II. RESEARCH CONCEPTS, CONSTRUCTS, PROPOSITIONS, VARIABLES, AND
HYPOTHESES
Research Concepts and Constructs
A concept or construct is a generalized idea about a class of objects, attributes,
occurrences, or processes that has been given a name.
Concepts are the building blocks of theory.
Concepts abstract reality (i.e., concepts express in words various events or objects).
Concepts may vary in degree of abstraction.
Ladder of abstraction—organization of concepts in sequence from the most concrete and
individual to the most general.
Moving up the ladder of abstraction, the basic concept becomes more general, wider in
scope, and less amenable to measurement.
The basic or scientific business researcher operates at two levels—on the abstract level of
concepts (and propositions) and on the empirical level of variables (and hypotheses).
Empirical level—level of knowledge that is verifiable by experience or observation.
Abstract level—level of knowledge expressing a concept that exists only as an idea or
a quality apart from an object.
Latent construct—a concept that is not directly observable or measurable, but can be
estimated through proxy measures.
Researchers are concerned with the observable world (i.e., reality).
Theorists translate their conceptualization of reality into abstract ideas.
Things are not the essence of theory; ideas are.
Concepts in isolation are not theories—to construct a theory we must explain how
concepts relate to other concepts.
Research Propositions and Hypotheses
Propositions are statements concerned with the relationships among concepts and
explain the logical linkage among certain concepts by asserting a universal connection
between concepts.
A hypothesis is a formal statement explaining some outcome and is a formal statement of
an unproven proposition that is empirically testable.
In its simplest form, a hypothesis is a guess.
A hypothesis is a proposition that is empirically testable, so when on estates a hypothesis,
it should be written in a manner that can be supported or shown to be wrong through an
empirical test.
Often apply statistics to data to empirically test hypotheses.
Empirical testing means that something has been examined against reality using data.
Variables are anything that may assume different numerical values; the empirical
assessment of a concept.
When the data are consistent with a hypotheses hypothesis is supported.
When the data are inconsistent with a hypothesis hypothesis is not supported.
From an absolute perspective, statistics cannot prove a hypothesis is true.
Because variables are at the empirical level, variables can be measured.
Operationalizing—the process of identifying the actual measurement scales to assess the
variables of interest.