Bibliometric and content analysis of publications that used logistics software to decision support
DOI:
https://doi.org/10.14488/1676-1901.v22i4.4793Keywords:
AnyLogistix®, Supply chain, Logistics, Bibliometrics, Content analysisAbstract
This work presents a bibliometric and content analysis about the field of study related to logistics and the use of anyLogistix® software. The aim of this analysis is to verify the following issues related to publications in this area: (i) The temporal evolution of publications; (ii) The distribution of publications per author over the years; (iii) Distribution of sample publications by country of origin; (iv) Distribution of publications by publication vehicle. Also, this work intends to identify and analyze the main trends in this field of study, highlighting the most prominent themes within bibliometrics. Bibliometrics covers articles from all publication periods found in the search databases through mid-2022. By bibliometric analysis, the study offers several insights into publications related to anyLogistix® software. Moreover, we verified the most discussed themes in conjunction with the application of the software. Also, the results obtained indicate that this topic is still incipient in publications, and although in 2020 the number of published researches increased considerably, from 2021 this number declined again.
Downloads
References
ALDRIGHETTI, Riccardo; ZENNARO, Ilenia; FINCO, Serena; BATTINI, Daria. Healthcare Supply Chain Simulation with Disruption Considerations: a case study from northern italy. Global Journal Of Flexible Systems Management, v. 20, n. 1, p. 81-102, 30 nov. 2019. Disponível em: https://link.springer.com/article/10.1007/s40171-019-00223-8. Acesso em: 01 out. 2022.
BARYKIN, Sergey Yevgenievich; KAPUSTINA, Irina Vasilievna; SERGEEV, Sergey Mikhailovich; YADYKIN, Vladimir Konstantinovich. Algorithmic Foundations of Economic and Mathematical Modeling of Network Logistics Processes. Journal Of Open Innovation: Technology, Market, and Complexity, v. 6, n. 4, p. 189, 2020. Disponível em: https://www.researchgate.net/publication/347618893. Acesso em: 30 set. 2022.
BARYKIN, Sergey Yevgenievich; BOCHKAREV, Andrey Aleksandrovich; KALININA, Olga Vladimirovna; YADYKIN, Vladimir Konstantinovich. Concept for a Supply Chain Digital Twin. International Journal Of Mathematical, Engineering And Management Sciences, v. 5, n. 6, p. 1498-1515, 2020b. Disponível em: https://www.researchgate.net/publication/346892385. Acesso em: 03 ago. 2022.
BROADUS, R. N. Toward a definition of “bibliometrics”. Scientometrics, v. 12, n. 5-6, p. 373-379, 1987. Disponível em: https://akjournals.com/view/journals/11192/12/5-6/article-p373.xml. Acesso em: 23 jun. 2022.
BURGOS, Diana; IVANOV, Dmitry. Food retail supply chain resilience and the COVID-19 pandemic: a digital twin-based impact analysis and improvement directions. Transportation Research Part e: Logistics and Transportation Review, v. 152, p. 102412, ago. 2021. Disponível em: https://www.researchgate.net/publication/352873521_Food_Retail_Supply_Chain_Resilience_and_the_COVID-19_Pandemic_A_Digital_Twin-Based_Impact_Analysis_and_Improvement_Directions. Acesso em: 30 jul. 2022.
CHEN, Jie; SOHAL, Amrik S.; PRAJOGO, Daniel I. Supply chain operational risk mitigation: a collaborative approach. International Journal Of Production Research, v. 51, n. 7, p. 2186-2199, abr. 2013. Disponível em: https://doi.org/10.1080/00207543.2012.727490. Acesso em: 03 ago. 2022.
DING, Can; LIU, Li; ZHENG, Yi; LIAO, Jianxiu; HUANG, Wenxing. Role of Distribution Centers Disruptions in New Retail Supply Chain: an analysis experiment. Sustainability, v. 14, n. 11, p. 6529, 2022. Disponível em: https://www.mdpi.com/2071-1050/14/11/6529. Acesso em: 30 jul. 2022.
DING, Qing; ABBA, Oumate Alhadji; JAHANSHAHI, Hadi; ALASSAFI, Madini O.; HUANG, Wen-Hua. Dynamical Investigation, Electronic Circuit Realization and Emulation of a Fractional-Order Chaotic Three-Echelon Supply Chain System. Mathematics, v. 10, n. 4, p. 625, 17 fev. 2022. Disponível em: https://www.mdpi.com/2227-7390/10/4/625. Acesso em: 30 set. 2022.
DOLGUI, Alexandre; IVANOV, Dmitry; SOKOLOV, Boris. Ripple effect in the supply chain: an analysis and recent literature. International Journal Of Production Research, v. 56, n. 1-2, p. 414-430, 2018. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2017.1387680. Acesso em: 30 jul. 2022.
DONTHU, Naveen; KUMAR, Satish; MUKHERJEE, Debmalya; PANDEY, Nitesh; LIM, Weng Marc. How to conduct a bibliometric analysis: an overview and guidelines. Journal Of Business Research, v. 133, p. 285-296, set. 2021. Disponível em: https://www.sciencedirect.com/science/article/pii/S0148296321003155. Acesso em: 23 jun. 2022.
ELLEGAARD, Ole; WALLIN, Johan A. The bibliometric analysis of scholarly production: how great is the impact?. Scientometrics, v. 105, n. 3, p. 1809-1831, 2015. Disponível em: https://link.springer.com/article/10.1007/s11192-015-1645-z. Acesso em: 23 jun. 2022.
GAUR, Ajai; KUMAR, Mukesh. A systematic approach to conducting review studies: an assessment of content analysis in 25 years of ib research. Journal Of World Business, v. 53, n. 2, p. 280-289, 2018. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1090951617308386?via%3Dihub. Acesso em: 23 jun. 2022.
GAWANKAR, Shradha A.; GUNASEKARAN, Angappa; KAMBLE, Sachin. A study on investments in the big data-driven supply chain, performance measures and organisational performance in Indian retail 4.0 context. International Journal Of Production Research, v. 58, n. 5, p. 1574-1593, 2019. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2019.1668070. Acesso em: 06 ago. 2022.
GIANESELLO, Pietro; IVANOV, Dmitry; BATTINI, Daria. Closed-loop supply chain simulation with disruption considerations: a case-study on tesla. International Journal Of Inventory Research, v. 4, n. 4, p. 257, 2017. Disponível em: https://www.researchgate.net/publication/323761995_Closed-loop_supply_chain_simulation_with_disruption_considerations_a_case-study_on_Tesla. Acesso em: 30 jul. 2022.
GONZÁLEZ-HERNÁNDEZ, Isidro Jesús; MARTÍNEZ-FLORES, José Luis; SÁNCHEZ-PARTIDA, Diana; GIBAJA-ROMERO, Damián Emilio. Relocation of the distribution center of a motor oil producer reducing its storage capacity: a case study. Simulation, v. 95, n. 11, p. 1097-1112, 2019. Disponível em: https://journals.sagepub.com/doi/10.1177/0037549718825299. Acesso em: 02 out. 2022.
HALLDORSSON, Arni; KOTZAB, Herbert; MIKKOLA, Juliana H.; SKJØTT‐LARSEN, Tage. Complementary theories to supply chain management. Supply Chain Management: An International Journal, v. 12, n. 4, p. 284-296, 2007. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/13598540710759808/full/html. Acesso em: 30 set. 2022.
HEIJ, J.C.J. de. The use of data models for assessing standard logistics software. Computers In Industry, v. 25, n. 2, p. 211-216, dez. 1994. Disponível em: https://wwwsciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/0166361594900493. Acesso em: 08 ago. 2022.
HERMOGENES, Lucas Ramon dos Santos; GOMES, Carlos Francisco Simões; SANTOS, Marcos dos; MEDINA, Afonso. Análise da cadeia de suprimentos de um e-commerce utilizando a ferramenta computacional AnyLogistix®. Revista Simep, João Pessoa, v. 2, n. 1, p. 34-50, jun. 2022. Disponível em: https://revista.simep.com.br/index.php/simep/article/view/40/23. Acesso em: 15 jul. 2022.
HOSSEINI, Seyedmohsen; IVANOV, Dmitry; DOLGUI, Alexandre. Ripple effect modelling of supplier disruption: integrated markov chain and dynamic bayesian network approach. International Journal Of Production Research, v. 58, n. 11, p. 3284-3303, jun. 2020. Disponível em: https://www.researchgate.net/publication/335717358_Ripple_effect_modelling_of_supplier_disruption_integrated_Markov_chain_and_dynamic_Bayesian_network_approach. Acesso em: 30 jul. 2022.
HOSSEINI, Seyedmohsen; IVANOV, Dmitry. A multi-layer Bayesian network method for supply chain disruption modelling in the wake of the COVID-19 pandemic. International Journal Of Production Research, p. 1-19, 2021. Disponível em: https://www.researchgate.net/publication/354185521. Acesso em: 30 jul. 2022.
HUANG, Yakun; LI, Jack; QI, Yuan; SHI, Victor. Predicting the Impacts of the COVID-19 Pandemic on Food Supply Chains and Their Sustainability: a simulation study. Discrete Dynamics In Nature And Society, v. 2021, p. 1-9, 2021. Disponível em: https://www.hindawi.com/journals/ddns/2021/7109432/. Acesso em: 15 ago. 2022.
IVANOV, Dmitry; SOKOLOV, Boris; SOLOVYEVA, Inna; DOLGUI, Alexandre; JIE, Ferry. Dynamic recovery policies for time-critical supply chains under conditions of ripple effect. International Journal Of Production Research, v. 54, n. 23, p. 7245-7258, 13 mar. 2016. Disponível em: https://www.researchgate.net/publication/298336933. Acesso em: 30 jul. 2022.
IVANOV, Dmitry. Simulation-based ripple effect modelling in the supply chain. International Journal Of Production Research, v. 55, n. 7, p. 2083-2101, 2017. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2016.1275873. Acesso em: 30 jul. 2022.
IVANOV, Dmitry. Disruption tails and revival policies: a simulation analysis of supply chain design and production-ordering systems in the recovery and post-disruption periods. Computers & Industrial Engineering, v. 127, p. 558-570, jan. 2019. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0360835218305230?via%3Dihub. Acesso em: 30 jul. 2022.
IVANOV, Dmitry; DOLGUI, Alexandre; SOKOLOV, Boris. The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal Of Production Research, v. 57, n. 3, p. 829-846, 2019. Disponível em: https://www.researchgate.net/publication/326046999. Acesso em: 29 jul. 2022.
IVANOV, Dmitry. ‘A blessing in disguise’ or ‘as if it wasn’t hard enough already’: reciprocal and aggravate vulnerabilities in the supply chain. International Journal Of Production Research, v. 58, n. 11, p. 3252-3262, 2020a. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2019.1634850. Acesso em: 30 jul. 2022.
IVANOV, Dmitry. Predicting the impacts of epidemic outbreaks on global supply chains: a simulation-based analysis on the coronavirus outbreak (covid-19/sars-cov-2) case. Transportation Research Part e: Logistics and Transportation Review, v. 136, p. 101922, 2020b. Disponível em: https://www.sciencedirect.com/science/article/pii/S1366554520304300?via%3Dihub. Acesso em: 30 jul. 2022.
IVANOV, Dmitry. Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies. International Journal Of Production Research, v. 59, n. 12, p. 3535-3552, 9 mar. 2021. Disponível em: https://www.researchgate.net/publication/349925210. Acesso em: 30 jul. 2022.
IVANOV, Dmitry; DOLGUI, Alexandre. A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, v. 32, n. 9, p. 775-788, 21 maio 2021. Disponível em: https://www.tandfonline.com/doi/full/10.1080/09537287.2020.1768450. Acesso em: 29 jul. 2022.
IVANOV, Dmitry. Blackout and supply chains: cross-structural ripple effect, performance, resilience and viability impact analysis. Annals Of Operations Research, 3 jun. 2022. Disponível em: https://link.springer.com/article/10.1007/s10479-022-04754-9. Acesso em: 30 jul. 2022.
KAUR, Gurvinder; PASRICHA, Sudhir; KATHURIA, Girish. Resilience Role of Distribution Centers amid COVID-19 Crisis in Tier-A Cities of India: a green field analysis experiment. Journal Of Operations And Strategic Planning, v. 3, n. 2, p. 226-239, dez. 2020. Disponível em: https://journals.sagepub.com/doi/pdf/10.1177/2516600X20970352. Acesso em: 20 ago. 2022.
KHAN, Ashraf; HASSAN, M. Kabir; PALTRINIERI, Andrea; DREASSI, Alberto; BAHOO, Salman. A bibliometric review of takaful literature. International Review Of Economics & Financev. 69, p. 389-405, set. 2020. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S1059056020301040. Acesso em: 23 jun. 2022.
KINRA, Aseem; IVANOV, Dmitry; DAS, Ajay; DOLGUI, Alexandre. Ripple effect quantification by supplier risk exposure assessment. International Journal Of Production Research, v. 58, n. 18, p. 5559-5578, 11 out. 2020. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2019.1675919. Acesso em: 29 jul. 2022.
LANG, Sebastian; REGGELIN, Tobias; MÜLLER, Marcel; NAHHAS, Abdulrahman. Open-source discrete-event simulation software for applications in production and logistics: an alternative to commercial tools?. Procedia Computer Science, v. 180, p. 978-987, 2021. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S1877050921004038. Acesso em: 06 ago. 2022.
LLAGUNO, Arrate; MULA, Josefa; CAMPUZANO-BOLARIN, Francisco. State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains. International Journal Of Production Research, v. 60, n. 6, p. 2044-2066, 8 fev. 2022. Disponível em: https://www.tandfonline.com/doi/full/10.1080/00207543.2021.1877842. Acesso em: 30 jul. 2022.
LOZANO-DIEZ, Jose; MARMOLEJO-SAUCEDO, Jose; RODRIGUEZ-AGUILAR, Roman. Designing a resilient supply chain: an approach to reduce drug shortages in epidemic outbreaks. Eai Endorsed Transactions On Pervasive Health And Technology, v. 6, n. 21, p. 164260, 11 maio 2020. Disponível em: https://www.researchgate.net/publication/341207365. Acesso em: 29 jul. 2022.
MACHLINE, Claude. Cinco décadas de logística empresarial e administração da cadeia de suprimentos no Brasil. Revista de Administração de Empresas, v. 51, n. 3, p. 227-231, jun. 2011. Disponível em: https://www.scielo.br/j/rae/a/wgnpzqtKsNSnQyCycRKh65L/?lang=pt. Acesso em: 01 out. 2022.
MARMOLEJO-SAUCEDO, J.A.; NIEMBRO-GARCÍA, J.; ALVA-GUERRA, Lf. Structural dynamics of logistic networks: a sustainable approach. Ifac-Papersonline, v. 52, n. 13, p. 2704-2709, 2019. Disponível em: https://www.sciencedirect.com/science/article/pii/S2405896319316040. Acesso em: 03 ago. 2022.
MARMOLEJO-SAUCEDO, Jose Antonio. Design and Development of Digital Twins: a case study in supply chains. Mobile Networks And Applications, v. 25, n. 6, p. 2141-2160, 6 jun. 2020. Disponível em: https://link.springer.com/article/10.1007/s11036-020-01557-9. Acesso em: 03 ago. 2022.
MÉNDEZ, Jorge Borrell; CREMADES, David; NICOLAS, Fernando; PEREZ-VIDAL, Carlos; SEGURA-HERAS, Jose Vicente. Conceptual and Preliminary Design of a Shoe Manufacturing Plant. Applied Sciences, v. 11, n. 22, p. 11055, 22 nov. 2021. Disponível em: https://www.mdpi.com/2076-3417/11/22/11055. Acesso em: 02 ago. 2022.
MOOSAVI, Javid; HOSSEINI, Seyedmohsen. Simulation-based assessment of supply chain resilience with consideration of recovery strategies in the COVID-19 pandemic context. Computers & Industrial Engineering, v. 160, p. 107593, out. 2021. Disponível em: https://www.sciencedirect.com/science/article/pii/S0360835221004976?via%3Dihub. Acesso em: 30 jul. 2022.
MUKHERJEE, Debmalya; LIM, Weng Marc; KUMAR, Satish; DONTHU, Naveen. Guidelines for advancing theory and practice through bibliometric research. Journal Of Business Research, v. 148, p. 101-115, set. 2022. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S0148296322003824. Acesso em: 23 jun. 2022.
NUNES, L.J.R.; CAUSER, T.P.; CIOLKOSZ, D. Biomass for energy: a review on supply chain management models. Renewable And Sustainable Energy Reviews, v. 120, p. 109658, mar. 2020. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1364032119308640?via%3Dihub. Acesso em: 30 set. 2022.
PONOMAROV, S. Y.; HOLCOMB, M. C. Understanding the concept of supply chain resilience. The International Journal of Logistics Management, v. 20, n. 1, p. 124– 143, 2009. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/09574090910954873/full/html. Acesso em: jun. 30 jul. 2022.
PROSSER, Wendy; FOLORUNSO, Olamide; MCCORD, Joseph; ROCHE, Gregory; TIEN, Marie; HATCH, Benjamin; SPISAK, Cary; GENOVESE, Eleonora; PARE, Bibata; DONATIEN, Koffi. Redesigning immunization supply chains: results from three country analyses. Vaccine, v. 39, n. 16, p. 2246-2254, abr. 2021. Disponível em: https://www.sciencedirect.com/science/article/pii/S0264410X21003182?via%3Dihub. Acesso em: 03 ago. 2022.
RINALDI, Marta; MURINO, Teresa; GEBENNINI, Elisa; MOREA, Donato; BOTTANI, Eleonora. A literature review on quantitative models for supply chain risk management: can they be applied to pandemic disruptions?. Computers & Industrial Engineering, v. 170, p. 108329, ago. 2022. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S0360835222003825. Acesso em: 15 ago. 2022.
SAFARA, Fatemeh. A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic. Computational Economics, v. 59, n. 4, p. 1525-1538, 5 nov. 2020. Disponível em: https://link.springer.com/article/10.1007/s10614-020-10069-3. Acesso em: 10 ago. 2022.
SASSMANNSHAUSEN, Sean Patrick; VOLKMANN, Christine. The Scientometrics of Social Entrepreneurship and Its Establishment as an Academic Field. Journal Of Small Business Management, v. 56, n. 2, p. 251-273, 18 jul. 2016. Disponível em: https://onlinelibrary.wiley.com/doi/abs/10.1111/jsbm.12254. Acesso em: 23 jun. 2022.
SHAVARANI, Seyed Mahdi; MOSALLAEIPOUR, Sam; GOLABI, Mahmoud; İZBIRAK, Gökhan. A congested capacitated multi-level fuzzy facility location problem: an efficient drone delivery system. Computers & Operations Research, v. 108, p. 57-68, ago. 2019. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S0305054819300784. Acesso em: 06 ago. 2022.
SILVA, Cristiane. R.; GOBBI, Beatriz. C.; SIMÃO, Ana. A. O uso da análise de conteúdo como uma ferramenta para a pesquisa qualitativa: descrição e aplicação do método. Organizações Rurais Agroindustriais, Lavras, v. 7, n. 1, p. 70-81, 2005. Disponível em: https://www.researchgate.net/publication/278001718. Acesso em: 23 jun. 2022.
SOUREK, David. Software Support of City Logistics´ Processes. Transportation Research Procedia, v. 55, p. 172-179, 2021. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S2352146521003665. Acesso em: 05 ago. 2022.
SU, Hsin-Ning; LEE, Pei-Chun. Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in technology foresight. Scientometrics, v. 85, n. 1, p. 65-79, 22 jun. 2010. Disponível em: https://link.springer.com/article/10.1007/s11192-010-0259-8. Acesso em: 23 jun. 2022.
SUN, Xu; ANDOH, Eugenia Ama; YU, Hao. A simulation-based analysis for effective distribution of COVID-19 vaccines: a case study in norway. Transportation Research Interdisciplinary Perspectives, v. 11, p. 100453, set. 2021. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S2590198221001585. Acesso em: 25 jul. 2022.
THE ANYLOGIC COMPANY. AnyLogistix® Overview. Disponível em: https://www.anylogic.com/resources/educational-videos/anyLogistix®-overview/. Acesso em: 25 jul. 2022a.
THE ANYLOGIC COMPANY. Better supply chain and logistics — anylogistix optimization, simulation, and analytics software tool. Disponível em: https://www.anylogistix.com/. Acesso em: 09 out. 2022b.
TIMPERIO, Giuseppe; TIWARI, Sunil; SÁNCHEZ, José Manuel Gaspar; MARTÍN, Rafael Adrián García; SOUZA, Robert de. Integrated decision support framework for distribution network design. International Journal Of Production Research, v. 58, n. 8, p. 2490-2509, 24 out. 2020. Disponível em: https://www.tandfonline.com/doi/abs/10.1080/00207543.2019.1680894?journalCode=tprs20. Acesso em: 30 set. 2022.
WANKE, Peter Fernandes; CORRêA, Henrique Luiz. The relationship between the logistics complexity of manufacturing companies and their supply chain management. Production, v. 24, n. 2, p. 233-254, jun. 2014. Disponível em: https://www.scielo.br/j/prod/a/d3YbdMx5P5zpRtHncCbm8DH/?lang=en. Acesso em: 01 out. 2022.
ZIELSKE, Malena; HELD, Tobias. Agile methods used by traditional logistics companies and logistics start-ups: a systematic literature review. Journal Of Systems And Software, v. 190, p. 111328, ago. 2022. Disponível em: https://www-sciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S016412122200070X. Acesso em: 08 ago. 2022.
ZMESKAL, Ekaterina; MAJERCÁK, Jozef; KURBATOVA, Anna; KURENKOV, Petr; SAFRONOVA, Anastasia. Software for the Application of the Restriction Assessment Methodology in Logistics Chains. Transportation Research Procedia, v. 54, p. 69-75, 2021. Disponível em: https://wwwsciencedirect.ez359.periodicos.capes.gov.br/science/article/pii/S235214652100212X. Acesso em: 05 ago. 2022.
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Revista Produção Online
This work is licensed under a Creative Commons Attribution 4.0 International License.
The Journal reserves the right to make spelling and grammatical changes, aiming to keep a default language, respecting, however, the style of the authors.
The published work is responsibility of the (s) author (s), while the Revista Produção Online is only responsible for the evaluation of the paper. The Revista Produção Online is not responsible for any violations of Law No. 9.610 / 1998, the Copyright Act.
The journal allows the authors to keep the copyright of accepted articles, without restrictions
This work is licensed under a Creative Commons License .
