Predicting the performance of digital business platforms based on changes in marketing strategies with a neural network approach

سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 84

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شناسه ملی سند علمی:

ICOCS05_024

تاریخ نمایه سازی: 7 شهریور 1401

چکیده مقاله:

According to research in the field of marketing, it seems that trust is the most essential component of creating, developing and maintaining successful relationships between sellers and corporate buyers. The nation band is considered between companies. The present research is a questionnaire in terms of applied purpose and in terms of descriptive survey research method based on data. In this research, descriptive statistics, inferential statistics and neural network methods have been used. The results show that because overconfident managers overestimate the expected return on corporate investment projects and underestimate the likelihood and impact of negative events, they may increase financial reporting risk for auditors. Accordingly, the number of sales centers will have the lowest amount of validation (Validation) among the variables expressed at the input of the neural network system. On the other hand, the hypothesis based on the fact that the factor of interactions between marketing and operational variables has no significant effect on the investment of financial assets, in other words, the null hypothesis is confirmed. Therefore, the overconfidence factor has no significant effect on the investment of financial assets. This means that people are not overly satisfied with their information and knowledge in their investments. The results also show that the positive effect of senior managers' overconfidence on cash flow investment sensitivity is more pronounced in companies with higher agency costs.

کلیدواژه ها:

Performance of digital business platforms ، neural network ، forecasting.

نویسندگان

Sepideh Taleirad

M.Sc., Department of Management MBA, Faculty of Management, Kharazmi University,Tehran, Iran.

Babak Ghorbanian

PhD, Department of Materials Engineering, Faculty of Materials Engineering, SemnanUniversity, Semnan, Iran