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HIRATA Enna
Graduate School of Maritime Sciences / Department of Maritime Sciences
Professor

Researcher basic information

■ Research Keyword
  • NLP
  • Industrial Engineering
  • AI
  • Big Data Analysis
  • Blockchain
  • Transport Economics
■ Research Areas
  • Informatics / Intelligent informatics / AI, Machine Learning, Deep Learning
  • Humanities & social sciences / Economic policy / Digitization, Competition, Shipping, Transport Economics
■ Committee History
  • Jun. 2022 - Present, Maritime Policy & Management, Associate Editor
  • Apr. 2022 - Present, Port Effectiveness and Public Private Cooperation for Competitiveness (PEPP II), International Advisory Board, https://projects.au.dk/pepp-ii/international-advisory-board
  • Nov. 2021 - Present, Japan Society of Logistics and Shipping Economics, International Exchange Committee

Research activity information

■ Award
  • Jul. 2023 Emerald Publishing, Emerald Literati Awards 2023 Outstanding Paper, Uncovering the impact of COVID-19 on shipping and logistics
    Enna Hirata, Takuma Matsuda

  • Jul. 2022 Emerald Publishing, Emerald Literati Awards 2022 Outstanding Paper, Blockchain technology in supply chain management: insights from machine learning algorithms
    Enna Hirata, Maria Lambrou, Daisuke Watanabe

  • Jun. 2018 The 11th International Conference of Asian Shipping and Logistics (ICASL 2018), Commended Paper Award
    Enna Hirata

  • Oct. 2016 Japan Society of Logistics and Shipping Economics, International Exchange Award
    Enna Hirata

■ Paper
  • Hisatoshi Naganawa, Enna Hirata
    Apr. 2025, Logistics, 9(2)(56) (56), 1 - 21, English
    [Refereed]
    Scientific journal

  • Hisatoshi Naganawa, Enna Hirata
    Mar. 2025, Electronics, 14(7)(1241) (1241), 1 - 13, English
    [Refereed]
    Scientific journal

  • Enna Hirata, Nailah Firdausiyah, Widha Kusumaningdyah
    Lead, Springer Science and Business Media LLC, Dec. 2024, Maritime Economics & Logistics, English
    [Refereed]
    Scientific journal

  • Enna Hirata, Kevin X. Li, Daisuke Watanabe
    Elsevier BV, Dec. 2024, Sustainable Futures, 8, 100358 - 100358, English
    [Refereed]
    Scientific journal

  • Muhammad I. Fahreza, Enna Hirata
    Last, Informa UK Limited, Nov. 2024, Maritime Policy & Management, 1 - 14, English
    [Refereed]
    Scientific journal

  • Strategy Generation and Selection for Maritime Piracy and Armed Robbery Problem in the Straits of Malacca and Singapore through Bayesian Network-based TOPSIS Analysis
    Muhammad I. Fahreza, Enna Hirata
    Nov. 2024, The Proceedings of the 70th JSCE Annual Meeting., 70, English
    Symposium

  • A Proposal for Container Transportation of Compressed Hydrogen in a Physical Internet Environment.
    野原郁哉, 平田燕奈
    Nov. 2024, 土木計画学研究・講演集, 70, Japanese
    Research institution

  • A Research on Prediction of People Flow around Stations Using Natural Language Processing
    樊世星, 平田燕奈
    Nov. 2024, 土木計画学研究・講演集, 70, Japanese
    Symposium

  • The 2024 Issue in Logistics: A Natural Language Processing Analysis Using YouTube Comment Data.
    Naganawa Hisatoshi, Hirata Enna
    Nov. 2024, 土木計画学研究・講演集, 70, Japanese
    Symposium

  • 平田燕奈
    Sep. 2024, 生活協同組合研究, 584, 30 - 37, Japanese
    [Invited]

  • Daiki Ueno, Enna Hirata
    (1) Background: This work focuses on improving the efficiency of warehouse operations with the goal of promoting efficiency in the logistics industry and mitigating logistics-related labor shortages. Many factors are involved in warehouse operations, such as the optimal allocation of manpower, the optimal layout design, and the use of automatic guided vehicles, which together affect operational efficiency. (2) Methods: In this work, we developed an optimal method for operating a limited number of workers or picking robots in a specific area, coping with cases of sudden disruptions such as a change in picking order or the blockage of aisles. For this purpose, the number of pickers, the storage capacity, and other constraints such as sudden changes in picking orders during the picking process, as well as blockages in the aisles of a warehouse site, are considered. The total travel distance is minimized using Gurobi, an optimization solver. (3) Results: The picking routes were optimized in three different scenarios using the shortest route between the starting point and the picking points, resulting in up to a 31% efficiency improvement in terms of the total distance traveled. (4) Conclusions: The main contribution of this work is that it focuses on the day-to-day work situations of sudden changes in the picking order and the presence of route blocks in real-world logistics warehouse sites. It demonstrates the feasibility of responding to sudden disruptions and simultaneously optimizing picking routes in real time. This work contributes to the overall efficiency of logistics by providing a simple, yet practical, data-driven solution for the optimization of warehouse operations.
    MDPI AG, Aug. 2024, Mathematics, 12(16) (16), 2580 - 2580, English
    [Refereed]
    Scientific journal

  • Hisatoshi Naganawa, Enna Hirata
    May 2024, the Proceedings of the 10th International Physical Internet Conference, 26 - 35, English, No password
    [Refereed]
    International conference proceedings

  • Enna Hirata, Daisuke Watanabe, Athanasios Chalmoukis, Maria Lambrou
    Apr. 2024, Sustainability, English, No password
    [Refereed]
    Scientific journal

  • Hisatoshi Naganawa, Enna Hirata, Nailah Firdausiyah, Russell G. Thompson
    Corresponding, Apr. 2024, Logistics, English, No password
    [Refereed]
    Scientific journal


  • フィジカルインターネットにおける物流拠点の最適立地と配送ルートの最適化
    長縄尚駿, 平田燕奈
    Nov. 2023, 土木計画学研究・講演集, 68, Japanese
    Research society

  • 物流倉庫におけるピッキングの最適化
    上野大樹, 平田燕奈
    Last, Nov. 2023, 土木計画学研究・講演集, 68, Japanese
    Research society

  • Enna Hirata, Takahiro Yamashita, Seiichi Ozawa
    Jul. 2023, Journal of Advanced Computational Intelligence and Intelligent Informatics, 27(4) (4), 603 - 608, English
    [Refereed]
    Scientific journal

  • Enna Hirata, Takuma Matsuda
    Elsevier BV, Apr. 2023, Asian Transport Studies, 9, 100110 - 100110, English
    [Refereed]
    Scientific journal

  • Enna Hirata, Takuma Matsuda
    PurposeThis research aims to uncover coronavirus disease 2019’s (COVID-19's) impact on shipping and logistics using Internet articles as the source. Design/methodology/approachThis research applies web mining to collect information on COVID-19's impact on shipping and logistics from Internet articles. The information extracted is then analyzed through machine learning algorithms for useful insights. FindingsThe research results indicate that the recovery of the global supply chain in China could potentially drive the global supply chain to return to normalcy. In addition, researchers and policymakers should prioritize two aspects: (1) Ease of cross-border trade and logistics. Digitization of the supply chain and applying breakthrough technologies like blockchain and IoT are needed more than ever before. (2) Supply chain resilience. The high dependency of the global supply chain on China sounds like an alarm of supply chain resilience. It calls for a framework to increase global supply chain resilience that enables quick recovery from disruptions in the long term. Originality/valueDiffering from other studies taking the natural language processing (NLP) approach, this research uses Internet articles as the data source. The findings reveal significant components of COVID-19's impact on shipping and logistics, highlighting crucial agendas for scholars to research.
    Emerald, Oct. 2022, Maritime Business Review, 7(4) (4), 305 - 317, English
    [Refereed]
    Scientific journal

  • Development of Researcher Network Visualization System by Matrix Researcher2vec
    Enna Hirata, Takahiro Yamashita, Seiichi Ozawa
    Sep. 2022, the Proceedings of the 30th Symposium on Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence, 240 - 243, English
    [Refereed]
    International conference proceedings

  • A Study on Market Forecast of International Logistics Using Natural Language Processing -Based on a Questionnaire Survey for Major Freight Forwarders in Japan
    Daisuke Watanabe, Enna Hirata, Maria Lambrou
    Sep. 2022, Proceedings of 2022 conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • Enna Hirata, Daisuke Watanabe, Maria Lambrou
    Shipping, like most industries, is undergoing a digital transformation process which influences existing business models and operational practices, in a multifaceted way. Today, the shipping business context has been changing to incorporate further social demands, environmental, innovation and sustainability priorities, into fundamental shipping strategies, while taking advantage of technological advancements. In the era of Industry 4.0, which constitutes a recent evolution of advanced communications and information technologies and further promotes sustainable, human-centric, and resilient business development strategies, shipping and port entities need to embrace a broader perspective and a deeper understanding of various elemental technologies, namely: Artificial Intelligence, Blockchain, Cloud Computing, Big Data, and Physical Internet, in addition to core maritime logistics matters. This chapter proposes a descriptive framework of shipping digitalization and port automation, while providing a review of related technologies and business approaches, also international initiatives, for automation in global ports. Hence the chapter offers insights for business practitioners to steer through the current challenging global environment, also for policy makers to gain a more informed understanding of maritime logistics developments, towards necessary coordination and oversight mechanisms implementation.
    IntechOpen, Jul. 2022, Supply Chain - Recent Advances and New Perspectives in the Industry 4.0 Era, English
    [Refereed][Invited]
    In book

  • Enna Hirata, Takuma Matsuda
    With the increasing availability of large datasets and improvements in prediction algorithms, machine-learning-based techniques, particularly deep learning algorithms, are becoming increasingly popular. However, deep-learning algorithms have not been widely applied to predict container freight rates. In this paper, we compare a long short-term memory (LSTM) method and a seasonal autoregressive integrated moving average (SARIMA) method for forecasting the comprehensive and route-based Shanghai Containerized Freight Index (SCFI). The research findings indicate that the LSTM deep learning models outperformed SARIMA models in most of the datasets. For South America and the east coast of the U.S. routes, LSTM could reduce forecasting errors by as much as 85% compared to SARIMA. The SARIMA models performed better than LSTM in predicting freight movements on the west and east Japan routes. The study contributes to the literature in four ways. First, it presents insights for improving forecasting accuracy. Second, it helps relevant parties understand the trends of container freight markets for wiser decision-making. Third, it helps relevant stakeholders understand overall container shipping market trends. Lastly, it can help hedge against the volatility of freight rates.
    {MDPI} {AG}, Apr. 2022, Journal of Marine Science and Engineering, 10(5) (5), 593 - 593, English, No password
    [Refereed]
    Scientific journal

  • Takuma Matsuda, Enna Hirata, Tomoya Kawasaki
    PurposeSince the 2010s, market conditions for container shipping companies have been deteriorating owing to decreasing container cargo trade and increasing supply capacity. This study aims to contribute to the empirical literature on the container shipping industry market structure. Specifically, this study aims to investigate the extent of market competition. Design/methodology/approachThis study analyzes the market structure and evaluates the market power of shipping companies through a non-structural test. FindingsThe H-statistic for the entire period of 2004–2018 was 0.37, which is significantly different from zero. This indicates the absence of monopoly pricing throughout the entire period. For the time-phased estimates, the H-statistic between 2004 and 2008 is 0.15, which is not significantly different from zero. On the other hand, the H-statistic from 2009 to 2018 was 0.40, which differs significantly from zero. Originality/valueAs the Far East Freight Conference had released tariffs and charge rates by item for container shipping routes, monopolistic pricing is said to have appeared until the European Union abolished the European Economic Community (No. 4056/86) in 2008, before the economic crisis. However, this study indicates that pricing in the container shipping industry has been distinctly non-monopolistic; further, competition seems to have intensified since 2008. Industry competitiveness is of interest not only to academics but also to practitioners, including policymakers, especially when considering competition policies.
    Emerald, Dec. 2021, Maritime Business Review, 7(4) (4), 318 - 331, English, No password
    [Refereed]
    Scientific journal

  • A Study on the Applicability of Blockchain Technology in Physical Internet
    Enna Hirata
    Dec. 2021, Maritime Transportation Research, 70, 67 - 77, Japanese
    [Refereed]
    Scientific journal

  • Similarity between Digital Platforms – A Machine Learning Approach
    Enna Hirata, Maria Lambrou, Daisuke Watanabe
    Nov. 2021, Proceedings of 2021 conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • Quazi Mohammed Habibus Sakalayen, Okan Duru, Enna Hirata
    Purpose Bulk shipping mostly facilitates the smooth flow of raw materials around the globe. Regardless, forecasting a bulk shipbuilding orderbook is a seldom researched domain in the academic arena. This study aims to pioneer an econophysics approach coupled with an autoregressive data analysis technique for bulk shipbuilding order forecasting. Design/methodology/approach By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The model has been evaluated through autoregressive integrated moving average analysis, and the outcome indicates a relatively stable good fit. Findings The outcomes of the econophysics model indicate a relatively stable good fit. Although relevant maritime data and its quality need to be improved, the flexibility in refining the predictive variables ensure the robustness of this econophysics-based forecasting model. Originality/value By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The research result helps shipping investors make decision in a capital-intensive and uncertainty-prone environment.
    Emerald, Sep. 2021, Maritime Business Review, 6(3) (3), 234 - 255, English
    [Refereed]
    Scientific journal

  • Yongpeng Wang, Daisuke Watanabe, Enna Hirata, Shigeki Toriumi
    In this study, we propose an effective method using deep learning to strengthen real-time vessel carbon dioxide emission management. We propose a method to predict real-time carbon dioxide emissions of the vessel in three steps: (1) convert the trajectory data of the fixed time interval into a spatial–temporal sequence, (2) apply a long short-term memory (LSTM) model to predict the future trajectory and vessel status data of the vessel, and (3) predict the carbon dioxide emissions. Automatic identification system (AIS) database of a liquefied natural gas (LNG) vessel were selected as the sample and we reconstructed the trajectory data with a fixed time interval using cubic spline interpolation. Applying the interpolated AIS data, the carbon dioxide emissions of the vessel were calculated based on the International Towing Tank Conference (ITTC) recommended procedures. The experimental results are twofold. First, it reveals that vessel emissions are currently underestimated. This study clearly indicates that the actual carbon dioxide emissions are higher than those reported. The finding offers insight into how to accurately measure the emissions of vessels, and hence, better execute a greenhouse gases (GHGs) reduction strategy. Second, the LSTM model has a better trajectory prediction performance than the recurrent neural network (RNN) model. The errors of the trajectory endpoint and carbon dioxide emissions were small, which shows that the LSTM model is suitable for spatial–temporal data prediction with excellent performance. Therefore, this study offers insights to strengthen the real-time management and control of vessel greenhouse gas emissions and handle those in a more efficient way.
    MDPI AG, Aug. 2021, Journal of Marine Science and Engineering, 9(8) (8), 871 - 871, English
    [Refereed]
    Scientific journal

  • Enna Hirata, Maria Lambrou, Daisuke Watanabe
    Purpose This paper aims to retrieve key components of blockchain applications in supply chain areas. It applies natural language processing methods to generate useful insights from academic literature. Design/methodology/approach It first applies a text mining method to retrieve information from scientific journal papers on the related topics. The text information is then analyzed through machine learning (ML) models to identify the important implications from the existing literature. Findings The research findings are three-fold. While challenges are of concern, the focus should be given to the design and implementation of blockchain in the supply chain field. Integration with internet of things is considered to be of higher importance. Blockchain plays a crucial role in food sustainability. Research limitations/implications The research findings offer insights for both policymakers and business managers on blockchain implementation in the supply chain. Practical implications This paper exemplifies the model as situated in the interface of human-based and machine-learned analysis, potentially offering an interesting and relevant avenue for blockchain and supply chain management researchers. Originality/value To the best of the knowledge, the research is the very first attempt to apply ML algorithms to analyzing the full contents of blockchain-related research, in the supply chain sector, thereby providing new insights and complementing existing literature.
    Emerald, May 2021, Maritime Business Review, 6(2) (2), 114 - 128, English, No password
    [Refereed]
    Scientific journal

  • Ziaul Haque Munim, Okan Duru, Enna Hirata
    Blockchain technology, since its introduction, has been expected to be implemented in many areas. Cryptocurrency is one unique example that established a functioning application. On the other hand, blockchain technology is not immune to various challenges related to the nature of itself, privacy management, and antitrust laws, among others. This study lays out the nature of blockchain and applications in the maritime industry, while highlighting the bottlenecks. Potential resolutions and anticipated developments are proposed. To do this, we adopt a systematic approach and present an overview of blockchain in maritime literature. In addition, the fundamental problems with blockchain are investigated, beginning from their essentials to the pain points that are claimed to need improvement. For establishing a legitimate and practically meaningful blockchain platform, stakeholders need to achieve pluralism (consensus validation), privacy, and security of the system.
    MDPI AG, Mar. 2021, Journal of Marine Science and Engineering, 9(3) (3), 266 - 266, English
    [Refereed]
    Scientific journal

  • Hoegwon Kim, Daisuke Watanabe, Shigeki Toriumi, Enna Hirata
    Many states are actively working toward regulating CO2 emissions from a wide range of industries. However, due to the international characteristic of shipping, the emissions from shipping have not yet been strictly controlled. Using Automatic Identification System (AIS) data acquired through satellites, this study estimates the emission inventory, such as, CO2, CH4, CH4, N2O, NOx, CO and non-methane volatile organic compounds (NMVOCs) around the world and bunker consumption from a liquified natural gas (LNG) fleet under the assumption that a LNG fleet uses LNG as fuel. Using position data calculated from an AIS database, we made comparisons regarding the LNG trade amount and bunker consumption of LNG fleet, as well as the total CO2 inventory and CO2 emissions from LNG fleet in the vicinity of the coasts of relevant countries. The result provides insights into (1) how the emissions and bunker consumption from LNG fleet is distributed, (2) which countries are taking relatively more advantages of LNG trade, and (3) which countries are suffering possible harmful effects.
    Last, {MDPI} {AG}, Jan. 2021, Sustainability, 13(3) (3), 1250 - 1250, English
    [Refereed]
    Scientific journal

  • Forecasting container freight rate: A comparison of traditional and deep learning-based models
    Enna Hirata, Takuma Matsuda
    Nov. 2020, The Asian Logistics Round Table (ALRT) 2020 Conference, English
    [Refereed]
    International conference proceedings

  • Enna Hirata
    Inderscience Publishers, Nov. 2020, International Journal of Shipping and Transport Logistics, 12(6) (6), 563 - 563, English
    [Refereed]
    Scientific journal

  • A Discussion on How Covid-19 Impacts Shipping and Logistics: Implications from Machine Learning Perspective
    Enna Hirata, Takuma Matsuda
    Sep. 2020, Proceedings of the 8th International Conference on Transportation and Logistics, English
    [Refereed]
    International conference proceedings

  • Application of Blockchain in Supply Chain: Insights from Machine Learning
    Enna Hirata, Maria Lambrou, Daisuke Watanabe
    Sep. 2020, Proceedings of 2020 Conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • Blockchain and port digitization : an overview of the TradeLens and the latest developments
    Enna Hirata
    Apr. 2020, 港湾荷役, 65(4) (4), 411 - 416, Japanese
    [Invited]
    Research institution

  • Discussions On The Possibility Of Using Block Chain Technology In Shipping And Logistics Industry
    Enna Hirata
    Oct. 2019, Journal of logistics and shipping economics, 53, 61 - 70, Japanese
    [Refereed]
    Scientific journal

  • Analyzing spatial autocorrelation in AIS based LNG emitted bunker consumption
    Howgwon Kim, Daisuke Watanabe, Enna Hirata
    Last, Aug. 2019, Proceedings of the International Conference on Logistics and Industrial Engineering (ICLIE2019), 1 - 6, English
    [Refereed]
    International conference proceedings

  • Measuring structure-conduct-performance in the container shipping market
    Enna Hirata
    Jun. 2019, Proceedings of 2019 Conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • Enna Hirata
    Elsevier {BV}, Mar. 2019, The Asian Journal of Shipping and Logistics, 35(1) (1), 24 - 29, English
    [Refereed]
    Scientific journal

  • Enna Hirata
    Inderscience Publishers, Oct. 2018, International Journal of Shipping and Transport Logistics, 10(5/6) (5/6), 500 - 500, English
    [Refereed]
    Scientific journal

  • Service characteristics in container liner shipping industry
    Enna Hirata
    Jun. 2018, Proceedings of the 11th International Conference of Asian Shipping and Logistics, English
    [Refereed]
    International conference proceedings

  • Service recovery and customer satisfaction in container liner shipping industry
    Enna Hirata
    Jun. 2017, Proceedings of 2017 conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • Enna Hirata
    Elsevier {BV}, Mar. 2017, The Asian Journal of Shipping and Logistics, 33(1) (1), 27 - 32, English
    [Refereed]
    Scientific journal

  • Demand Elasticity and Competitive Conditions in Container Liner Shipping Market
    Enna Hirata
    Sep. 2016, Proceedings of 2016 conference of International Association of Maritime Economists, English
    [Refereed]
    International conference proceedings

  • The Effect of Container Liner Shipping on Economic Growth: A Panel Data Analysis
    Enna Hirata, Hideki Murakami
    May 2016, Proceedings of International Forum on Shipping, Ports and Airports (IFSPA) 2015, 318 - 325, English
    [Refereed]
    International conference proceedings

  • Liner Shipping Market Contestability in Alliance Era
    Enna Hirata, Hideki Murakami
    日本海運経済学会, Oct. 2015, Journal of Logisistics and Shipping Economics, (49) (49), 41 - 50, English
    [Refereed]
    Scientific journal

■ MISC
  • Common challenges and solutions for shipping and aviation in the DX era
    Enna Hirata
    Lead, Nov. 2023, Takeoff, (173) (173), 24 - 31, Japanese
    [Invited]
    Introduction commerce magazine

  • Japanese Logistics in the Post-Corona Era as Seen in the SNS Data
    Enna Hirata, Takuma Matsuda
    Lead, Aug. 2022, 運輸と経済, 82(8) (8), Japanese
    [Invited]

  • Blockchain - A Breakthrough Technology for Trade and Logistics
    Enna Hirata
    Lead, Aug. 2019, Japan Maritime Daily, Japanese
    [Invited]
    Introduction commerce magazine

■ Books And Other Publications
  • Introduction to International Transport and Logistics
    平田 燕奈, 松田 琢磨, 渡部 大輔
    Joint work, 第1章 第6章 第8章 第13章 第14章, 晃洋書房, Sep. 2022, ISBN: 4771036721

  • Supply chain : recent advances and new perspectives in the industry 4.0 era
    Enna Hirata, Daisuke Watanabe, Maria Lambro
    Joint work, Chapter 7, IntechOpen, Jan. 2022, English, Shipping, like most industries, is undergoing a digital transformation process which influences existing business models and operational practices, in a multifaceted way. Today, the shipping business context has been changing to incorporate further social demands, environmental, innovation and sustainability priorities, into fundamental shipping strategies, while taking advantage of technological advancements. In the era of Industry 4.0, which constitutes a recent evolution of advanced communications and information technologies and further promotes sustainable, human-centric, and resilient business development strategies, shipping and port entities need to embrace a broader perspective and a deeper understanding of various elemental technologies, namely: Artificial Intelligence, Blockchain, Cloud Computing, Big Data, and Physical Internet, in addition to core maritime logistics matters. This chapter proposes a descriptive framework of shipping digitalization and port automation, while providing a review of related technologies and business approaches, also international initiatives, for automation in global ports. Hence the chapter offers insights for business practitioners to steer through the current challenging global environment, also for policy makers to gain a more informed understanding of maritime logistics developments, towards necessary coordination and oversight mechanisms implementation., ISBN: 9781803553726

  • Introduction to Data Science
    齋藤, 政彦, 小澤, 誠一, 羽森, 茂之, 南, 知惠子
    Contributor, Chapter 1 (pp.1-40), 培風館, Mar. 2021, Japanese, ISBN: 9784563016104

  • e-Shipping: Digitization in International Shipping Business
    Enna Hirata, Takayuki Mori
    Author, Kaibundo Publishing Co., Ltd, Oct. 2018, Japanese, ISBN: 9784303164140

■ Lectures, oral presentations, etc.
  • Next Generation;Logistics Network Physical Internet's Mechanism and Implementation Examples
    平田燕奈
    JB Press Japan Innovation Review Forum, Apr. 2024, Japanese
    [Invited]
    Public discourse

  • 物流倉庫におけるピッキングの最適化
    上野大樹, 平田燕奈
    2023土木計画研究会秋大会, Nov. 2023, Japanese
    Oral presentation

  • フィジカルインターネットにおける物流拠点の最適立地と配送ルートの最適化
    長縄尚駿, 平田燕奈
    2023土木計画研究会秋大会, Nov. 2023, Japanese
    Oral presentation

  • Research Topics and Methods in Maritime Decarbonization: A Natural Language Processing Approach
    Hirata, Enna, Li, Kevin, Watanabe, Daisuke
    International Association of Maritime Economists (2023), Sep. 2023, English
    Oral presentation

  • Industry 4.0: technologies for next-generation maritime logistics and shipping digitalization
    Enna Hirata
    Emerging Topics in Transportation Studies, Feb. 2023, English
    [Invited]
    Public discourse

  • Advanced Technologies and Recent Applications in Smart Ports
    Enna Hirata
    Utilizing Digital Technology in the Field of Trade Facilitation under the Current COVID-19 Pandemic and Beyond: Best-Practices Sharing Workshops, Asia-Pacific Economic Cooperation, Jan. 2023, English
    [Invited]
    Nominated symposium

  • Development of Researcher Network Visualization System by Matrix Researcher2vec
    Enna Hirata, Takahiro Yamashita, Seiichi Ozawa
    The 30th Symposium on Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence, Sep. 2022, English
    [Invited]
    Oral presentation

  • Decoding Logistics Trend in Japan using SNS Data
    Enna Hirata, Takuma Matsuda
    International Association of Maritime Economists Conference 2022, Sep. 2022, English
    Oral presentation

  • A Study on Market Forecast of International Logistics Using Natural Language Processing -Based on a Questionnaire Survey for Major Freight Forwarders in Japan
    Daisuke Watanabe, Enna Hirata, Maria Lambrou
    International Association of Maritime Economists Conference 2022, Sep. 2022, English
    Oral presentation

  • ブロックチェーン技術と国際物流
    平田燕奈
    JMC 海事振興セミナー, Jul. 2022, Japanese
    [Invited]
    Public discourse

  • SNSデータから見るポストコロナ時代の日本物流
    平田燕奈, 松田琢磨
    日本海運経済学会;日本交通学会, Jun. 2022, Japanese
    [Invited]
    Oral presentation

  • Maritime and Climate Change - Introduction of Related Research in Japan
    Enna Hirata
    JSPS JARA EVENT 2022 Denmark, Mar. 2022, English
    [Invited]
    Keynote oral presentation

  • Application of AI and Blockchain Technology in Smart Container Terminal
    Enna Hirata
    African Development Senior Managers Forum on Towards Smart Strategies for Sustainable Container Terminal in the era of Blockchain and Big Data, Jan. 2022, English
    [Invited]
    Invited oral presentation

  • Similarity between Digital Platforms – A Machine Learning Approach
    Enna Hirata, Maria Lambrou, Daisuke Watanabe
    International Association of Maritime Economists, Nov. 2021, English
    Oral presentation

  • Blockchain and Shipping
    Enna Hirata
    the Japan Society of Naval Architects and Ocean Engineers, Oct. 2021, Japanese
    [Invited]
    Nominated symposium

  • Covid-19 and Global Logistics –Implications from text mining perspective
    Enna Hirata, Takuma Matsuda
    International Conference of Transportation and Logistics, Sep. 2020, English
    Oral presentation

  • Identifying Trends for Blockchain Application in Supply Chain Using Text Mining
    Enna Hirata, Maria Lambrou, Daisuke Watanabe
    Conference of International Association of Maritime Economists, Jun. 2020, English
    Oral presentation

  • ブロックチェーン技術を活用したサプライチェーン管理
    平田燕奈
    日経 xTECH EXPO 2019, Oct. 2019, Japanese, International conference
    [Invited]
    Invited oral presentation

  • 外航海運業務電子化と革新的テクノロジー
    平田燕奈
    日本海運集会所, Sep. 2019, Japanese, Domestic conference
    Public discourse

  • Economic effects of M & A in the container shipping industry
    Takuma Matsuda, Enna Hirata Tomoya Kawasaki
    The 36th Annual Meeting of the Logistics Society of Japan, Sep. 2019, Japanese
    Oral presentation

  • A Blockchain Solution for Shipping and Logistics
    Enna Hirata
    International Association of Port and Harbors 2019, May 2019, English, International conference
    [Invited]
    Public discourse

  • 海運業界における業務電子化(現状と動向)
    平田燕奈
    海事振興連盟・海洋立国懇話会, Apr. 2019, Japanese, Domestic conference
    [Invited]
    Public discourse

  • Digitizing Global Supply Chain – An Application of Blockchain in Shipping
    Enna Hirata
    The Maritime CIO Forum, Oct. 2018, English, International conference
    [Invited]
    Public discourse

  • Service Characteristics and Customer Satisfaction in Container Liner Shipping Industry
    Enna Hirata
    the 11th International Conference of Asian Shipping and Logistics, Jun. 2018, English

  • Service characteristics in container liner shipping industry
    Enna Hirata
    The 11th International Conference of Asian Shipping and Logistics, Jun. 2018, English, International conference
    Oral presentation

  • コンテナ船業界のサービスリカバリーと顧客満足度
    平田燕奈
    日本海運経済学年次大会, Oct. 2017, Japanese, Domestic conference
    Oral presentation

  • Service recovery and customer satisfaction in container liner shipping industry
    Enna Hirata
    Service recovery and customer satisfaction in container liner shipping industry, Jun. 2017, English, International conference
    Oral presentation

  • Demand Elasticity and Competitive Conditions in Container Liner Shipping Market
    Enna Hirata
    The Conference of International Association of Maritime Economists, Aug. 2016, English, International conference
    Oral presentation

  • A Panel Data Analysis to the Effect of Container Liner Shipping on Economic Growth
    Enna Hirata
    International Forum on Shipping, Ports and Airports, Dec. 2015, English, International conference
    Oral presentation

■ Affiliated Academic Society
  • Japan Society of Civil Engineers
    Sep. 2023 - Present

  • Japan Logistics Society
    2021 - Present

  • The Japanese Society for Artificial Intelligence
    Feb. 2020 - Present

  • INFORMATION PROCESSING SOCIETY OF JAPAN
    Sep. 2019 - Present

  • Workshop For Logistics In Asia
    Jan. 2019 - Present

  • International Association of Maritime Economists (IAME)
    Apr. 2016 - Present

  • JAPAN SOCIETY OF LOGISTICS AND SHIPPING ECONOMICS
    Sep. 2015 - Present

■ Research Themes
  • フィジカルインターネットにおける物流拠点の設計
    平田 燕奈
    日本学術振興会, 科学研究費助成事業 基盤研究(C), 基盤研究(C), 神戸大学, Apr. 2023 - Mar. 2026, Principal investigator

  • Research on operational efficiency and environmental load reduction of ships and land transportation in smart ports
    渡部 大輔, 鳥海 重喜, 平田 燕奈, 近藤 智士
    Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Grant-in-Aid for Scientific Research (B), Tokyo University of Marine Science and Technology, Apr. 2021 - Mar. 2026, Coinvestigator

  • Hirata Enna
    Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Grant-in-Aid for Scientific Research (C), Kobe University, Apr. 2017 - Mar. 2020, Principal investigator
    The key research findings are summarized as follows. (1)The top three service characteristics influencing customer satisfaction in Container Liner Shipping (henceforth: CLS) industry are “quality of customer service representative”, “quality of digitization” and “quality of sales representative”. (2) Economy of scale in CLS industry has been fading since 2009 and dis-economy of scale has been observed in recent years. Larger share of fleet capacity (measured in numbers of twenty-foot equivalent unit owned) does not yield higher profitability for a shipping company (shipping company). (3) M&As in CLS industry do not have a positive effect on firms’ profitability but do improve firms’ stability and reduce risks of bankruptcy. The research findings were captured in four papers, out of which three were published in peer reviewed international scientific journals.

■ Social Contribution Activities
  • Container Shipping Summit (Singapore)
    Ocean Network Express
    Panelist, https://one-container.com/en/, 03 Aug. 2023 - 04 Aug. 2023

  • 物流におけるビッグデータ活用の最前線 ~ビジネスへの応用を探る!~
    Shippio Logistics DX Summit
    Panelist, https://service.shippio.io/conference/lds2023/, 02 Mar. 2023 - 03 Mar. 2023

  • Japan Society of Logistics and Shipping Economics Annual Conerence (2021)
    The University of Tokyo
    Panelist, ポストコロナ時代の海運・航空分野のデジタライゼーション, 17 Oct. 2021 - 17 Oct. 2021

  • Trends and outlook: Transitioning to a digital future
    Digital Ship
    Panelist, Aug. 2018

■ Media Coverage
  • 気鋭の有識者、国際物流変革にビッグデータやブロックチェーンは不可欠と指摘
    LOGI-BIZ, 06 Apr. 2023, https://online.logi-biz.com/78934/
    Internet

  • ブロックチェーンが切り開く貿易物流
    日本海事新聞, Aug. 2019
    Paper

  • ブロックチェーン技術を活用したエコシステム構築
    日経BP, Dec. 2018
    Internet

■ Academic Contribution Activities
  • ASIAN LOGISTICS ROUND TABLE (ALRT) CONFERENCE
    ASIAN LOGISTICS ROUND TABLE (ALRT) CONFERENCE
    University of Tasmania
    01 Sep. 2020 - Present
    Academic society etc

  • Transportation Research Part E: Logistics and Transportation Review
    Transportation Research Part E: Logistics and Transportation Review
    Elsevier
    01 Aug. 2020 - Present
    Peer review etc

  • Maritime Policy and Management
    Maritime Policy and Management
    Taylor & Francis
    01 Sep. 2018 - Present
    Peer review etc

  • International Association of Maritime Economists (IAME) conference 2023 (Long Beach), Session Chair
    International Association of Maritime Economists (IAME) conference
    05 Sep. 2023 - 08 Sep. 2023
    Academic society etc

  • International Conference on Neural Information Processing 2022
    International Conference on Neural Information Processing 2022
    22 Nov. 2022 - 26 Nov. 2022
    Competition etc

  • International Conference on Neural Information Processing 2021
    International Conference on Neural Information Processing 2021
    08 Dec. 2021 - 12 Dec. 2021
    Competition etc

  • Program Committee Member
    Program Committee Member
    International Joint Conference on Neural Networks (2021)
    18 Jul. 2021 - 20 Jul. 2021
    Competition etc

  • International Symposium on Sustainable Logistics
    International Symposium on Sustainable Logistics
    Toros University
    30 Apr. 2021 - 30 Apr. 2021
    Competition etc

  • Growth and Change, Wiley
    Growth and Change, Wiley
    Growth and Change, Wiley
    Peer review etc

  • The Asian Journal of Shipping and Logistics, Elsevier
    The Asian Journal of Shipping and Logistics, Elsevier
    The Asian Journal of Shipping and Logistics, Elsevier
    Peer review etc

  • International Journal of e-Navigation and Maritime Economy, Elsevier
    International Journal of e-Navigation and Maritime Economy, Elsevier
    International Journal of e-Navigation and Maritime Economy, Elsevier
    Peer review etc

  • Conference of International Association of Maritime Economists
    Conference of International Association of Maritime Economists
    Conference of International Association of Maritime Economists
    Competition etc

  • International Journal of Shipping and Transport Logistics, Inderscience
    International Journal of Shipping and Transport Logistics, Inderscience
    International Journal of Shipping and Transport Logistics, Inderscience
    Peer review etc

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