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Research: Why? What? How?

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Why do we perform research?
What exactly is research?
How to perform research?
How to perform natural science?
How to perform design science?
How to design research?

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Research: Why? What? How?

  1. 1. 1/27 | © www.janclaes.info Why? What? How? Research
  2. 2. 2/27 | © www.janclaes.info RESEARCH WHY DO WE PERFORM
  3. 3. 3/27 | © www.janclaes.info Why do we perform research? To explore To confirmTo explain Early stage Mid stage Late stage Quantitative statistics Application of reference theory Direct observation Expert interview ..research stage ..method Hypotheses Explanations Proof..result Typical..
  4. 4. 4/27 | © www.janclaes.info Why do we perform research? To satisfy human curiosity To advance human race Origin Goal Outcome Activity Cognitive advantage Science category Questions Answers Theories Research Learning Natural science Problems Solutions Artifacts Engineering Problem solving Design science
  5. 5. 5/27 | © www.janclaes.info SUMMARY SUMMARY Why do we perform research? To explore To confirmTo explain Hypotheses Explanations Proof To satisfy human curiosity To advance human race Knowledge building Research Artifact building Engineering
  6. 6. 6/27 | © www.janclaes.info RESEARCH WHAT EXACTLY IS
  7. 7. 7/27 | © www.janclaes.info Research(er) activities What exactly is research? SYSTEMATIC KNOWLEDGE BUILDING RESEARCH + = CREATIVE KNOWLEDGE BUILDING EXPLORATION + = SYSTEMATIC ARTIFACT BUILDING DEVELOPMENT + = CREATIVE ARTIFACT BUILDING DESIGN + =
  8. 8. 8/27 | © www.janclaes.info What exactly is research? Difference between Explorative research Exploration Systematic Hypotheses (Full) research paper Journal or conference Creative Ideas Idea paper Conference
  9. 9. 9/27 | © www.janclaes.info SUMMARY SUMMARY What exactly is research? Knowledge building Artifact building Research Exploration Development Design Systematic Creative
  10. 10. 10/27 | © www.janclaes.info RESEARCH HOW TO PERFORM
  11. 11. 11/27 | © www.janclaes.info How to perform research? Deduction Abduction Context + Result  Explanation Induction Context + Result  Rule Rule + Context  Result Effect Mechanism Cause PossibilityProbabilityCertainty Logical reasoning Typically used to reveal Result Inference from general theories Generalization of observations Search for best possible explanation Definition All elephants are grey Lucy is an elephant  Lucy is grey 40 swans were observed All of them are white  All swans are white The tiger cage is empty The cage door is open  The tiger escaped Example
  12. 12. 12/27 | © www.janclaes.info Artifact buildingKnowledge building Artifact buildingKnowledge building How to perform research? Engineering cycle Research cycle Nested cycles of research activities Problem investigation Problem investigation Results evaluation Solution evaluation Design evaluation Design evaluation Research execution Research design Solution implementation Solution design Problem investigation Problem investigation Results evaluation Solution evaluation Design evaluation Design evaluation
  13. 13. 13/27 | © www.janclaes.info How to perform research? Work soon on bigger circles = Make many assumptions Work first on smaller circles = Slow progress never-ending set of nested circles = RESEARCH
  14. 14. 14/27 | © www.janclaes.info SUMMARY SUMMARY Why do we perform research? Knowledge building Artifact building Problem investigation Research design Problem investigation Solution design Design evaluation Research execution Design evaluation Solution implementation Results evaluation Solution evaluation R R R R R R
  15. 15. 15/27 | © www.janclaes.info NATURAL SCIENCE HOW TO PERFORM
  16. 16. 16/27 | © www.janclaes.info How to perform natural science? Descriptive theory Explanatory theory Predictive theory Whole theory Prescriptive theory Which types of theories exist?
  17. 17. 17/27 | © www.janclaes.info How to perform natural science? How to evaluate theories? Usability Falsifiability Novelty Parsimony Consistency Plausibility Actual use is only measurable on a longer term Measurable and testable (= internal validity) Novel relations or existing relations in a novel way Using small number of constructs and associations Applies on multiple datasets (train set versus test set) Accurate and profound description Credibility Transferability Not conflicting with other theories Applies in different contexts (= external validity)
  18. 18. 18/27 | © www.janclaes.info DESIGN SCIENCE HOW TO PERFORM
  19. 19. 19/27 | © www.janclaes.info How to perform design science? Which types of artifacts exist? Constructs Models Methods Instantiations Symbols, languages, terminology, definitions, measures Keyword: Concepts Abstractions, representations, frameworks Keyword: Relations Approaches, strategies, algorithms Keyword: Order Prototypes, software implementations Keyword: Practical
  20. 20. 20/27 | © www.janclaes.info Construct validity Extent to which is measured what is claimed to be measured How to perform design science? How to evaluate constructs? – Measure validation Validity Content validity Criteria validity Reliability Computability Measure (only) measures what it is supposed to measure Extent to which all facets of the construct are represented Extent to which a measure is related to an outcome Consistency of measurements over time Calculable in a finite time and preferably quickly Ease of implementation Intuitiveness Computation implementation has reasonable difficulty Easy to understand and interpret the definition Independence Independence to other related properties
  21. 21. 21/27 | © www.janclaes.info How to perform design science? How to evaluate models? – The physics of notations Visual expressiveness Perceptual discriminability Graphic economy Dual coding Semiotic clarity Semantic transparency Use: shape, size, color, brightness, orientation, texture, horizontal position, vertical position Visual distance matches concept difference Maximum 6-7 values for each of the graphical variables Combine visual and textual information Exactly one symbol for one concept and vice versa Intuitiveness via analogies and standards Complexity management Cognitive integration Modularization and hierarchical structuring Clear links between different visualizations Cognitive fit Maximize fit with task and executor
  22. 22. 22/27 | © www.janclaes.info How to perform design science? How to evaluate methods? – Method Evaluation Model Actual effectiveness Actual efficiency Perceived usefulness Perceived ease of use Intention to use Actual usage How to evaluate instantiations? – Technology Acceptance Model
  23. 23. 23/27 | © www.janclaes.info SUMMARY SUMMARY How to perform science? Knowledge building Artifact building Descriptive theory Explanatory theory Constructs (concepts) Models (relations) Predictive theory Whole theory Methods (order) Instantiations (practical) Prescriptive theory
  24. 24. 24/27 | © www.janclaes.info RESEARCH HOW TO DESIGN
  25. 25. 25/27 | © www.janclaes.info How to design research? Research gap Literature gap Research objectives Research goal What is missing? Difference between what could and what does exist What is the problem? Why is this (still) a problem? What do you want to do? What general state do you aim to achieve? How do you want to do this? What measurable state(s) do you aim to achieve? Research questions What do you want to learn from this? What is the knowledge contribution?
  26. 26. 26/27 | © www.janclaes.info How to design research? Maximize focus Computer, software, notes, data, lighting, food & drinks Few days in a row, loading & offloading Maximize inspiration Conversations & activities, stimulating places, pen & paper, ambiance Clean desk, music or silence No email, visitors, phone calls & texts, social media Creative tasksHard work Goal All tools ready No distraction Long enough
  27. 27. 27/27 | © www.janclaes.info More at janclaes.info/resources Thank you!
  28. 28. 28/27 | © www.janclaes.info References Slide 4  March ST, Smith GF (1995) Design and natural science research on information technology. Decis. Support Syst. 15(4):251–266. Slide 12  Wieringa RJ, Heerkens JMG (2006) The methodological soundness of requirements engineering papers: a conceptual framework and two case studies. Requir. Eng. 11(4):295–307. Slide 13  Wieringa RJ (2009) Design science as nested problem solving. Proc. 4th Int. Conf. Des. Sci. Res. Inf. Syst. Technol. - DESRIST ’09. (ACM Press, New York, New York, USA). Slide 16  Gregor S (2006) The nature of theory in information systems. MIS Q. 30(3):611–642.  Example descriptive theory: Claes J, Vanderfeesten I, Reijers HA, Pinggera J, Weidlich M, Zugal S, Fahland D, Weber B, Mendling J, Poels G (2012) Tying process model quality to the modeling process: The impact of structuring, movement, and speed. Barros A, Gal A, Kindler E, eds. Proc. 10th Int. Conf. Bus. Process Manag. (BPM ’12), Tallinn, Est. Sept. 3, 2012. (LNCS 7481, Springer), 33–48.  Example explanatory theory: Claes J, Vanderfeesten I, Gailly F, Grefen P, Poels G (2015) The Structured Process Modeling Theory (SPMT) - A cognitive view on why and how modelers benefit from structuring the process of process modeling. Inf. Syst. Front. 17(6):1401–1425.  Example prescriptive theory: Claes J, Vanderfeesten I, Gailly F, Grefen P, Poels G (2017) Towards a structured process modeling method: Building the prescriptive modeling theory. Proc. BPM 2016 Conf. Work. (LNBIP 281, Springer), 168–179.  (Example method): Claes J, Vanderfeesten I, Gailly F, Grefen P, Poels G (2017) The Structured Process Modeling Method (SPMM) what is the best way for me to construct a process model? Decis. Support Syst. (in press) Slide 17  Gregor S (2006) The nature of theory in information systems. MIS Q. 30(3):611–642.  Grover V, Lyytinen K, Srinivasan A, Tan BCY (2008) Contributing to rigorous and forward thinking explanatory theory. J. Assoc. Inf. Syst. 9(2):40–47.  Weber R (2012) Evaluating and developing theories in the information systems discipline. J. Assoc. Inf. Syst. 13(1):1–31.  Weick KE (1989) Theory construction as disciplined imagination. Acad. Manag. Rev. 14(4):516–531.  Example: Claes J, Vanderfeesten I, Gailly F, Grefen P, Poels G (2015) The Structured Process Modeling Theory (SPMT) - A cognitive view on why and how modelers benefit from structuring the process of process modeling. Inf. Syst. Front. 17(6):1401–1425. Slide 19  Hevner ARR, March ST, Park J, Ram S (2004) Design science in information systems research. MIS Q. 28(1):75–105.  Slide 20  Smith SM, Albaum GS (2005) Fundamentals of Marketing Research (SAGE).  Polančič G, Cegnar B (2016) Complexity metrics for process models - A systematic literature review. Comput. Stand. Interfaces 51(July 2016):104–117. Slide 21  Moody DL (2009) The “physics” of notations: Toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Softw. Eng. 35(6):756–779.  Example: Claes J, Vanderfeesten I, Pinggera J, Reijers HA, Weber B, Poels G (2015) A visual analysis of the process of process modeling. Inf. Syst. E-bus. Manag. 13(1):147– 190. Slide 22  Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3):319–340.  Moody DL (2003) The method evaluation model: A theoretical model for validating information systems design methods. In: Ciborra CU, Mercurio R, Marco M de, Martinez M, Carignani A, eds. Proc. 11th Eur. Conf. Inf. Syst. (ECIS ’03). (AIS Electronic Library, Naples, Italy), 1327–1336.  Example: Claes J, Poels G (2014) Merging Event Logs for Process Mining: A Rule Based Merging Method and Rule Suggestion Algorithm. Expert Syst. Appl. 41(16):7291– 7306.

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