This bibliometric study analyzes 1535 publications from 1952 to 2020 on medical tourism. The aim of the study is to portray medical tourism publication trends from different perspectives such as the main subjects, word dynamics, authors’ originations and finally research gaps and future directions. The study shows that concepts like “perceived value” and “destination image” are among the emerging concerns in recent studies. The themes of research were grouped into six themes of marketing, economic & political, social & cultural, ethical, technological and governmental within these categories, factors affecting emotional aspects of tourists’ decision-making were found to be under-studies, compared to factors feeding the cognitive side of their choice of destinations.
"Virtual Teams will become as important as Web to companies" (Nader Ale Ebrahim)
Search This Blog
Thursday, 23 September 2021
Tuesday, 7 September 2021
Friday, 3 September 2021
A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis
Source: https://aapm.onlinelibrary.wiley.com/doi/full/10.1002/acm2.13394
A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis
All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Abstract
Purpose
Medical images are important in diagnosing disease and treatment planning. Computer algorithms that describe anatomical structures that highlight regions of interest and remove unnecessary information are collectively known as medical image segmentation algorithms. The quality of these algorithms will directly affect the performance of the following processing steps. There are many studies about the algorithms of medical image segmentation and their applications, but none involved a bibliometric of medical image segmentation.
Methods
This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.
Results
The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.
Conclusions
Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.
How to cite
Saturday, 14 August 2021
Trends and patterns in digital marketing research: bibliometric analysis
Source: https://link.springer.com/article/10.1057/s41270-021-00116-9#auth-Nader-Ale_Ebrahim
- Original Article
- Published:
Trends and patterns in digital marketing research: bibliometric analysis
Abstract
In today’s digital era, the importance of digital marketing has increased from one year to another as a way of providing novel properties for informing, engaging, and selling services and products to clients. The research’s aim is to investigate trends and patterns in the area of digital marketing research from 1979 to June 2020 through a bibliometric analysis technique. A total of 924 articles published were obtained from the Scopus database for the analysis. In this paper, we examine variant bar charts including the year of publication, writer, publication, keyword, and country to provide more insights. Results indicated that digital marketing research steadily increased during the study period and the maximum publications occurred in the year 2019 that reach to 163 documents. The trend of publications is still growing. The top 20 documents based on the times cited per year (TCpY) were qualitatively analyzed. The largest number of multiple (MCP) and single (SCP) publications was from the USA, followed by the UK and China. The top 20 most repeated authors’ keywords out of 1909 with their trends illustrated. The “real-time bidding”, “machine learning”, “big data”, “social media marketing”, and “influencer marketing” are the emerging keywords in the digital Marketing area. This bibliometric study generally provides the whole image of the field and suggests that researchers focus on novel areas to add new findings and knowledge in the literature if they conduct digital marketing research.
This is a preview of subscription content, access via your institution.
References
Abedini, A., R. Rahman, H.S. Naeini, and N. Ale Ebrahim. 2017. The 100 most cited papers in’industrial design’: A bibliometric analysis. Exacta – EP, São Paulo 15 (3): 515–526.
Aghaei Chadegani, A., H. Salehi, M. Yunus, H. Farhadi, M. Fooladi, M. Farhadi, and N. Ale Ebrahim. 2013. A comparison between two main academic literature collections: Web of Science and Scopus databases. Asian Social Science 9 (5): 18–26.
Aksnes, D.W. 2003. Characteristics of highly cited papers. Research Evaluation 12 (3): 159–170.
Ale Ebrahim, S., A. Ashtari, M.Z. Pedram, N. Ale Ebrahim, and A. Sanati-Nezhad. 2020. Publication trends in exosomes nanoparticles for cancer detection. International Journal of Nanomedicine 15: 4453.
Aria, M., and C. Cuccurullo. 2017. Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 11 (4): 959–975. https://doi.org/10.1016/j.joi.2017.08.007.
Barnes, S.J., and E. Scornavacca. 2004. Mobile marketing: The role of permission and acceptance. International Journal of Mobile Communications 2 (2): 128–139.
Baumgartner, H., and R. Pieters. 2003. The structural influence of marketing journals: A citation analysis of the discipline and its subareas over time. Journal of Marketing 67 (2): 123–139.
Bethu, S., V. Sowmya, B.S. Babu, G.C. Babu, and Y.J.N. Kumar. 2018. Data science: Identifying influencers in social networks. Periodicals of Engineering and Natural Sciences 6 (1): 215–228.
Bharadwaj, V., P. Chen, W. Ma, C. Nagarajan, et al. 2012. Shale: An efficient algorithm for allocation of guaranteed display advertising. Paper presented at the Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 1195–1203. https://doi.org/10.1145/2339530.2339718.
Brodie, R.J., and B. Juric. 2018. Customer engagement: Developing an innovative research that has scholarly impact. Journal of Global Scholars of Marketing Science 28 (3): 291–303.
Cai, H., K. Ren, W. Zhang, K. Malialis, J. Wang, Y. Yu, and D. Guo. 2017. Real-time bidding by reinforcement learning in display advertising. Paper presented at the Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 661–670. https://doi.org/10.1145/3018661.3018702.
Cavallo, R., R.P. McAfee, and S. Vassilvitskii. 2015. Display advertising auctions with arbitrage. ACM Transactions on Economics and Computation (TEAC) 3 (3): 1–23.
Diodato, V. 1994. Dictionary of bibliometrics psychology press. Binghamton: The Haworth Press.
Ferreira, M.P. 2011. A bibliometric study on Ghoshal's managing across borders. Multinational Business Review 19 (4): 357–375.
Ferreira, M.P., J.C. Santos, M.I.R. de Almeida, and N.R. Reis. 2014. Mergers & acquisitions research: A bibliometric study of top strategy and international business journals, 1980–2010. Journal of Business Research 67 (12): 2550–2558.
Fierro, I., D.A. Cardona Arbelaez, and J. Gavilanez. 2017. Digital marketing: A new tool for international education. Pensamiento & Gestión 42: 241–260.
Franceschini, F., and D. Maisano. 2011. Regularity in the research output of individual scientists: An empirical analysis by recent bibliometric tools. Journal of Informetrics 5 (3): 458–468.
Fujita, M., P. Harrigan, and G. Soutar. 2017. A netnography of a university’s social media brand community: Exploring collaborative co-creation tactics. Journal of Global Scholars of Marketing Science 27 (2): 148–164.
Ghanbari Baghestan, A., H. Khaniki, A. Kalantari, M. Akhtari-Zavare, E. Farahmand, E. Tamam, and M. Danaee. 2019. A crisis in “open access”: Should communication scholarly outputs take 77 years to become open access? SAGE Open 9 (3): 2158244019871044.
Ghosh, A., P. McAfee, K. Papineni, and S. Vassilvitskii. 2009. Bidding for representative allocations for display advertising. Paper presented at the International workshop on internet and network economics, 208–219.
Ghosh, A., B.I.P. Rubinstein, S. Vassilvitskii, and M. Zinkevich. 2009. Adaptive bidding for display advertising. Paper presented at the 18th International World Wide Web Conference, WWW 2009, Madrid, 251–260.
Gordhamer, S. 2009. Ways social media is changing business. New York: Mashable. Retrieved from http://Mashable.ComMedia-Business/2009/09/22/Social-Media-Business/.
Guercini, S., P.M. Bernal, and C. Prentice. 2018. New marketing in fashion e-commerce. Journal of Global Fashion Marketing 9 (1): 1–8.
Han, S.-L., T. Thao Nguyen, and V. Anh Nguyen. 2016. Antecedents of intention and usage toward customers’ mobile commerce: Evidence in Vietnam. Journal of Global Scholars of Marketing Science 26 (2): 129–151.
Hay, A.M., and K.S. Beavon. 1979. Periodic marketing: A preliminary graphical analysis of the conditions for part time and mobile marketing. Tijdschrift Voor Economische En Sociale Geografie 70 (1): 27–34.
Järvinen, J., and H. Karjaluoto. 2015. The use of Web analytics for digital marketing performance measurement. Industrial Marketing Management 50: 117–127.
Jayawardhena, C., A. Kuckertz, H. Karjaluoto, and T. Kautonen. 2009. Antecedents to permission based mobile marketing: an initial examination. European Journal of Marketing 43 (3/4): 473–499.
Kalantari, A., A. Kamsin, H.S. Kamaruddin, N.A. Ebrahim, A. Gani, A. Ebrahimi, and S. Shamshirband. 2017. A bibliometric approach to tracking big data research trends. Journal of Big Data 4 (1): 1–18.
Kamal, Y. (2016). Study of trend in digital marketing and evolution of digital marketing strategies. International Journal of Engineering Science 6 (5): 5300–5302.
Kaplan, A.M., and M. Haenlein. 2010. Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons 53 (1): 59–68.
Kargaran, S., M. J. Pour, and H. Moeini. 2017. Successful customer knowledge management implementation through social media capabilities. VINE Journal of Information and Knowledge Management Systems, 47 (3): 353–371.
Karjaluoto, H., and T. Alatalo. 2007. Consumers’ attitudes towards and intention to participate in mobile marketing. International Journal of Services Technology and Management 8 (2–3): 155–173.
Khodabandelou, R., N. Aleebrahim, A. Amoozegar, and G. Mehran. 2019. Revisiting three decades of educational research in Iran: A bibliometric analysis. Iranian Journal of Comparative Education 2 (1): 1–21.
Kim, J. 2018. Social dimension of sustainability: From community to social capital. Journal of Global Scholars of Marketing Science 28 (2): 175–181.
Kim, E.Y., and K. Yang. 2018. Self-service technologies (SSTs) streamlining consumer experience in the fashion retail stores: The role of perceived interactivity. Journal of Global Fashion Marketing 9 (4): 287–304.
Ko, E. 2019. Bridging Asia and the world: Global platform for the Interface between marketing and management. New York: Elsevier.
LABS, X. 2017. How is big data influencing digital marketing strategy? Retrieved from https://www.xcubelabs.com/blog/how-is-big-data-influencing-digital-marketing-strategy/.
Lamberton, C., and A.T. Stephen. 2016. A thematic exploration of digital, social media, and mobile marketing: Research evolution from 2000 to 2015 and an agenda for future inquiry. Journal of Marketing 80 (6): 146–172.
Levy, S., and Y. Gvili. 2015. How credible is e-word of mouth across digital-marketing channels?: The roles of social capital, information richness, and interactivity. Journal of Advertising Research 55 (1): 95–109.
Li, S., J.Z. Li, H. He, P. Ward, and B.J. Davies. 2011. WebDigital: A Web-based hybrid intelligent knowledge automation system for developing digital marketing strategies. Expert Systems with Applications 38 (8): 10606–10613.
Maghami, M.R., M.E. Rezadad, N.A. Ebrahim, and C. Gomes. 2015. Qualitative and quantitative analysis of solar hydrogen generation literature from 2001 to 2014. Scientometrics 105 (2): 759–771.
Martín-Consuegra, D., M. Faraoni, E. Díaz, and S. Ranfagni. 2018. Exploring relationships among brand credibility, purchase intention and social media for fashion brands: A conditional mediation model. Journal of Global Fashion Marketing 9 (3): 237–251.
Nerur, S.P., A.A. Rasheed, and V. Natarajan. 2008. The intellectual structure of the strategic management field: An author co-citation analysis. Strategic Management Journal 29 (3): 319–336.
Perlich, C., B. Dalessandro, R. Hook, O. Stitelman, T. Raeder, and F. Provost. 2012. Bid optimizing and inventory scoring in targeted online advertising. Paper presented at the Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 804–812. https://doi.org/10.1145/2339530.2339655.
Poushter, J., C. Bishop, and H. Chwe. 2018. Social media use continues to rise in developing countries but plateaus across developed ones. Retrieved from https://www.pewresearch.org/global/2018/06/19/social-media-use-continues-to-rise-in-developing-countries-but-plateaus-across-developed-ones/.
Ramos-Rodríguez, A.R., and J. Ruíz-Navarro. 2004. Changes in the intellectual structure of strategic management research: A bibliometric study of the Strategic Management Journal, 1980–2000. Strategic Management Journal 25 (10): 981–1004.
Ren, K., W. Zhang, K. Chang, Y. Rong, Y. Yu, and J. Wang. 2017. Bidding machine: Learning to bid for directly optimizing profits in display advertising. IEEE Transactions on Knowledge and Data Engineering 30 (4): 645–659.
Ren, K., W. Zhang, Y. Rong, H. Zhang, Y. Yu, and J. Wang. 2016. User response learning for directly optimizing campaign performance in display advertising. Paper presented at the Proceedings of the 25th acm international on conference on information and knowledge management, 679–688. https://doi.org/10.1145/2983323.2983347.
Saura, J.R., P. Palos-Sánchez, and L.M. Cerdá Suárez. 2017. Understanding the digital marketing environment with KPIs and web analytics. Future Internet 9 (4): 76.
Shafique, M. 2013. Thinking inside the box? Intellectual structure of the knowledge base of innovation research (1988–2008). Strategic Management Journal 34 (1): 62–93.
Taiminen, H.M., and H. Karjaluoto. 2015. The usage of digital marketing channels in SMEs. Journal of Small Business and Enterprise Development 22 (4): 633–651. https://doi.org/10.1108/JSBED-05-2013-0073.
Taylor, C.R., Y.-N. Cho, C.M. Anthony, and D.B. Smith. 2018. Photoshopping of models in advertising: A review of the literature and future research agenda. Journal of Global Fashion Marketing 9 (4): 379–398.
Van Eck, N.J., and L. Waltman. 2010. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84 (2): 523–538. https://doi.org/10.1007/s11192-009-0146-3.
Wang, J., W. Zhang, and S. Yuan. 2016. Display advertising with real-time bidding (RTB) and behavioural targeting. arXiv:1610.03013.
Weinberg, T. 2009. The new community rules: Marketing on the social web. Journal of Applied Communications 96(2): 11.
Whiting, A., and D. Williams. 2013. Why people use social media: A uses and gratifications approach. Qualitative Market Research 16 (4): 362–369.
Willett, P. 2007. A bibliometric analysis of the Journal of Molecular Graphics and Modelling. Journal of Molecular Graphics and Modelling 26 (3): 602–606.
Woodside, A.G., and P. Bernal Mir. 2019. Clicks and purchase effects of an embedded, social-media, platform endorsement in internet advertising. Journal of Global Scholars of Marketing Science 29 (3): 343–357.
Yang, Z., Y. Shi, and B. Wang. 2015. Search engine marketing, financing ability and firm performance in E-commerce. Procedia Computer Science 55: 1106–1112.
Yin, C., S. Ding, and J. Wang. 2019. Mobile marketing recommendation method based on user location feedback. Human-Centric Computing and Information Sciences 9 (1): 1–17.
Yodel, G. 2017. What is influencer marketing. Huffington Post. https://www.huffpost.com/entry/what-is-influcner-marketing_b_10778128#:~:text=Influencer%20marketing%20is%20simply%20the,the%20character%20of%20a%20brand.&text=Anyone%20with%20internet%20access%20can,well%20enough%2D%20become%20an%20influencer.
Yuan, S., J. Wang, and X. Zhao. 2013. Real-time bidding for online advertising: measurement and analysis. Paper presented at the Proceedings of the Seventh International Workshop on Data Mining for Online Advertising.
Zarrella, D. 2009. The social media marketing book. Sebastopol: O’Reilly Media Inc.
Zhang, M., and N. Dholakia. 2018. Conceptual framing of virtuality and virtual consumption research. Journal of Global Scholars of Marketing Science 28 (4): 305–319.
Zhang, W., Y. Rong, J. Wang, T. Zhu, and X. Wang. 2016. Feedback control of real-time display advertising. Paper presented at the Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 407–416. https://doi.org/10.1145/2835776.2835843.
Zhang, W., and J. Wang. 2015. Statistical arbitrage mining for display advertising. Paper presented at the Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1465–1474. https://doi.org/10.1145/2783258.2783269.
Zhang, W., Yuan, S., and Wang, J. (2014). Optimal real-time bidding for display advertising. Paper presented at the Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 1077–1086. https://doi.org/10.1145/2623330.2623633.
Author information
Affiliations
Social Science and Economics Department, Alzahra University, Vanak, Tehran, Iran
Zahra Ghorbani, Sanaz Kargaran & Manijeh Haghighinasab
Farabi Campus, University of Tehran, Tehran, Iran
Ali Saberi
Ministry of Education District 7, Eshragh Institute, Tehran, Iran
Seyedh Mahboobeh Jamali
Research and Technology Department, Alzahra University, Vanak, Tehran, Iran
Nader Ale Ebrahim
Corresponding author
Correspondence to Zahra Ghorbani.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ghorbani, Z., Kargaran, S., Saberi, A. et al. Trends and patterns in digital marketing research: bibliometric analysis. J Market Anal (2021). https://doi.org/10.1057/s41270-021-00116-9
Revised
Accepted
Published
Keywords
- Digital marketing
- Electronic commerce marketing
- Search engine marketing
- VoSviewer
- Bibliometric
Tuesday, 3 August 2021
How to Increase the Visibility and Impact of your Research
Source: https://doi.org/10.6084/m9.figshare.15101871.v1
Why would a researcher or a research department want to increase the visibility of their research? It can be as simple as wanting to improve their university ranking or academic impact by gaining more views and citations for their research articles. However, others may wish to increase their visibility to attract more opportunities for collaboration or even to highlight their research impact on a larger society.
Thursday, 29 July 2021
Tuesday, 27 July 2021
A bibliometric study of medical tourism
Source: https://doi.org/10.1080/13032917.2021.1954042
A bibliometric study of medical tourism
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The datasets generated and/or analyzed during the current study are available in the ZENODO repository http://doi.org/10.5281/zenodo.5025655 .
