A data science-based marketing decision support system for brand management
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Author(s)Galyna ChornousLink to ORCID Index: https://orcid.org/0000-0003-4889-1247
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Yana FareniukLink to ORCID Index: https://orcid.org/0000-0001-6837-5042
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Vincentas Rolandas GiedraitisLink to ORCID Index: https://orcid.org/0000-0002-0293-0645
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Erstida UlvidienėLink to ORCID Index: https://orcid.org/0000-0003-2172-465X
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Ganna KharlamovaLink to ORCID Index: https://orcid.org/0000-0003-3614-712X
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DOIhttp://dx.doi.org/10.21511/im.19(2).2023.04
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Article InfoVolume 19 2023, Issue #2, pp. 38-50
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- 584 Views
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227 Downloads
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Creative Commons Attribution 4.0 International License
To improve the marketing activity and brand management and justify the most effective marketing decisions, organizations should implement different information technologies, mathematical methods and models into the marketing decision support system (MDSS). The goal of this paper is to form an architecture of an MDSS, the model base of which is developed on Data Science tools, in particular regression analysis and machine learning methods. The proposed MDSS is a multi-agent information system comprising nine intellectual agents (market environment monitoring, data processing, marketing mix modeling, price policy support, portfolio management, strategic analysis, forecasting, customer segmentation, and customer classification). The functionality of these agents is realized through Data Science, which allows for the optimization of marketing activities (e.g., an effective brand management strategy and its elements (portfolio strategy, price policy, and media strategy) or solving the problems of attracting new and retaining current customers with the maximal return on marketing investments). The MDSS analyzes the marketing environment, media activity, and business indicators by constructing different models and forecasting various combinations of marketing factors to select the best one. The joint work of MDSS agents provides decision-makers with interactive reports. The research findings offer a scientific basis for making effective marketing decisions based on data, and the proposed MDSS can become part of an intelligent system for planning marketing activities.
- Keywords
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JEL Classification (Paper profile tab)M30, C10, С61, D81
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References39
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Tables1
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Figures3
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- Figure 1. Architecture of the proposed multi-agent MDSS for brand management
- Figure 2. Example of the optimal level of the price index considering the growth of market share in money
- Figure 3. Approach to the formation of an effective portfolio marketing strategy
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- Table 1. General functional structure of the multi-agent MDSS “Brand’s marketing management system”
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Business dynamism in the world economy
Zuzana Virglerova ,
Felice Addeo ,
Eliska Zapletalikova
doi: http://dx.doi.org/10.21511/ppm.18(3).2020.14
Problems and Perspectives in Management Volume 18, 2020 Issue #3 pp. 160-169 Views: 2359 Downloads: 275 TO CITE АНОТАЦІЯThe creation and growth of new enterprises and, on the other hand, their decline and market exit are crucial factors of business dynamism and economic growth. Thus, business dynamism is an important aspect in the market chain and productivity of an economy, as well as a trigger for market reforms. The aim is to analyze business dynamism using Global Competitiveness Index 4.0 and its variables worldwide and to verify the relationship between business dynamism in the EU states and economic characteristics such as Valued added at factor cost, Enterprise Birth Rate and Enterprise Death Rate. Data were collected from the 2019 Global Competitiveness Report and from the EUROSTAT database, using the most recently updated source for each indicator. The 11th pillar of the Global Competitiveness Index, focused on business dynamics, and a set of indicators were analyzed using PCA to verify if all the variables are effective representatives of the concept. It was found out that the pillar does not effectively represent the concept of business dynamism in case of the EU countries; therefore the new pillar was constructed. A strong and statistically significant correlation between business dynamism and Value Added was confirmed. A relationship between business dynamism and other economic indicators was not proven. From a territorial point of view, Oceania achieved the best overall result in the analyzed field. The process of starting a new business is the most challenging in terms of start-up costs in South America. By contrast, the EU has reached the best result in this process.
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Retraction: Leaders and decision making: a study of the drivers of courage
Rasoava Rijamampianina
doi: http://dx.doi.org/10.21511/ppm.16(1).2018.31
Problems and Perspectives in Management Volume 16, 2018 Issue #1 pp. 320-329 Views: 1953 Downloads: 171 TO CITE АНОТАЦІЯRetracted on the 15th of October, 2020 by the Journal’s Editor-in-Chief request dated October 12, 2020. The type of retraction – plagiarism.
The journal was asked to retract this article because of plagiarism. The request came from the author of the article. The author informed the journal that original idea published in this paper wasn’t his and asked to remove the article. -
Data science methods for comprehensive assessment of regional economic development
Liubov Chagovets ,
Svitlana Prokopovych ,
Viktor Kholod
doi: http://dx.doi.org/10.21511/dm.18(2).2020.05
The paper deals with the assessment of the socio-economic development of Ukrainian regions using Data Science methods and multidimensional analysis, including taxonomy, n-dimensional classification, and ensemble decision trees methods. The methodological bases of economic regions devel¬opment by the economic and mathematical modeling methods were investigated. The necessity of improving and further developing estimation models of the regional economic development using business analytics tools and multidimensional scaling methods was investigated.
The ensemble decision trees methods was applied for the classification model of economic development of the Ukrainian regions according to the conceptual base of the research on regional econom¬ic development. It will increase the quality level of administrative decisions making on regional de¬velopment asymmetry equalization. It is determined that in Ukraine, there is a significant imbalance of regions clusters with high and low economic level. Here was investigated the relationship between the two groups of economic development indicators – the indicators of the economic development regional performance and the group of economic potential. The results of the classification model allow identifying the set of indicators that have significant impact on the overall economic development. The developed ensemble model allows carrying out qualitative recognition and prediction of the state probability of economic development. It will improve the quality of decision making pro¬cesses on equalization of regional development asymmetry.
The further research gives the possibility to develop the system of levers directions of regional development imbalance equalization, to determine priority vectors of sustainable development of both the regions and the country.
