Applying Theories for Information Systems Research

Tiko Iyamu

• Editorial: Routledge
• Año: 2021
• ISBN:
  9781000455922
• Edición: 1
• Categoría: Negocios y empresa
• Categoría: Gestión de la información

This book sets out to provide postgraduate researchers with guidance on selecting and applying sociotechnical theories to the study of information systems, including how they can be combined to complement each other. Until now it has been difficult to source advice on the application of these theories, and there has been no single book that combines multiple theories as this does.

Examining the impacts of technological developments and seeking to understand how humans interact with computers and systems is a dynamic field but can often confuse researchers with the overwhelming number of social theories that are utilised to derive insights. Instead, the author in this book breaks down some of the most popular theories used to underpin information system research, such as activity theory (AT), actor-network theory (ANT), contingency theory (CT), diffusion of innovation (DOI) theory, structuration theory (ST), and the technology acceptance model (TAM). By doing so, this book serves to enable a simpler, faster selection of appropriate theories, and a more effective and productive application that leads to richer, more rigorous research outcomes.

Written for postgraduates, researchers, and academics in the fields of information technology and information systems, this book provides a valuable resource of sociotechnical research methodologies that will enable and enhance future studies.

1 Introduction

DOI: 10.4324/9781003184119-1

Table of contents

• Introduction
• The goal and synopsis of the problem
• Information systems
• Information systems research
• Sociotechnical theories in information systems
• Conclusion
• References

Introduction

I would like to begin by clarifying very important terms used in the chapters of this book: information systems and technology (IS/IT) and information technology (IT) solutions mean the same thing in the context of this book; also, environment and organisation mean the same thing. Thus, the terms are interchangeably used in this book.

The introductory chapter is divided into four sections: the introductory section, followed by a synopsis of the problem the book tries to address, which is presented in the second section. The third and fourth sections provide brief introductions of the information systems (IS) discipline and IS research. These sections highlight the significance of qualitative data and the essentiality of the data source, as detailed in Chapters 2 and 3. In the fifth section, six sociotechnical theories that are the focal point of this book are introduced. The theories are extensively and comprehensively covered in the last nine chapters of the book.

The goal and synopsis of the problem

Many challenges are implicitly associated with over-reliance on an interpretivist approach for analysis and interpretation of qualitative data in IS studies. Apparently, this is the main reason many IS researchers struggle to justify the rigour in their studies. It gets worse because the data sets are often small, compared to quantitative studies. The emergence of sociotechnical theories has been significant in improving rigour and justification in IS research. Within the last two decades, six of the theories have been applied more than 5 million times in IS studies. In that period, last two decades, two things have been achieved and are well documented in literature: (1) the theories are well described and explained, including critique and support; and (2) the theories have been well embraced and are increasingly applied in IS studies.

Despite these efforts, a fundamental gap exists, which is the way the theories, can be applied in IS studies. The challenges emerge from two different perspectives; namely, why and how the theory is applied in an IS study. Some of the challenges emanate from the lack of know-how. This discourages postgraduate students from selecting a theory, even though it would have been most appropriate for their studies. This is primarily because the aspect that is found to be challenging and pushes some researchers, including postgraduates, away from the complexity of using the theories. This book provides a guide for each of the theories that has been most selected and focused on by IS scholars. The theories are activity theory (AT), actor-network theory (ANT), contingency theory (CT), the diffusion of innovation (DOI) theory, structuration theory (ST), and the technology acceptance model (TAM).

For each of the theories, this book proposes a model that holistically guides data analysis from an interpretivist perspective. Through the models, better understanding can be gained about the components of each theory and how they relate to the activities in the phenomena being studied. This includes the process of data collection in qualitative research and how its challenges can possibly be avoided. The chapters in the book reveal and discuss how the theories are used as lenses to guide data analysis and interpretation from a qualitative research perspective in IS. Another contribution of the book is in its plausible explanation: the strength of the theories lies in how to connect human actions with the different aspects of technology solutions, including the interaction and relationships that happen in the course of development, implementation, management, and use of information technology (IT) solutions. Subsequently, this draws the attention of both IS practitioners and academics, particularly aspiring researchers and postgraduate students, to the usefulness of applying sociotechnical theories in IS research.

Information systems

Neither this chapter nor the book intends to redefine IS as a discipline. I only describe it based on my experience that IS is an academic discipline which constitutes two fundamental embodiments – information and systems – which are of pivotal importance to society and scholarly domains. Information is from the Latin word of information-. In the Oxford English dictionary, it is defined as knowledge acquired through experience or study, knowledge of specific and timely events or situation. Simplistically,a system consists of organised components that have relationships which go through integrated processes of different elements. The field of IS is a sociotechnical organisational system that is designed to gather, store, process, and distribute information (Ritchie, 1991). IS are made up of four main components: task, people, structure (or roles), and technology. None of the components operates in a vacuum; they influence one another to produce results or enhance usefulness. How, when, and why the components influence each other is determined through research.

In practice, people often change the IT solutions that they make use of by consciously or unconsciously modifying the properties through their interaction with the solutions. This happens even when a technology seems to be stable and functions appropriately. Thus, the stability of IT solutions and their application are only provisional. Consequently, because of the rapid evolution of IT solutions, which stems from the fact that different elements are continuously developed, existing functions fail and repairs are needed, new materials are invented, new standards are set, and users modify the artefact and/or its content for new and different uses. Thus, an understanding of how and why things evolve is key to findings in IS research. As has been seen or experienced for many years, there is increasing interest and the use of sociotechnical theories as lenses to examine and gain a better understanding of how and why things happen in the way that they do, in the development and implementation of IT solutions.

IS research is multifaceted and interdisciplinary, and is concerned with the study of the impacts and effects of information and systems on the behaviour of actors, agents, and organisations (Galliers, Markus & Newell, 2006). Hevner et al. (2004) explain how research in IS is used to create new solutions for both human and organisational capabilities. The solutions are constructs in the forms of models, frameworks, and methods (March & Smith, 1995). In addition, research is conducted for the purposes of innovation and contribution to knowledge. Essentially, research is vested in data and in the analysis of the data.

The analysis of data is aimed to answer research questions and to provide insights into solving problems. A research problem is not necessarily something that is broken. It could be enhancement, demonstration of knowledgeability, revelation of the unforeseen, or empirical confirmation of situations or circumstances. Data analysis is therefore a systematic approach which employs logical reasoning or techniques to describe, evaluate, and interpret data to find meanings that alter the ontological position before the research was conducted, and conclusively contribute to knowledge. Also, analysis is aimed to evaluate and examine sets of data, and to gain insights and an understanding on why and how systems’ components interact, interconnect, interrelate, and influence each other in the process. Substantially, this is often a complex exercise; therefore, it requires symmetric, asymmetric, and isometric logical interventions in achieving the aim and objectives of the research.

IS research

The reliance on IS makes it critical to understand the various ways in which IT solutions can be used to support and enable organisations’ operations. However, the selection, development, and implementation of IT solutions are not as simple as they are sometimes proclaimed, hence the existence of continuous challenges and the subsequent need for research. Owing to their complexities, from both technical and non-technical perspectives, organisations and researchers employ a more innovative approach, such as the use of theories, to underpin IS studies. Also, the use of theories add rigour, which improves reliability, credibility and legitimacy of the study. According to Rose and Scheepers (2001), theories contribute significantly to the development of the IS discipline because they help to gain a better understanding of human interactions with technologies in order to have a meaningful impact in an environment.

The interactions and relationships that occur among actors in the activities of IS are often unpredictable and sometimes unstructured, which makes it subjective in nature. However, subjectivism in a qualitative study does not necessarily make the examining and understanding of IT solutions easy. Qualitative studies in IS primarily focus on actors’ relationships and interactions, from the perspective of subjectivism. Callon (1986) defines an actor as being both a human and a non-human entity. According to Myers and Avison (2002: 70), ‘qualitative research methods were developed in the social sciences to enable researchers to study social and cultural phenomena’. The primary purpose of qualitative research is to understand a phenomenon as it is seen by respondents within contexts and over a period of time. Purposefully, this is achieved by studying the respondents’ views in the context of their natural settings. The outcomes from qualitative research are subject to the meanings which people give to them in real-life situations and contexts (Yin, 2010). However, the meaning which individuals and groups give or associate with events has never been easy for researchers and practitioners, without analysing or interpreting them.

Data analysis is critical in empirical studies, in that it entails the unpacking of data into perspectives (Bryman, 2012). Analysis is a process of making sense of the data that was gathered within context and the relevance of the phenomena being studied. The relevance of data is determined by the research questions and objectives. Increasingly, sociotechnical theories are employed to guide data analysis in an interpretivist study. There are two main components of theory: relevance and context. Relevance is symbolically representative of real-life issues or challenges. Context is deterministic of scope and boundaries. The components are viewed from different elements such as: (1) some theories are more complicated in nature than others; (2) one or a combination of theories can be applied in a research; (3) theories add rigour or quality to research; and (4) theories serve important purposes in that they shape the outcome of research.

The use of theories in IS tradition began around the mid-1990s. Since then, interest from various quarters of IS has grown significantly (Mueller & Urbach, 2013). The theories are employed to facilitate knowledge in the process of extracting findings. In the process, it has helped produce high-quality scholarly contributions (Tsang & Ellsaesser, 2011). Also, it helps to advance an understanding th...

Índice

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• List of figures
• List of tables
• Preface
• Acknowledgements
• 1 Introduction
• 2 Types and sources of qualitative data
• 3 Qualitative data for information systems research
• 4 Activity theory
• 5 Actor-network theory
• 6 Contingency theory
• 7 Diffusion of innovation
• 8 Structuration theory
• 9 Technology acceptance model
• 10 Selecting theories to underpin information systems research
• 11 Activity theory and actor-network theory
• 12 Structuration theory and actor-network theory
• Index