the acquisition field. We also provide a brief reconstruction of the debate among those who state that management scholars should favor precision and those who advocate for openness in construct measurement. We embrace the position that balances the two opposing views by seeking for clarity in construct measurement.
1.2 Constructs and Construct Measurement
Concepts and constructs represent the basic terms of theories. Constructs, Kaplan states (1964: 55), may be defined as ‘terms which, though not observational either directly or indirectly, may be applied or even defined on the basis of the observables.’ Typically, concepts are conceived as abstracts terms ‘semantically defined by its association or usage with other terms that are not directly observable’ (Van de Ven, 2007: 113). Constructs are middle-range terms that represent the constitutive parts of concepts. This distinction is used by Kaplan (1964) to discriminate between grand theories, built around concepts, and middle-range theories, built around constructs. Bacharach (1989) distinguishes between theoretical and observable terms and lumps together concepts and constructs as theoretical terms, a position we embrace in this book.
1.2.1 Construct Measurement
The process that identifies variables that measure those constructs is called construct measurement. In traditional, deductive approaches, construct measurement involves two aspects: the conceptualization and the operationalization (Singleton & Straits, 2005). In other, drawing on an inductive approach, data is typically gathered before they are gradually tied to concepts and constructs (Strauss & Corbin, 1990). In both cases, conceptualizing a construct implies defining its meaning. Van de Ven (2007) discusses two different definitions: the semantic and the constitutive definition. A semantic definition enables to describe the construct in terms of similarities or differences with other terms, while a constitutive definition identifies its component parts. In other words, semantic and constitute definitions, respectively, provide breadth (how similar to and different from other constructs at the same level of abstraction) and depth (what component terms comprise the construct at lower level of abstraction) to constructs. Constitutive definition also implies defining constructs as either unidimensional or multidimensional.
The use of multidimensional constructs in conceptual frameworks has become increasingly popular as management field develops and becomes better equipped to capture the complexity of the phenomena under investigation. Multidimensional constructs are those consisting of a number of interrelated attributes or dimensions and exist in multidimensional domains. In contrast to a set of interrelated unidimensional constructs, the dimensions of a multidimensional construct can be conceptualized under an overall abstraction, and it is theoretically meaningful and parsimonious to use this overall abstraction as a representation of the dimensions (Law, Wong, & Mobley, 1998). Sharfman and Dean (1991a, 1991b) outline how often dimensions are confused with constructs. Constructs, as specified earlier in this chapter, are abstract, while dimensions are manifest variables that are indicators of latent variables.
1.2.2 Openness Versus Precision in Defining Constructs
Management scholars have long debated about the importance of precision while defining constructs, a debate that is polarized between those of advocate for precision and those who argue for openness. Traditionally, researchers have been concerned with increasing precision. In 1981, Warriner, Hall, and McKelvey (1981: 173) made an ambitious call and invited management scholars to participate in formulating ‘a standard list of operationalized, observable variables for describing organizations.’ The invitation arose as an attempt to overcome problems resulting from the tendency of different investigators to use alternative sets of variables and, consequently, describe organizations of the same type, and even the same organizations, in quite different ways. Thus, Warriner et al. (1981: 175) argued that a more accurate representation of organizational phenomena could be achieved by establishing a repository of ‘pooled data’ on operational measures to be used in empirical research.
Osigweh (1989) provides a thorough examination of drawbacks of using imprecise concepts. He notes that if any of the concepts in a proposition are ill-defined, it may result an ambiguous research proposition or a disproportionate emphasis on certain aspects of an organizational phenomenon. Also, imprecise concepts make it difficult to cumulate knowledge (Bagozzi & Fornell, 1982). By contrast, precise concepts are thoroughly discriminating and, thus, are suitable for data-gathering purposes. They do not misinform their users as to the empirical implication of the theoretical propositions containing them; so, they do not misguide the efforts of researchers and practitioners using them. They assist organizational scientists in the continuing development of their discipline as a science.
Based on these considerations, Osigweh (1989) warns from concept stretching, a practice that may happen during concept traveling and that produces concepts that are universals only in name, because they are supra-empirical; they are too philosophical to be empirically observed or tested. This position reflects a positivistic view of science where knowledge accumulates through a process of filling substantive gaps with research findings serving as building blocks of the ever-growing ‘edifice of knowledge’ (Guba & Lincoln, 1994).
On the opposite end of the continuum, we find scholars who claim the importance of openness in construct measurement. One reason for openness is related to the nature of organizational science where much of the available knowledge is context-specific (e.g., Kast & Rosenzweig, 1985). Therefore, few universals concepts that can be accurately tested in different situations are possible (e.g., Cronbach, 1986). If this is true, then searching for universals in organizational science could produce frustration, and the aspirat...