Towards the development of a DSS supporting the integration of crowdsourcing in theory testing: Analytical framework design

Analytical Framework ◽

Research Process ◽

Theory Testing ◽

Analytic Framework ◽

Framework Design ◽

Internet Users ◽

© 2019 Association for Information Systems. All rights reserved. Crowdsourcing can be an adopted strategy for researchers where tasks are distributed to internet users to harness different forms of data, which adds to the reliability and validity of the research process. As theory testing is an essential part of the research process, involving activities that most times needs input from different and diverse participants, the need to consider adopting the crowdsourcing strategy for theory testing is paramount. Adopting a design science paradigm to manage this challenge, we design an analytic framework which comprises of important attributes that need to be considered if crowdsourcing is to be used for any of the theory testing activities. The framework which was justified using sample cases gives us an insight into what attributes make such activity crowdsource-able. The value of this artefact lies in its capacity to help researchers utilize crowdsourcing to their advantage.

Towards the development of a DSS supporting the integration of crowdsourcing in theory testing: Analytical framework design

10.26686/wgtn.12616922 ◽

2020 ◽

Author(s):

I Enwereuzo ◽

Pedro Antunes ◽

David Johnstone

Keyword(s):

Information Systems ◽

Design Science ◽

Analytical Framework ◽

Research Process ◽

Theory Testing ◽

Analytic Framework ◽

Framework Design ◽

Internet Users ◽

© 2019 Association for Information Systems. All rights reserved. Crowdsourcing can be an adopted strategy for researchers where tasks are distributed to internet users to harness different forms of data, which adds to the reliability and validity of the research process. As theory testing is an essential part of the research process, involving activities that most times needs input from different and diverse participants, the need to consider adopting the crowdsourcing strategy for theory testing is paramount. Adopting a design science paradigm to manage this challenge, we design an analytic framework which comprises of important attributes that need to be considered if crowdsourcing is to be used for any of the theory testing activities. The framework which was justified using sample cases gives us an insight into what attributes make such activity crowdsource-able. The value of this artefact lies in its capacity to help researchers utilize crowdsourcing to their advantage.

Towards the development of a DSS supporting the integration of crowdsourcing in theory testing: Analytical framework design

10.26686/wgtn.12616910.v1 ◽

2020 ◽

Author(s):

I Enwereuzo ◽

Pedro Antunes ◽

David Johnstone

Keyword(s):

Information Systems ◽

Design Science ◽

Analytical Framework ◽

Research Process ◽

Theory Testing ◽

Analytic Framework ◽

Framework Design ◽

Internet Users ◽

© 2019 Association for Information Systems. All rights reserved. Crowdsourcing can be an adopted strategy for researchers where tasks are distributed to internet users to harness different forms of data, which adds to the reliability and validity of the research process. As theory testing is an essential part of the research process, involving activities that most times needs input from different and diverse participants, the need to consider adopting the crowdsourcing strategy for theory testing is paramount. Adopting a design science paradigm to manage this challenge, we design an analytic framework which comprises of important attributes that need to be considered if crowdsourcing is to be used for any of the theory testing activities. The framework which was justified using sample cases gives us an insight into what attributes make such activity crowdsource-able. The value of this artefact lies in its capacity to help researchers utilize crowdsourcing to their advantage.

Patterns of testing theory with human subjects: A design science perspective

10.26686/wgtn.12616913.v1 ◽

2020 ◽

Author(s):

I Enwereuzo ◽

Pedro Antunes ◽

David Johnstone

Keyword(s):

Information Systems ◽

Conceptual Framework ◽

Design Science ◽

Human Subjects ◽

Theory Building ◽

Theory Testing ◽

Card Sorting ◽

Evaluation Strategy ◽

Testing Theory ◽

Analyze Data

© 2019 Association for Information Systems. All rights reserved. This paper addresses the challenges of theory testing. Adopting the design science paradigm, we address this challenge by delimiting the line that separates theory building from theory testing by conceptually characterizing its essential aspects: the relationships between humans, organizations and technology, which led to the development of a conceptual framework for theory testing. Practically, the methods, processes, instruments, and tools needed to acquire and analyze data for theory testing is considered, leading to the development of a pattern system. Card sorting was used as an evaluation strategy for the conceptual framework and the pattern model.

What Have We Learned from Almost 30 Years of Research on Causal Mapping? Methodological Lessons and Choices for the Information Systems and Information Technology Communities

Causal Mapping for Research in Information Technology ◽

10.4018/978-1-59140-396-8.ch003 ◽

2005 ◽

pp. 46-80 ◽

Cited By ~ 18

Author(s):

Gerard P. Hodgkinson ◽

Gail P. Clarkson

Keyword(s):

Information Technology ◽

Information Systems ◽

Full Range ◽

Computer Software ◽

Final Analysis ◽

Research Process ◽

Organization Studies ◽

Causal Mapping ◽

Methodological Choices

In this chapter we review major developments that have occurred over the past 30 years or so in the philosophical underpinnings, elicitation, analysis, aggregation and comparison of causal maps (also known as cause maps) across a wide range of domains of application in the fields of management and organization studies, in order to distill vital lessons concerning the strengths and weaknesses of various approaches for the information systems (IS) and information technology (IT) research communities. We offer some general guidelines to aid the would-be user in making methodological choices appropriate to particular contexts of application. The importance of attending to measurement issues in respect to reliability and validity at all stages of the research process, from initial data collection to final analysis and comparison, is highlighted and an accompanying appendix presents an overview of selected computer software systems supporting the full range of activities associated with causal mapping.

Patterns of testing theory with human subjects: A design science perspective

10.26686/wgtn.12616913 ◽

2020 ◽

Author(s):

I Enwereuzo ◽

Pedro Antunes ◽

David Johnstone

Keyword(s):

Information Systems ◽

Conceptual Framework ◽

Design Science ◽

Human Subjects ◽

Theory Building ◽

Theory Testing ◽

Card Sorting ◽

Evaluation Strategy ◽

Testing Theory ◽

Analyze Data

© 2019 Association for Information Systems. All rights reserved. This paper addresses the challenges of theory testing. Adopting the design science paradigm, we address this challenge by delimiting the line that separates theory building from theory testing by conceptually characterizing its essential aspects: the relationships between humans, organizations and technology, which led to the development of a conceptual framework for theory testing. Practically, the methods, processes, instruments, and tools needed to acquire and analyze data for theory testing is considered, leading to the development of a pattern system. Card sorting was used as an evaluation strategy for the conceptual framework and the pattern model.

DEVELOPMENT OF A METHOD FOR DESIGNING INFORMATION SYSTEMS FOR ENERGY COMPANIES

NEWS OF THE NATIONAL ACADEMY OF SCIENCES OF THE REPUBLIC OF KAZAKHSTAN ◽

10.32014/2020.2518-1726.82 ◽

2020 ◽

Vol 5 (333) ◽

pp. 53-57

Author(s):

T.B. Aldongar ◽

◽

F.U. Malikova ◽

G.B. Issayeva ◽

B.R. Absatarova ◽

...

Keyword(s):

Information Systems ◽

Business Processes ◽

Design Research ◽

Graphical Model ◽

Formal Model ◽

Workflow Management ◽

Research Process ◽

Information Models ◽

The Creation ◽

Concept Of Information

The creation of information models requires the use of known methods and the development of new methods of formalizing the pre-design research process. The modeling process consists of four stages: data collection on the object of management - pre-project research; creation of a graphical model of business processes taking place in the enterprise; development of a formal model of business processes; business research by optimizing the formal model. To support the creation of workflow management services and systems, the complex offers methodologies, standards and specialized software that make up the developer's tools. This can be ensured only by modern automated methods based on information systems. It is important that the information collected is structured to meet the needs of potential users and stored in a form that allows the use of modern access technologies. Before discussing the effectiveness of FIM, it should be noted that the basic concept of information itself is still not the same. In a pragmatic way, it is a set of messages in the form of an important document for the system. Information can be evaluated not only by volume, but also by various parameters, the most important of which are: timeliness, relevance, value, aging, accuracy, etc. in addition, the information may be clear, probable and accurate. The methods of its reception and processing are different in each case.

An Insight into the Debates Surrounding the Changing Nature, Scope and Focus of Information Systems Research

SSRN Electronic Journal ◽

10.2139/ssrn.2408809 ◽

2014 ◽

Author(s):

Ibrahim Osman Adam

Keyword(s):

Information Systems ◽

Systems Research ◽

Information Systems Research ◽

Guidelines for Conducting Design Science Research in Information Systems

Communications in Computer and Information Science - ICT Education ◽

10.1007/978-3-030-35629-3_11 ◽

2019 ◽

pp. 163-178

Author(s):

Alta van der Merwe ◽

Aurona Gerber ◽

Hanlie Smuts

Keyword(s):

Information Systems ◽

Design Science ◽

Science Research ◽

Design Science Research

Multi-province epidemiological research using linked administrative data: a case study from Canada.

International Journal for Population Data Science ◽

10.23889/ijpds.v3i3.443 ◽

2018 ◽

Vol 3 (3) ◽

Author(s):

Amanda Leanne Butler ◽

Mark Smith ◽

Wayne Jones ◽

Carol E Adair ◽

Simone Vigod ◽

...

Keyword(s):

Information Systems ◽

Administrative Data ◽

Research Process ◽

Health Data ◽

Provincial Government ◽

Data Systems ◽

Administrative Health Data ◽

Healthcare Data ◽

Research Activities

BackgroundCanada has a publicly-funded universal healthcare system with information systems managed by 13 different provinces and territories. This context creates inconsistencies in data collection and challenges for research or surveillance conducted at the national or multi-jurisdictional level. ObjectiveUsing a recent Canadian research project as a case study, we document the strengths and challenges of using administrative health data in a multi-jurisdictional context. We discuss the implications of using different health information systems and the solutions we adopted to deal with variations. Our goal is to contribute to better understanding of these challenges and the development of a more integrated and harmonized approach to conducting multi-jurisdictional research using administrative data. Context and ModelUsing data from five separate provincial healthcare data systems, we sought to create and report on a set of provincially-comparable mental health and addiction services performance indicators. In this paper, we document the research process, challenges, and solutions. Finally, we conclude by making recommendations for investment in national infrastructure that could help cut costs, broaden scope, and increase use of administrative health data that exists in Canada. ConclusionCanada has an incredible wealth of administrative data that resides in 13 territorial and provincial government systems. Navigating access and improving comparability across these systems has been an ongoing challenge for the past 20 years, but progress is being made. We believe that with some investment, a more harmonized and integrated information network could be developed that supports a broad range of surveillance and research activities with strong policy and program implications.