# Analysis on Port and Maritime Transport System Researches

Authors: Lingshan Chen; Xiang Xu; Ping Zhang; Xiaotian Zhang
Journal: Journal of Advanced Transportation
 (2018)

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## Abstract

This paper examines the past and current research in the container port and maritime field. Using rigorous bibliometric analysis, the paper identifies the core authors/affiliations, their rankings, and collaboration patterns. The analysis of the paper will enable new researchers to quickly build an understanding of the container port and maritime field by reading core authors’ papers published in specific journals.


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## Body

## 1. Introduction

The maritime industry has made great contributions to the world economy in recent decades. The “Maritime Review by 2015” reported by the United Nations Conference on Trade and Development (UNCTAD) shows that nearly 80% of global commodity trade in volume terms was completed through ports and maritime transport routes. The international maritime transportation industry contributes significantly to the welfare and development of nations adding around $380 billion a year via freight rates alone to the global economy. At the same time, the total amount of marine transport has steadily increased every year, and in 2014, it reached 9.84 billion tons [1–3]. Standing at the critical interface between inland and sea transportation, the container port is a critical connection between different modes of transportation and represents a critical point in the transportation chain [4]. For a country, maritime transportation not only ensures the import of scarce resources needed for production processes but also facilitates the export of excessive resources, which accumulates more wealth for the country. Maritime transport is also a key to economic globalization [5]. In particular, container transport has become the most important mode of transport in international trade and the new window for the development of foreign economic relationship and trade. Worldwide container port throughput increased from 36 million TEU in 1980 to 614 million TEU in 2017 and forecasts point to more than 800 million TEU in 2017 [6]. The flourishing industrial growth engendered numerous intellectual problems which, in turn, attracted academic interest. Subsequently, container port and maritime transportation has grown as a unique academic field.Therefore, it is highly important to develop an overview of this field, which will provide general and historical results that permit a retrospective evaluation. In general, a number of studies have attempted to address conceptualization, methodological issues, theoretical developments, academic taxonomy, and future research directions in areas relevant to maritime logistics literature, such as Lau et al. [7]; Lee and Song [8] survey the extant research in the field of ocean container transport. Shi and Li [5] examine maritime transport researches through a comprehensive review of papers published in 19 transportation journals over the period 2000–2014. Charles [9] provided a global evaluation of the marine academic studies. Woo et al. [10] reviewed published port literature from the 1980s to 2000s in order to investigate the methodological trends in seaport research. Talley [11] reviewed and analyzed maritime transportation academic research, summarized the research topic from maritime journals, and defined future maritime transportation research directions. Chang et al. [12] examined the top 50 authors, 50 affiliations, and 50 countries in the maritime transportation field and discussed the potential correlation between the methodological popularity and author performance.A number of reviews have been completed on specific aspects of maritime transportation research. For example, Wang et al. [3] pointed out the necessity and importance of port management and operations and suggested more research efforts on potential hot topics. Davarzani et al. [13] examined the past and present research on ‘green ports and maritime logistics’ and identified established research trends and future potential research areas. Several reviews have been more problem-specific and sustainable, such as the review by Mansouri et al. [14], who focused on the use of multiobjective decision methods in sustainable maritime transportation. In addition, with the increasing competition in ports, relevant research also expands rapidly. Sharaf et al. [15] provided an understanding of the efficiency analysis of container port through a comprehensive review of existing studies. Based on empirical evidence, Notteboom [16] analyzed the paths shipping lines and terminal operating companies were walking and also provided an overview of challenges port and maritime companies faced with in an ever-changing competitive environment.In spite of Chang et al. [12], to the best of the authors’ knowledge, no other studies have analyzed the authors, affiliations, and countries in maritime research. Our paper differs from Chang et al. [12] in four aspects. First, Chang et al. [12] prespecified a set of journals which are the most closely related to maritime research and they confined the literature search within these journals. In contrast, we search the literature in the whole Web of Science database. Second, different from Chang et al. [12], we conduct a more refined literature search; for example, papers that are related to “maritime” and “fish” are excluded. Third, Chang et al. [12] investigated the whole field of maritime papers and we focus on shipping and container port research. Fourth, Chang et al. [12] judged whether a paper is relevant based on its correlation with seven authors’ papers, which may not be accurate. We judge the relevance of all papers manually. Despite the differences, our research is based on Chang et al. [12]’s seminal work which provided a number of insightful ideas. Using rigorous bibliometric analysis methods, this paper reviews the literature of container port and maritime logistics research to accomplish the following goals. First, we provide some initial statistics of the key journals, authors, and institutions that have contributed to the field. Second, we identify the most active researchers, affiliations, and countries in the container port and maritime field and rank them by different scoring methods. Thus, we provide a better understanding of how maritime transportation research has been undertaken in a quantitative manner. And the ranking also helps to identify active authors. Research of active authors tends to be more advanced. Following their articles can help new comers to obtain new research hotspot more quickly.The remainder of this paper is organized as follows. Section2 explains the methodology and details the scope of articles, database searching, scoring methods, and measures of collaborative network. Section 3 reports the ranking of authors and affiliations by all periods of study (1996-2016) and changes over five-year periods (1996-2000, 2001-2005, 2006-2010, and 2011-2017). Section 4 discusses countries/regions’ ranking performance. Section 5 analyzes and identifies research topics and seminal research areas. Finally, we present the study’s conclusions and discuss the study’s limitations and potential future research directions in Section 6.


## 2. Methodology

The purpose of the literature review is to map and evaluate the body of the literature and identify potential research gaps. Structured literature reviews are completed by Saunders et al. [17] by iterative using search keywords defined appropriately, searching in the databases, and accomplishing the analysis. Rowley and Slack [18] recommend a structured methodology for scanning resources, designing the mapped structure of the literature review, writing the study, and building the bibliography. Inspired by Rowley and Slack [18] and Seuring and Gold [19], we design a four-step method to collect data and conduct a methodical, comprehensive analysis of the field. We aim to identify the remarkable research, make sure about the classical areas of current research interest, and provide insights for present research and directions for the future.


### 2.1. Choice of Search Word and Database

Through several trials and errors, we identify suitable search terms and keyword structures. We design the following method to establish the keywords search structure effectively inspired by Rowley and Slack [18] and Soring and Gold [19].(i)
Build original unit of keywords.(ii)
Review the search results and make sure whether typical papers and considerable journals are contained in obtained results, and make corresponding modifications to keyword set.(iii)
Identify the keywords needed to exclude, and make corresponding modifications to keyword set.(iv)
Search for ‘exclusion research areas’ to confine the search scope, and make corresponding modifications to keyword set.Initially, we relied on the prior work of Chang et al. [12] in the maritime logistics review papers to define the initial set of keywords. Thirteen search words were suggested based on these previous works. They were “port OR shipping OR maritime OR marine OR terminal OR ship OR liner OR vessel OR seaport OR water transport∗ OR ocean freight OR container” and “waterway transport∗.” First, search words were typed in the Web of Science database. This paper only retrieves academic articles (or journal papers) and rules out conference proceedings, book chapters, dissertations, and theses. The space of journals selected in this paper narrows down to Science Citation Index (SCI), Social Science Citation Index (SSCI), SCI (E), and SSCI-registered ones. Afterwards, we check the resulting articles and journals. A mass of words have a polysemic effect. For example, “vessel” means either a ship or a duct or canal holding or conveying blood or other fluid. The polysemy effect of “vessel” causes the initial search results to include a mass of papers about biological research. We also ruled out the articles that include the following irrelevant words, including “highway OR intersection OR helmet OR pedestrian OR fish OR guardrail OR aviation OR airport OR airline” and “fishery.”The initial search results left about 12279 articles after several trial and error attempts. The search results have expanded to a wide range of thematic areas beyond the scope of this paper. Hence, papers from irrelevant thematic areas need to rule out. Irrelevant subject areas are those that do not belong to the space of container and marine transport system. The unrelated areas were identified through discussions with other senior researchers in the field. The unrelated areas included (1) astronomy, planet sciences, and related areas, (2) agricultural sciences and related areas, (3) medicine, biology, and related areas, (4) physics and related areas, and (5) psychology. Finally, the authors went through 12,279 references and reduced the number of relevant articles to 5,534 as a refinement. Table1 shows the whole process of the material collection.Table 1
Process of the material collection.
Search results Step1 Search keywords 81,126 port OR shipping OR maritime OR marine OR terminal OR ship OR liner OR seaport OR (watertransport∗) OR (ocean freight) OR container OR (waterway transport∗)  Step2 Exclusion keywords 78,482 AND NOT highway OR intersection OR helmet OR pedestrian OR fish OR guardrail OR aviation OR airport OR airline OR fishery  Step3 Remove the irrelevant subject areas 12,279  Step4 Manual refinement of the search results 5,534


### 2.2. Scoring Method

In this paper, we used two criteria to rank researchers, affiliations, and countries, the number of their publications, and their impact score. The following text describes the composition of each indicator and the rationale for how to use them in detail. The number of publications is an important indicator of academic performance. Numerous studies have used this indicator to approximate author performance [13, 20]. However, only calculating the number of publications has the limitation of measuring the impact of authors on the whole field. In this case, the more crucial part the authors played in an article, the more important evaluation they should be given.Authors who publish their work in more prestigious journals deserve more respect and higher scores. In this case, it seems appropriate to use the impact factor of a journal to adjust the authors’ impact score. There is, in general, a widespread consensus among the authors that the impact factor measures the quality of journals approximately and reasonably. And usage of impact factor is prevalent [21, 22]. The Journal Citation Reports published by Thomson Reuters provided statistical data over the years. A number of journals had no statistical results for certain years, since they recently entered SCI (E) or SSCI, includingMaritime Policy and Management. In such a case, the impact factor in the entry year was applied to the nonentrance periods. For example, the 2011 impact factor forMaritime Policy and Management was applied to 2000-2010. Afterwards, the impact score was denoted by(1)Scorej=∑y=20002017∑iN1Iji×IMyiwhere Scorej is the impact score of author j, N is the number of papers published by author j, Iji represents the number of corresponding authors in paper i with author j, and IMyi is the impact factor of journals that paper i was published in in year y.Apart from impact score assessment, the number of citations of each paper is also included in the database we have obtained, which is more basic and fundamental and also a good indicator of the author's performance. We measured the total number of citations of an author i by(2)ci=∑n∈Nctnwhere ci is the citation score of authors i, N is the total number of publications of author i, and ctn is the citations of paper n.


## 2.1. Choice of Search Word and Database

Through several trials and errors, we identify suitable search terms and keyword structures. We design the following method to establish the keywords search structure effectively inspired by Rowley and Slack [18] and Soring and Gold [19].(i)
Build original unit of keywords.(ii)
Review the search results and make sure whether typical papers and considerable journals are contained in obtained results, and make corresponding modifications to keyword set.(iii)
Identify the keywords needed to exclude, and make corresponding modifications to keyword set.(iv)
Search for ‘exclusion research areas’ to confine the search scope, and make corresponding modifications to keyword set.Initially, we relied on the prior work of Chang et al. [12] in the maritime logistics review papers to define the initial set of keywords. Thirteen search words were suggested based on these previous works. They were “port OR shipping OR maritime OR marine OR terminal OR ship OR liner OR vessel OR seaport OR water transport∗ OR ocean freight OR container” and “waterway transport∗.” First, search words were typed in the Web of Science database. This paper only retrieves academic articles (or journal papers) and rules out conference proceedings, book chapters, dissertations, and theses. The space of journals selected in this paper narrows down to Science Citation Index (SCI), Social Science Citation Index (SSCI), SCI (E), and SSCI-registered ones. Afterwards, we check the resulting articles and journals. A mass of words have a polysemic effect. For example, “vessel” means either a ship or a duct or canal holding or conveying blood or other fluid. The polysemy effect of “vessel” causes the initial search results to include a mass of papers about biological research. We also ruled out the articles that include the following irrelevant words, including “highway OR intersection OR helmet OR pedestrian OR fish OR guardrail OR aviation OR airport OR airline” and “fishery.”The initial search results left about 12279 articles after several trial and error attempts. The search results have expanded to a wide range of thematic areas beyond the scope of this paper. Hence, papers from irrelevant thematic areas need to rule out. Irrelevant subject areas are those that do not belong to the space of container and marine transport system. The unrelated areas were identified through discussions with other senior researchers in the field. The unrelated areas included (1) astronomy, planet sciences, and related areas, (2) agricultural sciences and related areas, (3) medicine, biology, and related areas, (4) physics and related areas, and (5) psychology. Finally, the authors went through 12,279 references and reduced the number of relevant articles to 5,534 as a refinement. Table1 shows the whole process of the material collection.Table 1
Process of the material collection.
Search results Step1 Search keywords 81,126 port OR shipping OR maritime OR marine OR terminal OR ship OR liner OR seaport OR (watertransport∗) OR (ocean freight) OR container OR (waterway transport∗)  Step2 Exclusion keywords 78,482 AND NOT highway OR intersection OR helmet OR pedestrian OR fish OR guardrail OR aviation OR airport OR airline OR fishery  Step3 Remove the irrelevant subject areas 12,279  Step4 Manual refinement of the search results 5,534


## 2.2. Scoring Method

In this paper, we used two criteria to rank researchers, affiliations, and countries, the number of their publications, and their impact score. The following text describes the composition of each indicator and the rationale for how to use them in detail. The number of publications is an important indicator of academic performance. Numerous studies have used this indicator to approximate author performance [13, 20]. However, only calculating the number of publications has the limitation of measuring the impact of authors on the whole field. In this case, the more crucial part the authors played in an article, the more important evaluation they should be given.Authors who publish their work in more prestigious journals deserve more respect and higher scores. In this case, it seems appropriate to use the impact factor of a journal to adjust the authors’ impact score. There is, in general, a widespread consensus among the authors that the impact factor measures the quality of journals approximately and reasonably. And usage of impact factor is prevalent [21, 22]. The Journal Citation Reports published by Thomson Reuters provided statistical data over the years. A number of journals had no statistical results for certain years, since they recently entered SCI (E) or SSCI, includingMaritime Policy and Management. In such a case, the impact factor in the entry year was applied to the nonentrance periods. For example, the 2011 impact factor forMaritime Policy and Management was applied to 2000-2010. Afterwards, the impact score was denoted by(1)Scorej=∑y=20002017∑iN1Iji×IMyiwhere Scorej is the impact score of author j, N is the number of papers published by author j, Iji represents the number of corresponding authors in paper i with author j, and IMyi is the impact factor of journals that paper i was published in in year y.Apart from impact score assessment, the number of citations of each paper is also included in the database we have obtained, which is more basic and fundamental and also a good indicator of the author's performance. We measured the total number of citations of an author i by(2)ci=∑n∈Nctnwhere ci is the citation score of authors i, N is the total number of publications of author i, and ctn is the citations of paper n.


## 3. Analysis of Author and Affiliation

Section3.1 illustrates the overall trend of publications. Sections 3.2-3.3 report rankings of author and affiliation for 1996-2017, respectively.


### 3.1. Overall Trend

Figure1 shows the number of papers published each year. Between 1996 and 2012, the published paper counts in maritime transport system field increased every year. The number peaked in 2012 and decreased thereafter. In 2015, this number began to rise again. The rising paper numbers may be due to the Chinese government vigorously promoting the economic strategy of the Silk Road Economic Belt and the 21st Century Maritime Silk Road. The paper number of Chinese scholars has improved, thereby causing the total number of papers to increase in 2015. Section 3.3 reports the country rankings from 1996 to 2016 and supports this conclusion.Figure 1
Growth of maritime research paper.


### 3.2. Author Ranking Analysis

#### 3.2.1. Author Ranking for 1996-2016

Table2 displays the ranking of top 50 authors in the port and maritime transport system field according to the three metrics we mentioned above. Column 3 shows the ranking of the first metric, which is calculated based on the number of papers published. Numbers are counted when the author is one of all coauthors or the single author of a paper. For example, the top ranked Qiang Meng published 61 papers, either as an author or a coauthor. The second metric ranking is the impact score (column 6) that considers the journal impact factor. In terms of paper numbers, Qiang Meng is the top researcher and published 61 papers. Qiang Meng was followed by Shuaian Wang with 52 papers. After those two researchers, the differences between the subsequent authors are not substantial.Table 2
Rankings by author.
Rank Author No. papers Rank Author Impact Score Rank Author Citation Score 1 Meng, Qiang 61 1 Wang, Shuaian 47.95 1 Kim, Kap Hwan 1713  2 Wang, Shuaian 52 2 Meng, Qiang 41.66 2 Imai, Akio 1214  3 Kim, Kap Hwan 47 3 Notteboom, Theo 25.63 3 Christiansen, Marielle 1189  4 Fagerholt, Kjetil 45 4 Lam, Jasmine Siu Lee 25.00 4 Fagerholt, Kjetil 1147  5 Lam, Jasmine Siu Lee 36 5 Kim, Kap Hwan 23.63 5 Meng, Qiang 1107  5 Notteboom, Theo 36 6 Fagerholt, Kjetil 23.06 6 Papadimitriou, Stratos 1083  7 Wang, Jin 31 7 Celik, Metin 20.41 7 Voss, Stefan 1030  8 Christiansen, Marielle 30 8 Lee, Chung-Yee 19.00 8 Nishimura, Etsuko 1021  9 Lee, Loo Hay 28 9 Song, Dong-Ping 17.44 9 Stahlbock, R 960  10 Parola, Francesco 26 10 Zhen, Lu 17.35 10 Wang, Shuaian 751  10 Lu, Chin-Shan 26 11 Monios, Jason 17.10 11 Cullinane, Kevin 744  10 Chew, Ek Peng 26 12 Ding, Ji-Feng 15.76 12 Laporte, Gilbert 680  10 Lee, Paul Tae-Woo 26 13 Ng, ManWo 14.41 13 Kozan, Erhan 659  14 Luo, Meifeng 25 14 Lu, Chin-Shan 13.99 14 Song, Dong-Wook 624  15 Lun, Y. H. Venus 24 15 Talley, Wayne K 13.45 15 Vis, Iris F. A. 614  16 Celik, Metin 23 16 Tovar, Beatriz 13.27 16 Notteboom, Theo 577  16 Lee, Der-Horng 23 17 Lee, Paul Tae-Woo 12.62 17 Meisel, Frank 562  16 Song, Dong-Ping 23 18 Thai, Vinh V 12.56 18 Park, YM 540  19 Cheng, T. C. Edwin 22 19 Ducruet, Cesar 12.56 19 Wang, Jin 522  19 Cullinane, Kevin 22 20 Christiansen, Marielle 12.15 20 Liu, JY 519  22 Ng, Adolf K. Y. 21 21 Lun, Y. H. Venus 11.75 21 Ronen, David 506  21 Thai, Vinh V 21 22 Lee, Loo Hay 11.65 22 Wan, YW 505  21 Yang, Zaili 21 23 Luo, Meifeng 11.61 23 Steenken, D 500  24 Chang, Young-Tae 20 24 Petering, Matthew E. H. 11.22 24 Bierwirth, Christian 484  24 Lee, Chung-Yee 20 25 Wilmsmeier, Gordon 11.18 25 Lee, Der-Horng 450  24 Li, Kevin X 20 26 Lee, Der-Horng 11.14 26 Lu, Chin-Shan 436  27 Lai, Kee-hung 19 27 Lai, Kee-hung 10.96 27 Tongzon, J 431  27 Laporte, Gilbert 19 28 Akyuz, Emre 10.91 28 de Koster, R 424  29 Huynh, Nathan 18 29 Cullinane, Kevin 10.76 29 Lee, Loo Hay 422  29 Papadimitriou, Stratos 18 30 Parola, Francesco 10.54 30 Linn, RJ 422  31 Ducruet, Cesar 17 31 Wang, Jin 10.17 31 Celik, Metin 411  31 Imai, Akio 17 32 Boysen, Nils 10.09 32 Andersson, Henrik 395  31 Tovar, Beatriz 17 33 Chou, Chien-Chang 10.08 33 Legato, Pasquale 391  31 Yip, Tsz Leung 17 34 Dong, Jing-Xin 9.88 34 Kujala, Pentti 389  35 Hu, Hao 16 35 Wang, Xinchang 9.83 35 Chew, Ek Peng 385  35 Kavussanos, Manolis G 16 36 Meisel, Frank 9.62 36 Song, Dong-Ping 375  35 Lim, Andrew 16 37 Ng, Adolf K. Y. 9.52 37 Murty, Katta G. 368  35 Monios, Jason 16 38 Chew, Ek Peng 9.47 38 Lam, Jasmine Siu Lee 360  35 Pisinger, David 16 39 Laporte, Gilbert 9.47 39 Ng, WC 320  35 Song, Dong-Wook 16 40 Yang, Yi-Chih 8.98 40 Wang, Teng-Fei 317  35 Talley, Wayne K 16 41 Yang, Zaili 8.90 41 Kavussanos, Manolis G. 312  35 Yang, Zhongzhen 16 42 Chang, Young-Tae 8.81 42 Zhang, CQ 291  35 Zhen, Lu 16 43 Kujala, Pentti 8.57 43 Hummels, David 286  44 Ferrari, Claudio 15 44 Psaraftis, Harilaos N. 8.56 44 Pisinger, David 282  44 Hvattum, Lars Magnus 15 45 Cheng, T. C. Edwin 8.44 45 Gue, KR 270  44 Kozan, Erhan 15 46 Cariou, Pierre 8.24 46 Lun, Y. H. Venus 269  44 Kujala, Pentti 15 47 Yip, Tsz Leung 8.20 47 Ng, Adolf K. Y. 249  44 Voss, Stefan 15 48 Pisinger, David 8.13 48 Cheng, T. C. Edwin 240  44 Wilmsmeier, Gordon 15 49 Sun,Zhuo 8.09 49 Er, I. Deha 237  44 Wilson, William W 15 50 Bell, Michael G. H. 7.90 50 Hasle, Geir 233Considering the impact score, Meng and Wang still take the first and second places, but their ranks are reversed. The gap between the second and third is relatively large. A notable change can be seen. Among the top 10 authors, Metin Celik, Chung-Yee Lee, Dong-Ping Song, and Lu Zhen emerge. Celik’s ranking increased from 16th to 7th. Lee’s ranking increased from 24th to 8th. Song’s ranking increased from 16th to 9th. Zhen’s ranking increased from 35th to 10th.Significant changes can be observed on the citation score: Nishimura, Etsuko, and Stahlbock, R are the first time appearing in the top 10. Compared with the rank of number of papers, Imai, Akio, Voss, Stefan, and Papadimitriou, Stratos’s ranks up more than 25.


#### 3.2.2. Ranking Dynamics of Authors

This section examines the changes in the author’s performance over each five-year period. Table3 shows the dynamics of the impact score ranking of authors. The columns next to the impact score indicate the change of the ranking relative to the previous period in 2001-2005, 2006-2010, and 2011-2015, respectively. Ranking changes of an author will not be shown if he/she was outside the top 100 in the previous period. Overall, the rise and decline of core authors are prominent in the port and maritime transport system field. A notable point is that K.H. Kim maintains a top 10 ranking in every period. Numerous top 50 authors from 1996 to 2000 do not make the rankings in the next period, while most of the top 50 authors in 2001-2005 are new authors. A similar pattern appeared between 2006 and 2010 and 2011 and 2015. This field also had a new strength among the top 5 from 2011 to 2015. A typical example is S.A. Wang. Since all of his articles are published after 2010, he did not appear in the ranking of first three-time periods. Nevertheless, his centrality for 2011-2015 is quite high. Other examples include J.S.L. Lam and L. Zhen. It can be expected that these authors will contribute more to the field in the coming years. Only Notteboom maintains a top 5 position over the entirety of the last decade. The changeable ranking means this field is full of competition and opportunity.Table 3
Ranking dynamics of authors.
Author Impact Score (1996-2000) Author Impact Score (2001-2005)  Author Impact Score (2006-2010)  Author Impact Score (2011-2015) 1 Kim, Kap Hwan 3.82 Kim, Kap Hwan 3.75 - Celik, Metin 9.05 - Wang, Shuaian 34.45 - 2 Bennett, P 2.44 Suryanata, K 1.65 ▲ Chou, Chien-Chang 8.37 - Meng, Qiang 31.03 ▲ 3 Peterson, K 1.52 Peterson, K 1.52 - Notteboom, Theo 7.79 ▲ Notteboom, Theo 17.98 - 4 Lei, J 1.45 Lei, J 1.45 - Er, I. Deha 6.54 ▲ Lam, Jasmine Siu Lee 14.10 - 5 Zhou, JJ 1.45 Zhou, JJ 1.45 - Kim, Kap Hwan 6.22 ▼ Fagerholt, Kjetil 12.40 ▲ 6 Hartmann, Soenke 1.44 Hartmann, Soenke 1.44 - Ding, Ji-Feng 5.86 - Song, Dong-Ping 11.55 - 7 Hemp, P 1.37 Imai, Akio 1.41 ▲ Lai, Kee-hung 5.83 - Zhen, Lu 9.98 - 8 Matthews, HS 1.35 Nishimura, Etsuko 1.41 ▲ Petering, Matthew E. H. 5.79 ▲ Lee, Chung-Yee 9.66 - 9 Hart, R 1.23 Papadimitriou, Stratos 1.41 ▲ Lee, Der-Horng 5.40 ▲ Kim, Kap Hwan 9.38 ▼ 10 Wang, Jin 1.08 Lillie, N 1.38 ▲ Roso, Violeta 4.41 - Lee, Loo Hay 8.85 -  11 Holden, H 1.00 Hemp, P 1.37 ▼ Imai, Akio 3.81 ▲ Akyuz, Emre 7.63 - 12 Gierloff-Emden, HGR 0.96 Matthews, HS 1.35 ▼ Song, Dong-Wook 3.79 - Dong, Jing-Xin 7.31 ▲ 13 van Driel, Hugo 0.93 Oakley, Susan 1.29 - Vis, Iris F. A. 3.74 - Ng, ManWo 7.17 - 14 Suryanata, K 0.89 Hart, R 1.23 ▼ Hummels, David 3.43 - Yang, Zaili 7.05 - 15 Umemoto, KN 0.89 Karlsen, A 1.17 - Chen, Jiang Hang 3.42 - Kujala, Pentti 6.98 - 16 Krasnopolsky, VM 0.89 Cullinane, Kevin 1.15 ▲ Roe, Michael 3.33 - Tovar, Beatriz 6.94 - 17 Schiller, H 0.89 Wang, Jin 1.13 ▼ Lu, Chin-Shan 3.32 ▼ Ducruet, Cesar 6.74 ▲ 18 Lillie, N 0.88 Ng, WC 1.08 - Goodchild, Anne V 2.99 - Chew, Ek Peng 6.57 - 19 Zhang, CQ 0.85 Holden, H 1.00 ▼ Ducruet, Cesar 2.95 - Wilmsmeier, Gordon 6.56 - 20 Jetlund, AS 0.84 Gierloff-Emden, HGR 0.96 ▼ Papadimitriou, Stratos 2.80 ▼ Ng, Adolf K. Y. 6.42 ▲  21 Karimi, IA 0.84 van Driel, Hugo 0.93 ▼ Hirashima, Yoichi 2.79 - Celik, Metin 6.28 ▼ 22 Fossen, Thor I. 0.82 Umemoto, KN 0.89 ▼ Fremont, Antoine 2.77 - Liu, Zhiyuan 6.21 - 23 Park, YM 0.82 Liu, Jiyin 0.89 - Demaria, Federico 2.75 - Yang, Yi-Chih 5.99 - 24 Ronen, D. 0.80 Wan, Yat-wah 0.89 - Fagerholt, Kjetil 2.74 ▲ Cariou, Pierre 5.85 - 25 Jacobson, A 0.80 Krasnopolsky, VM 0.89 ▼ Kozan, Erhan 2.69 - Monios, Jason 5.69 - 26 Farrell, JA 0.79 Schiller, H 0.89 ▼ Asteris, Michael 2.67 - Rudd, Murray A. 5.68 - 27 Li, W 0.79 Tongzon, Jose 0.85 - Meng, Qiang 2.67 - Talley, Wayne K. 5.67 - 28 Lee, RM 0.78 Zhang, CQ 0.85 ▼ Paulauskas, Vytautas 2.67 - Sun, Zhuo 5.65 - 29 Linn, RJ 0.76 Legato, Pasquale 0.84 ▲ Meisel, Frank 2.63 - Laporte, Gilbert 5.65 - 30 Imai, Akio 0.76 Jetlund, AS 0.84 ▼ Ng, Adolf K. Y. 2.61 - Pisinger, David 5.56 -  31 Nishimura, Etsuko 0.76 Karimi, IA 0.84 ▼ Vasiliauskas, Aidas Vasilis 2.55 - Psaraftis, Harilaos N. 5.52 - 32 Papadimitriou, Stratos 0.76 Ronen, D. 0.80 ▼ Sharma, Mithun J. 2.53 - Petering, Matthew E. H. 5.43 ▼ 33 Ausloos, M 0.76 Jacobson, A 0.80 ▼ Yu, Song Jin 2.53 - Lee, Paul Tae-Woo 5.37 - 34 Ivanova, K 0.76 Lu, Chin-Shan 0.79 - Nishimura, Etsuko 2.51 ▼ Goerlandt, Floris 5.34 - 35 Fagerholt, Kjetil 0.75 Farrell, JA 0.79 ▼ Lee, Yusin 2.50 - Wang, Hua 5.24 - 36 Fairlie, DP 0.73 Li, W 0.79 ▼ Konings, Rob 2.47 - Hvattum, Lars Magnus 4.98 - 37 Lucke, AJ 0.73 Donderi, DC 0.78 - Saeed, Naima 2.43 - Yip, Tsz Leung 4.92 - 38 Singh, Y 0.73 McFadden, S 0.78 - Merrick, Jason R. W. 2.43 - Christiansen, Marielle 4.91 - 39 Tyndall, JDA 0.73 Lee, RM 0.78 ▼ Ramirez-Marquez, Jose Emmanuel 2.33 - Hanninen, Maria 4.89 - 40 Fung, Michael K. 0.72 Bish, EK 0.77 ▲ Kahraman, Cengiz 2.29 - Wang, Jin 4.83 ▼  41 Bish, EK 0.67 Linn, RJ 0.76 ▼ Hastings, Justin V. 2.27 - Featherstone, David 4.82 - 42 Yun, JE 0.67 Ausloos, M 0.76 ▼ Cebi, Selcuk 2.18 - Lee, Der-Horng 4.77 ▼ 43 Marin, PL 0.66 Ivanova, K 0.76 ▼ Panayides, Photis M 2.18 - Hu, Zhi-Hua 4.77 - 44 Sicotte, R 0.66 Umemoto, K 0.76 - Goulielmos, Alexander M. 2.11 - Kontovas, Christos A. 4.76 - 45 Legato, Pasquale 0.66 Sciomachen, Anna 0.75 - Cao, Jin Xin 2.10 - Knapp, Sabine 4.52 - 46 Bhargava, HK 0.66 Koutsavdis, E 0.74 - Park, Changkyu 2.09 - Luo, Meifeng 4.51 ▼ 47 Snoap, KJ 0.66 Rhee, SH 0.74 - Seo, Junyong 2.09 - Nathan Huynh 4.50 - 48 Altiok, T 0.64 Fairlie, DP 0.73 ▼ Wu, Wei-Ming 2.07 - Yeo, Gi-Tae 4.43 - 49 Cullinane, Kevin 0.63 Lucke, AJ 0.73 ▼ Fossen, Thor I. 2.05 ▼ Meisel, Frank 4.41 ▼ 50 Gold, C 0.62 Singh, Y 0.73 ▼ Low, Joyce M. W 2.03 - Bell, Michael G. H. 4.40 -Another point worth noting is that the five-year impact scores of active authors have a significant raise. For example, the impact scores of the top 3 between period 3 and period 4 soared from 9.05, 8.73, and 7.79, respectively, to 34.45, 31.03, and 17.98, respectively. It may have been influenced by the growing number of publications and more publications being published in high-impact journals (impact score =∑y=20002017∑iN1/Iji×IMyi).


#### 3.2.3. Core Authors and Collaboration Patterns

Derek Price prompted the celebrated “square root law" that states that half of the scientific papers are contributed by the top square root of the total number of scientific authors. The law was first proposed in Little Science-Big Science [23] and is heuristically based on Lotka's inverse square law. The Price’s law is calculated from the following equation:(3)M=0.749Nmaxwhere Nmax is the maximum number of the articles by one author. M is the minimum number of articles by a core author, which means the author whose published paper number is above M is the core author. In our data sample, Nmax equals 61, and according to Price’s law M equals 5.8. Thus, there are more than 190 authors who have published more than 6 papers in the field.For further analysis, we also tried to analyze the cooperation pattern of the core authors. The cooperation pattern means different authors appearing in multiple joint articles frequently. Table4 shows the results. An interesting observation is that the core authors (such as S.A. Wang, Q. Meng, E.P. Chew, L.H. Lee, and K. Fagerholt) in the container port and maritime field do frequently cooperate. This result indicates that most container port and maritime researchers are willing to cooperate with their familiar partners.Table 4
The most prolific paired authors.
Rank Paired authors Number of joint publications Rank Paired authors Number of joint publications 1 Meng, Q, Wang, SA 34 11 Papadimitriou, S, Nishimura, E 12  2 Chew, EP, Lee, LH 25 12 Fagerholt, K, Christiansen, M 12  3 Lai, KH, Cheng, TCE 17 13 Tan, KC, Chew, EP 11  4 Cheng, TCE, Lun, YHV 15 14 Tan, KC, Lee, LH 11  5 Yang, ZL, Wang, J 15 15 Wang, SA, Liu, ZY 11  6 Boile, M, Theofanis, S 14 16 Monios, J, Wilmsmeier, G 10  7 Lai, KH, Lun, YHV 14 17 Parola, F, Satta, G 10  8 Lee, DH, Chen, JH 13 18 Lee, DH, Cao, JX 10  9 Papadimitriou, S, Imai, A 13 19 Lai, KH, Wong, CWY 9  10 Imai, A, Nishimura, E 12 20 Christiansen, M, Andersson, H 9The top articles were considered as the lead articles of a research area [13]. The titles of core authors’ top 10 articles in the container port and maritime research area are also shown in Table 5. All of the top 3 articles are the overview in the port and maritime research area which may help new comers to understand quickly about container port and maritime field. The rest of the top 10 articles are interested in specific topics, including economics, operations research, business, and planning.Table 5
The top 10 articles of port and maritime research area.
Authour Title Citation Steenken, D; Voss, S; Stahlbock, R Container terminal operation and operations 500 research - a classification and literature review  Stahlbock, Robert; Voss, Stefan Operations research at container terminals: a 423 literature update  Vis, IFA; de Koster, R Transshipment of containers at a container 290 terminal: An overview  Christiansen, M; Fagerholt, K; Ship routing and scheduling: Status and 270 Ronen, D perspectives  Hummels, David Transportation costs and international trade in the 242 second era of globalization  Bierwirth, Christian; Meisel, A survey of berth allocation and quay crane 228 Frank scheduling problems in container terminals  Imai, A; Nishimura, E; The dynamic berth allocation problem for a 222 Papadimitriou, S container port  Kim, KH; Park, YM A crane scheduling method for port container 200 terminals  Tongzon, J; Heng, W Port privatization, efficiency and competitiveness: 169 Some empirical evidence from container ports (terminals)  Cullinane, K; Wang, TF; Song, The technical efficiency of container ports: 168 DW; Ji, P Comparing data envelopment analysis and stochastic frontier analysis


### 3.3. Affiliation Ranking Analysis

#### 3.3.1. Affiliation Ranking for 2000-2015

Table6 displays affiliation rankings for 1996-2016. In paper counts, the National University of Singapore (NUS), Hong Kong Polytechnic University (HKPU), Norwegian University of Science and Technology, Delft University of Technology, and the University of Antwerp (UA) are in the top 5. The top schools are all strong regardless of how they are ranked. The most productive school, NUS, published 184 papers and was followed by HKPU with 174 papers. As with the authors' ranking, the gap between the second and third in the affiliation rankings is also relatively large (60 papers). Below these schools, the gap between the subsequent affiliations is no longer substantial. The top ten affiliations for 1996-2016 published 986 papers, which equate to an annual average of 46.87 papers. The best performing schools is still NUS. Another notable point is the sudden increase of Nanyang Technological University (NTU) in the ranking. As for the rank of citation score, it is stable and similar to the rank of impact score except for some slight fluctuations. But there is still some sudden increase that needs to be noteworthy. Univ Georgia Inst Technol’s rank ups 16 places to 9th. Univ Hamburg is not among the top 50 in the impact score but places to 5th in citation score.Table 6
Rankings by affiliations.
Rank School No. Paper Rank School Impact Score Rank School Citation Score 1 Natl Univ Singapore 184 1 Natl Univ Singapore 148.06 1 Natl Univ Singapore 3342  2 Hong Kong Polytech Univ 174 2 Hong Kong Polytech Univ 130.64 2 Norwegian Univ Sci & Technol 2525  3 Norwegian Univ Sci & Technol 114 3 Norwegian Univ Sci & Technol 69.67 3 Pusan Natl Univ 2179  4 Delft Univ Technol 93 4 Delft Univ Technol 64.03 4 Hong Kong Polytech Univ 1558  5 Univ Antwerp 84 5 Nanyang Technol Univ 59.83 5 Univ Hamburg 1075  6 Erasmus Univ 82 6 Erasmus Univ 58.04 6 Erasmus Univ 1052  7 Nanyang Technol Univ 73 7 Pusan Natl Univ 56.32 7 Istanbul Tech Univ 951  8 Shanghai Jiao Tong Univ 68 8 Dalian Maritime Univ 53.49 8 Univ Antwerp 934  9 Pusan Natl Univ 66 9 Istanbul Tech Univ 52.56 9 Georgia Inst Technol 868  10 Dalian Maritime Univ 62 10 Tech Univ Denmark 50.78 10 Hong Kong Univ Sci & Technol 802  11 Univ Genoa 61 11 Univ Antwerp 50.53 11 Univ Calif Berkeley 785  12 Univ Piraeus 58 12 Natl Taiwan Ocean Univ 47.26 12 Natl Cheng Kung Univ 777  13 Natl Taiwan Ocean Univ 55 13 Univ Genoa 46.33 13 Tech Univ Denmark 758  14 Istanbul Tech Univ 54 14 Hong Kong Univ Sci & Technol 43.11 14 Delft Univ Technol 719  15 Hong Kong Univ Sci & Technol 53 15 Natl Cheng Kung Univ 42.08 15 HEC Montreal 699  16 Tech Univ Denmark 52 16 Natl Kaohsiung Marine Univ 41.71 16 Kobe Univ 689  17 Univ Plymouth 51 17 Univ Plymouth 41.24 17 Univ Plymouth 645  18 Natl Cheng Kung Univ 47 18 Old Dominion Univ 39.36 18 Univ Hong Kong 635  18 Rutgers State Univ 47 19 Univ Piraeus 38.91 19 Univ Calabria 618  20 Cardiff Univ 43 20 Shanghai Jiao Tong Univ 38.59 20 Nanyang Technol Univ 574  21 Georgia Inst Technol 40 21 Cardiff Univ 32.64 21 Liverpool John Moores Univ 569  22 Natl Kaohsiung Marine Univ 39 22 Natl Tech Univ Athens 31.14 22 Norwegian Marine Technol Res Inst MARINTEK 559  23 Univ Rijeka 38 23 Vilnius Gediminas Tech Univ 31.00 23 Univ Genoa 559  24 Edinburgh Napier Univ 37 24 Edinburgh Napier Univ 30.94 24 Univ Halle Wittenberg 539  24 Liverpool John Moores Univ 37 25 Georgia Inst Technol 29.72 25 Univ Wisconsin 525  24 Natl Tech Univ Athens 37 26 Shanghai Univ 29.51 26 Univ London Imperial Coll Sci Technol & Med 513  27 Old Dominion Univ 36 27 Aalto Univ 29.35 27 Rutgers State Univ 492  27 Texas A&M Univ 36 28 Liverpool John Moores Univ 27.55 28 Univ Michigan 488  29 Univ Aegean 35 29 Inha Univ 26.71 29 Shanghai Jiao Tong Univ 461  30 Inha Univ 34 30 Univ Las Palmas Gran Canaria 26.42 30 Aalto Univ 458  30 Norwegian Marine Technol Res Inst MARINTEK 34 31 Univ Hong Kong 26.02 31 Univ Piraeus 421  30 Univ Hong Kong 34 32 Univ Calabria 24.92 32 Univ Elect Sci & Technol China 416  33 Univ Calif Berkeley 32 33 Norwegian Marine Technol Res Inst MARINTEK 24.05 33 Chalmers University of Technology 411  34 Chung Ang Univ 31 34 Univ Wollongong 24.02 34 Cardiff Univ 409  34 Univ Valencia 31 35 Shanghai Maritime Univ 23.97 35 Natl Tech Univ Athens 409  36 Shanghai Maritime Univ 30 36 Univ Aegean 23.03 36 Univ Tecn Lisboa 369  36 Shanghai Univ 30 37 Univ Belgrade 21.50 37 Queensland Univ Technol 363  38 HEC Montreal 29 38 Queensland Univ Technol 21.50 38 Kobe Univ Mercantile Marine 354  38 Univ Calabria 29 39 Univ Wisconsin 20.74 39 Univ Newcastle Upon Tyne 346  38 Univ Illinois 29 40 Chalmers 20.68 40 Univ Maryland 344  41 Eindhoven Univ Technol 28 41 Chang Jung Christian Univ 20.53 41 City Univ Hong Kong 342  41 MIT 28 42 Eindhoven Univ Technol 20.27 42 Dalian Maritime Univ 336  41 Univ Las Palmas Gran Canaria 28 43 Texas A&M Univ 20.09 43 Molde Univ Coll 336  44 Aalto Univ 27 44 Wuhan Univ Technol 19.05 44 Univ Las Palmas Gran Canaria 334  45 Univ Hamburg 26 45 Rutgers State Univ 18.60 45 Univ Southampton 332  45 Univ Oviedo 26 46 Chung Ang Univ 18.59 46 Natl Kaohsiung Marine Univ 329  45 Univ Wisconsin 26 47 Univ Illinois 18.49 47 Purdue Univ 324  45 Wuhan Univ Technol 26 48 Univ London Imperial Coll Sci Technol & Med 18.29 48 Antwerp Maritime Acad 318  49 Chalmers 25 49 Univ Seville 18.04 49 Chinese Acad Sci 305  49 City Univ Hong Kong 25 50 Univ Valencia 18.03 50 Ecole Polytech 303The affiliation ranking shows a similar pattern to author rankings. NUS have an outstanding container port and maritime researcher; Meng and HKPU have Wang. The two authors publish in impact score journals in container port and maritime research. It seems to indicate a direct relationship between research infrastructure and researchers. The size of the research infrastructure and the number of researchers available in the field may impact the researchers’ effectiveness and strength of knowledge conversion. In other words, the more the numerous researchers and knowledge, the higher the probability of the affiliation obtaining substantial knowledge conversion.


#### 3.3.2. Ranking Dynamics for Affiliations

In Table7, the change of dynamic ranking of affiliations is relatively small. HKPU, NUS, and EU are consistently high. As we mentioned above, there seems to be a direct relationship between the affiliations and researchers. According to Foray and Lundvall [24], human capital (including graduates, highly skilled personnel, and public and private researchers) somewhat tends to flow to have more of the benefits from positive spillovers. Conversely, if there is not too much of a brain drain, the dynamics of affiliation ranking will remain relatively stable. However, if affiliations seek to remain competitive, it will have to retain a positive welfare system and take care of its producers in order to stem a brain drain.Table 7
Ranking dynamics of affiliations.
school impact score (1996-2000) school impact score (2001-2005)  school impact score (2006-2010)  school impact score (2011-2015) 1 Pusan Natl Univ 6.44 Pusan Natl Univ 7.12 - Natl Univ Singapore 34.97 ▲ Natl Univ Singapore 98.16 - 2 Natl Univ Singapore 3.68 Natl Univ Singapore 4.33 - Istanbul Tech Univ 24.40 - Hong Kong Polytech Univ 42.30 ▲ 3 Chinese Acad Sci 3.14 Hong Kong Polytech Univ 3.33 ▲ Hong Kong Polytech Univ 19.92 - Norwegian Univ Sci & Technol 39.96 ▲ 4 Univ Queensland 2.93 Univ Hawaii Manoa 3.30 ▲ Pusan Natl Univ 18.40 ▼ Nanyang Technol Univ 33.29 ▲ 5 Hong Kong Polytech Univ 2.73 Chinese Acad Sci 3.14 ▼ Natl Kaohsiung Marine Univ 12.50 - Dalian Maritime Univ 32.20 ▲ 6 Univ Edinburgh 2.44 Univ Queensland 2.93 ▼ Univ Calabria 12.16 ▲ Pusan Natl Univ 31.76 ▼ 7 Penn State Univ 2.39 Univ Hong Kong 2.60 ▲ Univ Genoa 10.31 ▲ Delft Univ Technol 29.53 ▲ 8 Norwegian Univ Sci & Technol 2.36 Norwegian Univ Sci & Technol 2.56 - Erasmus Univ 10.01 ▲ Univ Antwerp 29.44 ▲ 9 Erasmus Univ 2.28 Erasmus Univ 2.52 - Georgia Inst Technol 9.90 ▲ Erasmus Univ 28.32 ▼ 10 Carnegie Mellon Univ 2.25 Univ Genoa 2.52 ▲ Univ Wisconsin 9.85 - Shanghai Maritime Univ 27.10 ▲  11 Hong Kong Univ Sci & Technol 1.89 Univ Texas 2.44 - Univ Hong Kong 9.64 ▼ Tech Univ Denmark 25.07 - 12 Univ Hawaii Manoa 1.78 Hong Kong Univ Sci & Technol 2.29 ▼ Norwegian Univ Sci & Technol 9.54 ▼ Old Dominion Univ 24.22 - 13 Univ So Calif 1.76 Carnegie Mellon Univ 2.25 ▼ Univ Piraeus 8.96 ▲ Univ Wollongong 22.55 - 14 World Bank 1.71 Univ Piraeus 2.02 ▲ Univ Antwerp 8.41 - Univ Genoa 22.01 ▼ 15 Univ Tennessee 1.52 Natl Tech Univ Athens 1.99 ▲ Natl Cheng Kung Univ 8.39 ▲ Aalto Univ 21.88 - 16 Univ Genoa 1.51 Natl Cheng Kung Univ 1.83 ▲ Delft Univ Technol 8.06 - Univ Plymouth 21.64 ▲ 17 Univ Calif Riverside 1.40 Univ So Calif 1.76 ▼ Univ Plymouth 7.70 - Shanghai Univ 19.62 ▲ 18 Georgia Inst Technol 1.38 World Bank 1.71 ▼ Shanghai Maritime Univ 7.62 - Shanghai Jiao Tong Univ 19.36 ▼ 19 Natl Tech Univ Athens 1.36 Univ Calabria 1.68 ▲ Univ So Calif 7.29 ▼ Natl Kaohsiung Marine Univ 18.79 ▼ 20 Univ Calabria 1.32 Queensland Univ Technol 1.67 ▲ Vrije Univ Amsterdam 6.75 - Natl Taiwan Ocean Univ 18.51 ▲  21 Florida Int Univ 1.28 Georgia Inst Technol 1.61 ▼ Chinese Acad Sci 6.66 ▼ Hong Kong Univ Sci & Technol 18.46 ▼ 22 Univ Piraeus 1.25 Florida Int Univ 1.60 ▼ Chalmers 6.46 - Istanbul Tech Univ 17.41 ▼ 23 USN 1.24 Univ Tennessee 1.52 ▼ Univ Washington 6.16 - Cardiff Univ 16.12 ▼ 24 Swedish Univ Agr Sci 1.23 Fluent Inc 1.48 - Chang Jung Christian Univ 5.86 - Liverpool John Moores Univ 15.03 ▼ 25 Kobe Univ Mercantile Marine 1.19 Univ Calif Riverside 1.40 ▼ Cardiff Univ 5.46 - Tongji Univ 13.87 - 26 Liverpool John Moores Univ 1.17 Penn State Univ 1.32 ▼ Shanghai Jiao Tong Univ 5.19 - Norwegian Marine Technol Res Inst MARINTEK 13.81 - 27 Univ Hong Kong 1.03 Univ Adelaide 1.29 - Univ Western Australia 5.17 - Univ A Coruna 13.19 - 28 Univ Liege 1.00 Liverpool John Moores Univ 1.27 ▼ Univ London Imperial Coll Sci Technol & Med 5.14 - Edinburgh Napier Univ 13.16 - 29 Calif State Univ Bakersfield 0.96 Univ Missouri 1.25 ▲ Vilnius Gediminas Tech Univ 5.10 - Univ La Laguna 13.12 - 30 Univ Sydney 0.93 Swedish Univ Agr Sci 1.23 ▼ Rutgers State Univ 5.10 ▲ Natl Tech Univ Athens 13.06 ▲  31 Rutgers State Univ 0.92 Kobe Univ Mercantile Marine 1.19 ▼ Univ Portsmouth 5.08 - Univ Las Palmas Gran Canaria 12.88 - 32 Univ Glamorgan 0.92 World Maritime Univ 1.16 - Natl Taiwan Ocean Univ 5.04 ▲ Univ London Imperial Coll Sci Technol & Med 12.08 ▼ 33 Univ Ottawa 0.90 Natl Taiwan Ocean Univ 1.05 - Queensland Univ Technol 4.69 ▼ Univ Calabria 12.06 ▼ 34 Korea Adv Inst Sci & Technol 0.90 Texas A&M Univ 1.04 - Kobe Univ 4.63 ▲ Univ Aegean 11.41 - 35 Univ Missouri 0.90 Univ Delaware 1.02 ▲ Nanyang Technol Univ 4.29 - ExxonMobil Res & Engn Co 11.34 - 36 GKSS Forschungszentrum Geesthacht GmbH 0.89 Univ Liege 1.00 ▼ Univ Halle Wittenberg 4.24 - Eindhoven Univ Technol 11.33 - 37 NOAA 0.89 Newcastle Univ 0.98 - Univ Politecn Cataluna 4.19 - Chung Ang Univ 11.11 - 38 Cornell Univ 0.88 Calif State Univ Bakersfield 0.96 ▼ Natl Tech Univ Athens 4.19 ▼ Univ Seville 11.07 - 39 Univ Delaware 0.88 Univ Sydney 0.93 ▼ Univ Ulsan 4.18 - Inha Univ 10.97 - 40 Univ Illinois 0.81 Kobe Univ 0.91 - Scottish Agr Coll 4.13 - Univ Piraeus 10.66 ▼  41 Univ E Anglia 0.80 Univ Ottawa 0.90 ▼ Univ N Carolina 4.10 - Univ S Carolina 10.35 - 42 Queensland Univ Technol 0.76 Univ Michigan 0.89 - Molde Univ Coll 3.96 - Univ British Columbia 10.18 - 43 Aplus Flash Technol Inc 0.75 GKSS Forschungszentrum Geesthacht GmbH 0.89 ▼ Dalian Maritime Univ 3.82 - Univ Bergen 10.18 - 44 Kyungsung Univ 0.74 NOAA 0.89 ▼ Univ Calif Berkeley 3.77 - Newcastle Univ 9.76 ▼ 45 Univ Carlos III Madrid 0.73 Cornell Univ 0.88 ▼ Stevens Inst Technol 3.76 - Univ Sydney 9.50 ▼ 46 Natl Cheng Kung Univ 0.73 Fern Univ Hagen 0.82 - CNR 3.56 - Georgia Inst Technol 9.47 ▼ 47 Univ Pittsburgh 0.72 Univ Illinois 0.81 ▼ Hanyang Univ 3.48 - Univ Valencia 9.27 - 48 Korea Maritime Inst 0.72 Univ E Anglia 0.80 ▼ Purdue Univ 3.43 - Univ Politecn Valencia 9.08 - 49 Tech Univ Berlin 0.72 McGill Univ 0.78 - Tsinghua Univ 3.36 - Wuhan Univ Technol 9.04 - 50 Univ Wales Coll Cardiff 0.72 CNRS ULP 0.78 - Univ Sci & Technol China 3.29 - Univ Wisconsin 8.81 ▼


#### 3.3.3. Collaboration Patterns

We also analyzed the cooperation pattern of affiliations. Table8 shows the top ten paired affiliations. The result indicates that affiliations do not stay in static cliques. They are willing to cooperate with new partners in order to achieve diversity and novelty. Core affiliations in the maritime field play the role of spreading advanced research results and promoting the development of the field.Table 8
The most prolific paired affiliations.
Rank Paired affiliations Number of joint publications 1 Norwegian Marine Technol Res Inst MARINTEK, Norwegian Univ Sci 27 & Technol  2 Univ Naples Parthenope, Univ Genoa 19  3 Natl Univ Singapore, Univ Wollongong 14  4 Antwerp Maritime Acad, Univ Antwerp 14  5 HEC Montreal, Norwegian Univ Sci & Technol 11  6 Nanyang Technol Univ, RMIT Univ 11  7 Hong Kong Polytech Univ, Shanghai Univ 11  8 Hong Kong Polytech Univ, Chung Ang Univ 8  9 Nanyang Technol Univ, Univ Antwerp 8  10 Dalian Maritime Univ, Univ Antwerp 8


## 3.1. Overall Trend

Figure1 shows the number of papers published each year. Between 1996 and 2012, the published paper counts in maritime transport system field increased every year. The number peaked in 2012 and decreased thereafter. In 2015, this number began to rise again. The rising paper numbers may be due to the Chinese government vigorously promoting the economic strategy of the Silk Road Economic Belt and the 21st Century Maritime Silk Road. The paper number of Chinese scholars has improved, thereby causing the total number of papers to increase in 2015. Section 3.3 reports the country rankings from 1996 to 2016 and supports this conclusion.Figure 1
Growth of maritime research paper.


## 3.2. Author Ranking Analysis

### 3.2.1. Author Ranking for 1996-2016

Table2 displays the ranking of top 50 authors in the port and maritime transport system field according to the three metrics we mentioned above. Column 3 shows the ranking of the first metric, which is calculated based on the number of papers published. Numbers are counted when the author is one of all coauthors or the single author of a paper. For example, the top ranked Qiang Meng published 61 papers, either as an author or a coauthor. The second metric ranking is the impact score (column 6) that considers the journal impact factor. In terms of paper numbers, Qiang Meng is the top researcher and published 61 papers. Qiang Meng was followed by Shuaian Wang with 52 papers. After those two researchers, the differences between the subsequent authors are not substantial.Table 2
Rankings by author.
Rank Author No. papers Rank Author Impact Score Rank Author Citation Score 1 Meng, Qiang 61 1 Wang, Shuaian 47.95 1 Kim, Kap Hwan 1713  2 Wang, Shuaian 52 2 Meng, Qiang 41.66 2 Imai, Akio 1214  3 Kim, Kap Hwan 47 3 Notteboom, Theo 25.63 3 Christiansen, Marielle 1189  4 Fagerholt, Kjetil 45 4 Lam, Jasmine Siu Lee 25.00 4 Fagerholt, Kjetil 1147  5 Lam, Jasmine Siu Lee 36 5 Kim, Kap Hwan 23.63 5 Meng, Qiang 1107  5 Notteboom, Theo 36 6 Fagerholt, Kjetil 23.06 6 Papadimitriou, Stratos 1083  7 Wang, Jin 31 7 Celik, Metin 20.41 7 Voss, Stefan 1030  8 Christiansen, Marielle 30 8 Lee, Chung-Yee 19.00 8 Nishimura, Etsuko 1021  9 Lee, Loo Hay 28 9 Song, Dong-Ping 17.44 9 Stahlbock, R 960  10 Parola, Francesco 26 10 Zhen, Lu 17.35 10 Wang, Shuaian 751  10 Lu, Chin-Shan 26 11 Monios, Jason 17.10 11 Cullinane, Kevin 744  10 Chew, Ek Peng 26 12 Ding, Ji-Feng 15.76 12 Laporte, Gilbert 680  10 Lee, Paul Tae-Woo 26 13 Ng, ManWo 14.41 13 Kozan, Erhan 659  14 Luo, Meifeng 25 14 Lu, Chin-Shan 13.99 14 Song, Dong-Wook 624  15 Lun, Y. H. Venus 24 15 Talley, Wayne K 13.45 15 Vis, Iris F. A. 614  16 Celik, Metin 23 16 Tovar, Beatriz 13.27 16 Notteboom, Theo 577  16 Lee, Der-Horng 23 17 Lee, Paul Tae-Woo 12.62 17 Meisel, Frank 562  16 Song, Dong-Ping 23 18 Thai, Vinh V 12.56 18 Park, YM 540  19 Cheng, T. C. Edwin 22 19 Ducruet, Cesar 12.56 19 Wang, Jin 522  19 Cullinane, Kevin 22 20 Christiansen, Marielle 12.15 20 Liu, JY 519  22 Ng, Adolf K. Y. 21 21 Lun, Y. H. Venus 11.75 21 Ronen, David 506  21 Thai, Vinh V 21 22 Lee, Loo Hay 11.65 22 Wan, YW 505  21 Yang, Zaili 21 23 Luo, Meifeng 11.61 23 Steenken, D 500  24 Chang, Young-Tae 20 24 Petering, Matthew E. H. 11.22 24 Bierwirth, Christian 484  24 Lee, Chung-Yee 20 25 Wilmsmeier, Gordon 11.18 25 Lee, Der-Horng 450  24 Li, Kevin X 20 26 Lee, Der-Horng 11.14 26 Lu, Chin-Shan 436  27 Lai, Kee-hung 19 27 Lai, Kee-hung 10.96 27 Tongzon, J 431  27 Laporte, Gilbert 19 28 Akyuz, Emre 10.91 28 de Koster, R 424  29 Huynh, Nathan 18 29 Cullinane, Kevin 10.76 29 Lee, Loo Hay 422  29 Papadimitriou, Stratos 18 30 Parola, Francesco 10.54 30 Linn, RJ 422  31 Ducruet, Cesar 17 31 Wang, Jin 10.17 31 Celik, Metin 411  31 Imai, Akio 17 32 Boysen, Nils 10.09 32 Andersson, Henrik 395  31 Tovar, Beatriz 17 33 Chou, Chien-Chang 10.08 33 Legato, Pasquale 391  31 Yip, Tsz Leung 17 34 Dong, Jing-Xin 9.88 34 Kujala, Pentti 389  35 Hu, Hao 16 35 Wang, Xinchang 9.83 35 Chew, Ek Peng 385  35 Kavussanos, Manolis G 16 36 Meisel, Frank 9.62 36 Song, Dong-Ping 375  35 Lim, Andrew 16 37 Ng, Adolf K. Y. 9.52 37 Murty, Katta G. 368  35 Monios, Jason 16 38 Chew, Ek Peng 9.47 38 Lam, Jasmine Siu Lee 360  35 Pisinger, David 16 39 Laporte, Gilbert 9.47 39 Ng, WC 320  35 Song, Dong-Wook 16 40 Yang, Yi-Chih 8.98 40 Wang, Teng-Fei 317  35 Talley, Wayne K 16 41 Yang, Zaili 8.90 41 Kavussanos, Manolis G. 312  35 Yang, Zhongzhen 16 42 Chang, Young-Tae 8.81 42 Zhang, CQ 291  35 Zhen, Lu 16 43 Kujala, Pentti 8.57 43 Hummels, David 286  44 Ferrari, Claudio 15 44 Psaraftis, Harilaos N. 8.56 44 Pisinger, David 282  44 Hvattum, Lars Magnus 15 45 Cheng, T. C. Edwin 8.44 45 Gue, KR 270  44 Kozan, Erhan 15 46 Cariou, Pierre 8.24 46 Lun, Y. H. Venus 269  44 Kujala, Pentti 15 47 Yip, Tsz Leung 8.20 47 Ng, Adolf K. Y. 249  44 Voss, Stefan 15 48 Pisinger, David 8.13 48 Cheng, T. C. Edwin 240  44 Wilmsmeier, Gordon 15 49 Sun,Zhuo 8.09 49 Er, I. Deha 237  44 Wilson, William W 15 50 Bell, Michael G. H. 7.90 50 Hasle, Geir 233Considering the impact score, Meng and Wang still take the first and second places, but their ranks are reversed. The gap between the second and third is relatively large. A notable change can be seen. Among the top 10 authors, Metin Celik, Chung-Yee Lee, Dong-Ping Song, and Lu Zhen emerge. Celik’s ranking increased from 16th to 7th. Lee’s ranking increased from 24th to 8th. Song’s ranking increased from 16th to 9th. Zhen’s ranking increased from 35th to 10th.Significant changes can be observed on the citation score: Nishimura, Etsuko, and Stahlbock, R are the first time appearing in the top 10. Compared with the rank of number of papers, Imai, Akio, Voss, Stefan, and Papadimitriou, Stratos’s ranks up more than 25.


### 3.2.2. Ranking Dynamics of Authors

This section examines the changes in the author’s performance over each five-year period. Table3 shows the dynamics of the impact score ranking of authors. The columns next to the impact score indicate the change of the ranking relative to the previous period in 2001-2005, 2006-2010, and 2011-2015, respectively. Ranking changes of an author will not be shown if he/she was outside the top 100 in the previous period. Overall, the rise and decline of core authors are prominent in the port and maritime transport system field. A notable point is that K.H. Kim maintains a top 10 ranking in every period. Numerous top 50 authors from 1996 to 2000 do not make the rankings in the next period, while most of the top 50 authors in 2001-2005 are new authors. A similar pattern appeared between 2006 and 2010 and 2011 and 2015. This field also had a new strength among the top 5 from 2011 to 2015. A typical example is S.A. Wang. Since all of his articles are published after 2010, he did not appear in the ranking of first three-time periods. Nevertheless, his centrality for 2011-2015 is quite high. Other examples include J.S.L. Lam and L. Zhen. It can be expected that these authors will contribute more to the field in the coming years. Only Notteboom maintains a top 5 position over the entirety of the last decade. The changeable ranking means this field is full of competition and opportunity.Table 3
Ranking dynamics of authors.
Author Impact Score (1996-2000) Author Impact Score (2001-2005)  Author Impact Score (2006-2010)  Author Impact Score (2011-2015) 1 Kim, Kap Hwan 3.82 Kim, Kap Hwan 3.75 - Celik, Metin 9.05 - Wang, Shuaian 34.45 - 2 Bennett, P 2.44 Suryanata, K 1.65 ▲ Chou, Chien-Chang 8.37 - Meng, Qiang 31.03 ▲ 3 Peterson, K 1.52 Peterson, K 1.52 - Notteboom, Theo 7.79 ▲ Notteboom, Theo 17.98 - 4 Lei, J 1.45 Lei, J 1.45 - Er, I. Deha 6.54 ▲ Lam, Jasmine Siu Lee 14.10 - 5 Zhou, JJ 1.45 Zhou, JJ 1.45 - Kim, Kap Hwan 6.22 ▼ Fagerholt, Kjetil 12.40 ▲ 6 Hartmann, Soenke 1.44 Hartmann, Soenke 1.44 - Ding, Ji-Feng 5.86 - Song, Dong-Ping 11.55 - 7 Hemp, P 1.37 Imai, Akio 1.41 ▲ Lai, Kee-hung 5.83 - Zhen, Lu 9.98 - 8 Matthews, HS 1.35 Nishimura, Etsuko 1.41 ▲ Petering, Matthew E. H. 5.79 ▲ Lee, Chung-Yee 9.66 - 9 Hart, R 1.23 Papadimitriou, Stratos 1.41 ▲ Lee, Der-Horng 5.40 ▲ Kim, Kap Hwan 9.38 ▼ 10 Wang, Jin 1.08 Lillie, N 1.38 ▲ Roso, Violeta 4.41 - Lee, Loo Hay 8.85 -  11 Holden, H 1.00 Hemp, P 1.37 ▼ Imai, Akio 3.81 ▲ Akyuz, Emre 7.63 - 12 Gierloff-Emden, HGR 0.96 Matthews, HS 1.35 ▼ Song, Dong-Wook 3.79 - Dong, Jing-Xin 7.31 ▲ 13 van Driel, Hugo 0.93 Oakley, Susan 1.29 - Vis, Iris F. A. 3.74 - Ng, ManWo 7.17 - 14 Suryanata, K 0.89 Hart, R 1.23 ▼ Hummels, David 3.43 - Yang, Zaili 7.05 - 15 Umemoto, KN 0.89 Karlsen, A 1.17 - Chen, Jiang Hang 3.42 - Kujala, Pentti 6.98 - 16 Krasnopolsky, VM 0.89 Cullinane, Kevin 1.15 ▲ Roe, Michael 3.33 - Tovar, Beatriz 6.94 - 17 Schiller, H 0.89 Wang, Jin 1.13 ▼ Lu, Chin-Shan 3.32 ▼ Ducruet, Cesar 6.74 ▲ 18 Lillie, N 0.88 Ng, WC 1.08 - Goodchild, Anne V 2.99 - Chew, Ek Peng 6.57 - 19 Zhang, CQ 0.85 Holden, H 1.00 ▼ Ducruet, Cesar 2.95 - Wilmsmeier, Gordon 6.56 - 20 Jetlund, AS 0.84 Gierloff-Emden, HGR 0.96 ▼ Papadimitriou, Stratos 2.80 ▼ Ng, Adolf K. Y. 6.42 ▲  21 Karimi, IA 0.84 van Driel, Hugo 0.93 ▼ Hirashima, Yoichi 2.79 - Celik, Metin 6.28 ▼ 22 Fossen, Thor I. 0.82 Umemoto, KN 0.89 ▼ Fremont, Antoine 2.77 - Liu, Zhiyuan 6.21 - 23 Park, YM 0.82 Liu, Jiyin 0.89 - Demaria, Federico 2.75 - Yang, Yi-Chih 5.99 - 24 Ronen, D. 0.80 Wan, Yat-wah 0.89 - Fagerholt, Kjetil 2.74 ▲ Cariou, Pierre 5.85 - 25 Jacobson, A 0.80 Krasnopolsky, VM 0.89 ▼ Kozan, Erhan 2.69 - Monios, Jason 5.69 - 26 Farrell, JA 0.79 Schiller, H 0.89 ▼ Asteris, Michael 2.67 - Rudd, Murray A. 5.68 - 27 Li, W 0.79 Tongzon, Jose 0.85 - Meng, Qiang 2.67 - Talley, Wayne K. 5.67 - 28 Lee, RM 0.78 Zhang, CQ 0.85 ▼ Paulauskas, Vytautas 2.67 - Sun, Zhuo 5.65 - 29 Linn, RJ 0.76 Legato, Pasquale 0.84 ▲ Meisel, Frank 2.63 - Laporte, Gilbert 5.65 - 30 Imai, Akio 0.76 Jetlund, AS 0.84 ▼ Ng, Adolf K. Y. 2.61 - Pisinger, David 5.56 -  31 Nishimura, Etsuko 0.76 Karimi, IA 0.84 ▼ Vasiliauskas, Aidas Vasilis 2.55 - Psaraftis, Harilaos N. 5.52 - 32 Papadimitriou, Stratos 0.76 Ronen, D. 0.80 ▼ Sharma, Mithun J. 2.53 - Petering, Matthew E. H. 5.43 ▼ 33 Ausloos, M 0.76 Jacobson, A 0.80 ▼ Yu, Song Jin 2.53 - Lee, Paul Tae-Woo 5.37 - 34 Ivanova, K 0.76 Lu, Chin-Shan 0.79 - Nishimura, Etsuko 2.51 ▼ Goerlandt, Floris 5.34 - 35 Fagerholt, Kjetil 0.75 Farrell, JA 0.79 ▼ Lee, Yusin 2.50 - Wang, Hua 5.24 - 36 Fairlie, DP 0.73 Li, W 0.79 ▼ Konings, Rob 2.47 - Hvattum, Lars Magnus 4.98 - 37 Lucke, AJ 0.73 Donderi, DC 0.78 - Saeed, Naima 2.43 - Yip, Tsz Leung 4.92 - 38 Singh, Y 0.73 McFadden, S 0.78 - Merrick, Jason R. W. 2.43 - Christiansen, Marielle 4.91 - 39 Tyndall, JDA 0.73 Lee, RM 0.78 ▼ Ramirez-Marquez, Jose Emmanuel 2.33 - Hanninen, Maria 4.89 - 40 Fung, Michael K. 0.72 Bish, EK 0.77 ▲ Kahraman, Cengiz 2.29 - Wang, Jin 4.83 ▼  41 Bish, EK 0.67 Linn, RJ 0.76 ▼ Hastings, Justin V. 2.27 - Featherstone, David 4.82 - 42 Yun, JE 0.67 Ausloos, M 0.76 ▼ Cebi, Selcuk 2.18 - Lee, Der-Horng 4.77 ▼ 43 Marin, PL 0.66 Ivanova, K 0.76 ▼ Panayides, Photis M 2.18 - Hu, Zhi-Hua 4.77 - 44 Sicotte, R 0.66 Umemoto, K 0.76 - Goulielmos, Alexander M. 2.11 - Kontovas, Christos A. 4.76 - 45 Legato, Pasquale 0.66 Sciomachen, Anna 0.75 - Cao, Jin Xin 2.10 - Knapp, Sabine 4.52 - 46 Bhargava, HK 0.66 Koutsavdis, E 0.74 - Park, Changkyu 2.09 - Luo, Meifeng 4.51 ▼ 47 Snoap, KJ 0.66 Rhee, SH 0.74 - Seo, Junyong 2.09 - Nathan Huynh 4.50 - 48 Altiok, T 0.64 Fairlie, DP 0.73 ▼ Wu, Wei-Ming 2.07 - Yeo, Gi-Tae 4.43 - 49 Cullinane, Kevin 0.63 Lucke, AJ 0.73 ▼ Fossen, Thor I. 2.05 ▼ Meisel, Frank 4.41 ▼ 50 Gold, C 0.62 Singh, Y 0.73 ▼ Low, Joyce M. W 2.03 - Bell, Michael G. H. 4.40 -Another point worth noting is that the five-year impact scores of active authors have a significant raise. For example, the impact scores of the top 3 between period 3 and period 4 soared from 9.05, 8.73, and 7.79, respectively, to 34.45, 31.03, and 17.98, respectively. It may have been influenced by the growing number of publications and more publications being published in high-impact journals (impact score =∑y=20002017∑iN1/Iji×IMyi).


### 3.2.3. Core Authors and Collaboration Patterns

Derek Price prompted the celebrated “square root law" that states that half of the scientific papers are contributed by the top square root of the total number of scientific authors. The law was first proposed in Little Science-Big Science [23] and is heuristically based on Lotka's inverse square law. The Price’s law is calculated from the following equation:(3)M=0.749Nmaxwhere Nmax is the maximum number of the articles by one author. M is the minimum number of articles by a core author, which means the author whose published paper number is above M is the core author. In our data sample, Nmax equals 61, and according to Price’s law M equals 5.8. Thus, there are more than 190 authors who have published more than 6 papers in the field.For further analysis, we also tried to analyze the cooperation pattern of the core authors. The cooperation pattern means different authors appearing in multiple joint articles frequently. Table4 shows the results. An interesting observation is that the core authors (such as S.A. Wang, Q. Meng, E.P. Chew, L.H. Lee, and K. Fagerholt) in the container port and maritime field do frequently cooperate. This result indicates that most container port and maritime researchers are willing to cooperate with their familiar partners.Table 4
The most prolific paired authors.
Rank Paired authors Number of joint publications Rank Paired authors Number of joint publications 1 Meng, Q, Wang, SA 34 11 Papadimitriou, S, Nishimura, E 12  2 Chew, EP, Lee, LH 25 12 Fagerholt, K, Christiansen, M 12  3 Lai, KH, Cheng, TCE 17 13 Tan, KC, Chew, EP 11  4 Cheng, TCE, Lun, YHV 15 14 Tan, KC, Lee, LH 11  5 Yang, ZL, Wang, J 15 15 Wang, SA, Liu, ZY 11  6 Boile, M, Theofanis, S 14 16 Monios, J, Wilmsmeier, G 10  7 Lai, KH, Lun, YHV 14 17 Parola, F, Satta, G 10  8 Lee, DH, Chen, JH 13 18 Lee, DH, Cao, JX 10  9 Papadimitriou, S, Imai, A 13 19 Lai, KH, Wong, CWY 9  10 Imai, A, Nishimura, E 12 20 Christiansen, M, Andersson, H 9The top articles were considered as the lead articles of a research area [13]. The titles of core authors’ top 10 articles in the container port and maritime research area are also shown in Table 5. All of the top 3 articles are the overview in the port and maritime research area which may help new comers to understand quickly about container port and maritime field. The rest of the top 10 articles are interested in specific topics, including economics, operations research, business, and planning.Table 5
The top 10 articles of port and maritime research area.
Authour Title Citation Steenken, D; Voss, S; Stahlbock, R Container terminal operation and operations 500 research - a classification and literature review  Stahlbock, Robert; Voss, Stefan Operations research at container terminals: a 423 literature update  Vis, IFA; de Koster, R Transshipment of containers at a container 290 terminal: An overview  Christiansen, M; Fagerholt, K; Ship routing and scheduling: Status and 270 Ronen, D perspectives  Hummels, David Transportation costs and international trade in the 242 second era of globalization  Bierwirth, Christian; Meisel, A survey of berth allocation and quay crane 228 Frank scheduling problems in container terminals  Imai, A; Nishimura, E; The dynamic berth allocation problem for a 222 Papadimitriou, S container port  Kim, KH; Park, YM A crane scheduling method for port container 200 terminals  Tongzon, J; Heng, W Port privatization, efficiency and competitiveness: 169 Some empirical evidence from container ports (terminals)  Cullinane, K; Wang, TF; Song, The technical efficiency of container ports: 168 DW; Ji, P Comparing data envelopment analysis and stochastic frontier analysis


## 3.2.1. Author Ranking for 1996-2016

Table2 displays the ranking of top 50 authors in the port and maritime transport system field according to the three metrics we mentioned above. Column 3 shows the ranking of the first metric, which is calculated based on the number of papers published. Numbers are counted when the author is one of all coauthors or the single author of a paper. For example, the top ranked Qiang Meng published 61 papers, either as an author or a coauthor. The second metric ranking is the impact score (column 6) that considers the journal impact factor. In terms of paper numbers, Qiang Meng is the top researcher and published 61 papers. Qiang Meng was followed by Shuaian Wang with 52 papers. After those two researchers, the differences between the subsequent authors are not substantial.Table 2
Rankings by author.
Rank Author No. papers Rank Author Impact Score Rank Author Citation Score 1 Meng, Qiang 61 1 Wang, Shuaian 47.95 1 Kim, Kap Hwan 1713  2 Wang, Shuaian 52 2 Meng, Qiang 41.66 2 Imai, Akio 1214  3 Kim, Kap Hwan 47 3 Notteboom, Theo 25.63 3 Christiansen, Marielle 1189  4 Fagerholt, Kjetil 45 4 Lam, Jasmine Siu Lee 25.00 4 Fagerholt, Kjetil 1147  5 Lam, Jasmine Siu Lee 36 5 Kim, Kap Hwan 23.63 5 Meng, Qiang 1107  5 Notteboom, Theo 36 6 Fagerholt, Kjetil 23.06 6 Papadimitriou, Stratos 1083  7 Wang, Jin 31 7 Celik, Metin 20.41 7 Voss, Stefan 1030  8 Christiansen, Marielle 30 8 Lee, Chung-Yee 19.00 8 Nishimura, Etsuko 1021  9 Lee, Loo Hay 28 9 Song, Dong-Ping 17.44 9 Stahlbock, R 960  10 Parola, Francesco 26 10 Zhen, Lu 17.35 10 Wang, Shuaian 751  10 Lu, Chin-Shan 26 11 Monios, Jason 17.10 11 Cullinane, Kevin 744  10 Chew, Ek Peng 26 12 Ding, Ji-Feng 15.76 12 Laporte, Gilbert 680  10 Lee, Paul Tae-Woo 26 13 Ng, ManWo 14.41 13 Kozan, Erhan 659  14 Luo, Meifeng 25 14 Lu, Chin-Shan 13.99 14 Song, Dong-Wook 624  15 Lun, Y. H. Venus 24 15 Talley, Wayne K 13.45 15 Vis, Iris F. A. 614  16 Celik, Metin 23 16 Tovar, Beatriz 13.27 16 Notteboom, Theo 577  16 Lee, Der-Horng 23 17 Lee, Paul Tae-Woo 12.62 17 Meisel, Frank 562  16 Song, Dong-Ping 23 18 Thai, Vinh V 12.56 18 Park, YM 540  19 Cheng, T. C. Edwin 22 19 Ducruet, Cesar 12.56 19 Wang, Jin 522  19 Cullinane, Kevin 22 20 Christiansen, Marielle 12.15 20 Liu, JY 519  22 Ng, Adolf K. Y. 21 21 Lun, Y. H. Venus 11.75 21 Ronen, David 506  21 Thai, Vinh V 21 22 Lee, Loo Hay 11.65 22 Wan, YW 505  21 Yang, Zaili 21 23 Luo, Meifeng 11.61 23 Steenken, D 500  24 Chang, Young-Tae 20 24 Petering, Matthew E. H. 11.22 24 Bierwirth, Christian 484  24 Lee, Chung-Yee 20 25 Wilmsmeier, Gordon 11.18 25 Lee, Der-Horng 450  24 Li, Kevin X 20 26 Lee, Der-Horng 11.14 26 Lu, Chin-Shan 436  27 Lai, Kee-hung 19 27 Lai, Kee-hung 10.96 27 Tongzon, J 431  27 Laporte, Gilbert 19 28 Akyuz, Emre 10.91 28 de Koster, R 424  29 Huynh, Nathan 18 29 Cullinane, Kevin 10.76 29 Lee, Loo Hay 422  29 Papadimitriou, Stratos 18 30 Parola, Francesco 10.54 30 Linn, RJ 422  31 Ducruet, Cesar 17 31 Wang, Jin 10.17 31 Celik, Metin 411  31 Imai, Akio 17 32 Boysen, Nils 10.09 32 Andersson, Henrik 395  31 Tovar, Beatriz 17 33 Chou, Chien-Chang 10.08 33 Legato, Pasquale 391  31 Yip, Tsz Leung 17 34 Dong, Jing-Xin 9.88 34 Kujala, Pentti 389  35 Hu, Hao 16 35 Wang, Xinchang 9.83 35 Chew, Ek Peng 385  35 Kavussanos, Manolis G 16 36 Meisel, Frank 9.62 36 Song, Dong-Ping 375  35 Lim, Andrew 16 37 Ng, Adolf K. Y. 9.52 37 Murty, Katta G. 368  35 Monios, Jason 16 38 Chew, Ek Peng 9.47 38 Lam, Jasmine Siu Lee 360  35 Pisinger, David 16 39 Laporte, Gilbert 9.47 39 Ng, WC 320  35 Song, Dong-Wook 16 40 Yang, Yi-Chih 8.98 40 Wang, Teng-Fei 317  35 Talley, Wayne K 16 41 Yang, Zaili 8.90 41 Kavussanos, Manolis G. 312  35 Yang, Zhongzhen 16 42 Chang, Young-Tae 8.81 42 Zhang, CQ 291  35 Zhen, Lu 16 43 Kujala, Pentti 8.57 43 Hummels, David 286  44 Ferrari, Claudio 15 44 Psaraftis, Harilaos N. 8.56 44 Pisinger, David 282  44 Hvattum, Lars Magnus 15 45 Cheng, T. C. Edwin 8.44 45 Gue, KR 270  44 Kozan, Erhan 15 46 Cariou, Pierre 8.24 46 Lun, Y. H. Venus 269  44 Kujala, Pentti 15 47 Yip, Tsz Leung 8.20 47 Ng, Adolf K. Y. 249  44 Voss, Stefan 15 48 Pisinger, David 8.13 48 Cheng, T. C. Edwin 240  44 Wilmsmeier, Gordon 15 49 Sun,Zhuo 8.09 49 Er, I. Deha 237  44 Wilson, William W 15 50 Bell, Michael G. H. 7.90 50 Hasle, Geir 233Considering the impact score, Meng and Wang still take the first and second places, but their ranks are reversed. The gap between the second and third is relatively large. A notable change can be seen. Among the top 10 authors, Metin Celik, Chung-Yee Lee, Dong-Ping Song, and Lu Zhen emerge. Celik’s ranking increased from 16th to 7th. Lee’s ranking increased from 24th to 8th. Song’s ranking increased from 16th to 9th. Zhen’s ranking increased from 35th to 10th.Significant changes can be observed on the citation score: Nishimura, Etsuko, and Stahlbock, R are the first time appearing in the top 10. Compared with the rank of number of papers, Imai, Akio, Voss, Stefan, and Papadimitriou, Stratos’s ranks up more than 25.


## 3.2.2. Ranking Dynamics of Authors

This section examines the changes in the author’s performance over each five-year period. Table3 shows the dynamics of the impact score ranking of authors. The columns next to the impact score indicate the change of the ranking relative to the previous period in 2001-2005, 2006-2010, and 2011-2015, respectively. Ranking changes of an author will not be shown if he/she was outside the top 100 in the previous period. Overall, the rise and decline of core authors are prominent in the port and maritime transport system field. A notable point is that K.H. Kim maintains a top 10 ranking in every period. Numerous top 50 authors from 1996 to 2000 do not make the rankings in the next period, while most of the top 50 authors in 2001-2005 are new authors. A similar pattern appeared between 2006 and 2010 and 2011 and 2015. This field also had a new strength among the top 5 from 2011 to 2015. A typical example is S.A. Wang. Since all of his articles are published after 2010, he did not appear in the ranking of first three-time periods. Nevertheless, his centrality for 2011-2015 is quite high. Other examples include J.S.L. Lam and L. Zhen. It can be expected that these authors will contribute more to the field in the coming years. Only Notteboom maintains a top 5 position over the entirety of the last decade. The changeable ranking means this field is full of competition and opportunity.Table 3
Ranking dynamics of authors.
Author Impact Score (1996-2000) Author Impact Score (2001-2005)  Author Impact Score (2006-2010)  Author Impact Score (2011-2015) 1 Kim, Kap Hwan 3.82 Kim, Kap Hwan 3.75 - Celik, Metin 9.05 - Wang, Shuaian 34.45 - 2 Bennett, P 2.44 Suryanata, K 1.65 ▲ Chou, Chien-Chang 8.37 - Meng, Qiang 31.03 ▲ 3 Peterson, K 1.52 Peterson, K 1.52 - Notteboom, Theo 7.79 ▲ Notteboom, Theo 17.98 - 4 Lei, J 1.45 Lei, J 1.45 - Er, I. Deha 6.54 ▲ Lam, Jasmine Siu Lee 14.10 - 5 Zhou, JJ 1.45 Zhou, JJ 1.45 - Kim, Kap Hwan 6.22 ▼ Fagerholt, Kjetil 12.40 ▲ 6 Hartmann, Soenke 1.44 Hartmann, Soenke 1.44 - Ding, Ji-Feng 5.86 - Song, Dong-Ping 11.55 - 7 Hemp, P 1.37 Imai, Akio 1.41 ▲ Lai, Kee-hung 5.83 - Zhen, Lu 9.98 - 8 Matthews, HS 1.35 Nishimura, Etsuko 1.41 ▲ Petering, Matthew E. H. 5.79 ▲ Lee, Chung-Yee 9.66 - 9 Hart, R 1.23 Papadimitriou, Stratos 1.41 ▲ Lee, Der-Horng 5.40 ▲ Kim, Kap Hwan 9.38 ▼ 10 Wang, Jin 1.08 Lillie, N 1.38 ▲ Roso, Violeta 4.41 - Lee, Loo Hay 8.85 -  11 Holden, H 1.00 Hemp, P 1.37 ▼ Imai, Akio 3.81 ▲ Akyuz, Emre 7.63 - 12 Gierloff-Emden, HGR 0.96 Matthews, HS 1.35 ▼ Song, Dong-Wook 3.79 - Dong, Jing-Xin 7.31 ▲ 13 van Driel, Hugo 0.93 Oakley, Susan 1.29 - Vis, Iris F. A. 3.74 - Ng, ManWo 7.17 - 14 Suryanata, K 0.89 Hart, R 1.23 ▼ Hummels, David 3.43 - Yang, Zaili 7.05 - 15 Umemoto, KN 0.89 Karlsen, A 1.17 - Chen, Jiang Hang 3.42 - Kujala, Pentti 6.98 - 16 Krasnopolsky, VM 0.89 Cullinane, Kevin 1.15 ▲ Roe, Michael 3.33 - Tovar, Beatriz 6.94 - 17 Schiller, H 0.89 Wang, Jin 1.13 ▼ Lu, Chin-Shan 3.32 ▼ Ducruet, Cesar 6.74 ▲ 18 Lillie, N 0.88 Ng, WC 1.08 - Goodchild, Anne V 2.99 - Chew, Ek Peng 6.57 - 19 Zhang, CQ 0.85 Holden, H 1.00 ▼ Ducruet, Cesar 2.95 - Wilmsmeier, Gordon 6.56 - 20 Jetlund, AS 0.84 Gierloff-Emden, HGR 0.96 ▼ Papadimitriou, Stratos 2.80 ▼ Ng, Adolf K. Y. 6.42 ▲  21 Karimi, IA 0.84 van Driel, Hugo 0.93 ▼ Hirashima, Yoichi 2.79 - Celik, Metin 6.28 ▼ 22 Fossen, Thor I. 0.82 Umemoto, KN 0.89 ▼ Fremont, Antoine 2.77 - Liu, Zhiyuan 6.21 - 23 Park, YM 0.82 Liu, Jiyin 0.89 - Demaria, Federico 2.75 - Yang, Yi-Chih 5.99 - 24 Ronen, D. 0.80 Wan, Yat-wah 0.89 - Fagerholt, Kjetil 2.74 ▲ Cariou, Pierre 5.85 - 25 Jacobson, A 0.80 Krasnopolsky, VM 0.89 ▼ Kozan, Erhan 2.69 - Monios, Jason 5.69 - 26 Farrell, JA 0.79 Schiller, H 0.89 ▼ Asteris, Michael 2.67 - Rudd, Murray A. 5.68 - 27 Li, W 0.79 Tongzon, Jose 0.85 - Meng, Qiang 2.67 - Talley, Wayne K. 5.67 - 28 Lee, RM 0.78 Zhang, CQ 0.85 ▼ Paulauskas, Vytautas 2.67 - Sun, Zhuo 5.65 - 29 Linn, RJ 0.76 Legato, Pasquale 0.84 ▲ Meisel, Frank 2.63 - Laporte, Gilbert 5.65 - 30 Imai, Akio 0.76 Jetlund, AS 0.84 ▼ Ng, Adolf K. Y. 2.61 - Pisinger, David 5.56 -  31 Nishimura, Etsuko 0.76 Karimi, IA 0.84 ▼ Vasiliauskas, Aidas Vasilis 2.55 - Psaraftis, Harilaos N. 5.52 - 32 Papadimitriou, Stratos 0.76 Ronen, D. 0.80 ▼ Sharma, Mithun J. 2.53 - Petering, Matthew E. H. 5.43 ▼ 33 Ausloos, M 0.76 Jacobson, A 0.80 ▼ Yu, Song Jin 2.53 - Lee, Paul Tae-Woo 5.37 - 34 Ivanova, K 0.76 Lu, Chin-Shan 0.79 - Nishimura, Etsuko 2.51 ▼ Goerlandt, Floris 5.34 - 35 Fagerholt, Kjetil 0.75 Farrell, JA 0.79 ▼ Lee, Yusin 2.50 - Wang, Hua 5.24 - 36 Fairlie, DP 0.73 Li, W 0.79 ▼ Konings, Rob 2.47 - Hvattum, Lars Magnus 4.98 - 37 Lucke, AJ 0.73 Donderi, DC 0.78 - Saeed, Naima 2.43 - Yip, Tsz Leung 4.92 - 38 Singh, Y 0.73 McFadden, S 0.78 - Merrick, Jason R. W. 2.43 - Christiansen, Marielle 4.91 - 39 Tyndall, JDA 0.73 Lee, RM 0.78 ▼ Ramirez-Marquez, Jose Emmanuel 2.33 - Hanninen, Maria 4.89 - 40 Fung, Michael K. 0.72 Bish, EK 0.77 ▲ Kahraman, Cengiz 2.29 - Wang, Jin 4.83 ▼  41 Bish, EK 0.67 Linn, RJ 0.76 ▼ Hastings, Justin V. 2.27 - Featherstone, David 4.82 - 42 Yun, JE 0.67 Ausloos, M 0.76 ▼ Cebi, Selcuk 2.18 - Lee, Der-Horng 4.77 ▼ 43 Marin, PL 0.66 Ivanova, K 0.76 ▼ Panayides, Photis M 2.18 - Hu, Zhi-Hua 4.77 - 44 Sicotte, R 0.66 Umemoto, K 0.76 - Goulielmos, Alexander M. 2.11 - Kontovas, Christos A. 4.76 - 45 Legato, Pasquale 0.66 Sciomachen, Anna 0.75 - Cao, Jin Xin 2.10 - Knapp, Sabine 4.52 - 46 Bhargava, HK 0.66 Koutsavdis, E 0.74 - Park, Changkyu 2.09 - Luo, Meifeng 4.51 ▼ 47 Snoap, KJ 0.66 Rhee, SH 0.74 - Seo, Junyong 2.09 - Nathan Huynh 4.50 - 48 Altiok, T 0.64 Fairlie, DP 0.73 ▼ Wu, Wei-Ming 2.07 - Yeo, Gi-Tae 4.43 - 49 Cullinane, Kevin 0.63 Lucke, AJ 0.73 ▼ Fossen, Thor I. 2.05 ▼ Meisel, Frank 4.41 ▼ 50 Gold, C 0.62 Singh, Y 0.73 ▼ Low, Joyce M. W 2.03 - Bell, Michael G. H. 4.40 -Another point worth noting is that the five-year impact scores of active authors have a significant raise. For example, the impact scores of the top 3 between period 3 and period 4 soared from 9.05, 8.73, and 7.79, respectively, to 34.45, 31.03, and 17.98, respectively. It may have been influenced by the growing number of publications and more publications being published in high-impact journals (impact score =∑y=20002017∑iN1/Iji×IMyi).


## 3.2.3. Core Authors and Collaboration Patterns

Derek Price prompted the celebrated “square root law" that states that half of the scientific papers are contributed by the top square root of the total number of scientific authors. The law was first proposed in Little Science-Big Science [23] and is heuristically based on Lotka's inverse square law. The Price’s law is calculated from the following equation:(3)M=0.749Nmaxwhere Nmax is the maximum number of the articles by one author. M is the minimum number of articles by a core author, which means the author whose published paper number is above M is the core author. In our data sample, Nmax equals 61, and according to Price’s law M equals 5.8. Thus, there are more than 190 authors who have published more than 6 papers in the field.For further analysis, we also tried to analyze the cooperation pattern of the core authors. The cooperation pattern means different authors appearing in multiple joint articles frequently. Table4 shows the results. An interesting observation is that the core authors (such as S.A. Wang, Q. Meng, E.P. Chew, L.H. Lee, and K. Fagerholt) in the container port and maritime field do frequently cooperate. This result indicates that most container port and maritime researchers are willing to cooperate with their familiar partners.Table 4
The most prolific paired authors.
Rank Paired authors Number of joint publications Rank Paired authors Number of joint publications 1 Meng, Q, Wang, SA 34 11 Papadimitriou, S, Nishimura, E 12  2 Chew, EP, Lee, LH 25 12 Fagerholt, K, Christiansen, M 12  3 Lai, KH, Cheng, TCE 17 13 Tan, KC, Chew, EP 11  4 Cheng, TCE, Lun, YHV 15 14 Tan, KC, Lee, LH 11  5 Yang, ZL, Wang, J 15 15 Wang, SA, Liu, ZY 11  6 Boile, M, Theofanis, S 14 16 Monios, J, Wilmsmeier, G 10  7 Lai, KH, Lun, YHV 14 17 Parola, F, Satta, G 10  8 Lee, DH, Chen, JH 13 18 Lee, DH, Cao, JX 10  9 Papadimitriou, S, Imai, A 13 19 Lai, KH, Wong, CWY 9  10 Imai, A, Nishimura, E 12 20 Christiansen, M, Andersson, H 9The top articles were considered as the lead articles of a research area [13]. The titles of core authors’ top 10 articles in the container port and maritime research area are also shown in Table 5. All of the top 3 articles are the overview in the port and maritime research area which may help new comers to understand quickly about container port and maritime field. The rest of the top 10 articles are interested in specific topics, including economics, operations research, business, and planning.Table 5
The top 10 articles of port and maritime research area.
Authour Title Citation Steenken, D; Voss, S; Stahlbock, R Container terminal operation and operations 500 research - a classification and literature review  Stahlbock, Robert; Voss, Stefan Operations research at container terminals: a 423 literature update  Vis, IFA; de Koster, R Transshipment of containers at a container 290 terminal: An overview  Christiansen, M; Fagerholt, K; Ship routing and scheduling: Status and 270 Ronen, D perspectives  Hummels, David Transportation costs and international trade in the 242 second era of globalization  Bierwirth, Christian; Meisel, A survey of berth allocation and quay crane 228 Frank scheduling problems in container terminals  Imai, A; Nishimura, E; The dynamic berth allocation problem for a 222 Papadimitriou, S container port  Kim, KH; Park, YM A crane scheduling method for port container 200 terminals  Tongzon, J; Heng, W Port privatization, efficiency and competitiveness: 169 Some empirical evidence from container ports (terminals)  Cullinane, K; Wang, TF; Song, The technical efficiency of container ports: 168 DW; Ji, P Comparing data envelopment analysis and stochastic frontier analysis


## 3.3. Affiliation Ranking Analysis

### 3.3.1. Affiliation Ranking for 2000-2015

Table6 displays affiliation rankings for 1996-2016. In paper counts, the National University of Singapore (NUS), Hong Kong Polytechnic University (HKPU), Norwegian University of Science and Technology, Delft University of Technology, and the University of Antwerp (UA) are in the top 5. The top schools are all strong regardless of how they are ranked. The most productive school, NUS, published 184 papers and was followed by HKPU with 174 papers. As with the authors' ranking, the gap between the second and third in the affiliation rankings is also relatively large (60 papers). Below these schools, the gap between the subsequent affiliations is no longer substantial. The top ten affiliations for 1996-2016 published 986 papers, which equate to an annual average of 46.87 papers. The best performing schools is still NUS. Another notable point is the sudden increase of Nanyang Technological University (NTU) in the ranking. As for the rank of citation score, it is stable and similar to the rank of impact score except for some slight fluctuations. But there is still some sudden increase that needs to be noteworthy. Univ Georgia Inst Technol’s rank ups 16 places to 9th. Univ Hamburg is not among the top 50 in the impact score but places to 5th in citation score.Table 6
Rankings by affiliations.
Rank School No. Paper Rank School Impact Score Rank School Citation Score 1 Natl Univ Singapore 184 1 Natl Univ Singapore 148.06 1 Natl Univ Singapore 3342  2 Hong Kong Polytech Univ 174 2 Hong Kong Polytech Univ 130.64 2 Norwegian Univ Sci & Technol 2525  3 Norwegian Univ Sci & Technol 114 3 Norwegian Univ Sci & Technol 69.67 3 Pusan Natl Univ 2179  4 Delft Univ Technol 93 4 Delft Univ Technol 64.03 4 Hong Kong Polytech Univ 1558  5 Univ Antwerp 84 5 Nanyang Technol Univ 59.83 5 Univ Hamburg 1075  6 Erasmus Univ 82 6 Erasmus Univ 58.04 6 Erasmus Univ 1052  7 Nanyang Technol Univ 73 7 Pusan Natl Univ 56.32 7 Istanbul Tech Univ 951  8 Shanghai Jiao Tong Univ 68 8 Dalian Maritime Univ 53.49 8 Univ Antwerp 934  9 Pusan Natl Univ 66 9 Istanbul Tech Univ 52.56 9 Georgia Inst Technol 868  10 Dalian Maritime Univ 62 10 Tech Univ Denmark 50.78 10 Hong Kong Univ Sci & Technol 802  11 Univ Genoa 61 11 Univ Antwerp 50.53 11 Univ Calif Berkeley 785  12 Univ Piraeus 58 12 Natl Taiwan Ocean Univ 47.26 12 Natl Cheng Kung Univ 777  13 Natl Taiwan Ocean Univ 55 13 Univ Genoa 46.33 13 Tech Univ Denmark 758  14 Istanbul Tech Univ 54 14 Hong Kong Univ Sci & Technol 43.11 14 Delft Univ Technol 719  15 Hong Kong Univ Sci & Technol 53 15 Natl Cheng Kung Univ 42.08 15 HEC Montreal 699  16 Tech Univ Denmark 52 16 Natl Kaohsiung Marine Univ 41.71 16 Kobe Univ 689  17 Univ Plymouth 51 17 Univ Plymouth 41.24 17 Univ Plymouth 645  18 Natl Cheng Kung Univ 47 18 Old Dominion Univ 39.36 18 Univ Hong Kong 635  18 Rutgers State Univ 47 19 Univ Piraeus 38.91 19 Univ Calabria 618  20 Cardiff Univ 43 20 Shanghai Jiao Tong Univ 38.59 20 Nanyang Technol Univ 574  21 Georgia Inst Technol 40 21 Cardiff Univ 32.64 21 Liverpool John Moores Univ 569  22 Natl Kaohsiung Marine Univ 39 22 Natl Tech Univ Athens 31.14 22 Norwegian Marine Technol Res Inst MARINTEK 559  23 Univ Rijeka 38 23 Vilnius Gediminas Tech Univ 31.00 23 Univ Genoa 559  24 Edinburgh Napier Univ 37 24 Edinburgh Napier Univ 30.94 24 Univ Halle Wittenberg 539  24 Liverpool John Moores Univ 37 25 Georgia Inst Technol 29.72 25 Univ Wisconsin 525  24 Natl Tech Univ Athens 37 26 Shanghai Univ 29.51 26 Univ London Imperial Coll Sci Technol & Med 513  27 Old Dominion Univ 36 27 Aalto Univ 29.35 27 Rutgers State Univ 492  27 Texas A&M Univ 36 28 Liverpool John Moores Univ 27.55 28 Univ Michigan 488  29 Univ Aegean 35 29 Inha Univ 26.71 29 Shanghai Jiao Tong Univ 461  30 Inha Univ 34 30 Univ Las Palmas Gran Canaria 26.42 30 Aalto Univ 458  30 Norwegian Marine Technol Res Inst MARINTEK 34 31 Univ Hong Kong 26.02 31 Univ Piraeus 421  30 Univ Hong Kong 34 32 Univ Calabria 24.92 32 Univ Elect Sci & Technol China 416  33 Univ Calif Berkeley 32 33 Norwegian Marine Technol Res Inst MARINTEK 24.05 33 Chalmers University of Technology 411  34 Chung Ang Univ 31 34 Univ Wollongong 24.02 34 Cardiff Univ 409  34 Univ Valencia 31 35 Shanghai Maritime Univ 23.97 35 Natl Tech Univ Athens 409  36 Shanghai Maritime Univ 30 36 Univ Aegean 23.03 36 Univ Tecn Lisboa 369  36 Shanghai Univ 30 37 Univ Belgrade 21.50 37 Queensland Univ Technol 363  38 HEC Montreal 29 38 Queensland Univ Technol 21.50 38 Kobe Univ Mercantile Marine 354  38 Univ Calabria 29 39 Univ Wisconsin 20.74 39 Univ Newcastle Upon Tyne 346  38 Univ Illinois 29 40 Chalmers 20.68 40 Univ Maryland 344  41 Eindhoven Univ Technol 28 41 Chang Jung Christian Univ 20.53 41 City Univ Hong Kong 342  41 MIT 28 42 Eindhoven Univ Technol 20.27 42 Dalian Maritime Univ 336  41 Univ Las Palmas Gran Canaria 28 43 Texas A&M Univ 20.09 43 Molde Univ Coll 336  44 Aalto Univ 27 44 Wuhan Univ Technol 19.05 44 Univ Las Palmas Gran Canaria 334  45 Univ Hamburg 26 45 Rutgers State Univ 18.60 45 Univ Southampton 332  45 Univ Oviedo 26 46 Chung Ang Univ 18.59 46 Natl Kaohsiung Marine Univ 329  45 Univ Wisconsin 26 47 Univ Illinois 18.49 47 Purdue Univ 324  45 Wuhan Univ Technol 26 48 Univ London Imperial Coll Sci Technol & Med 18.29 48 Antwerp Maritime Acad 318  49 Chalmers 25 49 Univ Seville 18.04 49 Chinese Acad Sci 305  49 City Univ Hong Kong 25 50 Univ Valencia 18.03 50 Ecole Polytech 303The affiliation ranking shows a similar pattern to author rankings. NUS have an outstanding container port and maritime researcher; Meng and HKPU have Wang. The two authors publish in impact score journals in container port and maritime research. It seems to indicate a direct relationship between research infrastructure and researchers. The size of the research infrastructure and the number of researchers available in the field may impact the researchers’ effectiveness and strength of knowledge conversion. In other words, the more the numerous researchers and knowledge, the higher the probability of the affiliation obtaining substantial knowledge conversion.


### 3.3.2. Ranking Dynamics for Affiliations

In Table7, the change of dynamic ranking of affiliations is relatively small. HKPU, NUS, and EU are consistently high. As we mentioned above, there seems to be a direct relationship between the affiliations and researchers. According to Foray and Lundvall [24], human capital (including graduates, highly skilled personnel, and public and private researchers) somewhat tends to flow to have more of the benefits from positive spillovers. Conversely, if there is not too much of a brain drain, the dynamics of affiliation ranking will remain relatively stable. However, if affiliations seek to remain competitive, it will have to retain a positive welfare system and take care of its producers in order to stem a brain drain.Table 7
Ranking dynamics of affiliations.
school impact score (1996-2000) school impact score (2001-2005)  school impact score (2006-2010)  school impact score (2011-2015) 1 Pusan Natl Univ 6.44 Pusan Natl Univ 7.12 - Natl Univ Singapore 34.97 ▲ Natl Univ Singapore 98.16 - 2 Natl Univ Singapore 3.68 Natl Univ Singapore 4.33 - Istanbul Tech Univ 24.40 - Hong Kong Polytech Univ 42.30 ▲ 3 Chinese Acad Sci 3.14 Hong Kong Polytech Univ 3.33 ▲ Hong Kong Polytech Univ 19.92 - Norwegian Univ Sci & Technol 39.96 ▲ 4 Univ Queensland 2.93 Univ Hawaii Manoa 3.30 ▲ Pusan Natl Univ 18.40 ▼ Nanyang Technol Univ 33.29 ▲ 5 Hong Kong Polytech Univ 2.73 Chinese Acad Sci 3.14 ▼ Natl Kaohsiung Marine Univ 12.50 - Dalian Maritime Univ 32.20 ▲ 6 Univ Edinburgh 2.44 Univ Queensland 2.93 ▼ Univ Calabria 12.16 ▲ Pusan Natl Univ 31.76 ▼ 7 Penn State Univ 2.39 Univ Hong Kong 2.60 ▲ Univ Genoa 10.31 ▲ Delft Univ Technol 29.53 ▲ 8 Norwegian Univ Sci & Technol 2.36 Norwegian Univ Sci & Technol 2.56 - Erasmus Univ 10.01 ▲ Univ Antwerp 29.44 ▲ 9 Erasmus Univ 2.28 Erasmus Univ 2.52 - Georgia Inst Technol 9.90 ▲ Erasmus Univ 28.32 ▼ 10 Carnegie Mellon Univ 2.25 Univ Genoa 2.52 ▲ Univ Wisconsin 9.85 - Shanghai Maritime Univ 27.10 ▲  11 Hong Kong Univ Sci & Technol 1.89 Univ Texas 2.44 - Univ Hong Kong 9.64 ▼ Tech Univ Denmark 25.07 - 12 Univ Hawaii Manoa 1.78 Hong Kong Univ Sci & Technol 2.29 ▼ Norwegian Univ Sci & Technol 9.54 ▼ Old Dominion Univ 24.22 - 13 Univ So Calif 1.76 Carnegie Mellon Univ 2.25 ▼ Univ Piraeus 8.96 ▲ Univ Wollongong 22.55 - 14 World Bank 1.71 Univ Piraeus 2.02 ▲ Univ Antwerp 8.41 - Univ Genoa 22.01 ▼ 15 Univ Tennessee 1.52 Natl Tech Univ Athens 1.99 ▲ Natl Cheng Kung Univ 8.39 ▲ Aalto Univ 21.88 - 16 Univ Genoa 1.51 Natl Cheng Kung Univ 1.83 ▲ Delft Univ Technol 8.06 - Univ Plymouth 21.64 ▲ 17 Univ Calif Riverside 1.40 Univ So Calif 1.76 ▼ Univ Plymouth 7.70 - Shanghai Univ 19.62 ▲ 18 Georgia Inst Technol 1.38 World Bank 1.71 ▼ Shanghai Maritime Univ 7.62 - Shanghai Jiao Tong Univ 19.36 ▼ 19 Natl Tech Univ Athens 1.36 Univ Calabria 1.68 ▲ Univ So Calif 7.29 ▼ Natl Kaohsiung Marine Univ 18.79 ▼ 20 Univ Calabria 1.32 Queensland Univ Technol 1.67 ▲ Vrije Univ Amsterdam 6.75 - Natl Taiwan Ocean Univ 18.51 ▲  21 Florida Int Univ 1.28 Georgia Inst Technol 1.61 ▼ Chinese Acad Sci 6.66 ▼ Hong Kong Univ Sci & Technol 18.46 ▼ 22 Univ Piraeus 1.25 Florida Int Univ 1.60 ▼ Chalmers 6.46 - Istanbul Tech Univ 17.41 ▼ 23 USN 1.24 Univ Tennessee 1.52 ▼ Univ Washington 6.16 - Cardiff Univ 16.12 ▼ 24 Swedish Univ Agr Sci 1.23 Fluent Inc 1.48 - Chang Jung Christian Univ 5.86 - Liverpool John Moores Univ 15.03 ▼ 25 Kobe Univ Mercantile Marine 1.19 Univ Calif Riverside 1.40 ▼ Cardiff Univ 5.46 - Tongji Univ 13.87 - 26 Liverpool John Moores Univ 1.17 Penn State Univ 1.32 ▼ Shanghai Jiao Tong Univ 5.19 - Norwegian Marine Technol Res Inst MARINTEK 13.81 - 27 Univ Hong Kong 1.03 Univ Adelaide 1.29 - Univ Western Australia 5.17 - Univ A Coruna 13.19 - 28 Univ Liege 1.00 Liverpool John Moores Univ 1.27 ▼ Univ London Imperial Coll Sci Technol & Med 5.14 - Edinburgh Napier Univ 13.16 - 29 Calif State Univ Bakersfield 0.96 Univ Missouri 1.25 ▲ Vilnius Gediminas Tech Univ 5.10 - Univ La Laguna 13.12 - 30 Univ Sydney 0.93 Swedish Univ Agr Sci 1.23 ▼ Rutgers State Univ 5.10 ▲ Natl Tech Univ Athens 13.06 ▲  31 Rutgers State Univ 0.92 Kobe Univ Mercantile Marine 1.19 ▼ Univ Portsmouth 5.08 - Univ Las Palmas Gran Canaria 12.88 - 32 Univ Glamorgan 0.92 World Maritime Univ 1.16 - Natl Taiwan Ocean Univ 5.04 ▲ Univ London Imperial Coll Sci Technol & Med 12.08 ▼ 33 Univ Ottawa 0.90 Natl Taiwan Ocean Univ 1.05 - Queensland Univ Technol 4.69 ▼ Univ Calabria 12.06 ▼ 34 Korea Adv Inst Sci & Technol 0.90 Texas A&M Univ 1.04 - Kobe Univ 4.63 ▲ Univ Aegean 11.41 - 35 Univ Missouri 0.90 Univ Delaware 1.02 ▲ Nanyang Technol Univ 4.29 - ExxonMobil Res & Engn Co 11.34 - 36 GKSS Forschungszentrum Geesthacht GmbH 0.89 Univ Liege 1.00 ▼ Univ Halle Wittenberg 4.24 - Eindhoven Univ Technol 11.33 - 37 NOAA 0.89 Newcastle Univ 0.98 - Univ Politecn Cataluna 4.19 - Chung Ang Univ 11.11 - 38 Cornell Univ 0.88 Calif State Univ Bakersfield 0.96 ▼ Natl Tech Univ Athens 4.19 ▼ Univ Seville 11.07 - 39 Univ Delaware 0.88 Univ Sydney 0.93 ▼ Univ Ulsan 4.18 - Inha Univ 10.97 - 40 Univ Illinois 0.81 Kobe Univ 0.91 - Scottish Agr Coll 4.13 - Univ Piraeus 10.66 ▼  41 Univ E Anglia 0.80 Univ Ottawa 0.90 ▼ Univ N Carolina 4.10 - Univ S Carolina 10.35 - 42 Queensland Univ Technol 0.76 Univ Michigan 0.89 - Molde Univ Coll 3.96 - Univ British Columbia 10.18 - 43 Aplus Flash Technol Inc 0.75 GKSS Forschungszentrum Geesthacht GmbH 0.89 ▼ Dalian Maritime Univ 3.82 - Univ Bergen 10.18 - 44 Kyungsung Univ 0.74 NOAA 0.89 ▼ Univ Calif Berkeley 3.77 - Newcastle Univ 9.76 ▼ 45 Univ Carlos III Madrid 0.73 Cornell Univ 0.88 ▼ Stevens Inst Technol 3.76 - Univ Sydney 9.50 ▼ 46 Natl Cheng Kung Univ 0.73 Fern Univ Hagen 0.82 - CNR 3.56 - Georgia Inst Technol 9.47 ▼ 47 Univ Pittsburgh 0.72 Univ Illinois 0.81 ▼ Hanyang Univ 3.48 - Univ Valencia 9.27 - 48 Korea Maritime Inst 0.72 Univ E Anglia 0.80 ▼ Purdue Univ 3.43 - Univ Politecn Valencia 9.08 - 49 Tech Univ Berlin 0.72 McGill Univ 0.78 - Tsinghua Univ 3.36 - Wuhan Univ Technol 9.04 - 50 Univ Wales Coll Cardiff 0.72 CNRS ULP 0.78 - Univ Sci & Technol China 3.29 - Univ Wisconsin 8.81 ▼


### 3.3.3. Collaboration Patterns

We also analyzed the cooperation pattern of affiliations. Table8 shows the top ten paired affiliations. The result indicates that affiliations do not stay in static cliques. They are willing to cooperate with new partners in order to achieve diversity and novelty. Core affiliations in the maritime field play the role of spreading advanced research results and promoting the development of the field.Table 8
The most prolific paired affiliations.
Rank Paired affiliations Number of joint publications 1 Norwegian Marine Technol Res Inst MARINTEK, Norwegian Univ Sci 27 & Technol  2 Univ Naples Parthenope, Univ Genoa 19  3 Natl Univ Singapore, Univ Wollongong 14  4 Antwerp Maritime Acad, Univ Antwerp 14  5 HEC Montreal, Norwegian Univ Sci & Technol 11  6 Nanyang Technol Univ, RMIT Univ 11  7 Hong Kong Polytech Univ, Shanghai Univ 11  8 Hong Kong Polytech Univ, Chung Ang Univ 8  9 Nanyang Technol Univ, Univ Antwerp 8  10 Dalian Maritime Univ, Univ Antwerp 8


## 3.3.1. Affiliation Ranking for 2000-2015

Table6 displays affiliation rankings for 1996-2016. In paper counts, the National University of Singapore (NUS), Hong Kong Polytechnic University (HKPU), Norwegian University of Science and Technology, Delft University of Technology, and the University of Antwerp (UA) are in the top 5. The top schools are all strong regardless of how they are ranked. The most productive school, NUS, published 184 papers and was followed by HKPU with 174 papers. As with the authors' ranking, the gap between the second and third in the affiliation rankings is also relatively large (60 papers). Below these schools, the gap between the subsequent affiliations is no longer substantial. The top ten affiliations for 1996-2016 published 986 papers, which equate to an annual average of 46.87 papers. The best performing schools is still NUS. Another notable point is the sudden increase of Nanyang Technological University (NTU) in the ranking. As for the rank of citation score, it is stable and similar to the rank of impact score except for some slight fluctuations. But there is still some sudden increase that needs to be noteworthy. Univ Georgia Inst Technol’s rank ups 16 places to 9th. Univ Hamburg is not among the top 50 in the impact score but places to 5th in citation score.Table 6
Rankings by affiliations.
Rank School No. Paper Rank School Impact Score Rank School Citation Score 1 Natl Univ Singapore 184 1 Natl Univ Singapore 148.06 1 Natl Univ Singapore 3342  2 Hong Kong Polytech Univ 174 2 Hong Kong Polytech Univ 130.64 2 Norwegian Univ Sci & Technol 2525  3 Norwegian Univ Sci & Technol 114 3 Norwegian Univ Sci & Technol 69.67 3 Pusan Natl Univ 2179  4 Delft Univ Technol 93 4 Delft Univ Technol 64.03 4 Hong Kong Polytech Univ 1558  5 Univ Antwerp 84 5 Nanyang Technol Univ 59.83 5 Univ Hamburg 1075  6 Erasmus Univ 82 6 Erasmus Univ 58.04 6 Erasmus Univ 1052  7 Nanyang Technol Univ 73 7 Pusan Natl Univ 56.32 7 Istanbul Tech Univ 951  8 Shanghai Jiao Tong Univ 68 8 Dalian Maritime Univ 53.49 8 Univ Antwerp 934  9 Pusan Natl Univ 66 9 Istanbul Tech Univ 52.56 9 Georgia Inst Technol 868  10 Dalian Maritime Univ 62 10 Tech Univ Denmark 50.78 10 Hong Kong Univ Sci & Technol 802  11 Univ Genoa 61 11 Univ Antwerp 50.53 11 Univ Calif Berkeley 785  12 Univ Piraeus 58 12 Natl Taiwan Ocean Univ 47.26 12 Natl Cheng Kung Univ 777  13 Natl Taiwan Ocean Univ 55 13 Univ Genoa 46.33 13 Tech Univ Denmark 758  14 Istanbul Tech Univ 54 14 Hong Kong Univ Sci & Technol 43.11 14 Delft Univ Technol 719  15 Hong Kong Univ Sci & Technol 53 15 Natl Cheng Kung Univ 42.08 15 HEC Montreal 699  16 Tech Univ Denmark 52 16 Natl Kaohsiung Marine Univ 41.71 16 Kobe Univ 689  17 Univ Plymouth 51 17 Univ Plymouth 41.24 17 Univ Plymouth 645  18 Natl Cheng Kung Univ 47 18 Old Dominion Univ 39.36 18 Univ Hong Kong 635  18 Rutgers State Univ 47 19 Univ Piraeus 38.91 19 Univ Calabria 618  20 Cardiff Univ 43 20 Shanghai Jiao Tong Univ 38.59 20 Nanyang Technol Univ 574  21 Georgia Inst Technol 40 21 Cardiff Univ 32.64 21 Liverpool John Moores Univ 569  22 Natl Kaohsiung Marine Univ 39 22 Natl Tech Univ Athens 31.14 22 Norwegian Marine Technol Res Inst MARINTEK 559  23 Univ Rijeka 38 23 Vilnius Gediminas Tech Univ 31.00 23 Univ Genoa 559  24 Edinburgh Napier Univ 37 24 Edinburgh Napier Univ 30.94 24 Univ Halle Wittenberg 539  24 Liverpool John Moores Univ 37 25 Georgia Inst Technol 29.72 25 Univ Wisconsin 525  24 Natl Tech Univ Athens 37 26 Shanghai Univ 29.51 26 Univ London Imperial Coll Sci Technol & Med 513  27 Old Dominion Univ 36 27 Aalto Univ 29.35 27 Rutgers State Univ 492  27 Texas A&M Univ 36 28 Liverpool John Moores Univ 27.55 28 Univ Michigan 488  29 Univ Aegean 35 29 Inha Univ 26.71 29 Shanghai Jiao Tong Univ 461  30 Inha Univ 34 30 Univ Las Palmas Gran Canaria 26.42 30 Aalto Univ 458  30 Norwegian Marine Technol Res Inst MARINTEK 34 31 Univ Hong Kong 26.02 31 Univ Piraeus 421  30 Univ Hong Kong 34 32 Univ Calabria 24.92 32 Univ Elect Sci & Technol China 416  33 Univ Calif Berkeley 32 33 Norwegian Marine Technol Res Inst MARINTEK 24.05 33 Chalmers University of Technology 411  34 Chung Ang Univ 31 34 Univ Wollongong 24.02 34 Cardiff Univ 409  34 Univ Valencia 31 35 Shanghai Maritime Univ 23.97 35 Natl Tech Univ Athens 409  36 Shanghai Maritime Univ 30 36 Univ Aegean 23.03 36 Univ Tecn Lisboa 369  36 Shanghai Univ 30 37 Univ Belgrade 21.50 37 Queensland Univ Technol 363  38 HEC Montreal 29 38 Queensland Univ Technol 21.50 38 Kobe Univ Mercantile Marine 354  38 Univ Calabria 29 39 Univ Wisconsin 20.74 39 Univ Newcastle Upon Tyne 346  38 Univ Illinois 29 40 Chalmers 20.68 40 Univ Maryland 344  41 Eindhoven Univ Technol 28 41 Chang Jung Christian Univ 20.53 41 City Univ Hong Kong 342  41 MIT 28 42 Eindhoven Univ Technol 20.27 42 Dalian Maritime Univ 336  41 Univ Las Palmas Gran Canaria 28 43 Texas A&M Univ 20.09 43 Molde Univ Coll 336  44 Aalto Univ 27 44 Wuhan Univ Technol 19.05 44 Univ Las Palmas Gran Canaria 334  45 Univ Hamburg 26 45 Rutgers State Univ 18.60 45 Univ Southampton 332  45 Univ Oviedo 26 46 Chung Ang Univ 18.59 46 Natl Kaohsiung Marine Univ 329  45 Univ Wisconsin 26 47 Univ Illinois 18.49 47 Purdue Univ 324  45 Wuhan Univ Technol 26 48 Univ London Imperial Coll Sci Technol & Med 18.29 48 Antwerp Maritime Acad 318  49 Chalmers 25 49 Univ Seville 18.04 49 Chinese Acad Sci 305  49 City Univ Hong Kong 25 50 Univ Valencia 18.03 50 Ecole Polytech 303The affiliation ranking shows a similar pattern to author rankings. NUS have an outstanding container port and maritime researcher; Meng and HKPU have Wang. The two authors publish in impact score journals in container port and maritime research. It seems to indicate a direct relationship between research infrastructure and researchers. The size of the research infrastructure and the number of researchers available in the field may impact the researchers’ effectiveness and strength of knowledge conversion. In other words, the more the numerous researchers and knowledge, the higher the probability of the affiliation obtaining substantial knowledge conversion.


## 3.3.2. Ranking Dynamics for Affiliations

In Table7, the change of dynamic ranking of affiliations is relatively small. HKPU, NUS, and EU are consistently high. As we mentioned above, there seems to be a direct relationship between the affiliations and researchers. According to Foray and Lundvall [24], human capital (including graduates, highly skilled personnel, and public and private researchers) somewhat tends to flow to have more of the benefits from positive spillovers. Conversely, if there is not too much of a brain drain, the dynamics of affiliation ranking will remain relatively stable. However, if affiliations seek to remain competitive, it will have to retain a positive welfare system and take care of its producers in order to stem a brain drain.Table 7
Ranking dynamics of affiliations.
school impact score (1996-2000) school impact score (2001-2005)  school impact score (2006-2010)  school impact score (2011-2015) 1 Pusan Natl Univ 6.44 Pusan Natl Univ 7.12 - Natl Univ Singapore 34.97 ▲ Natl Univ Singapore 98.16 - 2 Natl Univ Singapore 3.68 Natl Univ Singapore 4.33 - Istanbul Tech Univ 24.40 - Hong Kong Polytech Univ 42.30 ▲ 3 Chinese Acad Sci 3.14 Hong Kong Polytech Univ 3.33 ▲ Hong Kong Polytech Univ 19.92 - Norwegian Univ Sci & Technol 39.96 ▲ 4 Univ Queensland 2.93 Univ Hawaii Manoa 3.30 ▲ Pusan Natl Univ 18.40 ▼ Nanyang Technol Univ 33.29 ▲ 5 Hong Kong Polytech Univ 2.73 Chinese Acad Sci 3.14 ▼ Natl Kaohsiung Marine Univ 12.50 - Dalian Maritime Univ 32.20 ▲ 6 Univ Edinburgh 2.44 Univ Queensland 2.93 ▼ Univ Calabria 12.16 ▲ Pusan Natl Univ 31.76 ▼ 7 Penn State Univ 2.39 Univ Hong Kong 2.60 ▲ Univ Genoa 10.31 ▲ Delft Univ Technol 29.53 ▲ 8 Norwegian Univ Sci & Technol 2.36 Norwegian Univ Sci & Technol 2.56 - Erasmus Univ 10.01 ▲ Univ Antwerp 29.44 ▲ 9 Erasmus Univ 2.28 Erasmus Univ 2.52 - Georgia Inst Technol 9.90 ▲ Erasmus Univ 28.32 ▼ 10 Carnegie Mellon Univ 2.25 Univ Genoa 2.52 ▲ Univ Wisconsin 9.85 - Shanghai Maritime Univ 27.10 ▲  11 Hong Kong Univ Sci & Technol 1.89 Univ Texas 2.44 - Univ Hong Kong 9.64 ▼ Tech Univ Denmark 25.07 - 12 Univ Hawaii Manoa 1.78 Hong Kong Univ Sci & Technol 2.29 ▼ Norwegian Univ Sci & Technol 9.54 ▼ Old Dominion Univ 24.22 - 13 Univ So Calif 1.76 Carnegie Mellon Univ 2.25 ▼ Univ Piraeus 8.96 ▲ Univ Wollongong 22.55 - 14 World Bank 1.71 Univ Piraeus 2.02 ▲ Univ Antwerp 8.41 - Univ Genoa 22.01 ▼ 15 Univ Tennessee 1.52 Natl Tech Univ Athens 1.99 ▲ Natl Cheng Kung Univ 8.39 ▲ Aalto Univ 21.88 - 16 Univ Genoa 1.51 Natl Cheng Kung Univ 1.83 ▲ Delft Univ Technol 8.06 - Univ Plymouth 21.64 ▲ 17 Univ Calif Riverside 1.40 Univ So Calif 1.76 ▼ Univ Plymouth 7.70 - Shanghai Univ 19.62 ▲ 18 Georgia Inst Technol 1.38 World Bank 1.71 ▼ Shanghai Maritime Univ 7.62 - Shanghai Jiao Tong Univ 19.36 ▼ 19 Natl Tech Univ Athens 1.36 Univ Calabria 1.68 ▲ Univ So Calif 7.29 ▼ Natl Kaohsiung Marine Univ 18.79 ▼ 20 Univ Calabria 1.32 Queensland Univ Technol 1.67 ▲ Vrije Univ Amsterdam 6.75 - Natl Taiwan Ocean Univ 18.51 ▲  21 Florida Int Univ 1.28 Georgia Inst Technol 1.61 ▼ Chinese Acad Sci 6.66 ▼ Hong Kong Univ Sci & Technol 18.46 ▼ 22 Univ Piraeus 1.25 Florida Int Univ 1.60 ▼ Chalmers 6.46 - Istanbul Tech Univ 17.41 ▼ 23 USN 1.24 Univ Tennessee 1.52 ▼ Univ Washington 6.16 - Cardiff Univ 16.12 ▼ 24 Swedish Univ Agr Sci 1.23 Fluent Inc 1.48 - Chang Jung Christian Univ 5.86 - Liverpool John Moores Univ 15.03 ▼ 25 Kobe Univ Mercantile Marine 1.19 Univ Calif Riverside 1.40 ▼ Cardiff Univ 5.46 - Tongji Univ 13.87 - 26 Liverpool John Moores Univ 1.17 Penn State Univ 1.32 ▼ Shanghai Jiao Tong Univ 5.19 - Norwegian Marine Technol Res Inst MARINTEK 13.81 - 27 Univ Hong Kong 1.03 Univ Adelaide 1.29 - Univ Western Australia 5.17 - Univ A Coruna 13.19 - 28 Univ Liege 1.00 Liverpool John Moores Univ 1.27 ▼ Univ London Imperial Coll Sci Technol & Med 5.14 - Edinburgh Napier Univ 13.16 - 29 Calif State Univ Bakersfield 0.96 Univ Missouri 1.25 ▲ Vilnius Gediminas Tech Univ 5.10 - Univ La Laguna 13.12 - 30 Univ Sydney 0.93 Swedish Univ Agr Sci 1.23 ▼ Rutgers State Univ 5.10 ▲ Natl Tech Univ Athens 13.06 ▲  31 Rutgers State Univ 0.92 Kobe Univ Mercantile Marine 1.19 ▼ Univ Portsmouth 5.08 - Univ Las Palmas Gran Canaria 12.88 - 32 Univ Glamorgan 0.92 World Maritime Univ 1.16 - Natl Taiwan Ocean Univ 5.04 ▲ Univ London Imperial Coll Sci Technol & Med 12.08 ▼ 33 Univ Ottawa 0.90 Natl Taiwan Ocean Univ 1.05 - Queensland Univ Technol 4.69 ▼ Univ Calabria 12.06 ▼ 34 Korea Adv Inst Sci & Technol 0.90 Texas A&M Univ 1.04 - Kobe Univ 4.63 ▲ Univ Aegean 11.41 - 35 Univ Missouri 0.90 Univ Delaware 1.02 ▲ Nanyang Technol Univ 4.29 - ExxonMobil Res & Engn Co 11.34 - 36 GKSS Forschungszentrum Geesthacht GmbH 0.89 Univ Liege 1.00 ▼ Univ Halle Wittenberg 4.24 - Eindhoven Univ Technol 11.33 - 37 NOAA 0.89 Newcastle Univ 0.98 - Univ Politecn Cataluna 4.19 - Chung Ang Univ 11.11 - 38 Cornell Univ 0.88 Calif State Univ Bakersfield 0.96 ▼ Natl Tech Univ Athens 4.19 ▼ Univ Seville 11.07 - 39 Univ Delaware 0.88 Univ Sydney 0.93 ▼ Univ Ulsan 4.18 - Inha Univ 10.97 - 40 Univ Illinois 0.81 Kobe Univ 0.91 - Scottish Agr Coll 4.13 - Univ Piraeus 10.66 ▼  41 Univ E Anglia 0.80 Univ Ottawa 0.90 ▼ Univ N Carolina 4.10 - Univ S Carolina 10.35 - 42 Queensland Univ Technol 0.76 Univ Michigan 0.89 - Molde Univ Coll 3.96 - Univ British Columbia 10.18 - 43 Aplus Flash Technol Inc 0.75 GKSS Forschungszentrum Geesthacht GmbH 0.89 ▼ Dalian Maritime Univ 3.82 - Univ Bergen 10.18 - 44 Kyungsung Univ 0.74 NOAA 0.89 ▼ Univ Calif Berkeley 3.77 - Newcastle Univ 9.76 ▼ 45 Univ Carlos III Madrid 0.73 Cornell Univ 0.88 ▼ Stevens Inst Technol 3.76 - Univ Sydney 9.50 ▼ 46 Natl Cheng Kung Univ 0.73 Fern Univ Hagen 0.82 - CNR 3.56 - Georgia Inst Technol 9.47 ▼ 47 Univ Pittsburgh 0.72 Univ Illinois 0.81 ▼ Hanyang Univ 3.48 - Univ Valencia 9.27 - 48 Korea Maritime Inst 0.72 Univ E Anglia 0.80 ▼ Purdue Univ 3.43 - Univ Politecn Valencia 9.08 - 49 Tech Univ Berlin 0.72 McGill Univ 0.78 - Tsinghua Univ 3.36 - Wuhan Univ Technol 9.04 - 50 Univ Wales Coll Cardiff 0.72 CNRS ULP 0.78 - Univ Sci & Technol China 3.29 - Univ Wisconsin 8.81 ▼


## 3.3.3. Collaboration Patterns

We also analyzed the cooperation pattern of affiliations. Table8 shows the top ten paired affiliations. The result indicates that affiliations do not stay in static cliques. They are willing to cooperate with new partners in order to achieve diversity and novelty. Core affiliations in the maritime field play the role of spreading advanced research results and promoting the development of the field.Table 8
The most prolific paired affiliations.
Rank Paired affiliations Number of joint publications 1 Norwegian Marine Technol Res Inst MARINTEK, Norwegian Univ Sci 27 & Technol  2 Univ Naples Parthenope, Univ Genoa 19  3 Natl Univ Singapore, Univ Wollongong 14  4 Antwerp Maritime Acad, Univ Antwerp 14  5 HEC Montreal, Norwegian Univ Sci & Technol 11  6 Nanyang Technol Univ, RMIT Univ 11  7 Hong Kong Polytech Univ, Shanghai Univ 11  8 Hong Kong Polytech Univ, Chung Ang Univ 8  9 Nanyang Technol Univ, Univ Antwerp 8  10 Dalian Maritime Univ, Univ Antwerp 8


## 4. Analysis of the Countries/Regions

Table9 displays country rankings from 1996 to 2016. USA, China, and England are the top 3 countries irrespective of the scoring method. Although none of the authors or affiliations in the USA reached the top five, it still has dominant positions in these fields. It is true that local academic researchers could contribute to the competitiveness of the territory. However, in the context of world metropolis, the competition is no longer subject to natural geographical constraints, but more dependent on the territory itself to attract and retain human capital. The advantage of country competitiveness is actively built and not passively suffered. This may also indicate that the American government is good at attracting and promoting research.Table 9
The ranking of the countries/regions.
Rank Country No. papers Rank Country Impact Score 1 USA 993 1 USA 1170.25  2 PEOPLES R CHINA 714 2 PEOPLES R CHINA 972.35  3 ENGLAND 305 3 ENGLAND 384.71  4 CHINESE TAIPEI 263 4 CHINESE TAIPEI 354.65  5 SOUTH KOREA 205 5 SPAIN 269.14  6 ITALY 196 6 NORWAY 265.79  7 SPAIN 194 7 SINGAPORE 263.14  8 NORWAY 189 8 ITALY 263.10  9 GERMANY 183 9 NETHERLANDS 246.82  10 NETHERLANDS 182 10 GERMANY 246.18  11 SINGAPORE 172 11 SOUTH KOREA 244.03  12 AUSTRALIA 154 12 AUSTRALIA 212.31  13 CANADA 141 13 FRANCE 212.21  14 FRANCE 141 14 CANADA 197.57  15 GREECE 131 15 TURKEY 166.71  16 TURKEY 107 16 GREECE 161.82  17 JAPAN 99 17 BELGIUM 117.86  18 BELGIUM 87 18 DENMARK 113.96  19 SWEDEN 78 19 SWEDEN 108.00  20 DENMARK 74 20 JAPAN 107.91  21 CROATIA 69 21 PORTUGAL 76.12  23 PORTUGAL 56 22 INDIA 69.68  24 SCOTLAND 52 23 SCOTLAND 67.00  25 IRAN 51 24 FINLAND 64.27  26 INDIA 49 25 IRAN 61.00  27 RUSSIA 49 26 BRAZIL 58.16  28 POLAND 40 27 SWITZERLAND 44.00  29 BRAZIL 39 29 WALES 40.62  30 FINLAND 38 30 POLAND 39.64  31 WALES 36 31 CROATIA 36.24  32 LITHUANIA 33 32 LITHUANIA 34.05  33 SWITZERLAND 26 33 SERBIA 27.93  34 CHILE 24 34 ISRAEL 24.99  35 ISRAEL 23 35 CYPRUS 21.23  36 SLOVENIA 23 36 NEW ZEALAND 21.16  37 SERBIA 20 37 RUSSIA 21.15  38 MALAYSIA 18 38 AUSTRIA 20.00  39 NEW ZEALAND 16 39 CHILE 19.75  40 SOUTH AFRICA 16 40 MALAYSIA 19.25  41 AUSTRIA 14 41 SLOVENIA 17.52  42 CYPRUS 12 42 U ARAB EMIRATES 16.55  43 MEXICO 12 43 SOUTH AFRICA 14.76  44 U ARAB EMIRATES 12 44 MEXICO 13.88  45 UKRAINE 11 45 THAILAND 12.11  46 MONTENEGRO 10 46 LEBANON 10.98  47 IRELAND 8 47 IRELAND 9.59  48 LEBANON 8 48 CZECH REPUBLIC 9.18  49 THAILAND 8 49 NIGERIA 6.83  50 ARGENTINA 6 50 MONTENEGRO 6.49Going further into country publications in the port and maritime transport system field, the top 20 countries ranking by the annual number of publications are discussed. Figure2 shows the change among the top 20 countries over time. It can be seen that the general trend of annual journal publication has increased. Over the past decade, however, the publications of China have grown much faster than in the United States and other countries. In addition, China has kept up with the United States approximately with the same number of journal publications in the port and maritime transport system field since 2014, as indicated in Figure 2. Interestingly, the pioneers are not American or Chinese, even though they are the most influential countries in this field, since they did not publish papers from the beginning.Figure 2
Trend of the countries/regions.


## 5. Analysis of Research Terms

In bibliometric analysis, it is useful to select several keywords as a representation of important research topics in this field if a researcher wants to explore every facet of a field’s major research topics and their relationships down to the finest detail. Term Frequency-Inverse Document Frequency (TF-IDF) promoted by Salton and Buckley [25] is a typical method of identifying important terms by combining their popularity and discrimination. The TF-IDF method can also be applied to bibliometric analysis. For example, Jaboska-Sabuka et al. [26] used TF-IDF to identify informative words from publication keywords of the research domain in order to predict research trends. Roche [27] used TF-IDF to select publication keywords of scientific fields and categorized them into unusual terms, established terms, and cross-sectional terms. (tf-idft) is calculated for each word. Salton et al. [28] from the following equation: (4)tfidft=∑dNtft,d×log⁡Ndftwhere tft,d is frequency of the word t in the document d, N is number of the articles, and dft is the number of articles where word t existed.


### 5.1. Overall Analysis

Various research terms are observed in articles published in the time period from 1996 to 2016. Table10 shows the top 60 research terms of these fields. From Table 10, we can indicate that port and maritime transport system field have been classified in the literature in terms of shipping or port research and their respective methodologies applied in the research. We also built the word cooccurrence table to create highly cooccurring word sets. The input words in the table satisfy the following two limitations. First, the tf-idf factor of these words is greater than the A threshold value. Second, the number of publications which contained a candidate word is within the specified range by the B threshold. An analysis of Table 11 reveals that the specific shipping topics include seafarers, short sea shipping, shipping performance/management, shipping finance, and shipping safety. Specific port topics include port governance/privatization, port performance, port state control, port competition, and port choice.Table 10
The top 60 research terms.
Word TF-IDF Word TF-IDF port 201.99 management 58.21  container 171.73 simulation 57.80  terminal 130.71 supply 57.59  shipping 121.37 dynamic 56.89  ship 120.68 liner 56.88  cost 100.25 company 56.76  transport 97.69 logistics 56.56  control 92.95 cargo 56.49  network 90.09 factor 56.44  service 86.66 impact 56.28  algorithm 85.17 route 55.70  maritime 82.58 rate 55.62  vessel 77.78 planning 55.03  market 75.80 development 54.87  transportation 74.55 optimization 54.57  risk 73.53 safety 54.32  freight 72.68 yard 54.17  approach 72.35 truck 53.48  operation 71.54 price 52.32  optimal 70.83 trade 52.11  data 67.46 traffic 51.59  efficiency 64.82 heuristic 51.58  crane 64.69 marine 51.10  scheduling 63.60 capacity 51.04  process 63.14 level 50.22  policy 61.66 economic 50.06  strategy 60.64 flow 48.94  emission 59.64 sea 48.66  chain 59.52 condition 47.73  industry 58.51 function 47.45Table 11
The top 6 words cooccurrence table for port and shipping.
Cooccurrence word Frequent Cooccurrence word Frequent shipping management 603 port perform 824  shipping perform 354 port state control 383  shipping network 232 port governance/government 209  shipping short-term 168 port choice 188  shipping safety 157 port competition 183  shipping finance 91 port private(privatization) 135Table12 shows the dynamics of the research terms. Although there are several new words that arise throughout time, the rise and fall of research terms are prominent in the port and maritime transport system field. In 2006-2010, some new words such as berth and vessel turned up as new research objects. In 2001-2015, the word emission turned up as a new research topic and reached the top 5. This may be caused by some environment protection policy such as Regulation 14 of the IMO that required ships to switch to low sulfur fuels in ECA areas. Another notable point is the rank change of the words risk and liner. Risk was a top 8 word in 1996-2000, but fell to 18th in 2011-2015. By inspecting the papers that include the word risk, we determined that the author Jin Wang published numerous papers examining maritime risk in 1996-2000, but he did not publish as much from 2011 to 2015, and his rank fell from 10 to 40. We can draw an obvious conclusion that Shuaian Wang is a specialized researcher investigating liners, and he is the top author in 2011-2015. This finding indicates that a specific research may be influenced by one or two authors.Table 12
Ranking dynamics of research terms.
Word TF-IDF Word TF-IDF  Word TF-IDF  Word TF-IDF (1996-2000) (2001-2005)  (2006-2010) (2011-2015) 1 freight 2.88 container 3.46 ▲ port 16.37 ▲ port 20.67 -  2 network 2.34 port 3.24 ▲ container 14.64 ▼ container 18.52 -  3 science 2.11 yard 2.45 - shipping 8.27 ▲ shipping 14.50 -  4 container 2.09 cost 2.28 ▲ terminal 8.07 ▲ ship 13.86 ▲  5 carrier 2.00 truck 2.19 ▲ cost 7.86 ▼ emission 12.10 -  6 intermodal 1.99 heuristic 1.98 - maritime 7.45 - terminal 11.02 ▼  7 transportation 1.83 ship 1.90 ▲ transport 7.42 ▲ cost 9.75 ▼  8 risk 1.82 terminal 1.86 ▲ market 7.09 ▲ network 9.46 ▲  9 port 1.76 vehicle 1.76 - crane 6.94 ▲ transport 9.29 ▼  10 policy 1.65 safety 1.76 ▲ transportation 6.85 ▲ service 8.69 ▲  11 terminal 1.56 policy 1.73 ▼ yard 6.27 ▼ freight 8.48 ▼  12 truck 1.56 transport 1.71 ▲ berth 6.17 - control 8.47 -  13 ocean 1.54 crane 1.67 - scheduling 5.97 - algorithm 8.43 ▲  14 service 1.51 transportation 1.65 ▼ ship 5.94 ▲ approach 8.16 ▲  15 market 1.50 algorithm 1.62 - network 5.87 ▼ liner 7.93 -  16 operation 1.49 capacity 1.61 - operation 5.79 - crane 7.91 ▼  17 ship 1.45 market 1.57 ▼ service 5.61 ▲ maritime 7.73 ▼  18 transport 1.44 shipping 1.48 - approach 5.43 - risk 7.66 ▼  19 cost 1.41 service 1.48 ▼ vessel 5.36 - optimal 7.61 -  20 safety 1.31 product 1.44 - algorithm 5.34 - cargo 7.48 -


## 5.1. Overall Analysis

Various research terms are observed in articles published in the time period from 1996 to 2016. Table10 shows the top 60 research terms of these fields. From Table 10, we can indicate that port and maritime transport system field have been classified in the literature in terms of shipping or port research and their respective methodologies applied in the research. We also built the word cooccurrence table to create highly cooccurring word sets. The input words in the table satisfy the following two limitations. First, the tf-idf factor of these words is greater than the A threshold value. Second, the number of publications which contained a candidate word is within the specified range by the B threshold. An analysis of Table 11 reveals that the specific shipping topics include seafarers, short sea shipping, shipping performance/management, shipping finance, and shipping safety. Specific port topics include port governance/privatization, port performance, port state control, port competition, and port choice.Table 10
The top 60 research terms.
Word TF-IDF Word TF-IDF port 201.99 management 58.21  container 171.73 simulation 57.80  terminal 130.71 supply 57.59  shipping 121.37 dynamic 56.89  ship 120.68 liner 56.88  cost 100.25 company 56.76  transport 97.69 logistics 56.56  control 92.95 cargo 56.49  network 90.09 factor 56.44  service 86.66 impact 56.28  algorithm 85.17 route 55.70  maritime 82.58 rate 55.62  vessel 77.78 planning 55.03  market 75.80 development 54.87  transportation 74.55 optimization 54.57  risk 73.53 safety 54.32  freight 72.68 yard 54.17  approach 72.35 truck 53.48  operation 71.54 price 52.32  optimal 70.83 trade 52.11  data 67.46 traffic 51.59  efficiency 64.82 heuristic 51.58  crane 64.69 marine 51.10  scheduling 63.60 capacity 51.04  process 63.14 level 50.22  policy 61.66 economic 50.06  strategy 60.64 flow 48.94  emission 59.64 sea 48.66  chain 59.52 condition 47.73  industry 58.51 function 47.45Table 11
The top 6 words cooccurrence table for port and shipping.
Cooccurrence word Frequent Cooccurrence word Frequent shipping management 603 port perform 824  shipping perform 354 port state control 383  shipping network 232 port governance/government 209  shipping short-term 168 port choice 188  shipping safety 157 port competition 183  shipping finance 91 port private(privatization) 135Table12 shows the dynamics of the research terms. Although there are several new words that arise throughout time, the rise and fall of research terms are prominent in the port and maritime transport system field. In 2006-2010, some new words such as berth and vessel turned up as new research objects. In 2001-2015, the word emission turned up as a new research topic and reached the top 5. This may be caused by some environment protection policy such as Regulation 14 of the IMO that required ships to switch to low sulfur fuels in ECA areas. Another notable point is the rank change of the words risk and liner. Risk was a top 8 word in 1996-2000, but fell to 18th in 2011-2015. By inspecting the papers that include the word risk, we determined that the author Jin Wang published numerous papers examining maritime risk in 1996-2000, but he did not publish as much from 2011 to 2015, and his rank fell from 10 to 40. We can draw an obvious conclusion that Shuaian Wang is a specialized researcher investigating liners, and he is the top author in 2011-2015. This finding indicates that a specific research may be influenced by one or two authors.Table 12
Ranking dynamics of research terms.
Word TF-IDF Word TF-IDF  Word TF-IDF  Word TF-IDF (1996-2000) (2001-2005)  (2006-2010) (2011-2015) 1 freight 2.88 container 3.46 ▲ port 16.37 ▲ port 20.67 -  2 network 2.34 port 3.24 ▲ container 14.64 ▼ container 18.52 -  3 science 2.11 yard 2.45 - shipping 8.27 ▲ shipping 14.50 -  4 container 2.09 cost 2.28 ▲ terminal 8.07 ▲ ship 13.86 ▲  5 carrier 2.00 truck 2.19 ▲ cost 7.86 ▼ emission 12.10 -  6 intermodal 1.99 heuristic 1.98 - maritime 7.45 - terminal 11.02 ▼  7 transportation 1.83 ship 1.90 ▲ transport 7.42 ▲ cost 9.75 ▼  8 risk 1.82 terminal 1.86 ▲ market 7.09 ▲ network 9.46 ▲  9 port 1.76 vehicle 1.76 - crane 6.94 ▲ transport 9.29 ▼  10 policy 1.65 safety 1.76 ▲ transportation 6.85 ▲ service 8.69 ▲  11 terminal 1.56 policy 1.73 ▼ yard 6.27 ▼ freight 8.48 ▼  12 truck 1.56 transport 1.71 ▲ berth 6.17 - control 8.47 -  13 ocean 1.54 crane 1.67 - scheduling 5.97 - algorithm 8.43 ▲  14 service 1.51 transportation 1.65 ▼ ship 5.94 ▲ approach 8.16 ▲  15 market 1.50 algorithm 1.62 - network 5.87 ▼ liner 7.93 -  16 operation 1.49 capacity 1.61 - operation 5.79 - crane 7.91 ▼  17 ship 1.45 market 1.57 ▼ service 5.61 ▲ maritime 7.73 ▼  18 transport 1.44 shipping 1.48 - approach 5.43 - risk 7.66 ▼  19 cost 1.41 service 1.48 ▼ vessel 5.36 - optimal 7.61 -  20 safety 1.31 product 1.44 - algorithm 5.34 - cargo 7.48 -


## 6. Conclusions

In this paper, we have analyzed maritime-related academic research. We utilized bibliometric analysis method to illustrate the evolution of this field. The two criteria used in ranking were the number of published papers and the impact score (reflecting the prestige of the journals). We focused on the papers published in journals included in the Science Citation Index and Social Science Citation Index.Ranking criteria influences the overall rankings for authors and affiliations sensitively. In terms of the impact score, the most active researchers are S.A. Wang, Q. Meng, T. Notteboom, J.S.L. Lam, and K.H. Kim. The most active affiliations were the National University of Singapore, Hong Kong Polytechnic University, the Norwegian University of Science and Technology, Delft University of Technology, and the Nanyang Technology University. Affiliations rankings seem to have been affected by authors ranking. For example, the top affiliation has the top author. However, the network features of authors and affiliations are quite different. At the microlevel, overall research terms in the container port and maritime field are identified by the TF-IDF algorithm.This paper has limitations. In terms of the scoring method, especially impact score, the impact factor does not reflect a journals quality perfectly. For instance, several highly respected journals have a low impact factor. There are several other indicators that can measure the impact, such as the H index and the number of citations for authors.



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*Source: 6471625-2018-11-21.xml*