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

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.

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

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.

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

2020 ◽  
Author(s):  
I Enwereuzo ◽  
Pedro Antunes ◽  
David Johnstone
Keyword(s):  
Information Systems ◽  
Design Science ◽  
Reliability And Validity ◽  
Analytical Framework ◽  
Research Process ◽  
Theory Testing ◽  
Analytic Framework ◽  
Framework Design ◽  
Internet Users ◽  
Insight Into

© 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.

scholarly journals An exploratory design science study on theory testing using crowdsourcing

2021 ◽  
Author(s):  
◽  
Ijay Ushaka
Keyword(s):  
Conceptual Framework ◽  
Design Science ◽  
Large Data ◽  
Science Research ◽  
Design Science Research ◽  
Theory Testing ◽  
Data Sets ◽  
Decision Tool ◽  
Research Activities ◽  
Principles Of Design

<p>Theory in Information Systems (IS) is very important to the development of the field. Theory building, and theory testing seeks to accumulate knowledge about the relationships between people and technology. Testing theory can be difficult to accomplish, especially when it involves humans, a diversity of methods and sources, multiple experiments, large data sets, and careful tuning of conditions and instruments. Crowdsourcing is a strategy supporting the distribution of activities to crowd workers, which suggests that it may be used to support theory testing.  This exploratory study seeks to analyse the adoption of crowdsourcing in theory testing, and to develop guidance for researchers to instantiate the strategy in their research projects.  The study adopts the design science research paradigm to explore incorporating the crowdsourcing strategy in theory testing, and to evaluate its viability and utility. According to the principles of design science research, the study is structured around the construction of several interconnected IS artefacts: 1) a conceptual framework articulating the main principles of theory testing; 2) a pattern model of theory testing, which codifies existing research approaches to theory testing; and 3) a decision tool, which codifies guidelines for researchers making decisions on which research activities to crowdsource.  In order to build the conceptual framework and pattern model, the study conducts a systematic review of theory testing in the IS domain. Both the conceptual framework and pattern model are then operationalized in the decision tool. The utility of the various artefacts is then assessed with the participation of research practitioners.  This study is relevant because it synthesizes knowledge about theory testing, builds innovative artefacts supporting the adoption of crowdsourcing in theory testing, helps academic researchers understanding the theory testing process, and enables them to adopt crowdsourcing for theory testing.</p>

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

2020 ◽  
Author(s):  
I Enwereuzo ◽  
Pedro Antunes ◽  
David Johnstone
Keyword(s):  
Information Systems ◽  
Design Science ◽  
Reliability And Validity ◽  
Analytical Framework ◽  
Research Process ◽  
Theory Testing ◽  
Analytic Framework ◽  
Framework Design ◽  
Internet Users ◽  
Insight Into

© 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.

scholarly journals On the adoption of crowdsourcing for theory testing

2020 ◽  
Author(s):  
E Ijeoma ◽  
Pedro Antunes ◽  
David Johnstone ◽  
M Tate
Keyword(s):  
Systematic Review ◽  
Information Systems ◽  
Technical Change ◽  
Data Gathering ◽  
Theory Building ◽  
Theory Testing ◽  
European Conference

© 26th European Conference on Information Systems: Beyond Digitization - Facets of Socio-Technical Change, ECIS 2018. All Rights Reserved. This paper examines the possibilities of using the crowdsourcing strategy for theory testing. We first analyse the relationships between theory building and theory testing activities. Then, based on a systematic review of 248 papers published in MISQ, we characterise the intents and pattern systems of activities that have been used for theory testing. Finally, we ascertain which activities can be crowdsourced or not and pinpoint a set of pathways supporting partial and total crowdsourcing. The obtained results show that a large number of activities related to data gathering can be crowdsourced, and that a number of intents have viable pathways supporting partial crowdsourcing.

scholarly journals On the adoption of crowdsourcing for theory testing

2020 ◽  
Author(s):  
E Ijeoma ◽  
Pedro Antunes ◽  
David Johnstone ◽  
M Tate
Keyword(s):  
Systematic Review ◽  
Information Systems ◽  
Technical Change ◽  
Data Gathering ◽  
Theory Building ◽  
Theory Testing ◽  
European Conference

© 26th European Conference on Information Systems: Beyond Digitization - Facets of Socio-Technical Change, ECIS 2018. All Rights Reserved. This paper examines the possibilities of using the crowdsourcing strategy for theory testing. We first analyse the relationships between theory building and theory testing activities. Then, based on a systematic review of 248 papers published in MISQ, we characterise the intents and pattern systems of activities that have been used for theory testing. Finally, we ascertain which activities can be crowdsourced or not and pinpoint a set of pathways supporting partial and total crowdsourcing. The obtained results show that a large number of activities related to data gathering can be crowdsourced, and that a number of intents have viable pathways supporting partial crowdsourcing.

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

2020 ◽  
Author(s):  
I Enwereuzo ◽  
Pedro Antunes ◽  
David Johnstone
Keyword(s):  
Information Systems ◽  
Design Science ◽  
Reliability And Validity ◽  
Analytical Framework ◽  
Research Process ◽  
Theory Testing ◽  
Analytic Framework ◽  
Framework Design ◽  
Internet Users ◽  
Insight Into

© 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.

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

2020 ◽  
Author(s):  
I Enwereuzo ◽  
Pedro Antunes ◽  
David Johnstone
Keyword(s):  
Information Systems ◽  
Design Science ◽  
Reliability And Validity ◽  
Analytical Framework ◽  
Research Process ◽  
Theory Testing ◽  
Analytic Framework ◽  
Framework Design ◽  
Internet Users ◽  
Insight Into

© 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.

scholarly journals An exploratory design science study on theory testing using crowdsourcing

2021 ◽  
Author(s):  
◽  
Ijay Ushaka
Keyword(s):  
Conceptual Framework ◽  
Design Science ◽  
Large Data ◽  
Science Research ◽  
Design Science Research ◽  
Theory Testing ◽  
Data Sets ◽  
Decision Tool ◽  
Research Activities ◽  
Principles Of Design

<p>Theory in Information Systems (IS) is very important to the development of the field. Theory building, and theory testing seeks to accumulate knowledge about the relationships between people and technology. Testing theory can be difficult to accomplish, especially when it involves humans, a diversity of methods and sources, multiple experiments, large data sets, and careful tuning of conditions and instruments. Crowdsourcing is a strategy supporting the distribution of activities to crowd workers, which suggests that it may be used to support theory testing.  This exploratory study seeks to analyse the adoption of crowdsourcing in theory testing, and to develop guidance for researchers to instantiate the strategy in their research projects.  The study adopts the design science research paradigm to explore incorporating the crowdsourcing strategy in theory testing, and to evaluate its viability and utility. According to the principles of design science research, the study is structured around the construction of several interconnected IS artefacts: 1) a conceptual framework articulating the main principles of theory testing; 2) a pattern model of theory testing, which codifies existing research approaches to theory testing; and 3) a decision tool, which codifies guidelines for researchers making decisions on which research activities to crowdsource.  In order to build the conceptual framework and pattern model, the study conducts a systematic review of theory testing in the IS domain. Both the conceptual framework and pattern model are then operationalized in the decision tool. The utility of the various artefacts is then assessed with the participation of research practitioners.  This study is relevant because it synthesizes knowledge about theory testing, builds innovative artefacts supporting the adoption of crowdsourcing in theory testing, helps academic researchers understanding the theory testing process, and enables them to adopt crowdsourcing for theory testing.</p>

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