Table 6. Illustrative examples of theory... | Emerald Publishing

Table 6.

Illustrative examples of theory classification using Gregor’s (2006) taxonomy

Theory type	Primary goal	Example paper (author, year, title)	Why classified this way	Alignment with Gregor (2006)
Analysis (AA)	To describe, structure or classify “what is”	Chenhall, R. H. (2008, AOS)–Accounting for the horizontal organization: A review essay	The paper synthesises and organises prior literature on horizontal organisational forms and associated management control practices. Its contribution is conceptual and classificatory, developing structured understanding and identifying research directions rather than proposing or empirically testing causal hypotheses or predictive relationships	Gregor (2006) defined analysis theory as theory that describes and structures phenomena without specifying causal relationships or predictive propositions
Explanation (EE)	To explain how and why phenomena occur	Mouritsen, J., Hansen, A., and Hansen, C. (2009, AOS)–Short and long translations: Management accounting calculations and innovation management	The study uses actor–network theory to explain how accounting calculations shape innovation processes through organisational “translations.” The objective is interpretive understanding rather than forecasting outcomes	Gregor (2006) characterised explanation theory as providing causal or process understanding of phenomena without necessarily generating testable predictive propositions
Prediction (PP)	To forecast outcomes or relationships	Allee, K.D., Deangelis, MD and Moon, J. (2018, JAR) – Disclosure “Scriptability”	While it has explanatory elements, its primary contribution is a metric designed to forecast the speed of market reaction to digital disclosures. The study develops a novel metric (“scriptability”) and evaluates its ability to predict variation in market reaction speed and information dissemination. Its contribution centres on improving predictive capability rather than developing rich causal mechanisms	Gregor (2006) described prediction theory as theory that states what will be and supports forecasting through testable propositions, even where justificatory explanation is limited
Explanation and prediction (EP)	To explain causal relationships and test them empirically	Banker, R. D., Bardhan, I. R., and Chen, T. (2008, AOS)–The role of manufacturing practices in mediating the impact of activity-based costing on plant performance	The paper develops a mediation model explaining how manufacturing practices influence the effectiveness of ABC systems and empirically tests the proposed relationships using plant-level data	Gregor (2006) defined explanation-and-prediction theory as providing causal explanation alongside empirically testable predictions about observed outcomes
Design and action (DA)	To prescribe how artefacts, practices or systems can be constructed or implemented	Wouters, M., and Wilderom, C. (2008, AOS)–Developing performance-measurement systems as enabling formalization	The study examines prescriptive design principles for the development and implementation of performance-measurement systems. Drawing on a longitudinal action-research case, it specifies how experience-based development, experimentation with measures, employee professionalism and system transparency can be used to construct performance-measurement systems that function as enabling rather than coercive forms of control. The contribution lies in articulating how such systems should be designed and developed in practice, rather than merely explaining or predicting their effects	Gregor (2006) defined design-and-action theory as prescriptive knowledge that explains how artefacts, methods or systems can be constructed. This study aligns with that definition by offering actionable principles for designing and developing performance-measurement systems as organisational artefacts, specifying how design and implementation processes should be structured to achieve enabling outcomes

Theory type	Primary goal	Example paper (author, year, title)	Why classified this way	Alignment with Gregor (2006)
Analysis (AA)	To describe, structure or classify “what is”	Chenhall, R. H. (2008, AOS)–Accounting for the horizontal organization: A review essay	The paper synthesises and organises prior literature on horizontal organisational forms and associated management control practices. Its contribution is conceptual and classificatory, developing structured understanding and identifying research directions rather than proposing or empirically testing causal hypotheses or predictive relationships	Gregor (2006) defined analysis theory as theory that describes and structures phenomena without specifying causal relationships or predictive propositions
Explanation (EE)	To explain how and why phenomena occur	Mouritsen, J., Hansen, A., and Hansen, C. (2009, AOS)–Short and long translations: Management accounting calculations and innovation management	The study uses actor–network theory to explain how accounting calculations shape innovation processes through organisational “translations.” The objective is interpretive understanding rather than forecasting outcomes	Gregor (2006) characterised explanation theory as providing causal or process understanding of phenomena without necessarily generating testable predictive propositions
Prediction (PP)	To forecast outcomes or relationships	Allee, K.D., Deangelis, MD and Moon, J. (2018, JAR) – Disclosure “Scriptability”	While it has explanatory elements, its primary contribution is a metric designed to forecast the speed of market reaction to digital disclosures. The study develops a novel metric (“scriptability”) and evaluates its ability to predict variation in market reaction speed and information dissemination. Its contribution centres on improving predictive capability rather than developing rich causal mechanisms	Gregor (2006) described prediction theory as theory that states what will be and supports forecasting through testable propositions, even where justificatory explanation is limited
Explanation and prediction (EP)	To explain causal relationships and test them empirically	Banker, R. D., Bardhan, I. R., and Chen, T. (2008, AOS)–The role of manufacturing practices in mediating the impact of activity-based costing on plant performance	The paper develops a mediation model explaining how manufacturing practices influence the effectiveness of ABC systems and empirically tests the proposed relationships using plant-level data	Gregor (2006) defined explanation-and-prediction theory as providing causal explanation alongside empirically testable predictions about observed outcomes
Design and action (DA)	To prescribe how artefacts, practices or systems can be constructed or implemented	Wouters, M., and Wilderom, C. (2008, AOS)–Developing performance-measurement systems as enabling formalization	The study examines prescriptive design principles for the development and implementation of performance-measurement systems. Drawing on a longitudinal action-research case, it specifies how experience-based development, experimentation with measures, employee professionalism and system transparency can be used to construct performance-measurement systems that function as enabling rather than coercive forms of control. The contribution lies in articulating how such systems should be designed and developed in practice, rather than merely explaining or predicting their effects	Gregor (2006) defined design-and-action theory as prescriptive knowledge that explains how artefacts, methods or systems can be constructed. This study aligns with that definition by offering actionable principles for designing and developing performance-measurement systems as organisational artefacts, specifying how design and implementation processes should be structured to achieve enabling outcomes

Source(s): Authors’ own creation