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THE HALLMARKS OF SCIENTIFIC RESEARCH 25

Objectivity

The conclusions drawn through the interpretation of the results of data analysis
should be objective; that is, they should be based on the facts of the findings
derived from actual data, and not on our own subjective or emotional values. For
instance, if we had a hypothesis that stated that greater participation in decision
making will increase organizational commitment, and this was not supported by
the results, it makes no sense if the researcher continues to argue that increased
opportunities for employee participation would still help! Such an argument
would be based, not on the factual, data-based research findings, but on the sub-
jective opinion of the researcher. If this was the researcher’s conviction all along,
then there was no need to do the research in the first place!
Much damage can be sustained by organizations that implement non-data-
based or misleading conclusions drawn from research. For example, if the
hypothesis relating to organizational commitment in our previous example was
not supported, considerable time and effort would be wasted in finding ways to
create opportunities for employee participation in decision making. We would
only find later that employees still keep quitting, remain absent, and do not
develop any sense of commitment to the organization. Likewise, if research
shows that increased pay is not going to increase the job satisfaction of employ-
ees, then implementing a revised increased pay system will only drag down the
company financially without attaining the desired objective. Such a futile exer-
cise, then, is based on nonscientific interpretation and implementation of the
research results.
The more objective the interpretation of the data, the more scientific the
research investigation becomes. Though managers or researchers might start with
some initial subjective values and beliefs, their interpretation of the data should
be stripped of personal values and bias. If managers attempt to do their own
research, they should be particularly sensitive to this aspect. Objectivity is thus
another hallmark of scientific investigation.

Generalizability
Generalizability refers to the scope of applicability of the research findings in one
organizational setting to other settings. Obviously, the wider the range of applic-
ability of the solutions generated by research, the more useful the research is to
the users. For instance, if a researcher’s findings that participation in decision
making enhances organizational commitment are found to be true in a variety of
manufacturing, industrial, and service organizations, and not merely in the par-
ticular organization studied by the researcher, then the generalizability of the
findings to other organizational settings is enhanced. The more generalizable the
research, the greater its usefulness and value. However, not many research find-
ings can be generalized to all other settings, situations, or organizations.
For wider generalizability, the research sampling design has to be logically
developed and a number of other details in the data-collection methods need to
be meticulously followed. However, a more elaborate sampling design, which