The search for criteria separating science from non-science dates back to the beginnings of western philosophy.93 A foundation for the epistemological analysis of Austrian economics on principles of the philosophy of science follows.
Assumptions can objectively be correct or incorrect and tested for that property. But in contrast to hypotheses no claim about their truth can be made. Their purpose in science is to simplify a complex problem and the analysis of the problem. There are two caveats against the excessive use of assumptions: Firstly, the employment of assumptions necessarily omits important parts of a problem. Secondly, a model which is based on strict assumptions might immunize itself against reality and empirical testing and thus become unfalsifiable (see section 3.2.2, pp. 14f.).94
The expression for a certain phenomenon, like ‘costs’, is called ‘term’. If there is uncertainty about a term, it needs to be defined,95 thus definitions become the bases for terms. A definition consists of two parts: a short ‘definiendum’ (to be defined) is connected to a longer ‘definiens’ (paraphrase of the definiendum).96 Definitions in themselves carry neither information nor truth and they are neither right nor wrong;97 they are just agreements and conventions.98 The purpose of definitions is to shorten and clarify the language as groundwork for broadly understandable theories.99 Terms can be evaluated by their precision, consistency and validity. Ambiguously understood terms are often a major setback for empirical studies, if the correct measurement of designated events is especially important.100
“Scientific hypotheses are suppositions about the structural nature of reality”.101 While they subjectively claim to be true,102 scientific hypotheses always have a preliminary character and can, in contrast to definitions, thus be proven wrong.103 The ‘truth’ of statements has to be distinguished into logically (L-) determined and factu[Seite 12↓]ally (F-) determined statements. The former are proven by logic and mathematics. Important for this study are the F-determined statements. Their truth can only be examined in reality or with empirical means.104 Usually a hypothesis passes four stages: the first stage can be called speculation; the second is the empirically tested hypothesis, which is only valid for the explanation of a single phenomenon; at the third stage hypotheses are grounded on a connection to existing knowledge that has not yet been tested. Hypotheses at the fourth stage are called reliable. They have proven to be worthwhile in multiple empirical tests. A reliable hypothesis that has a general scope as well is called a law or a statement of invariance.105 This assumes that nature, society or man follow some constant pattern or regularity.106 Similar to terms, acceptable laws fulfil some criteria as well. A law should be applicable to more than one class of events (generality), it should be strictly tested (reliability) and belong to a system of laws.107 Such a system of laws then forms a theory.108
A few scientists regard the creation and definition of terms as the goal of science, whereas the majority of scientists refuse this essentialist view, being inclined to test hypotheses and create new theories.109. Even though “the term ‘theory’ is vague and ambivalent not only in the social realm, but also in the philosophy of science”,110 there are descriptions of the nature of theories. Theories are systems of laws that contain scientific information in an easily understandable manner. Regularly those hypotheses that reached the status of laws form the basis of such a system, and are called axioms there. Axioms in a theory must be consistent, i.e. they may not contradict each other. Furthermore, the single axioms are preferably independent of each other.111 “Theories establish a general cause/effect-connection [and] […] describe [Seite 13↓]empirical regularity or invariance in the nature or the social world […]”.112 A typical statement from a theory would then be the following: Cause x1 implies the effects y1, y2 and y3. Once a theory has been established on grounds of acceptable laws, it should vice versa be possible to suggest and derive new laws and hypotheses from the theory. Examples are Kepler’s and Galilei’s laws that can be derived from Newton’s theory of gravitation.113
The distinction between good and useful theories as opposed to worthless assumptions or, more generally, between knowledge on the one hand and magic, superstition, speculation and dreaming on the other, is very important for the philosophy of science.114 The following criteria have been developed to assess the potential of theories or their basic ingredients, i.e. hypotheses. The first two criteria (universality and precision) determine the empirical content of a hypothesis. The empirical content and its converse of logical scope in turn determine the falsifiability of a hypothesis.
Good hypotheses, laws, and theories should have a universal character respectively reliability across space and time, which means that their empirical (informational) content grows with increasing validity at different places and points in time. What is similarly important is the conditionality that is expressed in the ‘if-then-form’, e.g. condition p is the cause for consequence q or short: if p, then q. If either the if- or then-component is altered, the empirical content of the hypothesis and thus its explanatory power is altered. The universality of a hypothesis depends on the if-component. Increasing content of the if-component decreases the universality of the hypothesis, and vice versa.115 To put it in other words: the more conditions there are in the if-component, the less likely will the then-component be. On the contrary, the fewer conditions are connected to the if-component, the likelier is the occurrence of the then-component. The precision of a hypothesis is determined by an alteration of its then-component. A reduced (increased) content of the then-component implies [Seite 14↓]lower (higher) precision of the whole expression.116 Put differently: the more possible outcomes the then-component allows, the lower is the hypothesis’ explanatory power. If the universality and precision of a hypothesis grow, its empirical content increases, but the more precise and universal a hypothesis claims to be, the bigger is the number of potentially contradicting events and the risk of falsification.117 “Theories are valued largely for their explanatory power and simplicity […]”,118 so the scientist’s objective should always be to strive for more general and more precise hypotheses.119
The logical scope of a hypothesis describes the class of logical possibilities that is compatible with it. Logical scope and empirical content are converse to each other: the latter covering the class of logical possibilities that are incompatible with the hypothesis.120 An example is in order. We assume that a company increases its promotional activities, implying three possible outcomes: sales will increase, stay constant, or decrease. If we hypothesize that sales increase with increased promotional activity, the logical scope (=increasing sales) of the hypothesis is small while the empirical content (=constant or decreasing sales) is large. The notion of constant or decreased sales is incompatible with the hypothesis. Should this notion be made, the hypothesis would be proven wrong or falsified. If we restate our hypothesis to “Sales will increase or stay constant with increased promotion”, the logical scope has grown compared to the first case, whereas the empirical content is smaller. It has become more difficult to falsify the hypothesis, because now more outcomes are compatible with the hypothesis. In case of a statement claiming that sales will increase, stay constant or decrease with increased promotion the logical scope is at its maximum, because all conceivable outcomes are now compatible with the statement. Unfortunately, the empirical content is zero and the statement cannot be falsified anymore. It follows that the more outcomes a statement excludes, the larger is its empirical or informational content and the more will it tell about reality. A theory with a larger class of incompatible outcomes is more bound to fail – it is easier falsified.121 Falsificationism in the modern philosophy of science stems from Popper’s “The Logic of Scientific Discov[Seite 15↓]ery”.122 The so-called approach of “critical rationalism”123 rejects verification and the possibility that a hypothesis or theory can ever definitely be proven to be true, because a finite number of observations never allow conclusions to be drawn about an infinite number of possible outcomes.124 Many believe that critical rationalism is superior to other epistemological approaches in marketing.125 In the social sciences, if rigorous testing via observations and experiments in reality provides evidence against a statement, the statement is falsified and should be rejected. Until then, the statement is tentatively entertained.126 To summarize, a good theory has much empirical content, thus offering many possibilities for falsification, but always withstands the attempt to do so.127
The basic necessity of a theory is truth, but truth is not sufficient.128 High empirical content is also important, but unfortunately a conflict of aims between truth and high empirical content of F-determined statements hinders theory development. This conflict induces that the better fulfilment of aim A1 (truth) results in a worsened position for aim A2 (empirical content).129 There are few theories in the social sciences that claim to be true always and everywhere.130 Sometimes depicting the world realistically is not even the goal of a theory, but presenting a simplified or distorted picture of the world.131 Since there is a trade-off between a high likelihood and high empirical content, scientists must emphasise one of the two. They usually prefer high empirical content.132 A hypothesis with a high likelihood can be highly probable just because it does not tell much or nothing at all.133
The former reflections can be extended by novelty to the ‘triangular problem’ (see fig. 1, p. 76). Novelty can either be expressed in a totally new idea, or in making new [Seite 16↓]connections of ideas already known, or creating a new form of representing an idea. The generalized conflict of aims exists between the search for truth, empirical content and novelty. Fulfilling two out of those three objectives can be simple. Novelty and truth are expressed in trivialities that have no empirical content; novelty and empirical content without truth are found in fantastic speculations; truth and empirical content without novelty are e.g. found as plagiarisms of existing theories. Besides of empirical content, novelty is the dominating objective for scientific statements,134 though major breakthroughs are only achieved if all three conditions are fulfilled.
Theories are created to solve problems of theoretical or practical relevance.135 The first category contains intellectually stimulating problems,136 and those with important implications for theoretical systems.137 The second category subsumes problems that real persons regard as important for their actions.138
Describing real facts and events – though not offering much reputation – is a distinctive and essential part of scientific work. In the field of marketing, there are many descriptions of particular cases, e.g. about tendencies of concentration in business sectors, distribution channels, market shares etc.139 Popper pointed out the essence of theorizing in a metaphor: “The theory is the net we cast out to catch ‘the world’ – for rationalisation, description and domination”,140 i.e. theories are created to simplify, describe, and understand our environment.
Schanz claims that the ability to explain is the most important property of theories.141 To be explained (the explanandum) with the help of theories are why-questions, the answers to which provide reasons that explain why things are in one way and not the [Seite 17↓]other.142 In marketing this could be employing the neoclassical notion that increased prices for normal goods ceteris paribus (c.p.) decrease the consumers’ propensity to buy,143 or the thesis from the behavioural sciences that satisfaction exercises an effect on customer loyalty.144 One law and at least one secondary condition or assumption is necessary to explain problems found in reality. If we want to explain why a customer is very loyal to a coffee-brand, we can find the law “Customers who experience satisfaction with a good or service will be loyal”. In connection with the exemplary secondary condition “The customer loves the taste and smell of his coffee”, the problem is solved. If the law is assumed to be true, the secondary condition causes loyalty. This scheme of logical deduction of an explanandum from an explanans (law and secondary condition) is called “Hempel-Oppenheim-” or “Hempel-Popper-Scheme”.145 Hempel and Oppenheim put up four constituting demands for the simple explanation (which is called deductive-nomological or DN-explanation): Firstly, the explanandum must be a logical consequence of the explanans. Secondly, the explanans must contain at least one law. Thirdly, the explanans must have empirical content and, fourth, the explanans must be true.146 If one considers the rejection of verification, the last demand diminishes to “the explanans may not have been falsified so far”. Another, not generally accepted demand is the possibility of independently testing explanandum and explanans to avoid ad-hoc and circular explanations.147
Since “[p]redictions can be seen as the bridge between science and action”,148 successful predictions often turn out to “[…] mark the turning point in acceptance of a theory that has been offered”.149 Prognoses are those predictions that are based on theories.150 Schneider sees the origin of predictive theories in the missing link between empirical problems and best-practice examples. The explanatory theory sys[Seite 18↓]tematizes existing knowledge and then offers solutions for the future.151 The initial situation for predictions is opposed to that of explanations (see fig. 2, p. 76). In the latter case, what was to be explained was given; fitting secondary conditions and one or more laws were to be found. Predictions work the other way round: the goal is to derive predictions from the given laws and secondary conditions. A predicted incident is contingent on two conditions: at first, the secondary conditions have to materialize and second, the relevant laws must be powerful. Laws with a high empirical content allow predictions because they rule out the possibility that certain events happen in the future.152 A non-technological prognosis does not offer exact suggestions for action because the occurrence of the secondary conditions is not controllable. The prognosis will be flawless only if those conditions can be actively controlled (technological prognosis).153
Technological prognoses are feasible only after transforming a theory into its technological form, which is a tautological transformation to clarify the relevance for practical problems.154 The transformed theory puts forward a ‘technique’ or ‘policy’.155 The cause/effect-framework is changed to a means/ends-framework.156 Kotler claims that “[m]arketing is a descriptive science involving the study of how transactions are created, stimulated, facilitated and valued. Marketing management is a normative science involving the efficient creation and offering of values to stimulate desired transactions”.157 The task of marketing technology thus becomes assisting “[…] marketing decision makers by developing normative decision rules and models, […] based on the findings of marketing science”.158
Theories from the social sciences can be used to criticize social or ideological conditions. As a theory allows conclusions to be drawn about the relations of causes and effects in reality, it informs us not only about a given state, but about possible situations as well. Questions about the consequences of different measures are answered with the help of theoretical knowledge. It becomes possible to criticize current social [Seite 19↓]realities using this information.159 Criticism of ideologies via theories is established on the claim that well-founded theories inform about prejudices. Ideologies which often claim to be based on scientific theories can only be successfully attacked with superior theories.160
93 Cf. Laudan (1980).
94 Cf. Chmielewicz (1988), pp. 121f.
95 Cf. Schanz (1988), p. 17.
96 Cf. Chmielewicz (1988), p. 452; Popper (1992), p. 17.
97 Cf. Chmielewicz (1994), p. 49; Balzer (1997), p. 66.
98 Cf. Popper (1989), p. XIX.
99 Cf. Balzer (1997), pp. 65f.; Popper (1992), pp. 22f., 26f.
100 Cf. Schanz (1988), pp. 20-22.
101 Schanz (1988), p. 24; [„Realwissenschaftliche Hypothesen sind Vermutungen über die strukturelle Beschaffenheit der Realität“]. Emphasis in original; cf. Schneider (2001), pp. 24f.
102 Cf. Chmielewicz (1994), p. 119.
103 Cf. Schanz (1988), pp. 25; 27.
104 Cf. Chmielewicz (1988), p. 456.
105 Cf. Schanz (1988), pp. 27f.
106 Cf. Albert (1964), p. 40.
107 Cf. Schanz (1988), p. 29.
108 Cf. Bunge (1967a), p. 381.
109 Cf. Chmielewicz (1988), p. 452; Müller-Hagedorn (2000), p. 28. Even though Mephistopheles told one of Faust’s students that “Grey, dear friend, is all theory, and green life’s golden tree” [“Grau, teurer Freund, ist alle Theorie, und grün des Lebens goldner Baum”], “There is nothing more useful for practice than theory” [“Nichts nützt der Praxis mehr als die Theorie”]. Goethe (1961), verses 2038-2039, p. 60; Albert (1971), p. 219.
110 Chmielewicz (1994), p. 162; [“Der Theoriebegriff ist aber in der Wissenschaftstheorie ebenso wie im Sozialleben vage und mehrdeutig“]. Emphasis in original.
111 Cf. Schanz (1988), pp. 24; 29-31; Popper (1989), p. 41.
112 Chmielewicz (1994), p. 11; [„Theoretische Aussagen konstatieren einen generellen Ursache/Wirkungs-Zusammenhang [und] […] eine empirische Regelmäßigkeit der Natur- oder Sozialwelt […]“].
113 Cf. Chmielewicz (1994), p. 163.
114 Cf. Feyerabend (1965), p. 331.
115 Cf. Schanz (1988), pp. 32f.
116 Schanz (1988), pp. 33f.
117 Cf. Chmielewicz (1994), p. 124.
118 Bakker/Clark (1988), p. 4.
119 Cf. Schanz (1988), p. 34.
120 Cf. Schanz (1988), pp. 35f.
121 Cf. Popper (1989), p. 77.
122 Cf. Durbin (1988), p. 103; Popper (1980); the first edition was issued in German in 1934 (with date of 1935); for a short critique of Popper, cf. Chalmers (2001), pp. 73-86.
123 Cf. Albert (1960).
124 Cf. Suppe (1977), p. 167; Kloten/Kuhn (1965), p. 311.
125 Cf. Raffée (1995), col. 1674; Easton (2002), p. 104.
126 Cf. Chalmers (2001), p. 52.
127 Cf. Chalmers (2001), p. 56.
128 Cf. Chmielewicz (1988), p. 456.
129 Cf. Chmielewicz (1994), p. 129.
130 Cf. Bayer/Stölting (1994), p. 304.
131 Cf. Eberhard (1999), p. 15.
132 Cf. Popper (1989), p. 314.
133 Cf. Popper (1989), p. 352. An example is the saying “If the cock screams the weather changes or stays like it is”, which is always correct but does not help at all.
134 Cf. Chmielewicz (1994), pp. 131f.
135 Cf. Franke (2002), pp. 13f.
136 Cf. Zaltman/Lawther (1979), pp. 501f.
137 Cf. Witte (1998), p. 740.
138 Cf. Schanz (1992), p. 58.
139 Cf. Müller-Hagedorn (2000), p. 29.
140 Popper (1989), p. 31; [“Die Theorie ist das Netz, das wir auswerfen, um ‘die Welt’ einzufangen, - sie zu rationalisieren, zu erklären, und zu beherrschen“]. The original metaphor was written by Novalis: “Hypotheses are nets, only he will catch, who casts out…” [“Hypothesen sind wie Netze, nur der wird fangen, der auswirft…”]; Novalis (1789).
141 Cf. Schanz (1988), p. 56.
142 Cf. Bunge (1967b), pp. 3-9.
143 Cf. Varian (1999), p. 98.
144 Cf. e.g. Anderson/Sullivan (1993); for an overview, cf. Homburg/Giering/Hentschel (1999), pp. 93-96.
145 Cf. Hempel (1965), pp. 335-354; Popper (1989), pp. 31f.
146 Cf. Hempel (1965), pp. 247f.
147 Cf. Popper (1972), pp. 30f.
148 Schanz (1988), p. 65; [“Voraussagen können gleichsam als Brücke zwischen Theorie und Handlung betrachtet werden”].
149 Bakker/Clark (1988), p. 21.
150 Cf. Schanz (1988), p. 65.
151 Cf. Schneider (2001), p. 273.
152 Cf. Schanz (1988), pp. 65-68.
153 Cf. Albert (1964), p. 62.
154 Cf. Schanz (1988), pp. 76-78.
155 Cf. Albert (1984), p. 206.
156 Cf. Chmielewicz (1994), pp. 11f.
157 Kotler (1972), p. 52.
158 Hunt (1983), p. 12.
159 Cf. Schanz (1988), pp. 82f.
160 Cf. Albert (1964), p. 70.
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