Abstract
Engineering is the “discipline of the particular” par excellence. Engineers develop heuristic knowledge to build action-oriented solutions for specific situations. This type of knowledge is concrete, contingent, goal-oriented, particular, temporal, contextual, uncertain, value-laden, and task-specific, and as such it challenges the traditional ideals of scientific knowledge, which is typically assumed to be abstract, unconditional, disinterested, universal, timeless, utopian, certain, value-neutral, and theory-bound. A large part of social-systems engineering produces knowledge through models, with no a priori theories about human action, e.g., there is no homo oeconomicus. For instance, system-dynamics models capture decision rules that define processes driven by actors in concrete situations. Such an epistemology shows a valuable lack of concern for empirically-sourced (induced) knowledge. Non-inductive engineering knowledge is generated neither from “generalizable” data nor from “general laws” for social systems, but rather from the ability to design in operational terms. This knowledge grows through trial-and-error. This chapter demarcates these epistemological aspects to show how and why a model-based science denotes an engineering attitude that improves action and change in specific settings. This stance is a consistent way of facing the contingency of systems that are formed by free, innovative actors and, furthermore, of developing a science of management.
[The military helicopter’s bay door rolls open to reveal a handful of ordinary-looking people already waiting inside. They all wear bewildered expressions. It seems they’ve all gotten the same treatment. Helen steps inside. A young man offers Helen his hand.]
Hi. I’m Yusef.
Helen.
Helen, do you have any idea why this is happening to us?
No.
Well, think. What do we have in common?
What do you do for a living, Yusef?
I’m a nuclear physicist.
I’m an astronomer.
Geologist.
I’m an astrobiologist.
All right. So here we’re all scientists.
No, not me. I’m an engineer.
From the Film “The Day the Earth Stood Still”
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Notes
- 1.
Henri Fayol’s 14 principles of management are as follows: Division of work, authority, discipline, unity of command, unity of direction, subordination of individual interests to the general interest, remuneration, centralization, scalar chain, order, equity, stability of tenure of personnel, initiative, and esprit de corps (Parker and Ritson 2005; Pryor and Taneja 2010).
- 2.
“Positivism” or “idealism” are more accurate words, though they have been widely misused in management research literature; see Blackmore’s (1979) clarification.
- 3.
Qualitative-based researchers collect data to interpret, understand, construct statements, and build theories: “Qualitative research involves the studied use and collection of a variety of empirical materials—case study; personal experience; introspection; life story; interview; artifacts; cultural texts and productions; observational, historical, interactional, and visual texts—that describe routine and problematic moments and meanings in individuals’ lives” (Denzin and Lincoln 2000, p. 3). As for quantitative research, Black (1999) also stresses the following in his well-known text: “Empirical indicates that the information, knowledge and understanding are gathered through experience and data collection…At the foundation of the process of trying to understand events and their causes are observations” (pp. 3, 4, 6).
- 4.
Wacker (1998), in his research guidelines for theory-building, stresses that as long as a theory can provide answers to questions like Could a specific event occur?, Should a specific event occur?, or Would a specific event occur?, then we have a theory: “Good theory-building research’s purpose is to build an integrated body of knowledge to be applied to many instances by explaining who, what, when, where, how and why certain phenomena will occur” (p. 371).
- 5.
Almost any issue of the Academy of Management Journal illustrates this bias that fabricates induced-from-data, and general (though restricted), law-like, causal, theoretic propositions. The following are examples: (1) “Executives who either scrutinize the interest of potential partners or target strong direct ties are likely to form new interorganizational ties more efficiently” (Hallen and Eisenhardt 2012, p. 50); (2) “Cognitive team diversity positively relates to individual team member creativity” (Shin et al. 2012, p. 200); and (3) “Market commonality, resource similarity, and their interaction are related in the same direction with both the likelihood of foothold attack and foothold withdrawal” (Upson et al. 2012, p. 104). Usually the research questions are biased toward law-like causality, such as the following: (1) What are the determinants of power? (Finkelstein 1992); (2) What are the factors for successful inter-partner learning? (Hamel 1991); and (3) What are the determinants of absorptive capacity? (van den Bosch et al. 1999).
- 6.
Nevertheless, we can also establish general classes of models, e.g., “generic structures,” which are theories of structures (feedback loops, levels, rate equations, etc.) that are linked with corresponding dynamic behaviors (Lane and Smart 1996) which can fuel processes of conceptualization, model construction, and generation of trials. This fact marks an intersection with typical scientific knowledge that aims to enhance understanding, either within a domain of application or across different domains, by transferring structures across them. In general, models can help to build theories that transcend concrete situations (Schwaninger and Groesser 2008).
- 7.
In fact, one forecaster of the dairy industry states: “Forecasting the dairy markets has almost be-come a fool’s errand, because of the frequency with which ‘black swan events’ turn our outlooks upside down. There is no ‘normal’ anymore” (Levitt 2011, p. 34).
- 8.
This situation is somewhat ironic, because the most influential scientists of modern times (e.g., Newton, Darwin, and Einstein) were non-justificationists: Newtonian mechanics, the evolutionary theory of Darwin, and the theory of relativity were not induced from particular cases or “data.” As Popper (1974, p. 171) stated, “induction is a myth,” a very popular one in the social sciences.
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Acknowledgements
This chapter is an opportunity to express to Professor Schwaninger my gratitude for his inspiring example. I thank the editors for their invitation to contribute to this project and for their suggestions on my submitted draft. Further thanks go to two anonymous reviewers for thorough criticism. Finally, thanks go to Isaac Beltrán, César García, and Andrea García for reading, commenting on, and discussing earlier versions.
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Olaya, C. (2012). The Importance of Being Atheoretical: Management as Engineering. In: Grösser, S., Zeier, R. (eds) Systemic Management for Intelligent Organizations. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29244-6_2
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