Marketing and business intelligence with help of ant colony algorithm

Seidlová, Romana; Poživil, Jaroslav; Seidl, Jaromír

doi:10.1080/0965254x.2018.1430058

Cited by 18 publications

(4 citation statements)

References 20 publications

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“…The information received will be material for managers in dealing with problems in the field. A more recent study by Seidlova, (2019) highlighted that in today's wave of changing business world, companies are faced with unpredictable environmental changes, which are so fast that constant readiness is essential. Against this background, marketing intelligence serves as a key input, because the quality of marketing information affects the effectiveness of decision-making in all industries and each industry must design the means to survive and compete, thereby producing innovative products (Jarek, 2019).…”

Section: Conceptual Background Empirical Review and Hypothesis Develo...mentioning

confidence: 99%

Marketing intelligence: Innovation ability to anticipate global competition

Aripin

Suganda

Kusumah

2022

IJRBS

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Making strategic decisions in a dynamic business environment has become a challenge for business people, especially in small and medium-sized enterprises (SMEs). Contextual knowledge gained in understanding the external environment is a factor that must be owned by every business person so that they gain a competitive advantage in increasing competition. This study aims to test the Entrepreneurial Performance model. The research was conducted on SMEs in West Java, in the city of Bandung. The sample selection was determined using the purposive sampling method and obtained 170 respondents as a sample. The analysis was carried out using the Structural Equation Model (SEM). The results of the study indicate the fit model after modification and produce an alternative model in the form of a correlation between Marketing Intelligence and Entrepreneurial Performance. Marketing Intelligence, Product Innovation and Competitive Advantage have a direct significant influence on Entrepreneurial Performance. Product Innovation partially has no significant effect on Competitive Advantage. This research is expected to contribute to SMEs in the city of Bandung to always have a good knowledge before making a decision. This knowledge includes an understanding of trends, media, competitors, and suppliers. The limitation in this study is also in its scope, which is only limited to a few SMEs in the city of Bandung. It is expected that future researchers will add samples and use other variables that can improve entrepreneurial performance.

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Section: Conceptual Background Empirical Review and Hypothesis Develo...mentioning

confidence: 99%

Marketing intelligence: Innovation ability to anticipate global competition

Aripin

Suganda

Kusumah

2022

IJRBS

View full text Add to dashboard Cite

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“…It is important to mention that data mining and neural networks are recommended in banking and business intelligence. For example, studies have applied algorithms based on artificial colonies of ants [31]. Alzeaideen [32], however, developed an artificial neural network model as a decision support system for evaluating credit approval in Jordanian commercial banks.…”

Section: A Business Intelligence Solutions In Bankingmentioning

confidence: 99%

“…It is important to highlight the adoption of business intelligence methodologies for any type of information technology to make further improvements [17]. On the other hand, artificial intelligence and block technology are considered to be prospects for the future of banking [31], [33]. In this study, the results that were presented, with a reduction from 59.49 to 1.350 minutes in the work per process, are extremely significant for decision-making in the internet banking business unit.…”

Section: B the Effect On Internet Banking Companiesmentioning

confidence: 99%

Methodology for Business Intelligence Solutions in Internet Banking Companies

Viteri¹,

Cruzado²,

Huamán³

2022

International Journal on Advanced Science, Engineering and Information Technology

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Business intelligence in the banking industry has been studied extensively in the last decade; however, business executives still do not perceive efficiency in the decision-making process since the management and treatment of information are very timeconsuming for the deliverer, generating costs in the process. On the other hand, there is no formal methodology for developing business intelligence solutions in this sector. This work aims to optimize decision-making in a business unit that works with internet banking companies, reducing the time, the number of people, and the costs involved in decision-making. To meet the objective, basic and applied research was conducted. The basic research allowed the construction of a new methodology from a study of critical success factors and approaches from the business intelligence literature. The applied research involved the implementation of a business intelligence solution applying the new methodology in a pre-experimental study. Thirty decision-making processes were analyzed using pre-test and post-test data. Tools such as a stopwatch and observation were used to collect and record data on time spent, the number of people, and the decision-making costs. This information was processed in the specialized Minitab18 statistical software, which allowed the observation and confirmation of relevant results regarding time reduction, the number of people, and the costs generated. Therefore, it was concluded that the business intelligence solution, applying the new methodology, optimized decision making in the business unit that works with internet banking for companies.

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“…They reduce the degree of congestion and reduce casu-alties and property losses [3]. Different evacuation scenes have different evacuation characteristics, and the exit position and internal structure of the evacuation scene have an important influence on the evacuation process [4]. Evacuation modeling based on the corresponding characteristics of the evacuation scene is beneficial to the improvement of the performance of the evacuation route plan.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Sports Venue Based on Ant Colony Algorithm and Artificial Intelligence

Zhang

Sun

Tsai

2021

Wireless Communications and Mobile Computing

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In order to improve the congestion of the evacuation plan and further improve the evacuation efficiency, this paper proposes the priority Pareto partial order relation and the vector pheromone routing method based on the priority Pareto partial order relation. Numerical experiments show that compared with the hierarchical multiobjective evacuation path optimization algorithm based on the hierarchical network, the fragmented multiobjective evacuation path optimization algorithm proposed in this paper effectively improves the evacuation efficiency of the evacuation plan and the convergence of the noninferior plan set. However, the congestion condition of the noninferior evacuation plan obtained by the fragmented multiobjective evacuation route optimization algorithm is worse than the congestion condition of the noninferior evacuation plan obtained by the hierarchical multiobjective evacuation route optimization algorithm. The multiple factors that affect the routing process considered in the probability transfer function used in the traditional ant colony algorithm routing method must be independent of each other. However, in actual route selection, multiple factors that affect route selection are not necessarily independent of each other. In order to fully consider the various factors that affect the routing, this paper adopts the vector pheromone routing method based on the traditional Pareto partial order relationship instead of the traditional ant colony algorithm. The model mainly improves the original pheromone distribution and volatilization coefficient of the ant colony, speeds up the convergence speed and accuracy of the algorithm, and obtains ideal candidate solutions. The method is applied to the location of sports facilities and has achieved good results. The experimental results show that the improved ant colony algorithm model designed in this paper is suitable for solving the problem of urban sports facilities location in large-scale space.

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Marketing and business intelligence with help of ant colony algorithm

Cited by 18 publications

References 20 publications

Marketing intelligence: Innovation ability to anticipate global competition

Marketing intelligence: Innovation ability to anticipate global competition

Methodology for Business Intelligence Solutions in Internet Banking Companies

Simulation of Sports Venue Based on Ant Colony Algorithm and Artificial Intelligence

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