Assessing Inventive Step of patent applications using a multicriteria index: An empirical validation.

Fritz Dolder [1], Christoph Ann [2] and Mauro Buser [3]

Cite as: Dolder F., Ann C., & Buser M., "Assessing Inventive Step of patent applications using a multicriteria index: An empirical validation.", In European Journal of Law and Technology, Vol 5., No. 1., 2014.


Inventive step constitutes the condition for patentability of inventions most difficult to determine (Art. 56 EPC). The assessment is currently performed by the Boards of Appeal of EPO without pre-determined and structured procedures and usually results in one-reason decisions. To improve the reproducibility of the assessment a multicriteria index ISPI (Inventive Step Perception Index) was applied accumulating the reasoning of past decisions of the Appeal Boards of EPO. The present investigation was performed in order to validate this instrument and to compare the results obtained with the results of one-reason decisions.

Empirical work was staged on two test cases decided in the past by two different Appeal Boards of EPO. One of them was positive (grant of the patent), the other was negative with regard to inventive step (revocation of the patent). Large samples of students (each about N = 200) were called to assess inventive step in these two cases with either the support of the ISPI index, or with the usual unstructured procedures (control group).

The reproducibility of the assessment was judged by calculating inter-rater concordance of the results using Cronbach's Alpha (target value: > 0.9), their inter-criteria concordance (target value: < 0.3); hence it is suggested that in an efficient assessment tool the targeted ratio between the two values should be below < 0.5.

A consistent cut-off value of the cumulated ISPI score was selected by the ideal observer's view, minimising false results (mis-classifications) as compared to the decision of the Appeal Boards. By using this selected cut-off value the rate of mis-classifications could be significantly reduced (37.81%, 25.00 % respectively) as compared to the rate obtained by evaluating the identical set of facts with unstructured holistic procedures (65.61 %).

Our findings are consistent with findings of Arkes et al (2010) and (2006) showing that multicriteria assessments offer advantages against one-reason decisions. The results are explained in part by the fact that applying ISPI creates a consistent constraint for completeness of assessment for the decision-maker, while such a constraint is not felt when unstructured procedures are used in one-reason decisions.

The empirically validated index will prove useful not only in patent prosecution and patent litigation, but also in valuing patent assets in a business context.

1. Introduction

Decisions in different areas of law are based on the assessment of performance or quality of complicated technological, scientific, medical, or social phenomena on the background of a statutory term all to often defined in a general, and hence vague form. This assessment can be performed either by holistic (one-reason) or by multicriteria procedures. Since holistic assessing is based on or at least linked to an overall impression incorporating almost necessarily subjective and irrational elements, it leads more or less inevitably to one-reason decisions selecting one decisive attribute of the object, or one criterion of assessing. A serious drawback of this procedures consists in that raters may find it easier to slip illegitimate, or irrelevant but appealing criteria into their ratings when using such unstructured holistic procedures (Arkes et al. 2010, 265).

Multicriteria heuristics, on the other hand, is based on a predetermined algorithm of steps: Defining and selecting a plurality of relevant attributes and criteria of the phenomenon to be assessed, attributing relative weights to the criteria, setting scales for assessing the criteria, assessing the score of each of the relevant criteria and aggregating the scores of the individual criteria into a multicriteria score of the object to be assessed. This multicriteria procedure requires predetermined framework comprising definitions of the presumably relevant criteria, their relative weight and scales, and a mechanism by which the scores of the individual criteria are aggregated into a final over-all score of the phenomenon to be qualified.

The superiority of systematic multicriteria over one-reason holistic heuristics has been established in a variety of areas and for a variety of different tasks other than legal decision making (Ravinder et al. 1991, Ravinder 1992, Arkes et al. 2006, Arkes et al., 2010, Zopounidis & Doumpos 2002). However, evidence for a number of practical advantages of one-reason heuristics in areas other than legal decision making have been equally reported. (Gigerenzer 2007, Rieskamp et al. 1999)

Inventive step constitutes the condition for patentability of inventions most difficult to determine (Art. 56 EPC). The assessment is currently performed by the Technical Boards of Appeal (TBA) of EPO without pre-determined and structured procedures and usually results in one-reason decisions. To improve the reproducibility of the assessment a multicriteria index ISPI (Inventive Step Perception Index) was proposed accumulating the reasoning of past decisions of the Appeal Boards of EPO. The purpose of the present study is to validate empirically the different features of this multicriteria index ISPI within the legal framework of the European Patent Convention (EPC). In order to validate this index and to compare the results obtained with the results of the one-reason decisions an empirical investigation was performed by experimental assessments of selected TBA test cases by large samples of student raters.

2. Assessing inventive step by one-reason-decisions

2.1 Inventive Step (Non-obvious Subject Matter, Non-obviousness)

Inventive step (non-obvious subject matter, non-obviousness) has been considered for decades to be the requirement of patentability of inventions which is by far the most difficult to evaluate and to yield results which are safely reproduced from one decision-maker to another.

Art. 56 EPC: An invention shall be considered as involving an inventive step if, having regard to the state of the art, it is not obvious to a person skilled in the art. (....)

The applicable statute does in wording not provide efficient and detailed guidance with regard to the procedures and methods to be applied for decision making in individual cases. The Guidelines for Examination of EPO although containing a catalogue of relevant (and apparently: independent) criteria (Part G- Chapter VII) are conceived apparently on the paradigm of the one-reason-decision. Therefore, they do not offer a consistent algorithm for taking into account all criteria which might be (equally and simultaneously) relevant in a given case and for aggregating the scores of such different criteria: The examples relating to the requirement of inventive step in Guidelines EPO June 2012, Part G - Chapter VII-13 Annex- indicators are indicated here together with the code of the corresponding criteria of ISPI (see infra Section 2):

  1. Application of known measures (F2)
  2. Obvious combination of features (P 21.2)
  3. Obvious selection (P 25)
  4. Overcoming a technical prejudice ( A 42)
Therefore, decision making on inventive step is currently achieved in most cases of the TBA through holistic procedures based on implicit preferences of the decision-makers and regularly result in one-reason-decisions: The rater selects one single attribute of the patent application to be assessed and applies one single criterion for assessing this attribute thereby implicitly avoiding all other, perhaps equally and simultaneously relevant criteria. In the following examples of typical reasoning of Technical Appeal Boards of EPO the decision was exclusively based on one single independent criterion.

TBA 1199/08 of May 3, 2012.

No. 38. The only difference between the sperm sample of claim 14 and the one of document D30 lies in the use of an extender comprising Tris, whereas in document D30 the extender consists of a combination of egg yolk and citrate of sodium. (....)

No. 40. Appellant I argued that a skilled person would have been discouraged to replace the egg yolk/citrate sodium extender of document D30 by a Tris-based extender (....)

No. 41. Thus, the skilled person looking for an alternative for the egg yolk / citrate of sodium extender used in document D30, (....), would have had no reason to ignore the teaching in document D5. By exchanging the extender disclosed in the closest prior art by one of the extenders disclosed in document D5 as being known to be useful for freezing of bovine sperm he/she would have arrived at the subject-matter of claim 14 in an obvious manner.

No. 42. Thus, the Board decides that the subject-matter of claim 14 does not involve an inventive step and that the main request does not comply with the requirements of Article 56 EPC.

The decisive criterion applied in this case consisted of whether a technical prejudice existed among the skilled workers against transferring knowledge of a given document of the state of the art to the patent application in suit (reasoning under Guidelines EPO G-VII- Annex 4, see item # A42 of ISPI, infra 2.2):

TBA 1616/08 - Gift order/AMAZON of November 11, 2009, No. 9.

The mere wish to automate process steps that have previously been performed manually is usually regarded as obvious. The automation details may naturally be inventive, but in the present case the problem of how to extract the delivery information is left entirely to the skilled person. Thus an inventive step is neither involved in the idea to extract information automatically, nor in its implementation. The subjectmatter of claim 1 is therefore obvious.

In this case the decisive criterion was the classification of the invention into the category (mere) automation of a process which had been previously performed manually (corresponding to code T 33.1 of ISPI).

From the Decision of the Opposition Division in continuation of case of TBA 1616/08 - Gift order/ AMAZON of June 21, 2013:

Claim 1 of the third auxiliary request is based on two different groups of features.
a) the features of claim 1 of the second auxiliary request and
b) a selection of the features of the single-action ordering to the main request discussed in T 1244/07. The opposition division does not see any kind of technical interaction between these two sets of features, they are therefore, in the view of the Opposition Division, just aggregated. According to the practice of the EPO the mere aggregation of non inventive subject-matter cannot involve an inventive step. [....] During the oral proceedings, the patentee agreed that indeed claim 1 can be divided in the two above defined set of features but was of the opinion that a synergetic effect had to be acknowledged in the claimed combination. [....]

The opposition division cannot follow that argumentation because it is not possible to recognise any new technical effect (i.e. an effect which is not present when either one or the other of the two sets of features is used) resulting from the claimed combination. In conclusion, the Opposition Division, in view of the above cited decisions of the Board, is of the opinion that the subject-matter of claim 1 of the third auxiliary request does not fulfil the requirements of Art. 56 EPC because it is a mere aggregation on non inventive features. [....]

In this case the decision was based again exclusively on one single criterion, namely the famous aggregation - combination issue as advised by Guidelines EPO G-VII- Annex 4, see code P 21.2 of ISPI:

2. Obvious combination of features? 2.1 Obvious and consequently non-inventive combination of features: The invention consists merely in the juxtaposition or association of known devices or processes functioning in their normal way and not producing any non-obvious working inter-relationship.

2.2 Poor Reproducibility of One-Reason Decisions

In view of this widespread one-reason mechanism it is not surprising that poor reproducibility of the results of assessment of inventive step is accepted in the patent community to constitute a central problem and one of the main difficulties of patent prosecution & litigation since the development of inventive step into a statutory requirement of patentability in the early 20th century. Within the context of EPO prosecution, this is evidenced in part by the remarkably high percentage of cases which are reversed by the TBAs (assuming that the TBA decisions are in their overwhelming majority (90 % ?) based on an assessment of inventive step differing from that of the examination, or opposition divisions):

European Patent Office 2009, Annual Report : Cases settled by TBAs in 2009: 1918, allowed (in part) 740 (38.6 %), dismissed 589, otherwise (e.g. withdrawal) 589; based on opposition procedures (inter-partes): cases settled 1116, allowed (in part) 508 (45.5 %), dismissed 337, other 271 (page 41). Opposition procedures: Patent revoked 43.6 %, patent maintained in amended form 30.1 %, opposition rejected 26.3 % (page 19).

In the course of our investigation this relatively poor reproducibility of inventive step assessment was evidenced by the fact that two test cases could easily be found which had been both reversed by their respective TBAs (see infra Section 3.1).

Recent opinions of eminent experts of the US patent community have not unexpectedly confirmed this current state of poor reproducibility of decisions on inventive step. As was stated by U.S. federal appellate judge Richard A. Posner in NYT International Weekly of 15th October 2012 (Duhigg / Lohr 2012):

"There's a real chaos. The standards for granting patents are too loose."

And in the same issue of NYT another U.S. patent expert, Raymond Persino, a patent attorney who had previously worked as an examiner, was reported to state: "If you give the same application to 10 different examiners, you will get 10 different results"

2.3 Person Skilled in the Art and Other Formulae

The notional person skilled in the art (Durchschnittsfachmann) has contributed little to improve this unsatisfactory situation: Although this fictitious person is still mentioned in the Guidelines (June 2012 Part G - Chapter VII-3 and 3.1 ) it has never been disputed that art. 56 EPC (and its equivalents in the national statutes) does not address the layman in the street who will not even understand semantically patent documents. Furthermore, it was never disputed that the standards for evaluation of inventive step should be set by the expert knowledge available in the relevant scientific specialities. Thus, although being currently mentioned in decisions of the TBAs the person skilled in the art proved to be of modest cognitive value so far and was not able to steer decision making under art. 56 EPC to a significant extent.

Other notional formulae or tests proposed under art. 56 EPC are of equally modest cognitive value and have made equally small contributions in improving the inter-personal reproducibility of decisions. The following two formulae both appeal to the subjective personal perception of the decision maker with regard to the probability of success in a given technical context and can as such not be expected to improve the inter-personal reproducibility of decisions significantly:

Could - would approach (Guidelines June 2012, Part G-Chapter VII-5.3): This notional test is based on the reasoning that "the point is not whether the skilled person could have arrived at the invention by adapting or modifying the closest prior art, but whether he would have done so because the prior art incited him to do so". The difficulties in using this test in a reproducible way are evidenced by the statement that:

"even an implicit prompting or implicitly recognisable incentive is sufficient to show that the skilled person would have combined the elements from the prior art (see T 257/98 and T 35/04)".

This notional test was invented in a patent litigation in 1928 by Sir Stafford Cripps, K.C., in Sharp & Dohme Inc. v. Boots Pure Drugs Company Ltd. [1928] 45 R.P.C. 153, Court of Appeal (CA) March 9, 1928 (Bryant, 1997, p. 60-62) and this test had an unexpected renaissance after the EPO started examination of patent applications in 1978.

The contrast between reasonable expectation of success (angemessenen und realistischen Erfolgserwartung) and mere hope of achievement (blosse Hoffnung auf gutes Gelingen) is equally praised to be a valuable instrument for making decisions under art. 56 EPC: T 296/93 and T 207/94. But this notional contrast is merely a verbal expression of the probability of success as subjectively perceived by the decision maker. As ruled in T 207/94 the hope of achievement expresses a desire, while the expectation of success requires a scientific evaluation of the facts in a specific case.

As a contrast to such sophisticated, but not really helpful legal semantics it should be realistically acknowledged that practical legal decision-making under art. 56 EPC is based more or less implicitly on the simple understanding that to be inventive a technical performance has to be more than average in a specific technical context.

3. The Multicriteria Index ISPI

The multicriteria Index ISPI (Inventive Step Perception Index) for assessing inventive step of inventions was proposed to provide the decision-maker with a structured instrument for the various criteria of assessment in view of improving the reproducibility and accuracy of assessing inventive quality (Dolder 2003). ISPI applies the classical procedure of Simple Additive Weighting (SAW), which is probably the most widely used MCDA method, but in the present context has the great advantage to be easily understood by the non- statistician, i.e. patent practitioners. This linear weighted sum:

V(x) = Σ wi vi (xi)

was assumed to provide a good overall measure of inventive performance (xi: single attributes / criteria, wi : weights, and vi: value functions), particularly since it allows compensation, i.e. the assessed patent application may compensate poor scores on a particular criterion x1 by better scores on other criteria xn.

3.1 Selecting attributes and criteria

Since ISPI was conceived to continue the experience and standards of past EPO case law, the authors of ISPI were not free in their choice of criteria, but rather bound to the lines of argumentation of past TBA decisions. Therefore, ISPI criteria were selected exclusively from

patterns of reasoning found in the past decisions of the TBAs and, to a some extent, in the Guidelines for Examination 2012 of EPO. ISPI therefore assesses inventive step exclusively

on the basis of criteria which were previously held to be relevant in the past reasoning of EPO. The mere fact that a criterion was applied in the reasoning of the TBAs (at least once) was the only condition for admitting the criterion into the catalogue of ISPI index.

With regard to the number of criteria, it is commonly accepted that the risk of confounding, i.e. yielding higher scores than could be expected statistically from independent attributes increases with increasing number of attributes. This results in the same attribute being implicitly assessed more than once, therefore being implicitly over-weighted. Since the criteria applied should be as independent as possible from each other, the number of criteria was restricted to the minimum required by the past TBA case law providing input in this respect (i.e. group F = 5 criteria, P = 3, T = 2, A = 6, total of 14 criteria, and if group T applies, to a total of 16 criteria).

A relatively low number of criteria is also desirable from another standpoint: Already Galtung (1967) stated that in order to be applied successfully in practice an index (i.e. a multicriteria assessment instrument) should be easily understood by the persons called to assess given phenomena. The instrument should make immediate sense to the user apart from its mere mathematical mechanisms. This condition can of course be fulfilled much easier with a relatively low number of criteria.

ISPI therefore evaluates the inventive step of inventions on the basis of only four groups of criteria: F (formalities), P (type of patents), T (trivial measures), and A (additional indicators) amounting to a total of 14, or 16 different items (Dolder 2003). The criteria used by ISPI shown in Table 1 reflect a diversity of viewpoints about inventive step, and the four groups of attributes (F, P, T., A) are as independent, as can be expected from their common theoretical starting point, namely the idea that a high inventive step should yield a high score in all three groups.

In a retrospective series of observations the statistical correlation between criteria were determined and were found to be independent to an encouraging extent (see infra Section 4). In contrast to working with holistic mechanisms generating one-reason-decisions the rater of ISPI has to consider criteria which he is prima facie not personally inclined to take into account and which he would otherwise not have considered.

It should be noticed that the well balanced catalogue of ISPI criteria should be applied to a given set of facts in an exclusive way, and not be extended on a case-by-case basis by modifications. Any such extension of the catalogue on a case-by-case basis would harm or un-balance the instrument and would therefore generate biased results. Such admission of modifications ad hoc would be harmful for the conceptual qualities of the system (cf. Katz/Baitsch 2006).

3.2 Scaling qualitative and semi-quantitative criteria

The majority of the criteria used in ISPI are qualitative, i.e. can be expressed only in a verbal, or linguistic way and be answered in a YES-NO, or typical - not typical way. Therefore, the scaling procedure for the criteria applied with ISPI had to take into account a majority of qualitative criteria, such as e.g.

A 43 Was there a long-felt need for the invention? Were previous attempts not successful?
Applicable YES-NO.
F 4 Was there scientific / technological competition resulting in the invention ?
Typical - not typical

The different realisations ("values") of such qualitative attributes are not measured by exact numerical methods, but are prima facie expressed in verbal patterns. These verbal patterns have to be subsequently transformed into numerical scores, which requires that such attributes are carefully operationalised. In such situations, scales should be avoided which are too differentiated, e.g. scales from 1 to 10, since they suggest a (not existing) exact measurement, lead to undesired compromising and are prone to capture implicit prejudice, or bias.

Unwarranted / exaggerated fine scales furthermore suggest the raters to give medium ratings and do not urge the rater to make real hard decisions and lead to apparently minor corrections introduced after the assessment has been performed. The more differentiated the scales are, the more they are subjected to undesired effects, such as the halo effect, i.e. scores influenced by the general impression of the object to be assessed. Therefore to assess qualitative attributes successfully relatively rough scales should be applied which are able to avoid the misleading arising from too refined scales (cf. Katz / Baitsch 2006).

In view of these difficulties, the scales for the criteria used in ISPI were conceived as rough as possible, not suggesting a non-existing objectivity, but requesting real hard decisions from the raters. In a first step, the scores for the qualitative criteria are expressed using linguistic patterns such as high (H), moderate (M) (or: intermediate, medium), and absent (A), or typical - not typical generating a linguistic set of values for assessment.

v (H, M, A), or v (T, -T)

In a second step these linguistic values of the qualitative criteria are transformed in a numerical scale so that the score obtained for each individual criterion is either (0-1-2) resulting in a theoretical maximum score of 24 points. A minority of the criteria are of a semi- quantitative nature:

F3 What was the age of the nearest state of the art on the application date ?
Less than < 10 years, 10 to 20 years, more than > 20 years ?
P 21.1 What number of technical specialities generated the attributes of the invention ?
1 speciality, 2 specialities, or more than > 2 specialities ?
These (semi)-quantitative criteria of ISPI assessed by numerical methods were likewise transformed into the rough score (0-1-2):

F1 Number of the intellectual steps required to attain the invention starting from the nearest state of the art: 1, 2 or more >2 ?

The essential point being that one criterion cannot yield more than a maximum of 2 points indicating a highly positive contribution to the overall inventive step of the patent application.

3.3 Attributing weights to individual criteria

Attributing different weights to the criteria of a multicriteria instrument can be either implicit, or explicit: Implicit by attributing different maximum scores to different criteria, explicit through attributing specific factors of multiplication to particular criteria.

Attributing different weights to different criteria in a multicriteria instrument can rarely be justified in a consistently scientific and rational way. If it is applied, it is usually based on some pre-formed or inside conceptions of the value of certain criteria with regard to the overall score of the phenomena in question. Therefore, it is preferable to apply neither implicit, nor explicit weighting of the individual criteria of a multicriteria instrument, but rather to attribute equal maximum score to each criterion and to abstain from using different weights for different criteria ( Katz / Baitsch 2006, p. 17-18: "Wissenschaftlich lässt sich unterschiedliche Gewichtung kaum je begründen"). This corresponds with findings in other fields of decision making which show that attributing different weights to different criteria adds little to the accuracy of the results as compared to attributing equal weight to all criteria (Dawes 1979).

Furthermore, complicated weighting of criteria can even less be justified in a context full of uncertain estimates, i.e. in a low-validity environment like inventive step: Already in 1967 Galtung (1967: 242 ) warned that multicriteria instruments should be easily understood by their prospective users, since otherwise they would not be used at all.

Starting from these general considerations attribution of weights to the criteria used in ISPI had to take into account the specific experience of one-reason decisions of the TBA case law: Due to this one-reason approach the criteria applied in the case law are always, or at least: usually observed isolated from other criteria. Furthermore, the criteria are always found in a winning function, the loosing criteria not even being explicitly mentioned. Therefore, no consistent ranking, or different weight of single criteria, or groups of criteria could be conclusively derived from empirical observations of the past TBA case law. Since ISPI was conceived in order to replicate past TBA case law results in a safe way, this basic finding suggested that each individual criterion should be attributed equal weight as all other criteria: On the basis of the one-reason approach observed in past decisions of the TBAs no criteria, or group of criteria consistently surfaced to generate more decisive power than other criteria, or groups of criteria. Therefore, in the context of assessing inventive step under Art. 56 EPC based on exclusively rational reasoning a consistent attribution of different weights to different criteria, or groups of criteria could not be discovered and proposed for further use by the authors.

3.4 Aggregation / combination procedure

To be accepted by the relevant practitioners, a multicriteria instrument should be easily understood by these practitioners. The instrument should make sense to the user apart from its mathematical mechanisms (Galtung, 1967, p. 242 ). ISPI therefore applies the classical procedure of Simple Additive Weighting (SAW), which is probably the most widely used MCDA method. In the present context this method of aggregating has the great advantage to make immediate sense to users i.e. is easily understood by the non- statistician, legal or patent practitioners. This linear weighted sum

V(x) = Σ wi vi (xi)

can be realistically assumed to provide a good overall measure of inventive performance, where xi: attributes / criteria, wi : weights, and vi: value functions. As already explained, each value function vi (xi) assesses the partial performance of the patent application in attribute xi in an increasing 0-1-2 scale.

As already mentioned this traditional Simple Additive Weighting (SAW) of individual scores allows compensation from one criterion to another: Since the final score obtained by ISPI is based on summation, the assessed patent application may compensate poor scores on a particular criterion x1 by better scores on other criteria xn. Thus, ISPI functions essentially on a balance-sheet mechanism where positive and negative performances on different attributes of the assessed invention are equally considered.

We are aware that even within this balance-sheet mechanism it is not excluded that particular criteria are attributed higher (or: lower) scores than they would realistically merit under the influence of a good (or: bad) general impression of the assessed patent application This halo effect can be reduced, but not radically excluded, by selecting and using independent criteria for assessment ( Thorndike 1920, Rosenzweig 2007, see infra Section 4).

4. Material and Methods

4.1 The test cases:

To avoid particular difficulties of the raters in understanding the underlying technical facts, both test cases of our investigation were chosen from the field of (relatively) trivial mechanical engineering. Two different test cases were assessed by the participants, one of which resulted in the grant of a patent, the other in final rejection of the patent application, both reversed the decision of the first instances (examination, or opposition division).

Test case A: TBA 176/84 - Pencil sharpener / Möbius, in re Möbius; Examination division 14.3.84: Application rejected; appeal of the applicant 10.5.84, decision of the appeal board 3.2.1 on 22.11.85: Patent granted (technical details: OJ EPO 1986, 50 = Dolder, 2003:124, case 23).

Test case B: TBA 144/85 - Stitching device, Examination division 13.1.1982: patent granted, two oppositions I and II, opposition division 9.4.1985 interlocutory decision: patent upheld in part, board of appeal 25.6.1987: Patent revoked (technical details: Dolder, 2003: 100, case 21).

In the first test case TBA 176/84 - Pencil sharpener / Möbius, inventive step was confirmed and a patent granted on appeal by the applicant. The TBA classified the application as a transfer, or substitution of elements from one technical area (sharpening of pencils) to another technical area (security mechanisms for savings-box slots) The board ruled that these two specialities were connected only by the general field of container closing and that the distance between the two specialities was as large as to confer inventive step to the surpassing of this distance:

5.3.2 In the present case, even adopting the same premise as the Examining Division that the person skilled in the art by abstracting the problem would eventually, in his search for suggestions as to how he might solve the problem underlying the application, turn to the broader, that is to say general field of container closing, while he would then have entered what the Examining Division considers to be the generic field, he would not have reached the field of securing mechanisms for savings-box slots. In view of the technological differences between the two fields - storage of coins in a container as opposed to sharpening of pencils with provision for collection of shavings - there is no reason why it should occur to a skilled person to refer to this specific area - which the Examining Division considers to be part of the same broader field - to see how similar problems had been solved there. (....)

5.3.4 The field of such securing mechanisms is therefore not one of the neighbouring fields to which a skilled person concerned with the development of pencil sharpeners would also refer, should the need arise, in search of appropriate solutions to his problem.

5.4 In terms of what is therefore the sole relevant state of the art for pencil sharpeners, the subject-matter of Claim 1 accordingly involves an inventive step under Article 56 EPC as has been shown.

In the second test case TBA 144/85 - Stitching device inventive step was denied by the TBA and the patent revoked in its entirety. The Board ruled that the teaching of the application was only a compilation of known elements resulting in a mere addition of these elements not achieving any combinatorial (synergistic) effects.

4.7 Therefore claim 1 contains in its essential part a series of items which are all known in the same special field to which the general part belongs and make use of their equally known advantageous properties in their predetermined way. Although these partial effects contribute to improve (optimise) the handling of the stitching element, this does not result - contrary to the allegation of the patentee - in a combination effect in the sense that a surprising, not predictable effect representing more than the sum of the individual effects is achieved. The said items display exclusively their specific predetermined effect without influencing each other (....) In a general way, as disclosed by the patentee, the slider can be brought into the fastening position without a ramp (ascent piece) - although with increased manual power. Therefore the ramp (ascent piece) is neither a condition for the positioning of the ending border (ledge), nor does it contribute with this ending border (ledge) to a surprising total effect.

4.8 Based on these findings it can be said that the object of Claim 1 is obvious to a person skilled in the art having regard to the state of the art and accordingly does not involve an inventive step in the sense of art. 56 EPC. (....)

4.2 Organisation of the investigation

The test case Stitching device was assessed by seven groups of students involving a total of 188 individual raters, while the test casePencil sharpener was assessed by nine groups of students involving a total of 201 individual raters. Control group X assessing the test case Pencil sharpener with unstructured procedures comprised a total of n = 189 raters.

For practical reasons, university students acted as raters/assessors, since it would have been impossible to recruit equally large samples of persons (of n = 200) consisting of experienced professional raters (i.e. patent examiners and patent attorneys). Besides this practical reason, it was the intention of the authors to validate ISPI not only as an instrument for professionals with long-term experience, but also to explore its potential as an educational tool for familiarising students with the difficulties of art. 56 EPC. The prospective raters (undergraduate students, mainly of engineering and science) were taught one introductory lesson (45 minutes) on inventive step as a condition of patentability in which the different criteria of assessment were outlined and the structure of ISPI explained. In this introductory lesson students were given a simple model case which they evaluated in small informal groups of four to five and/or in informal discussions with their teachers (Dolder (2003): 79, case 16, T 460/88 of May 21, 1990 - Zentrierring).

In a second lesson (45 minutes) the student raters were asked to assess the application individually and were supplied to this purpose with one of the patent applications to be assessed and the documents of the state of the art as relied on by the EPO examination sections and appeal boards. In addition to this, the documentation at the disposal of the raters included the IPC classification of the patent documents of the cases (for a preliminary report on the organisation see Dolder et al. 2011).

The selected criteria for assessment of the test cases are shown in Table 1 in summary form. The exact wording of the questions to be answered by the raters were described in Dolder (2003). ISPI was shortened for this study to criteria F1 to F5 (formalities), P23.1 to P23.3 (Pencil sharpener), or P21.1 to P21.3 (Stitching device), and A42 to A46 (optional evidence), giving a total of 14 criteria. The maximum scores obtainable were therefore F1 to F5: 8 points, P21 or P23: 6 points, and A42 to A46: 10 points, i.e. a maximum score of 24 points.

Table 1

5. Results

5.1 Independence of criteria

From a theoretical standpoint inter-criteria, or: inter-item correlation, i.e. interdependence of criteria of a multicriteria instrument should be modest and not statistically significant. This is necessary in order to control and reduce artefacts caused by (a) invisible or disguised redundancies of individual criteria and (b) halo effects which could both contribute to exaggerate positive ratings of those objects, which were viewed by the raters in an overall "positive" light (Thorndike 1920, Rosenzweig 2007, Bechger et al. 2010).

To test the criteria used in ISPI the inter-item (inter-criteria) correlation (Pearson) and rank correlation (Spearman) between the scores generated by pairs of criteria were calculated. Since the scores achieved in individual criteria were not likely to be normally distributed, we preferred to use nonparametric rank correlation (Spearman) which are independent of a specific distribution pattern. As expected, the values found for inter-criteria correlation within their groups (intra-group, i.e. F, P,T,and A) were slightly lower as compared with the inter-group correlation. This difference is probably due to aggregating effects within the groups of criteria.

While inter-group rank correlation varied from Rs= -.0596 to .2949 in the pencil sharpener sample (41 raters), they varied from Rs = .1230 to .2602 in the stitching device sample (44 raters). (Table 2.1). In contrast to these findings intra-group rank correlation based on a sample of 85 raters in the two test cases (41 raters, case pencil sharpener and 44 raters, case stitching device) varied from Rs = -.0195 to .1717 (F group) and from Rs = -.0091 to -.2364 (A group), intra-group correlation within the two P groups (P21 and P23) varied from Rs = -.0241 to .3062 (group P 21, 44 raters, case stitching device) and from Rs = -.0526 to .1960 (group P23, 41 raters, pencil sharpener). (Table 2.2 and Table 2.3).

Additional evidence for an only modest interdependence in content between the criteria was found by calculating the rank correlation Rs between any two criteria of a sample of n = 59 raters of the pencil sharpener test case. Of a total of 91 possible Spearman Rs correlation between any two criteria of this data matrix only 8 (8.8%) attained values higher than Rs = +/-(0.3000) and critical values of t > 2.00 at the .05 level of significance (two-tailed test). Of these 8 values only 6 were significant at the .01 level (t > 2.660, two-tailed test).

Table 2

Table 2.2

Table 2.3

H.R. Arkes et al. (2010, 253) staged their empirical investigation of the merits of holistic and disaggregated judgements on seven criteria for 60 randomly selected colleges and universities and determined the absolute value of the largest correlation between any two criteria (characteristics) to be .20, which was not significant (p > .10). Therefore the seven criteria "were deemed to be orthogonal", and therefore held acceptable for experimental use.

Katz / Baitsch (2006) reported correlation for their ABAKABA index for assessing working place requirements with maximum values for inter-group correlation (Pearson's) of .62 and for intra-group correlation .73. These maximum values were considered to by sufficient for assuming independence of the criteria and for practical use of the ABAKABA index ( "als durchwegs gering bezeichnet werden"; "zeugen aber dennoch von einer ausreichenden Unabhängigkeit auch der Einzelmerkmale").

The observed minute inter-criteria correlation found with ISPI index compare advantageously with the correlation found in these previous reports on multicriteria instruments. The criteria used in our investigation were therefore considered to have an acceptable degree of independence from each other and as a practical result were deemed to be sufficient, adequate and suitable for practical use of index ISPI in assessing inventive step in patent applications and potential inventions.

5.2 Inter-rater reproducibility

5.2.1 The instruments

The patent practitioner using ISPI is mainly interested in whether or not the scores obtained with ISPI are accurately reproduced from one individual rater to another. This inter-rater reproducibility of results, representing one aspect of the reliability of the index, can be assessed on the basis of the statistical concordance between the scores obtained by different raters (inter-rater concordance). This concordance is usually measured by Cronbach's Alpha taking into account the ratings obtained from every individual rater for every individual item (criterion), thus establishing a two-dimensional matrix of results. In order to avoid unwarranted assumptions, the nonparametric rank correlation of Spearman were again applied as the basis of the calculations. This was necessary, since a normal distribution of the scores could not be expected ( Cronbach 1951, see supra 2.2).

Cronbach's Alpha is usually applied to measure inter-criteria concordance, but can also be used to measure inter-rater concordance (Cortina 1993). A relatively high inter-rater concordance (a > 0.7) is desirable to indicate sufficient reproducibility of the results of a multicriteria test procedure.

5.2.2 Inter-rater alpha observed

As expected, we found high values (a > 0.9) for inter-rater concordances by Cronbachs Alpha (Table 3). As could also be expected, the values of Cronbachs Alpha increase slightly with the number of raters: Smaller samples (n < 40) resulted in values below 0.95, while both over-all samples of about n = 200 raters each attained a value of around 0.99. (cf. Cortina 1993, 103) It should be noticed that in the context of ISPI relatively small samples of raters with n < 40 seem to be sufficient to obtain a value of inter-rater alpha sufficient and suitable for all practical purposes.

Table 3

5.2.3 Critical Ratio q < 0.5

It should be considered that the set of facts in both test cases were mis-classified once by their respective examination boards before they were re-classified correctly by the TBAs. Both test cases can therefore be considered as borderline cases and therefore as comparatively difficult tasks for assessment. In the light of this constellation of facts the observed highly significant inter-rater reproducibility of the ISPI scores could not be expected prima facie. Therefore, the reliability of the index, as established on this set of test cases, can be considered to be satisfactory for practical purposes and ISPI can be expected to improve inter-rater reproducibility in the assessment of inventive step significantly as contrasted to non-structured holistic procedures.

Based on these findings it is suggested that a multicriteria index used for legal decision making should have a ratio q of inter-item and inter-rater concordance (expressed as Cronbach's Alpha) not exceeding q < 0.5:

q = a (inter-item) / a (inter-rater) < 0.5.

5.3 Distinctive power

5.3.1 Multicriteria vs. one-reason heuristics

The patent practitioner assessing inventive quality with ISPI is furthermore interested whether this method is capable to distinguish between two inventions with regard to inventive step which he could not safely distinguish with unstructured procedures. In other words, he is interested to what extent ISPI is capable to safely detect differences of inventive step bet-ween inventions which he could not safely detect by unstructured procedures, like the one-reason decisions quoted earlier (see supra Section 1).

In the present study this aspect was obviously important since both test cases were borderline cases located near the borderline between presence & absence of inventive step and could obviously not be distinguished safely by unstructured procedures. This latter finding is evidenced by the fact that each test case had been mis-classified in the first decision by the respective examination divisions and the result subsequently reversed by the TBA.

The distinctive power of a diagnostic instrument like ISPI can be assessed by a number of statistical tests which decide whether under a pre-determined level of significance a difference existing in a population is evidenced also as a difference between two samples drawn from this population. They answer the hypothesised question (Ho) whether the observed independent samples (e.g. frequency distributions) have been drawn from the same population (or from populations with the same distribution) and can therefore be consistently distinguished by the diagnostic method applied.

5.3.2 Comparing mean values

In a first step the distinctive power of ISPI was evaluated by comparing the mean values by the t-test assuming that the ISPI ratings of the two test cases had unequal variances and represented normal distributions which is a reasonable assumption for large samples of raters as used in our investigation.

Example # 1: Large number of raters n = 201 and n = 188

Ho: Hypothesised mean difference is 0
Pencil sharpener Stitching device
Total n 201 188
Mean 8.33 5.95
SD 2.44 2.59
degrees of freedom n = 381
test statistics t = 9.3136
critical values of t: 2.5888 (two-tailed) , 2.3362 (one-tailed) , p = .99
1.9662 (two-tailed), 1.6489 (one-tailed), p = .95
Therefore H0 is rejected at both levels of significance.

Given the observed standard deviations (SD) the frequency distributions of the scores in the two test cases showed a considerable area of overlap in small and large samples. However, based on the relatively large number of raters involved the results of the t-test comparing means were significant at both the 0.01 and the 0.05 level. It can be inferred therefore that ISPI had in fact the capacity to distinguish the two patent applications with regard to inventive step in a significant and safe way. In contrast to the fact that both inventions had been mis-classified once by their competent boards of examination and could therefore be considered not to be safely distinguished by unstructured holistic procedures.

5.3.3 Comparing frequency distributions

The Kolmogorov - Smirnov two-sample test answers the practical question whether the cumulative frequency distributions observed in two independent samples can be distinguished assuming a predetermined level of significance. In contrast to the t-test (for comparison of mean values) this test offers the advantage that it does not require the population(s) from which the samples were drawn to be normal distribution(s), but only that the variable under study is continuous (Smirnov 1948, Siegel 1956).

Therefore, the cumulative frequency distributions of the ISPI scores observed in the two test cases Pencil sharpener and Stitching device were calculated for different numbers of raters and the significance of the differences D between the two distributions was evaluated with the Kolmogorov-Smirnov two sample test.

Example # 2

Hypothesis Ho: The two observed cumulative frequency distributions are identical, i.e. they are drawn from the identical population.
Values of the frequency distribution 0 ≤ xi ≤ 15
Test case: Pencil Sharpener Number of raters n1 = 201
Observed: Mean 8.33, SD 2.44
Test case: Stitching part Number of raters n2 = 188
Observed: Mean 5.95, SD 2.59
Two-sample test of Kolmogorov-Smirnov (see Siegel, p. 128, formula 6.10a):

Value observed D = maximum [Sn1 (X) - Sn2(X)] = 0.3785
p < 10 -4 (one sided) p < 10 -4 (two sided)
Levels of significance of D, if n1 = 201, n2 = 188
D = F .SQRT [( n1 + n2) / n1 . n2] = F. SQRT [( 188 + 201) / 188 . 201] = F . 0.1015
1 - α = 0.95 (5 %) : F = 1.36, hence D = .1380
1 - α = 0.99 (1 %) : F = 1.63, hence D = .1654
The maximum difference D between the cumulative frequency distributions observed in the two test cases by large numbers of raters (Example # 2 n 1 = 201, n2 = 188) was equally significant at both the 0.95 (F = 1.36) and the 0.99 level of significance (F = 1.63), while the exact value for p was found to be less than p < 10-4. Hence, it is extremely unlikely that the two cumulative frequency distributions observed in example #2 were drawn from the same population. And therefore, hypothesis Ho could again be safely rejected.

Although the two assessed inventions have a similar case history, and although the mean values of the frequency distributions generated by a large number of raters (Example # 2) are similar (Pencil sharpener mean = 8.33; Stitching device mean = 5.95) and the corresponding standard deviations (SD) are practically identical, applying ISPI to these two inventions results in a statistically significant distinction between the two test cases.

5.4 Selecting a Reference Cut-off Value

5.4.1 Cut-off values in legal decision making

When evaluating a set of facts described by some criteria, there are different kinds of analyses that can be performed in order to provide support to decision-makers. Alternative facts can be arranged in a rankordering allowing to identify the best and the worst alternative; or the alternative facts can be classified or sorted into predefined groups. While rankordering and selecting the best are based on comparative judgements and depend on the considered group of alternatives, the decision-maker applies abstract and predefined reference points for making classification & sorting decisions ( Roy, 1985, Zopounidis et al., 2002).

In legal decision making, the ratings obtained through multicriteria procedures can be used either for comparing and ranking a given set of facts within a group of similar phenomena. Example: Selecting the highest ranking alternative from a group of alternatives, e.g. selecting the best offer within a group of offers from different contractors in public procurement.

On the other hand, the ratings obtained through multicriteria procedures can be applied as a tool for classification and decision making of phenomena without direct comparison within a group of alternatives. In this situation a criteria aggregation model based on absolute judgements is used, which provides a rule for the classification of the alternatives on the basis of reference points (cut-off points) that distinguish the classes (Gaganis et al. 2006). To perform this task, the total scores of the phenomena under assessment are compared with a reference cut-off threshold which is either met or failed. This reference cut-off threshold can be selected inter alia on the basis of past experience, if continuation of this past experience is desired - as is usually the case in legal decision making. Example: Decision on early remission of individual offenders in criminal law based on an assessment of the immanent risk of recidivism (König 2010).

5.4.2 ISPI: From past experience to consistent cut-off values:

The function of ISPI consists in classifying patent applications into two classes which satisfy or fail the statutory requirement of inventive step (EPC Art. 56). The normal approach to address such classification problems is to develop a rule for the classification of the alternatives with one (or more) reference cut-off point(s) which distinguish the classes. (Gaganis et al. 2006, 107/108). Starting from the basic consensus to achieve replication of past decision experience and past decision standards the classification rule with its cut-off threshold t0 can be selected so that the pre-existing classification of applications provided by past experience can be replicated as accurately as possible. The basis of the classification is thus not a ranking or comparison within an existing group of results (scores), but a comparison of a given result (score) with past experience. Based on the ISPI scores of the patent applications as defined by the value function V(xi), their classification into two groups C1 (+) and C2 (-) can be performed in a straightforward way through the introduction of one cut-off threshold t0 such that

V(xi) ≥ t0 « application belongs to group C1 « inventive step (YES)

V(xi) < t0 « application belongs to group C2 « inventive step (NO)

Therefore, in the context of validating ISPI minimising the rate of mis-classifications (as compared to the results of the two template cases, i.e. on past case law) was the obvious approach for determining this cut-off point t0. A mis-classification consisted in a deviation from past decision standards, i.e. non-compliance with the classification rule t0. Based on this common consensus (assumption, i.e. continuation and replication of the standards of past case law), the reference cut-off threshold t0 could be selected empirically: The two test cases decided in the past (pencil sharpener, stitching device) which resulted in opposite decisions (grant - rejection of grant) were assessed by a number of independent raters and the two frequency distributions of the ratings were determined. Of each ISPI rating generated by an individual rater it was known whether it was classified in the past by the TBA as inventive C1 (pencil sharpener), or non-inventive C2 (stitching device). Applying the theory of diagnostic tests (Armitage et al. 2002) to these findings an empirically consistent cut-off value t0 could be selected, which complied with the standards of past decisions of the TBAs of EPO.

5.4.3 Minimising mis-classification through the approach of the ideal observer

Since minimising the rate of mis-classifications (as compared to the results of the two test cases A and B, i.e. on past case law) was the obvious approach for determining the cut-off point t0, the rate of mis-classifications violating the rule of t0 was observed and minimised by selecting the cut-off point through the approach of the ideal observer. Total mis-classification error represents the sum of the rate of false positive (fp) and the rate of false negative (fn) results depending on the particular cut-off point t0. The criterion is based on the assumption that false positive results (fp, &alpha-errors) and false negative results (fn, &beta-errors) in the assessment are equally important from a practical point of view.

This assumption is justified in the present context for two reasons: ISPI is based on the implicit community consensus that the standards for evaluating inventive step applied in the past should be continued and maintained in the future. Thus, mis-classifications in both directions are equally undesired from the viewpoint of continuation. The second reason for assuming equal importance to both types of mis-classifications is based on the empirical observation that the percentage of granted and failed patent applications in European patent prosecution is approximately equal and nearly constant in the long-term, i.e. about equal percentages of grants as compared with rejections and withdrawals of patent applications and revocations of patents granted (EPO 2009). Therefore, the frequency of mis- classifications can also be expected to be similar in both directions.

The approach of the ideal observer based on minimising total mis-classification offers a consistent cut-off point for continuation of the standards of past decision-making. Through this procedure a cut-off point is chosen by relying on the standards of past experience and applying this cut-off point to future cases means to assess new cases by the standards of past decisions.

Table 4.1 shows the frequency of false negative (fn) decisions (b-errors: test case A pencil sharpener) and of false positive (fp) decisions (a-errors: test case B stitching device) in relation to various cut-off points chosen under the rule of the ideal observer. If a cut-off value of t0 = 7 is applied, 49 (24.13 %) false negative decisions are observed in the pencil sharpener case, while 71 (37.76 %) false positive decisions are found in the stitching device case. If however a cut-off threshold of t0 = 8 is applied, the quota of false negative decisions is found to be 76 (37.44 %) of a total of 201 ratings in test case A (pencil sharpener), while the quota of false positive decisions in the test case B (stitching device) is 47 (25 %) of a total of 188 ratings. Therefore the two cut-off values t0 = 7, or t0 = 8 ISPI points are virtually equivalent with regard to complying with the ideal observer 's rule of minimising mis- classifications. Following this line of reasoning a cut-off threshold of t0 = 8, is suggested as a consistent value for future use of ISPI, since a slightly smaller rate of false negative decisions (t0 = 8) is preferred.

Table 4.1

Almost identical cut-off values t0 are obtained if points (scores) instead of individual decisions (results) are used for minimising mis-classification (Table 4.2): Taking the magnitude of the mis-classified scores into account should therefore not change, or influence the choice of the consistent cut-off point to a significant extent.

Table 4.2

The rate of correct/false decisions generated by applying ISPI was compared to the rate of correct/false decisions observed, when unstructured holistic procedures were applied on the same test case. In the pencil sharpener test case A the control group X (189 raters) generated only 65 (34.39 %) correct classifications, while the raters (n1 = 201) using ISPI would have produced 62.19 % correct decisions, if a cut-off point of t 0 = 8 was applied. Therefore, within the limited context of our study the multicriteria decisions were clearly superior to the holistic decisions with regard to avoiding mis-classifications. This finding is in keeping with the research of Gaganis (2006) on assessing the financial soundness of banks and Arkes et al. (2006) on the evaluation of scientific presentations.

Furthermore, the results of Table 4.1 / 4.2 and the classifications obtained by the students with ISPI (i.e. 62.19 % correct classifications in the first round) seem to point to the fact that the expertise contained in IPSI does not only help teaching this essential point of patent law, but that ISPI can enable students to achieve valid assessments of inventive step.

5.4.4 Area under the ROC-curve (ROC-AUC)

Minimising errors by the approach of the ideal observer corresponds to the choice of an optimum operating point in a ROC curve (receiver operating characteristic curve).It remains controversial to what extent the observed area under the ROC-curve (ROC-AUC) can be considered a quality measure of multicriteria instruments. AUC values of .60 have been qualified as not sufficient, while values of .80 were considered to be satisfactory and of .90 to be high (Andrej König 2010). In a different context, a ROC-AUC value of .75 was considered high and indicating that the effect measured was a large size effect (Dolan and Doyle 2000). However, the capacity of ROC-AUC as an instrument to measure the quality of multicriteria instruments is restricted by the fact that the value of ROC-AUC varies according to the size of the effect measured with a particular multicriteria index. Therefore, this parameter can be safely applied for quality measurement of multicriteria instruments only, if the identical set of facts is assessed using a number of different multicriteria instruments and the obtained results from these instruments are subsequently compared.

Under these not yet definitely established theoretical foundations it remains open to discussion which inferences can be drawn from our finding that the area under the ROC-AUC of ISPI was calculated to be .7076 for the selected optimum cut-off value of t0 = 8 (Table 4.1).

It is equally controversial to what extent the observed values of ROC-AUCs are influenced, or falsified by the so called base rate fallacy (Maya Bar-Hillel 1980, D. Kahnemann / P. Slovic / A. Tversky 1982, König 2010, 69-71). However, this effect on ROC-AUC can be neglected, if the long-term base rate is approximately R = 1. This value is achieved in European patent prosecution, since the number of granted and failed patent applications in the EPO is nearly equal and constant in the long-term perspective: about equal percentages of grants as confronted to rejections and withdrawals of patent applications and revocations of patents granted (EPO 2009). Therefore, the effect of base rate fallacy should not be critical for assessing inventive step with ISPI.

6. Formation of groups of patent applications

Patent applications can be classified into more than two groups C1, C2, ....Ci on the basis of their ISPI scores introducing more than one cut-off points ti. (for group formation in different contexts of multicriteria analysis see Gaganis (2006) and Jessop (2001).

In a first attempt for group formation the mean values of 5.95 and 8.33 obtained in the two test cases A and B respectively generated reference points for classifying ISPI scores (i.e. patent applications) into three groups (Table 5). Applications with ISPI scores xi £ 6 (group I, mean xi = 5,95) would indicate a highly probable lack of inventive step, applications with ISPI ratings xi ≥ 8 (group III, mean xi = 8.33) would be relatively safe indicators of positive inventive step, while applications with ISPI ratings in a grey area between 6 < xi < 8 (group II) should be further examined to decide definitely on inventive step.

The selection of the boundaries of the grey area is obvious: Since inventive step is (at least implicitly) based on the perception of more than average performance, it would seem reasonable that ISPI scores higher than the mean value in a case found to be inventive by the court in the past (test case A) could safely be qualified to be inventive. It would seem equally indicated that ISPI scores lower than the mean score of a case found to be non- inventive (test case B) could be qualified safely to be non-inventive.

Table 6

An alternative approach to generate multiple cut-off points ti. could follow the standard procedure of the first round of Delphi assessments to sort out values by means of the quartile values of their respective frequency distribution (Sackmann (1974): 45 - 49, Scheibe et al. 1975: 277, Kern, W. / H.-H. Schröder, 1977: 152/153).In our sample of test cases A and B the upper limit of the third quartile (Q3) of the scores of test case A would form the upper boundary (xi = 9.545), while the value of the first quartile (Q1) of the data of test case B (xi = 3.722) would form the lower boundary of the grey area.

This classification of patent applications into three different groups based on multicriteria scores corresponds with a classification of cases into three categories with regard to conforming with statutory terms as proposed by Koch / Rüssmann (1982): 194 based on normative reasoning (Drei-Bereiche-Modell:). A first group of cases complying safely with the requirements of the statute (positive candidates), a second group missing the requirement (negative candidates), and a third intermediary group (neutral candidates) which cannot be assigned in a first round safely to either group and should therefore be evaluated with additional procedures

7. Discussion

The present study was performed in order to validate empirically the properties of ISPI as an instrument for improving reliability (reproducibility) in assessing inventive step of patent applications as compared to one-reason decision making. As expected, the features of ISPI which were studied proved to be efficient for performing their functions: Independence of the applied criteria, inter-rater reproducibility of results, and distinctive power.

The essential advantage of assessing inventive step by ISPI as compared to unstructured holistic methods, may be found in the consistent constraint for completeness and standardisation exerted on the decision-maker. This constraint towards completeness requires the rater to assess a relatively large number of relevant criteria and should prevent him from taking one-reason decisions using one single criterion of reasoning.

The multicriteria instrument ISPI can improve reliability (reproducibility) in assessing inventive step, but will not eliminate all controversies in legal decision making related to this topic. However, the remaining controversies should be considerably reduced in number and limited in scope to a small number of critical issues in a specific case. This could improve the quality management of decisions on inventive step as compared to controversies related to inventive step arising from unstructured holistic procedures, i.e. one-reason decisions.

The present investigation could be extended in various directions, such as introducing different technology-specific criteria into ISPI reflecting the special technological environment in different scientific specialities. Furthermore it is obvious that ISPI could not only be used in legal decision making arising in patent prosecution and patent litigation, but also in valuing patent assets for financial transactions. In our opinion, the potential of multicriteria instruments for legal decision making has not been adequately recognised so far. It has not escaped our attention that in a number of other legal areas containing difficult statutory expressions multicriteria analysis could find additional applications and improve the accuracy and reproducibility of decisions.


The authors gratefully acknowledge valuable advice from two reviewers in the course of peer review of the paper.

Arkes HR / Claudia Gonzalez-Vallejo, Aaron J. Bonham, Yi-Han Kung, Nathan Bailey 2010, Assessing the merits and faults of Holistic and Disaggregated Judgments, Journal of Behavioral Decision Making 23: 250-270.

Arkes HR, Victoria A. Shaffer, Robyn M. Dawes 2006, Comparing holistic and disaggregated ratings in the evaluation of scientific presentations, Journal of Behavioral Decision Making 19: 429-439.

Armitage P. / G. Berry / J.N.S. Matthews 2002, Statistical Methods in Medical Re-

search , 4th ed. Oxford etc., p. 697.

Bar-Hillel M. 1980, The base-rate fallacy in probability judgments, Acta Psychologica 44 (), 211-233.

Bechger TM., Gunter Maris, and Ya Ping Hsiao 2010, Detecting halo effects in performance-based examinations, Applied Psychological Measurement 34, 607- 619

Bryant, Chris, 1997, Stafford Cripps, The first modern Chancellor, London 1997, 60-62.

Büttner J. 1993, in: Evaluation Methods in Laboratory Medicine (ed. R. Haeckel), Weinheim etc., p. 27 f.

Cortina JM. 1993, What is coefficient Alpha ? Journal of Applied Psychology 78, 98-104.

Cronbach LJ. 1951, Coefficient Alpha and the internal structure of tests, Psychometrika 16, 297 - 334;

Dawes R.M. 1979, The robust beauty of improper linear models in decision making. American Psychologist 34 , 571-82

Dolan M., M. Doyle 2000, Violence risk prediction, British Journal of Psychiatry 177, 303-311, 304/5.

Dolder F. 2003, Erfindungshöhe, Köln etc. 2003, Catalogue of criteria: pp. 332. application of the Delphi technique in assessing non-obviousness of patent applications: p. 339.

Dolder F., Ann Ch., Buser M. 2011, Beurteilung der Erfindungshöhe mit Hilfe eines additiven multi-item Indexes, GRUR 113, 177- 183

Duhigg C / Steve Lohr 2012, An arms race of patents, NYT International Weekly, 15. October 2012, , page 4.

European Patent Office 1986, Test cases: Case pencil sharpener: EP 031 470 (Pencil sharpener), T 176/84 - pencil sharpener / Möbius OJ EPO 1986, 50 = GRUR Int. 1986, 265 = Dolder, ibid. case 23, p. 124.; State of the art: DE-C- 1 003 093 (pencil sharpener), DE-A- 2 513 051 (pencil sharpener), DE-C- 1 960 978 (securing mechanism for savings-box slots);

Case stitching device: EP 011 819 (stitching device). T 144/85 - stitching device = Dolder, ibid. case 21, p. 100 - 112.state of the art: GB-A-1 417 580, DE-U-7 118 031.

European Patent Office 2009, Annual Report, lists 134'542 applications filed (Euro and Euro-PCT), 102'178 European examinations and 51'696 patents granted in 2009 (p. 62/63). Cases settled by TBAs in 2009: 1918, allowed (in part) 740 (38.6 %), dismissed 589, otherwise (e.g. withdrawal) 589; based on opposition procedures (inter-partes): cases settled 1116, allowed (in part) 508 (45.5 %), dismissed 337, other 271 (page 41). Opposition procedures: Patent revoked 43.6 %, patent maintained in amended form 30.1 %, opposition rejected 26.3 % (page 19).

Gaganis Ch., F. Pasiouras and C. Zopounidis 2006, A MCD Framework for measuring banks' soundness around the world, Journal of MCDA 14, 103-111.

Galtung, Johan, 1967, Theory and methods of social research, Oslo 1967, p. 242.

Gigerenzer G. 2007, Bauchentscheidungen, München 2007, 13 ff.

Jessop A. 2001, Multiple attribute probabilistic assessment of the performance of some airlines, in: M. Köksalan, S. Zionts, Multiple criteria decision making in the new millenium, Lecture Notes in Economics and Mathematical Systems, Vol. 507, Berlin etc.: Springer 2001, 417-426.

Kahnemann D. / P. Slovic/ A. Tversky 1982, Judgement under uncertainty: Heuristics and biases, Cambridge 1982, p. 153-160.

Katz, Christian P., Christof Baitsch, Arbeit bewerten - Personal beurteilen, Zurich 2006: "Wissenschaftlich lässt sich unterschiedliche Gewichtung kaum je begründen" (p. 18).

Kern, W. / H.-H. Schröder, 1977, Forschung und Entwicklung in der Unternehmung, Reinbek 1977, p. 152 /153.

Koch H-J / Helmut Rüssmann 1982 , Juristische Begründungslehre, München 1982, pp. 194- 201

König A. 2010 Der Nutzen standardisierter Risikoprognoseinstrumente für Einzelfallentscheidungen in der forensischen Praxis. Recht & Psychiatrie 28: 67-73, 68.

Ravinder H.V. 1992, Random error in holistic evaluations and additive decompositions of multiattribute utility - An empirical comparison, Journal of Behavioral Decision Making 5: 155-167.

Ravinder H.V., Don N. Kleinmuntz 1991, Random error in additive decomposition of multiattribute utility, Journal of Behavioral Decision Making 4: 83-97 (1991).

Rieskamp J. / U. Hoffrage 1999, When do people use simple heuristics, and how can we tell ? in: G. Gigerenzer / P.M. Todd, Simple heuristics that make us smart, New York/Oxford 1999, p. 141 ff.

Rosenzweig, P. 2007, The halo effect, New York etc. 2007

Roy, B., 1985. Méthodologie Multicritère d'Aide à la Décision. Economica, Paris.

Sackmann, H., Delphi Assessment: Expert opinion, forecasting, and group process, RAND Santa Monica 1974 (R-1283-PR).

Scheibe M. / Skutsch, M. / Schofer, J. 1975, Experiments in Delphi methodology. In: Linstone, H.A., Turoff, M. (eds.): The Delphi Method: Techniques and Applications. Addison-Wesley, Mass. 1975.

Siegel S. 1956, Nonparametric statistics for the behavioral sciences, New York etc. 1956: McGraw-Hill, p. 127- 136.

Smirnov, N. 1948, Table for estimating the goodness of fit of empirical distributions, Annals of Mathematical Statistics 19 ,279-281.

Thorndike E L. 1920, A constant error in psychological ratings, J. Appl. Psychology 4, 25-29.

Zopounidis, Constantin, and Michael Doumpos 2002, Multicriteria classification and sorting methods, European Journal of Operational Research 138, 229-246

[1] Prof. Dr.iur., University of Basel, Switzerland

[2] Prof. Dr.iur. Chair for Corporate and IP Law, Munich Technical University, Germany

[3] Dr.phil.nat, Nonparametric Statistics, Basel, Switzerland