Interdisciplinarity of information science: an evolutionary perspective of theory application
| Date | 20 November 2023 |
| Pages | 392-426 |
| DOI | https://doi.org/10.1108/JD-07-2023-0135 |
| Published date | 20 November 2023 |
| Subject Matter | Library & information science,Records management & preservation,Document management,Classification & cataloguing,Information behaviour & retrieval,Collection building & management,Scholarly communications/publishing,Information & knowledge management,Information management & governance,Information management,Information & communications technology,Internet |
| Author | Chao Zhang,Fang Wang,Yi Huang,Le Chang |
Interdisciplinarity of information
science: an evolutionary
perspective of theory application
Chao Zhang, Fang Wang and Yi Huang
Department of Information Resources Management, Business School,
Nankai University, Tianjin, China, and
Le Chang
College of Management and Economics, Tianjin University, Tianjin, China
Abstract
Purpose –This paper aims to reveal the interdisciplinarity of informationscience (IS) from the perspective of
the evolution of theory application.
Design/methodology/approach –Select eight representative IS journals as data sources, extract the
theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by
conducting theory co-occurrence network analysis, diversity measure and evolution analysis.
Findings –As a young and vibrant discipline, IS has been continuously absorbing and internalizing external
theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of
some kernel theories, the interdisciplinarityof IS appears to be decreasing and gradually converging into a few
neighboringdisciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting
from a theory centered one to a technology centered one.
Research limitations/implications –This study helps to understand the evolution of the
interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight
journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.
Originality/value –This study identifies the kernel theories in IS research, measures the interdisciplinarity
of IS based on the evolution of the co-occurrencenetwork of theory source disciplines and reveals the paradigm
shift being happening in IS.
Keywords Interdisciplinarity, Information science, Theory application, Evolution, Network analysis,
Kernel theories
Paper type Article
1. Introduction
Solving complex and fuzzy problems frequently requires multidisciplinary knowledge, which
promotes the cross-combination of theories, methods and technologies among different
disciplines and forming interdisciplinary research (Xu et al., 2016). The concept
“interdisciplinary research”was first proposed by Woodorth in 1926, referring to research
activities involving two or more disciplines beyond the existing boundaries of a specific
discipline (Ying et al., 2019). The essence of interdisciplinary research is the integration of
multiple disciplinary methods, theories, tools and concepts, reflecting the flow of knowledge
between disciplines (Wagner et al., 2011). Interdisciplinary research can not only help
researchers obtain more diversified opinions and thinking patterns, synthesize
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The authors give special thanks to the reviewers and editors for their valuable comments and
suggestions. This work is funded by the major project of the Chinese National Planning Fund for
Philosophy and Social Sciences (Grant No. 20ZDA039).
CRediT authorship contribution statement Chao Zhang: Methodology, Data analysis, Writing –
draft and editing. Fang Wang: Supervision, Conceptualization, Methodology, Writing –review and
editing. Yi Huang: Theoretical extraction and experiment. Le Chang: Data Annotation, Writing –
original draft and review.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0022-0418.htm
Received 19 July 2023
Revised 6 October 2023
Accepted 8 October 2023
Journal of Documentation
Vol. 80 No. 2, 2024
pp. 392-426
© Emerald Publishing Limited
0022-0418
DOI 10.1108/JD-07-2023-0135
multidisciplinary knowledge and propose better research questions (Chakraborty, 2018) but
also recombine knowledge from different disciplines to get rid of popular theories and
paradigms and bring pioneering progress (Fortunato et al., 2018;Chai and Menon, 2019).
In this sense, interdisciplinary research is crucial in promoting academic innovation and
improving the development level of modern science (Valentin et al., 2016).
The origin of information science (IS) is the publication of As We May Think (Bush) in
(1945) according to Saracevic (1999). Although there is no universally accepted definition for
IS (Buckland, 2012;Furner, 2010;Saracevic, 1999;Cibangu, 2013), the unanimous view of the
academic community is that IS is a discipline with a distinctly interdisciplinary nature
(Sugimoto et al., 2011;Tatjana et al., 2013;Arafat et al., 2014;Madsen, 2016). To limit the
research boundary to a relatively definite scope, the present study defines IS as a science that
includes the conventional and emerging IS fields, except pure library research areas.
Although existing studies have analyzed the interdisciplinarity of IS based on author
institution (Chang, 2018), citation relationship (Chen et al., 2018a,b) and research theme
(Vakkari et al., 2022) in publications, most of them have ignored the key role of theories in IS
research, which may lead to a bias in their conclusions.
For an independent and relatively young discipline, the research, application, and
deepening of theories are key to discipline development (Smith and Hitt, 2006). Theory is the
basis for disciplines to construct research problems, establish arguments and interpret
results, helping disciplines delineate their boundaries and establish central knowledge
systems (Pettigrew and McKechnie, 2001). The formation of theories mark the independence
and maturity of a discipline (Brookes, 1980), and the category and boundary of theories define
the scope and boundary of a discipline (Pettigrew and McKechnie, 2001). Therefore, theory is
the core of the scientific research paradigm of disciplines (Kuhn, 2012), and the growth and
progress of disciplines can be measured by the degree of theory application (Koh, 2013).
To reveal the interdisciplinary nature of IS research, some studies identified hot theories
and their source disciplines and compared their application between different IS research
areas and different countries or regions (Pettigrew and McKechnie, 2001;Wang et al., 2016;
Wang et al., 2018a,b). However, the static description of overall theory application in IS failed
to reveal the evolution process of theory generation, enhancement, contraction and extinction,
as well as the cooperative relationship between different theories, in the course of discipline
development. This practice of justifiably regarding theory as a necessity for research without
examining its dynamic alternation over time, leads to a lack of understanding of the structure
and dynamic mechanisms of disciplinary development. In view of this research gap,
a quantitative measurement of the interdisciplinarity of IS and its evolution from the
perspective of theory application will be conducted in this study, which is also expected to
address the fragmentation of the research on IS theory application.
To achieve this research goal, the current study extracts theories from the full papers of
eight English IS journals from 2001 to 2021 and confirms their source disciplines, and then
delineates their dynamic alternation at one-year intervals. Social network analysis is adopted
to reveal theory co-occurrence at different years, and diversity analysis is used to
quantitatively measure the variety, balance and disparity of the application of IS theory.
Based on the results, the interdisciplinary degree and development trend of IS are judged.
This study can help to understand the evolution of the interdisciplinarity of IS, reveal its
paradigm shift and predict its future direction.
2. Literature review
2.1 Theory definition
The definition of theory varies with research field and researcher (Merton, 1968;Kerlinger,
1973;Wang et al., 2018a,b). In IS, theory is a system of a set of propositions with internal
Information
science
393
logical relationships, aiming to reveal the basic attributes, casual relationship or the laws of
motion of information related things and can be used to explain or predict information related
phenomena (Wang et al., 2018a,b). Theory is dynamically evolving, reflecting the
development of scientific knowledge (Coccia, 2020;Kilduff et al., 2011). There are different
views on the evolution of theory. The transformative view holds that theoretical change is
dramatic. Due to anomalies found in existing scientific rules or theories that cannot be
resolved, scholars are compelled to think and argue from a completely new direction, thereby
change the accepted paradigm and propose a new theory (Kuhn, 2012). In contrast, the
revisionist view holds that the appearance of an anomaly does not change the theory in a
revolutionary way but rather initiates a process of revision (Alexander, 1979). Models,
concepts and propositions reflecting new issues shape new theoretical frameworks and guide
the update and development of specific theories. Similarly, the cumulative perspective argues
that theory is driven by the accumulation of propositions, concepts or the refinement of
research. The accumulation of empirical evidence can filter out erroneous or inapplicable
theories, and the current theories thus formed gain legitimacy through the accumulation,
development and restructuring of past knowledge (Seidman, 1987). In reality, there exist
theories formed in the above three ways. Among them, whether fine-tuning theories (i.e. the
TAM2, TAM3 and UTAUT models that have been adjusted from the existing technology
acceptance model [TAM]) or transformative theories (i.e. the information theory and the
system theory) have made independently contributions to their problem areas, and are
therefore taken as different theories in the present study.
Similar concepts to theories include law, principle, model, framework, algorithm and so on.
Wang et al. (2018a,b,2021a,b) put forward that theory reveals the casual relationship
between things, model reflects the structural characteristics of things, law explains the
natural processes independent of human consciousness and framework refers to a structural
system composed of a group of components and their interactive relations. All of them are
abstractions of complex phenomena to a certain extent. Model is a substantive theory with a
lower level of abstraction (Glaser and Strauss, 1967). Framework can be taken as a theoretical
prototype that needs to be developed. Law can be taken as a theory that has been proven at
the current stage. Pettigrew et al. (2001) used “theory,”“model,”“framework,”“concept,”or
“based on”in their research as the equivalents of theory. Considering their similarity in
revealing the essence of social or natural things in abstract form and together forming the
core of human knowledge system, the current study takes theory, model, law, principle and
framework as the subjects of theory extraction in a less rigorous sense. This simplification
can ignore their subtle differences and facilitate the statistical analysis of the evolution of IS
theoretical knowledge over a longer period.
2.2 Theory application in IS research
Theory application refers to the behavior that an author applies a particular theory or
theories in some capacity (Kumasi et al., 2013). According to Jeong and Kim (2005), the depth
of theory application can be divided into five levels, including spot citing, background review,
theory discussion, theory application and analytical evaluation. They found that the theory
applications of the majority (47.38%) of the IS researches in South Korean were at the level of
background review rather than more profound levels (2006). Based on the literature data of
different periods, previous studies found that less than half of the journal papers in IS apply
theories (Pettigrew and Mckechnie, 2001;Kim and Jeong, 2006;Julien et al., 2011;Wang et al.,
2015;Wang et al., 2018a,b). This may be due to the relative dearth of theories in IS (Cibangu,
2013;Park et al., 2022).
Due to the lack of inherent theories, theory borrowing has become a tradition of IS (Hall,
2004), leading to the diversity of the source disciplines of the theories applied in IS research
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