Information System Development: Research Approaches

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Table of Contents

Introduction
Research approaches used in Information systems
Contributions and findings
Similarities and differences of research methods
Implications and suggestions for future research
References

Introduction

The extent to which an organization can be effective is often pre-determined by a myriad of factors. For instance, the characteristic in terms of how the given organization operates is an important factor to bear in mind. Also, the model used to implement policies and strategies devised by the organization as well as how the human resource pool organized is yet another factor that may determine the success level of an organization. All these are vital in achieving an organization’s purpose in production.

Besides, the running of an organization and achieving its purposes requires knowledge in the use of information technology and its management. To acquire this knowledge, some paradigms can be applied as much as they may be different altogether. These two paradigms are design science and behavioral science. Due to this, researchers have come up with various ways on how to acquire them for use in managerial and organizational purposes. This essay will examine the research approaches used in information system development within the organization and the implications.

Research approaches used in Information systems

Organizations and information systems supporting them are made up of work systems, technologies, structures, and people. Most of the design work is done by the managers and the IS practitioners. Making information system effective requires proper strategy with a design activity that is extensive and covers organizational design and organizational infrastructure (Robey & Boudreau, 1999). The need to acquire knowledge of information systems has caused the researchers to adopt two distinct paradigms to come up with a way of developing an information system within an organization (Hevner et al., 2004).

One of the approaches that have been used in information systems research is the behavioral science paradigm. This approach applies research methods based on natural science to justify and develop on other theories such as principles and laws theories. These theories explain human and organizational phenomena and assist practitioners and researchers by informing them of the interaction that needs to be managed among organizations, technology and people (Lapointe & Rivard, 2005).

These interactions in an organization include improving the efficiency and effectiveness of the information system. It is important to note that the phenomena that the principles and laws theories explain surround the use of information systems, its management, implementation, design, and analysis (Mathew, 2011). Moreover, human interfaces are greatly affected by these theories that are part and parcel of functional capabilities and information systems needed in any organization. Also, design decisions impact on the behavioral science paradigm theories made according to the system development methodology (Robey & Boudreau, 1999).

On the other hand, design science has been used in the IS research cycle. It provides solutions to identified organizational problems through evaluation and creation of IT artifacts. This problem-solving paradigm, besides deriving its base from engineering and the science of the artificial, creates innovations that enable efficient and effective accomplishment of the information system (Hevner et al., 2004).

This is achieved through management, design, implementation, and analysis of products, technical capabilities, practices and ideas (Mathew, 2011). The design science paradigm artifacts also work on the natural laws theory and behavioral theory. The artifacts used to address the IS problems include instantiations, methods, models, and constructs. The latter is used to provide language communication for solutions if IS problems while model represents the solution space, design problem and the real world solution (Lapointe & Rivard, 2005).

There are quite several methods that are imperative when exploring design science. Firstly, solutions can be sought through offering informal guidance or through the use of texts. A more complicated approach may entail the use of mathematical algorithms. On the other hand, the implementation of methods, models or constructs in a working system is carried out through instantiations (Robey & Boudreau, 1999). The intended purpose and sustainability of an artifact is concretely assessed by the instantiations. Also, besides demonstrating feasibility, they help researchers to know how the use of artifacts affects the world.

The research approaches used in evaluating IS works on a conceptual framework. This framework aids in executing, understanding and combining design science paradigms and the behavioral science paradigms (Robey & Boudreau, 1999). According to it, IS problem space is defined in its environment and this becomes a phenomenon of interest towards a solution. In the IS research framework, such an environment composed of planned or existing technologies, organizations and people (Hevner et al., 2004). The environment also assists in defining the various information perceptions valued within a given workplace.

Additionally, goals, tasks, and opportunities are well defined under this category. It is important to note that these perceptions in an organization are controlled by the characteristics of people, their capabilities and roles while the assessment and evaluation of the needs within an organization are done within the existing business process, culture and organizational strategies (Beath & Orlikowski, 1994). The researcher perceives the needs within an organization together with development capabilities, communication architectures, applications, and the existing technology infrastructure as the problems and addresses these needs through framing a relevant research activity (Robey & Boudreau, 1999).

The research approach necessary to provide a solution to the articulated business IS needs is in two complementary phases- design science and behavioral science (Lapointe & Rivard, 2005). The goals or objectives of the two research approaches- design science and behavioral science- are utility and truth respectively and these are inseparable (Robey & Boudreau, 1999). This is true in the sense that utility informs theory while truth informs design.

The foundational theories that have been provided by results from prior IS research including instantiations, methods, models, constructs, instruments, and framework (Robey & Boudreau, 1999). It is worth observing that the phase of evaluation and justification guidelines is provided by methodologies (Beath & Orlikowski, 1994). Therefore, the two components forming the knowledge base are necessary to achieve rigor. While on one hand empirical analysis techniques and data collection are methodology methods in behavioral science, the methodology applied in evaluating the effectiveness and quality of artifacts in design science are computational and mathematical methods (Mathew, 2011).

The technology-based solutions offered by the two approaches when well developed and implemented are vital to the solution of the IS problems (Hevner et al., 2004). Design science adopts a different approach to solving organizational IS problems through innovative construction of artifacts (Robey & Boudreau, 1999). Researchers have argued that design science theory overcomes IS challenges through combining people-based artifacts, organization-based artifacts, and technology-based artifacts. People-based artifacts include consensus building, training and so on while organizational artifacts include social systems, reporting relationships, compensation and structure (Beath & Orlikowski, 1994). Additionally, technology-based artifacts include interfaces, technical capabilities, practices, representations, and systems conceptualizations (Robey & Boudreau, 1999).

Contributions and findings

The findings from the two paradigms require the application of routine design. It offers solutions to organizational problems through the existing knowledge base such as using artifacts such as instantiations, methods, constructs, and models, and constructing a financial information system (Hevner et al., 2004). Additionally, the findings from the IS research on better radical organizational change through determinants or enablers such as the advanced information technology lacks consistency in its deterministic logic implicit (Lapointe & Rivard, 2005).

Different studies on the research findings have proposed the use of the logic of opposition to counter contradictory empirical findings related to information technology and its organizational consequences. A logic of opposition focuses on opposing forces in explaining organizational change and factors that promote and oppose the social changes (Robey & Boudreau, 1999).

Furthermore, the findings indicate that there is a need to combine both the logic of opposition and the logic of determination to bring about the desired IS outcome. In logics of determination, a set of predictor variables causes variations of consequences (Lapointe & Rivard, 2005). These consequences result in a change. Both logics-opposition and deterministic- determine a wider range of outcomes in an organization and theoretically offers a model that accounts for the variables and their orderly relationships (Beath & Orlikowski, 1994). The contradictory findings are evidence of flawed research findings rather than seeking consistency and tackling the issues of empirical contradiction in organizational IS (Hevner et al., 2004). The findings of the research offer a strategy that other than having many assumptions, neglect what is essential in explaining variance in outcomes such as interaction effects and neglected variables.

Similarities and differences of research methods

The research methods carried out on the organizational improvement and solving of information technology problems bear the similarity of the researchers seeking to explain the difficulties and lack of success the inefficient methods of solving IS problems have on organizations (Mathew, 2011). The research methodologies given of addressing issues like inappropriate coordination mechanisms and inadequate resources centers around finding solutions through design science and behavioral science (Hevner et al., 2004). The prescription involves the improvements of the artifacts as well as developing new methodologies (Robey & Boudreau, 1999).

On the other hand, while some researchers support the theories of science design and behavior design, others differ, criticize and offer other theories like organizational learning theory, institutional theory, organizational culture, and organizational politics (Beath & Orlikowski, 1994). In the aforementioned theories, the researchers argue that they are useful in analyzing the roles of IS bringing out desired changes through application of multiple interpretations, process research, using opposing hypotheses statement and through empirical identification of opposing forces (Mathew, 2011).

Implications and suggestions for future research

To sum up, it is important to look at the implications and suggest how to make future research on related issues effectively. Research on IS should be able to provide practical solutions to problems affecting information systems in an organization. Several research methods should be applied to come up with the desired and appropriate method of dealing with IS issues (Mathew, 2011). Furthermore, there is a need to improve on the already existing theories and practical methods in order to enhance the efficiency and the effectiveness of the information systems, implementation, design, analysis, technical capabilities, and practices. This will make future research efforts easy to apply, more practical and productive.

References

Beath, C.M. & Orlikowski, W.J. (1994): The Contradictory Structure Of Systems Development Methodologies: Deconstructing The IS-User Relationship. Information Systems Research, 5(4),:350-377.

Hevner, A.R. et al. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1): 75-105.

Lapointe, L. & Rivard, S. (2005). A Multilevel Model of Resistance to Information Technology Implementation. MIS Quarterly. 29(3): 461-492.

Mathew, N. (2011). Research in action. Baylor Business Review, 29(2): 50-51. Retrieved May 21, 2011, from ABI/INFORM Global.

Robey, D. & Boudreau, M.C. (1999): Accounting For the Contradictory Organizational Consequences of Information Technology: Theoretical Directions and Methodological Implications. Information Systems Research, 10(2): 167-186.

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