Structural Coupling of Regulatory Elements and Reality Challenges: When Mixing Matters

Structural Coupling of Regulatory Elements and Reality Challenges: When Mixing Matters

Mirko Pečarič
DOI: 10.4018/IJPADA.2020040104
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Abstract

Different realities are possible and thus also different decisions. They are based on predispositions faced with different challenges that people (do not) acknowledge. The research objective is to point at differences when the reality is based on the opinions of experts, public delivery deliberation, a small group of experts or committees, an individual who decides based on diverse inputs, a small group of experts that does the same, or on collective wisdom. This paper presents a way of independent managing of various perspectives that nevertheless can exhibit their symbiosis in collective opinions as one form of (collective) reality, here named as a “visa” approach of decision making. This paper, based on presented differences, systemic regulatory elements, and their challenges, presents them as synergies (structural coupling) in the form of collective decision making. Independent and individual participation based on collective intelligence can diminish the pressure of interest groups, lobbying, or other informal influences, and can better align various interests.
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Introduction

Public problems are at least indirectly connected with problems of administration, with institutions that do not or do not know how to prevent the financial and other social crises, how to end wars, prevent poverty and provide access to clean water, safe food, etc. Holmberg and Rothstein (2012) go even further and claim that dysfunctional government institutions cause such problems. Although 705 million people were still in extreme poverty in 2015 − (the measure of ‘one dollar per day’) (Roser and Esteban, 2017), the enormous rise of applications allocated to a judicial formation of the European Court of Human Rights from 1999 (8.400) to 2016 (53.600) (with the peak in 2013 with 65.800) (ECHR, 2017), and more pipelines in the world for the gas, liquid petroleum gas, oil and refined products, and not for water as the basic ingredient of life (CIA, 2016) − on average people live better than in the past. This inference depends on a context in which institutions formally recognise and act on such (dis)comforting information.1 Dysfunctionality or legitimacy depends on criteria and a time frame in which institutions operate. They do so based on decision-making, as the lifeblood of every organization and the central focus in the practice of evidence-based management (OECD, 2014, 2012, 2011; Rousseau, 2013).2 Despite such promising focus, problems are still trying to be solved in the classical regulatory frames developed in the 18th-19th century, notwithstanding the known methods developed in other fields like the mathematical Bayes theorem (Ayres and Nalebuff, 2015; Carrier, 2012; Finkelstein and Fairley, 1970; Hacking, 2001), statistical sampling (Dodge and Romig, 1959; Fiedler and Juslin, 2006; Schilling and Neubauer, 2009; Wetherill, 2013), decisional analysis (Edwards, 1999; Edwards et al., 2007; Keeney and Raiffa, 1993; Raiffa, 1994) and risk analysis (Black, 2012; Franklin, 1998; Hood et al., 2001; Molak, 1996; Slovic, 1996). It seems an underlying systems structure has to be changed before changes can be implemented. A gap between theory and practice, between – officially and/or even constitutionally proclaimed – democratic participation and practices should be filled by the people. How come Amazon, Internet Movie Database and many Internet shops allow users’ reviews, while this is not common to public operations? Decision-makers − despite their professionality that “suppose to know-how”,3 − struggle to cope with the unpredictable future. Their decisions are also frequently not immune on the rigidity of human character: personal decisions are often obfuscated by erroneous or incomplete analyses that e.g. use relative risks instead of absolute ones (Gigerenzer, 2003; Rifkin and Bouwer, 2007), are prone to heuristics and biases (Kahneman, 2013; Terje, 2003; Tversky and Kahneman, 1974), without real, scientific evidence that results in a measurable reduction in risk or improvement in decisions (Hubbard, 2009, 2007), with the lack of good communication and confrontation of risk management solutions with reliable partners (Beck, 1992; Lynch, 2009), etc. It is hence no wonder why different opinions exist on the same matter.

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