Innovation and Patenting within Containerized Liner Shipping

Increasingly, in many industries, companies commercialize their technology and innovations through patenting to gain an edge over competition. Within the maritime sector, while literature on innovation is expanding, issues related to the importance of intangible assets, such as patenting, for the participant firms of the industry remain unaddressed. Utilizing innovational frameworks and patent data withdrawn from European Patent Organization’s (EPO’s) database, the aim of this paper is to investigate the innovative level, in terms of patents granted, of incumbent market actors in liner shipping. Apart from patent counts, this exercise sheds light on the areas to which these patents apply, providing a classification while also investigating additional attributes which relate to patent citations, investors and applicants. Although results indicate a varying degree of utilization of the patenting system amongst liner carriers, they nonetheless affirm to some extent that knowledge creation is a valuable tool in the arsenal of some liner carriers, and that patenting is one of the various means utilized to enhance their market position and achieve a sustained competitive advantage. In addition, findings suggest that liner carriers’ innovative efforts have, based on the forward citations received, some significance, while they focus primarily the development of patented technologies which enhance the operational efficiency of their vessels. In this respect, the investigation undertaken sheds some light and provides a novel perspective on understanding the behaviour and innovative propensity of liner shipping companies.

Predicting the Potential Applicability to Other Technical Fields Through the Linkage Between Backward and Forward Citations

This article is a modest attempt to shed some light on the question of linkages between backward and forward citations in technical fields posed by Trajtenberg et al. (1997). They found interesting similarities and high correlations between equivalent measures looking forward and backward. They also implied the linkage between distant backward and distant forward citations. There are several questions to be posed in applying their insights to Japanese patent applications, however, due to the differences in the patent classification system and the subject of citation, i.e., citations by the applicant or examiner, between the US and Japan. In addition, and most importantly, the possibility that subsequent classifications may match, even if the first classification is different, is unavoidable with existing measurement methods of technical distance. In order to investigate these research questions, the author proposes a new measurement method for the technological proximity between examiner’s citations and their originating patents using IPC-based patent classifications. Using such a proposed method, the author created two hypotheses and tested them for about 14,000 examined patent applications filed in 2008 with the JPO. As a result of testing Hypothesis I, the author confirmed that Trajtenberg et al.’s insights can be applied to Japanese patent applications using citations by the examiners and IPC-based patent classifications. In other words, it was confirmed that patent applications citing backward citations categorized in a technical field distant from the invention are more likely to be cited by forward citations categorized in a technical field distant from the invention. As a result of the verification of Hypothesis Ⅱ, it was further confirmed in some technical fields that the backward citations categorized in a technical field distant from the invention are more likely to be in the same technical field as the forward citations categorized in a technical field distant from the invention. The author believes that these verified results indicate the possibilities of using backward citations as a starting point from which we can find patent applications for inventions at an early stage with potential applicability to other technical fields.

Effects of knowledge spillovers between competitors on patent quality: what patent citations reveal about a global duopoly

This paper analyses the effects on patent quality of a type of spillovers arising from the disclosure of patent information by firms engaged in competition in a global duopoly. Both firms are involved in producing new technologies and they do not cooperate on joint patents. In this context, we explored whether the disclosure of crucial knowledge in the patents of one of the firms affects the patent quality of its respective competitor. The empirical methodology relies on forward citations as an indicator of quality, and backward citations to the competitor as a measure of spillovers. We estimated several count models with a sample of 7750 patent families (divided into subsamples) owned by two large companies, Airbus and Boeing. Our econometric findings show that, for technologies in which the two firms account for the majority of the global patents, neither of the firms in the duopoly was able to harness spillovers from the rival to improve the quality of its patents. However, knowledge from the competitor becomes relevant, at least for one of the focal firms, in explaining patent quality of other technologies in which the two firms do not exert a dominant position.

Patent Valuation Using Citations: A Review and Sensitivity Analysis

As a result of studies demonstrating a correlation between a patent’s value and its forward citation count, patent valuation using forward citations has been increasingly used by practitioners when a patent’s value has not been otherwise established. Although potential limitations of patent citation analysis have been discussed in the past, there is little empirical research demonstrating the sensitivity of estimated patent values to various assumptions embedded within the method. We first summarize an approach that has been used by prior practitioners to estimate the relative value of patents within a portfolio using forward citations, and then perform various analyses to investigate the sensitivity of the approach to certain assumptions. We find that some concerns of prior literature are well-founded, while others are less so. For example, we confirm that biased valuations will result from failure to properly control for patent age and technology. Our analysis also finds that truncation bias is a problem when analyzing recently issued patents, which confirms findings from existing literature. We estimate the rate at which such truncation bias dissipates as patents age and find that the bias for the median patent is reduced to below 10% within five years from the date of publication, although additional variation can remain on an individualized level. Regarding the issue of self-citations, we find that the valuation approach using forward citation analysis can be (but is not always) sensitive to the issue of self-citations, with a median difference of 16.8%. Finally, the valuation approach using forward citation analysis appears to be robust to assumptions underlying patent cohort construction.

A measure of innovation performance: the Innovation Patent Index

PurposeThe measure of companies' Innovation Performance is fundamental for enhancing the value and decision-making processes of firms. The purpose of this paper is to present a new measure of Innovation Performance, called Innovation Patent Index (IPI), which makes it possible to quantitatively summarize different aspects of firms' innovation.Design/methodology/approachIn order to define the IPI, a secondary source, i.e. patent data, has been used. The five dimensions of IPI, i.e. efficiency, time, diversification, quality and internationalization have been defined both analyzing the literature and applying three different machine learning algorithms (regularized least squares, deep neural networks and decision trees), considering patent forward citations as a proxy of the innovation performance.FindingsResults show that the IPI index is a very useful tool, simple to use and very promptly. In fact, it is possible to get important results without making time consuming analysis with primary sources. It is a tool that can be used by managers, businessmen, policymakers, organizations, patent experts and financiers to evaluate and plan future activities, to enhance the innovation capability, to find financing and to support and improve innovation.Research limitations/implicationsPatent data are not widely used in all the sectors. Moreover, the pure number of forward citations is not the only forward looking indicator suggested by the literature.Originality/valueThe demand for a useable Innovation Performance tool, as well as the lack of tools able to grasp different aspects of the innovation, highlight the need to develop new instruments. In fact, although previous studies provide several measures of Innovation Performance, these are often difficult for managers to use, do not appreciate different aspects of the innovation and are not forward looking.

STATE OWNERSHIP AND INNOVATION: THE RELATIVE MERITS OF LOCAL AND CENTRAL STATE JUDGED BY INNOVATION PERFORMANCE

This paper compares the innovation performance of state-owned firms owned by different levels of government, with that of privately owned firms. Analysis of a 116-firm panel dataset for the Chinese solar photovoltaic industry from 1999 to 2015 suggests that government’s financial support increases the quantity of innovation outputs. However, the efficiency in utilising the financial resources is determined by the effectiveness of agency relationships. Applying agency theory to the Chinese politico-economic context indicates that innovation quality depends on length and complexity of agency chains, engagement of monitors, and the tenure of managers. By using forward citations and proportion of patents in active use, two measures of innovation quality that are more valid and reliable than patent counts, our study finds that municipally owned firms are superior in terms of innovation productivity to those under central ownership, and comparable to private firms.

Measuring Patent Value Indicators with Patent Renewal Information

This paper attempts to fill a research gap of literature by constructing the dynamic model into which both ex ante and ex post patent value indicators are incorporated. A patent renewal model is tested using a large set of Pharmaceutical patents granted by the European Patent Office between 1996 and 2009. We test five ex ante indicators and single ex post indicator including family size, patent backward citations, backward references to non-patent literature, number of claims, number of inventors, renewal fee, patent age, application year, and the ex post indicator forward citations. Empirical findings show that three citation related indicators, family size, and the number of claims are positively associated with patent values, while the number of inventors, renewal fee, patent age, and application year are negatively correlated. In addition, forward citations seem to have persistent learning effects on patent values.

Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks

Modeling and forecasting forward citations to a patent is a central task for the discovery of emerging technologies and for measuring the pulse of inventive progress. Conventional methods for forecasting these forward citations cast the problem as analysis of temporal point processes which rely on the conditional intensity of previously received citations. Recent approaches model the conditional intensity as a chain of recurrent neural networks to capture memory dependency in hopes of reducing the restrictions of the parametric form of the intensity function. For the problem of patent citations, we observe that forecasting a patent's chain of citations benefits from not only the patent's history itself but also from the historical citations of assignees and inventors associated with that patent. In this paper, we propose a sequence-to-sequence model which employs an attention-of-attention mechanism to capture the dependencies of these multiple time sequences. Furthermore, the proposed model is able to forecast both the timestamp and the category of a patent's next citation. Extensive experiments on a large patent citation dataset collected from USPTO demonstrate that the proposed model outperforms state-of-the-art models at forward citation forecasting.

Patentometric: monitoring the scientific and technological trends of Additive Manufacturing in Medical Applications

<p>Patents are a means of protecting inventions developed by firms, institutions or individuals, and they may be interpreted as indicators of invention. Patents indicators convey information on the processes of inventive activities. Therefore, patent statistics will assess science and technology (S&amp;T) activities. Besides, additive manufacturing (AM) has become a revolutionary technology that is changing medical science. For this reason, the patent statistics will allow us to monitor what is the state of the inventive activity of AM in medical applications. The database used in order to retrieve patent information is Patseer and the data have been analyzed through the analytics package called Quick Stats. From the data obtained, it can be concluded that, additive manufacturing in medical applications is an emerging technology with huge market potential. Undoubtedly, the core of invention is located in United States, followed by Germany, United Kingdom and China somewhat behind. Firms are the main holders of legal rights, and the firm’s market value and the knowledge diffusion of technology are ensured by the technological diversity and the number of forward citations presented by patents.</p>