**3.3. Relationships between features of scientific papers and their citedness from all/ high-feature-valued patents**

In this subsection, I explored which features of papers affect their citedness from patents to grasp basic nature of patent-paper citations which might influence the nature of indicators presented in the following sections. Since we utilized information on patent-patent citations in which patents citing papers obtained, the analysis in this section was executed for Period 1 (PY1998–2000) in **Figure 1**.


**Table 4.** Result of logistic regression of rate of patent-paper citations.

**Independent variable Coefficient Std. err Z value Pr(>|z|) Signif. codes**

citations to distinguish it from other kinds of citations), and patent generality index. They are three of the four components of "composite index 4" presented in [8]. "Claims," which was the rest of the four, was not included in the study because it was not included in the Patstat comprehensively (only the US patents and European patents comprehensively included it exceptionally). As for "patent-patent forward citations," a dummy variable which distinguished whether patents obtained the top 1% of citations from other patents or not (it was presented as a "breakthrough" indicator in [8]) was used. The percentile of patent-patent cita-

Here, logistic regression analysis, of which independent variables were three patent feature values mentioned above, was executed. "Granted" flag in TLS201\_APPLN table in the Patstat was selected as dependent variable, since it should represent an aspect of patent quality. Please note that this analysis was executed in the initial stage of the study before the specification of dataset was decided; therefore, all types of patents (such as utility models) were

The results are shown in **Table 3**. All coefficients of the three independent variables were significant at 0.1 percent level. Two of them (patent family size and patent-patent forward citations) were positive, and the rest was negative. As far as grant of patents was regarded as representative of patent quality, the former represents some aspects of patent quality. Patent family size could be thought of as quality assessed by applicants themselves (self-assessed quality), since "applicants might be willing to accept additional costs and delays of extending protection to other countries only if they deem it worthwhile" (p. 14) [8], while patent-patent forward citations could be deemed as quality assessed mainly by other applicants or examiners. On the other hand, the patent generality index seemed not to represent patent quality in

**3.3. Relationships between features of scientific papers and their citedness from all/**

In this subsection, I explored which features of papers affect their citedness from patents to grasp basic nature of patent-paper citations which might influence the nature of indicators presented in the following sections. Since we utilized information on patent-patent citations in which patents citing papers obtained, the analysis in this section was executed for Period 1

Intercept 0.474038 0.004213 112.51 <2e-16 \*\*\* Patent family size 0.257991 0.001038 248.62 <2e-16 \*\*\* Patent-patent forward citation (Top 1%) 0.029541 0.000276 107.02 <2e-16 \*\*\* Patent Generality Index −0.188278 0.006765 −27.83 <2e-16 \*\*\*

Signif. codes: "\*\*\*" 0.001, "\*\*" 0.01, "\*" 0.05, "." 0.1, ""1.

included.

158 Scientometrics

the aspect of patentability.

**high-feature-valued patents**

(PY1998–2000) in **Figure 1**.

**Table 3.** Result of logistic regression analysis of patent feature values.

tions was calculated by each of the 35 technology fields defined in [10].

I tried to include broad feature values of papers which might affect their citedness from patents as widely as possible to grasp characteristics of patent-paper citations comprehensively. Six feature values (document type, international co-authorship, impact factor (hereafter IF), paper-paper citations, institutional sectors and disciplines) shown in **Table 4** were selected from [13]. In **Table 4**, the variable "Review" and "Int-Coauthored" represents the feature value "document type" and "international co-authorship," respectively, and the variables "University" to "Other" and "AGS" to "SSS" represent "institutional sectors" and "disciplines," respectively.

flag, it might show a statistically significant difference if difference of countries was taken into account. However, the number of international co-authored papers was limited, so we did not

Exploring Characteristics of Patent-Paper Citations and Development of New Indicators

http://dx.doi.org/10.5772/intechopen.77130

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IF showed positive relationships with all kinds of patent-paper citations. This result reinforced analysis of Guan and He [14]. They showed nine of ten journals most frequently appeared as non-patent literatures in Chinese inventors' US patent were ranked within the top ten in their categories in the Journal Citation Report. Therefore, papers published in prestigious journals

The top 10% of paper-paper citations also showed positive relationships with all kinds of

Institutional sectors showed some interesting tendencies; corporations showed relatively strong tendencies to be cited from all four kinds of patents ((a)-(d)). Although university and public institutes tended not to be cited from patents generally, they were not so from patents with high patent generality indexes. Latter tendencies might be explained that universities and public institutes produce generic knowledge, not focus on specific industrial applica-

As for disciplines, some of the life sciences (biology and biochemistry, immunology, microbiology, molecular biology and genetics, pharmacology and toxicology) showed tendencies to be more cited (than clinical medicine, which was a reference discipline), while most physical sciences (engineering, materials science, physics) showed opposite tendencies. Similar results were reported in previous studies, such as [11]. However, it also showed some interesting tendencies when citations from high-feature-valued patents were focused on. For example, computer science tended to be more cited relatively, while they tended to be less cited from large patent families; engineering and materials science tended not to be cited from patents, while they tended to be cited from patents of top 1% patent-patent forward citations; microbiology showed an opposite tendency in that they tended to be cited from patents, while they tended not to be cited from patents of top 1% patent-patent forward citations. What caused such differences? To answer this question, further investigation from the patent side is needed.

**4. Improvement of the patent-paper citation index (PPCI) (analysis 2)**

In the previous study, we proposed an impact indicator of patent-paper citations, named patent-paper citation index (PPCI) [9]. PPCI is based on rates of the papers cited from patents in the targets' publications. We proposed a method to overview targets' research activities from both scientific and technological impacts compared to the world average by using normalized citation impact (NCI) [13] in combination. Differences in both document types and disciplines were ignored in the previous study [9]. However, the analysis in Section 3.3 revealed their effects on papers' tendencies to be cited from patents. Therefore, I propose an improved ver-

tended to be more cited than those published in lesser known journals.

patent-paper citations, as many previous studies [5, 6, 11].

tions, so patents citing them tended to also have a generic nature.

divide them into specific countries.

**4.1. Definition of improved PPCI**

sion of PPCI in this section.

I executed logistic regression analyses of which independent variables were six feature values of papers mentioned above and dependent variables were distinct from whether papers were cited from (all or high-feature-valued) patents (1) or not (0). To ignore the shape of distributions of patent-paper citations, I discarded information on the number of citations but used distinction of cited or not.

IFs were obtained from the Journal Citation Reports produced by Clarivate Analytics. Since IFs changed every year, years of IFs were defined as publication years of papers. This was because I intended to use them as the journals' quality indicators independent of the target papers. IFs in a year Y were calculated using papers published in years Y-1 and Y-2; therefore, they did not contain the target papers in the calculation. As it was well known, values of IFs differed largely by discipline; therefore, they were normalized by the following process: (1) IFs were attributed to each paper in the WoS (but IFs could not be given to some papers exceptionally); (2) mean values of IFs attributed to papers by ESI discipline were calculated for each year; (3) IF attributed to each paper was normalized by mean IF of its ESI discipline.

The threshold values of feature values of patents were decided according to the criteria: number of papers cited in high-feature-valued patents should be almost the same. As the number of papers cited from the top 1% patent-patent forward citation patents was predetermined, it was used as the reference value of number of papers cited from high-feature-valued patents. Threshold values were set to 15 for patent family size, 0.85 for patent generality index. Therefore, patents of which patent-patent forward citations were within top 1% or patent family sizes or patent generality indexes were equal to or more than the abovementioned thresholds were defined as high-feature-valued patents in this study.

Document types "Article" and discipline "Clinical Medicine (CLM)" were set to reference, since they were classified exclusively.

The results of the logistic analyses were shown in **Table 4**. Since patent-paper citations from high-feature-valued patents ((b), (c), (d)) were subsets of the whole patent-paper citations, they showed somewhat similar tendencies.

As for document type, reviews showed positive relationships to probabilities of being cited from both patent ((a)) and all three types of high-featured-valued patents ((b)-(d)). The result on patent ((a)) reinforced the result by Hicks et al. [11]. This result showed that indicators should be weighted by document type as far as possible.

International co-authorship showed no statistically significant relationship to any kinds of paper citedness. While Japan's co-authorships with any country were combined into the same flag, it might show a statistically significant difference if difference of countries was taken into account. However, the number of international co-authored papers was limited, so we did not divide them into specific countries.

IF showed positive relationships with all kinds of patent-paper citations. This result reinforced analysis of Guan and He [14]. They showed nine of ten journals most frequently appeared as non-patent literatures in Chinese inventors' US patent were ranked within the top ten in their categories in the Journal Citation Report. Therefore, papers published in prestigious journals tended to be more cited than those published in lesser known journals.

The top 10% of paper-paper citations also showed positive relationships with all kinds of patent-paper citations, as many previous studies [5, 6, 11].

Institutional sectors showed some interesting tendencies; corporations showed relatively strong tendencies to be cited from all four kinds of patents ((a)-(d)). Although university and public institutes tended not to be cited from patents generally, they were not so from patents with high patent generality indexes. Latter tendencies might be explained that universities and public institutes produce generic knowledge, not focus on specific industrial applications, so patents citing them tended to also have a generic nature.

As for disciplines, some of the life sciences (biology and biochemistry, immunology, microbiology, molecular biology and genetics, pharmacology and toxicology) showed tendencies to be more cited (than clinical medicine, which was a reference discipline), while most physical sciences (engineering, materials science, physics) showed opposite tendencies. Similar results were reported in previous studies, such as [11]. However, it also showed some interesting tendencies when citations from high-feature-valued patents were focused on. For example, computer science tended to be more cited relatively, while they tended to be less cited from large patent families; engineering and materials science tended not to be cited from patents, while they tended to be cited from patents of top 1% patent-patent forward citations; microbiology showed an opposite tendency in that they tended to be cited from patents, while they tended not to be cited from patents of top 1% patent-patent forward citations. What caused such differences? To answer this question, further investigation from the patent side is needed.
