Modelling the effectiveness index of digital marketing strategy oriented to increase the popularity of maritime education

• Autorzy: Mickienė R. , Valionienė E.

Identyfikatory

DOI

10.12716/1001.15.03.08

• Języki publikacji: EN

Abstrakty

EN

Digitization of the maritime transport formed a paradoxical situation of an increased interest in informatics and data sciences among youth, whilst the level of interest of these programmes in the maritime education and training (MET) field remained relatively low. Based on theoretical modelling the solution to the problem is divided in two parts, one of which is related to adding data sciences to MET and the other refers to increasing intensity of digital advertising to solve the problem of low knowability index (KI) of MET. The research showed that KI is the output of effective digital marketing strategy. Thus, all parameters characterizing effectiveness could be divided into categories and by applying AHP methods the weight of each criteria could be assessed. Based on the weights and on the analytical measurements collected from monitoring tools the KI was calculated. Analysis of KI component and whole KI found out main ways of increasing MET popularity, which could be implemented through on increasing advertising intensity in the social networks the whole year and also by adding new content which are related within the digitization into MET study programmes’ modules.

Słowa kluczowe

EN

Maritime Education and Training; Popularity of Maritime Education; Maritime Education; Knowability Index; Effectiveness Index; Digital Marketing; Digital Marketing Strategy; System in Lithuania

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2021
• Tom: Vol. 15 No. 3
• Strony: 559--567
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Mickienė R.

• Lithuanian Maritime Academy, Klaipeda, Lithuania

autor

Valionienė E.

• Lithuanian Maritime Academy, Klaipeda, Lithuania

Bibliografia

• 1. Achen, R.M.: Measuring social media marketing: moving towards a relationship-marketing approach. null. 22, 1, 33–53 (2017). https://doi.org/10.1080/23750472.2017.1379883.
• 2. Ajina, A.S.: The perceived value of social media marketing: an empirical study of online word-of-mouth in Saudi Arabian context. Entrepreneurship and Sustainability Issues. 6, 3, 1512–1527 (2019). https://doi.org/10.9770/jesi.2019.6.3(32).
• 3. Basak, S.K.: A Framework on the Factors Affecting to Implement Maritime Education and Training System in Educational Institutions: A Review of the Literature. Procedia Engineering. 194, 345–350 (2017). https://doi.org/10.1016/j.proeng.2017.08.155.
• 4. Chaffey, D., Patron, M.: From web analytics to digital marketing optimization: Increasing the commercial value of digital analytics. Journal of Direct, Data and Digital Marketing Practice. 14, 1, 30–45 (2012). https://doi.org/10.1057/dddmp.2012.20.
• 5. Dwivedi, Y.K., Ismagilova, E., Hughes, D.L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A.S., Kumar, V., Rahman, M.M., Raman, R., Rauschnabel, P.A., Rowley, J., Salo, J., Tran, G.A., Wang, Y.: Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management. 102168 (2020). https://doi.org/10.1016/j.ijinfomgt.2020.102168.
• 6. Dyagileva, O., Goridko, N., Popova, H., Voloshynov, S., Yurzhenko, A.: Ensuring sustainable development of education of future maritime transport professionals by means of network interaction. E3S Web Conf. 166, (2020). https://doi.org/10.1051/e3sconf/202016610003.
• 7. Hossain, T.M.T., Akter, S., Kattiyapornpong, U., Dwivedi, Y.: Reconceptualizing Integration Quality Dynamics for Omnichannel Marketing. Industrial Marketing Management. 87, 225–241 (2020). https://doi.org/10.1016/j.indmarman.2019.12.006.
• 8. Hossain, T.M.T., Akter, S., Kattiyapornpong, U., Dwivedi, Y.K.: Multichannel integration quality: A systematic review and agenda for future research. Journal of Retailing and Consumer Services. 49, 154–163 (2019). https://doi.org/10.1016/j.jretconser.2019.03.019.
• 9. Kalvaitiene, G., Bartusevičiene, I., Sencila, V.: Improving MET Quality: Relationship Between Motives of Choosing Maritime Professions and Students’ Approaches to Learning. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation. 5, 4, 535–540 (2011).
• 10. Lin, C.-T., Hsu, P.-F.: Selection of Internet advertising networks using an analytic hierarchy process and grey relational analysis. International Journal of Information and Management Sciences. 14, 2, 1–16 (2003).
• 11. Manuel, M.E.: Vocational and academic approaches to maritime education and training (MET): Trends, challenges and opportunities. WMU Journal of Maritime Affairs. 16, 3, 473–483 (2017). https://doi.org/10.1007/s13437-017-0130-3.
• 12. McNie, E., Weinstock, D., Browne, S., Holden, M.: Education and Training for Autonomous Shipping: Implications for a Maritime University. Presented at the CRITICAL MASS - MARAD July 22 (2019).
• 13. Moran, N., Curtin, K.: Education, Workforce Development & Training for Automation, Digital Leadership. Presented at the Maritime Education, Training, Research & Innovation (METRI) Virtual Summit November 9 (2020).
• 14. Podvezko, V.: Application of AHP technique. Journal of Business Economics and Management. 10, 2, 181–189 (2009). https://doi.org/10.3846/1611-1699.2009.10.181-189.
• 15. Pophali, G.R., Chelani, A.B., Dhodapkar, R.S.: Optimal selection of full scale tannery effluent treatment alternative using integrated AHP and GRA approach. Expert Systems with Applications. 38, 9, 10889–10895 (2011). https://doi.org/10.1016/j.eswa.2011.02.129.
• 16. Saura, J.R., Palos-Sánchez, P., Cerdá Suárez, L.M.: Understanding the Digital Marketing Environment with KPIs and Web Analytics. Future Internet. 9, 4, (2017). https://doi.org/10.3390/fi9040076.
• 17. Shareef, M.A., Mukerji, B., Dwivedi, Y.K., Rana, N.P., Islam, R.: Social media marketing: Comparative effect of advertisement sources. Journal of Retailing and Consumer Services. 46, 58–69 (2019). https://doi.org/10.1016/j.jretconser.2017.11.001.
• 18. Sharma, M., Joshi, S.: Online Advertisement Using Web Analytics Software: A Comparison Using AHP Method. International Journal of Business Analytics (IJBAN). 7, 2, 13–33 (2020). https://doi.org/10.4018/IJBAN.2020040102.
• 19. Stephen, A.T.: The role of digital and social media marketing in consumer behavior. Current Opinion in Psychology. 10, 17–21 (2016). https://doi.org/10.1016/j.copsyc.2015.10.016.
• 20. Zhou, Y., Yuen, K.F., Tan, B., Thai, V.V.: The effect of maritime knowledge clusters on maritime firms’ performance: An organizational learning perspective. Marine Policy. 128, 104472 (2021). https://doi.org/10.1016/j.marpol.2021.104472.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).