A six-stage framework for evolutionary IS research using path models. Conceptual development and a social networking illustration
| Published date | 14 March 2016 |
| Date | 14 March 2016 |
| DOI | https://doi.org/10.1108/JSIT-04-2015-0028 |
| Pages | 64-88 |
| Author | Ned Kock,Murad Moqbel |
| Subject Matter | Information & knowledge management,Information systems |
A six-stage framework for
evolutionary IS research using
path models
Conceptual development and a social
networking illustration
Ned Kock
Division of International Business and Technology Studies,
Texas A&M International University, Laredo, Texas, USA, and
Murad Moqbel
Department of Health Information Management,
University of Kansas Medical Center, Kansas City, Kansas, USA
Abstract
Purpose – The purpose of this study is to ll a gap in evolutionary theorizing in the eld of
information systems. Evolutionary theorizing has recently been added as a useful tool to the research
repertoire of information systems investigators. However, the literature on evolutionary theorizing and
related empirical research lacks a clear framework that explicitly shows how information systems
researchers can go, step-by-step, from a generic model of the evolution of traits in our ancestral past to
a more specic model depicting the effects of technology facilitation of those traits among modern
humans. The purpose of this study is to ll this gap through a framework composed of six stages.
Design/methodology/approach – To discuss and illustrate the framework, the authors develop an
easy-to-understand generic path model explicitly depicting relationships among variables related to
events that occurred in our evolutionary past. We then incrementally adapt this generic path model,
eventually arriving at a focused path model depicting causal relationships among social networking site
use, job satisfaction, organizational commitment and job performance. In doing so, the authors also
develop a theoretical model about how social networking site use can affect job performance, where a
positive total effect is predicted via positive intermediate effects on job satisfaction and organizational
commitment.
Findings – To discuss the nal stage in the framework, the authors present an illustrative example
where the focused path model is tested based on a study of the effect of Facebook use on job performance
among 178 working professionals across the USA. This illustrative example provides general support
for the theoretical model.
Research limitations/implications – The counterintuitive hypothesis that Facebook use is
associated with increased job performance is supported.
Practical implications – Social networking site use by organizational employees is likely to be
associated with improved job performance.
Originality/value – This study provides a clear framework that shows how researchers can go from
a generic evolutionary path model in our ancestral past to a more specic model comprising technology
effects in modern humans.
Keywords Evolutionary biology, Path analysis, Theory development
Paper type Research paper
The current issue and full text archive of this journal is available on Emerald Insight at:
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JSIT
18,1
64
Received 2 April 2015
Revised 8 October 2015
Accepted 27 October 2015
Journalof Systems and
InformationTechnology
Vol.18 No. 1, 2016
pp.64-88
©Emerald Group Publishing Limited
1328-7265
DOI 10.1108/JSIT-04-2015-0028
Introduction
Evolutionary theorizing has recently made an entrance in the eld of information
systems (IS) as a new research tool (Abraham et al., 2011;Blau and Barak, 2012;Kock,
2009;Kock and Chatelain-Jardón, 2011;Vlahovic et al., 2012;Zahedi and Bansal, 2011).
We predict that the use of evolutionary theorizing will increase in the eld of IS in the
future, but only if clear theory development frameworks are made available to guide
that theorizing and related empirical assessment. There are a number of reasons why
evolutionary theorizing can be an attractive approach for IS researchers, two of which
are particularly noteworthy.
The rst is that evolved responses tend to be uniformly observed across different
cultures, and IS are increasingly global, often including features that are used across
cultures. That is, evolved responses are often the reason for common observed
behavioral patterns in the context of technology use across cultures, even when
behavior is quite different overall. The existence of evolved behavioral patterns does not
mean that all people behave the same way toward technology, but rather that often the
commonalities in behavior have a hidden evolutionary basis (Kock, 2009).
The second particularly noteworthy reason why evolutionary theorizing can be an
attractive approach is that evolved behavioral responses are often tied to subconscious
mental mechanisms, and thus are frequently not self-evident and even counterintuitive.
Evolutionary theorizing can help explain behavioral responses that would otherwise
appear strange, disconnected from reality, and contradictory with commonsense
assumptions.
Evolution is a process whereby genotypes associated with traits that enhanced
reproductive success in our evolutionary past rst appeared at random and then spread
through populations through selection forces. The environments of our evolution,
although varied, often incorporated common characteristics across generations and
populations that were very different from those found in our modern world (Barkow
et al., 1992;Buss, 1999).
The literature on evolutionary theorizing currently lacks a clear framework that
explicitly shows how IS researchers can go, step-by-step, from a generic view of the
evolution of traits in our ancestral past to hypotheses about the effects of technology
facilitation of those traits among modern humans. To ll this gap, we show, through
a multi-stage theory development and empirical analysis framework, that path
models can be used to explicate the evolution of traits in our ancestral past, and also
to better understand their expression in modern humans through modied path
models derived from those ancestral path models. Moreover, we show that modied
path models can demonstrably be used to predict the effects that technologies that
facilitate the expression of evolved traits will have in modern tasks and
environments.
The stages of the theory development and empirical analysis framework are
exemplied through an illustrative example where a focused path model is developed,
based on a generic ancestral path model, and used to hypothesize relationships among
social networking site use (SNUse), job satisfaction (JSaft), organizational commitment
(OComm) and job performance (JPerf). The illustrative example also includes an
analysis of data from 178 working professionals across the USA, all of whom used
Facebook to various degrees.
65
Framework for
evolutionary IS
research
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