Aken - Management Research - Design Science as a Prescriptive-driven Research

What is the most important contribution of this paper?

The most important contribution of this paper is the proposal of a new research paradigm/approach for management: the design science. It’s purpose is to bridge the classic academic descriptive-based research (theory, often not well applicable) and real practice in the real world (business problems).

Van Aken introduces a term “Management Theory”, which is derived from design sciences (like medicine or engineering) and which focuses on developing knowledge to solve construction or improvement problems.

Core product of this new paradigm are technological rules (“chunks of general knowledge”) that link actions X to desired outputs Y in specific context/environment Z.

• they have to be field-tested and properly grounded

Last part of the paper introduces the rigorous clinical research strategy to ensure that the technological rules and artefacts are scientifically valid. This is done by:

• multiple case studies
• alpha and beta testing

So the paper argues that the prescription-driven research could be both academically respectable and also be useful to professionals in real life.

• the utilization problem in academic management research is that even though the research is scientifically rigorous, it is often not well applicable in the real management world - thus it is often not used practically
  • it’s because the academic management research is primarily “description-driven”, meaning it is following the paradigm of explanatory sciences (like biology, physics or sociology)
    • also described as Mode 1 knowledge production
  • it’s focused on understanding and explaining the problem, not solving it
• according to Aken, this problem could be mitigated by a collaboration of academic management research and “prescription-driven” research in the paradigm of design sciences (engineering) - also called Mode 2 knowledge production
  • it is aimed on developing knowledge to solve real-world problems

Two types of theory

• Organization theory - results from description-driven research
  • for conceptual use and understanding
• Management theory - results from prescription-driven research
  • designing solutions for management problems
• the goal should be to combine these
  • the “technical part” should provide rigorous testing and grounding to be “more academic”
  • the “academical part” should be more open to let technological rules in and focus on providing valid and reliable knowledge that could be used on solving real-world business issues

Key concepts

Field-tested and grounded technological rules

• what is a technological rule?
  • it comes from Management theory and it’s defined as a “chunk of general knowledge” that links a specific action or artefact to desired outcome
  • “if you want to achieve Y in situation Z, then perform action X” ← technological rule is the “X”
• technological rules have to be field-tested
  • this is done with clinical researchs and multiple case studies
  • application of the reflective cycle: test the rule in the environment, see the reaction and refine the rule based on the real-world results
  • A testing = the creator of the rule does the testing in it’s own environment and context (e.g. a CEO in his company)
  • B testing = the independent third parties (other companies, researchers etc.) are testing the rule in different environments
    • the B testing is more important, it verifies the robustness and identifies possible blockers
    • it also tests the translation, how well can the rule be adapted to new environments and settings
    • it also reveals the flaws that were overlooked or underestimated by the creator
• technological rules should be grounded
  • = supported by scientific knowledge explaining why it works
  • management rules are often grounded in generative mechanisms, these could be:
    • material factors (like physical constraints in the factory)
    • immaterial, sense-making factors (communication styles, rules etc.)
  • grounding helps to demonstrate the rules, to understand them, to communicate them to interested people etc. making it easier to adapt
    • it is also possible to transform the rule and adapt it to a different context (by knowing, which mechanisms “drive” the success and which mechanisms “block” it)
  • grounding also explains, why is the technological rule/action needed, why is it successful
  • grounding also helps to achieve academic respectability
    • it distinguish rigorous methods from popular management literature with general advice with no scientific background

Heuristics vs. algorithms

• these are two types of prescriptions in the Management Theory
• algorithms
  • they work like recipes, provide high-specific information and have quantitative format
  • they can be proven through deterministic or statistical generalization (thanks to their precision)
  • they also need highly predictable environments and stable inputs, so they are not used that much in general management
• heuristics
  • most technological rules are heuristics in nature
  • heuristics are not that precise, they involve a “indeterminate nature”, like “something like action X will help”
  • they cannot be proven easily - need for case studies and other real-life testing strategies
  • they are rather in the form of “general rules”, which have to be translated and adapted to the specific, unique problem
    • using creativity, experience and understanding of the local environment

Clinical research and the reflective cycle

• testing in clinical research is the primary strategy for developing knowledge
  • it involves testing the technological rules and artefacts in the environment of intended use, so we learn how the rule/artefact interacts with the real world
  • explanatory sciences often use laboratories and other closed systems
• core mechanism is: multiple case study using the reflective cycle to build knowledge:
  • 1. choosing a case - a specific problem in specific environment to test
  • 2. planning and intervention - implement an action or design based on the problem-solving cycle (diagnosis, design and execution)
  • 3. reflection - analyse the results of the intervention
  • 4. development - refining the design knowledge or technological rule based on the results, so it could be tested in the next case
• this iterative cycle allows the researchers to gain application-domain knowledge