Data Mining, Financial Performance and Financial Decisions on Business: Evidence from Digital Marketing

2020 ◽  
Vol 24 (1) ◽  
pp. 1160-1168
Author(s):  
Ari Warokka
Keyword(s):  
Data Mining ◽  
Financial Performance ◽  
Digital Marketing ◽  
Financial Decisions

scholarly journals Using Importance-Performance Matrix Analysis to Evaluate the Financial Performance of American Banks During the Financial Crisis

SAGE Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 215824402090207
Author(s):  
Mohamed M. Khalifa Tailab
Keyword(s):  
Financial Performance ◽  
Structural Equation ◽  
Secondary Data ◽  
Poor Performance ◽  
Path Model ◽  
Matrix Analysis ◽  
Equation Modeling ◽  
Financial Decisions ◽  
Performance Matrix ◽  
Target Construct

This research applies a technique that identifies areas of improvement that can be addressed by managerial decisions or policy activities. It extends the application of partial least squares structural equation modeling (PLS-SEM) using an importance-performance map analysis (IPMA). The IPMA determines priority factors that should receive management’s attention. The PLS path model was tested by comparing 140 failed U.S. banks with the same number of nonfailed banks from 2006 to 2008. This model assembles 15 indicators with four predecessor constructs (i.e., profitability of 2006, profitability of 2007, risk of 2006, and risk of 2007) and one final target construct (i.e., profitability of 2008). Profitability and risk of 2007 mediate the path of profitability and risk of 2006 and profitability of 2008. The IPMA indicated that failed banks were predisposed to decreasing financial performance in 2008 because of their poor performance in 2006 and 2007. Conversely, nonfailed banks were more likely to experience increasing financial performance in 2008 because of their positive performance in 2006 and 2007. This study indicates that managers who use IPMA to prioritize their financial decisions will obtain useful conceptual insights and are unlikely to be misled. Although IPMA can be conducted on the indicator level as well, this article limits its analysis by focusing on the construct level only. The use of IPMA is ubiquitous in end-user surveys, but its application to banking is still in its embryonic state. For originality, this work prioritizes the application of IPMA using secondary data collected from financial statements to assess the performance of American banks during the crisis.

Data Mining in Digital Marketing

2018 ◽  
pp. 44-61 ◽  
Author(s):  
Mahmut Tekin ◽  
Mehmet Etlioğlu ◽  
Özdal Koyuncuoğlu ◽  
Ertuğrul Tekin
Keyword(s):  
Data Mining ◽  
Digital Marketing

scholarly journals Evaluating Financial Performance of Saudi Listed Firms: Using Statistical Failure Prediction Models

2019 ◽  
Vol 2 (1) ◽  
pp. 1-18
Author(s):  
Deena Saleh Merza Radhi ◽  
Adel Sarea
Keyword(s):  
Financial Performance ◽  
Prediction Models ◽  
Stock Exchange ◽  
Failure Prediction ◽  
Financial Decisions ◽  
Listed Firms ◽  
Industrial Companies ◽  
Statistical Relationships ◽  
The Given ◽  
Altman Model

The study aims to compare the classification power of three statistical failure prediction models for evaluating financial performance of Saudi Listed Firms. The study sample consisted of 122 listed industrial companies in the Saudi Stock Exchange for the period from 2014 to 2016. Altman model 1968, Kida model and Zmijewski are used as examples of statistical failure prediction models to evaluate the classification power of the given models to assess the financial performance of firms listed on Saudi Stock Exchange. The results showed that Zmijewski model was more powerful in predicting the financial performance of Saudi listed firms than Altman model (1986) and Kida model. The results showed that there are a statistical relationships between some ratios included in the three models and the financal performance of industrial companies, which was measured by EPS. The study recommended users of financial statements of Saudi listed companies to use Zmijewski ?model, which performs well in evaluating their finacial position to be used when making the ?financial decisions.

scholarly journals Keputusan Keuangan dan Good Corporate Governance terhadap Kinerja Dimoderasi Ukuran Perusahaan

2019 ◽  
Vol 3 (1) ◽  
pp. 1-11
Author(s):  
AINUN JARIAH
Keyword(s):  
Corporate Governance ◽  
Financial Performance ◽  
Financial Management ◽  
Linear Regression Analysis ◽  
Investment Decisions ◽  
Multiple Linear Regression Analysis ◽  
Company Performance ◽  
Manufacturing Companies ◽  
Financial Decisions ◽  
Good Corporate Governance

Optimal financial performance is a company goal that can be achieved through the implementation of financial management functions. One way to improve company performance in addition to financial decisions is to implement good corporate governance. This study aims to determine the effect of financial management decisions and good corporate governance, partially or simultaneously on financial performance with the size of the company as moderating manufacturing in Indonesia. The number of samples is 37 manufacturing companies that routinely publish financial statements for the period 2014-2017. Using multiple linear regression analysis and moderation techniques, the results of the study show that partially funding decisions and good corporate governance significantly affect financial performance. Only investment decisions that have a significant partial effect on the size of the company. Investment decisions, funding decisions, dividend policies and good corporate governance simultaneously have a significant effect on both company size and financial performance. And the size of the company does not moderate the influence of financial decisions and good corporate governance on financial performance.

Data mining techniques for predicting the financial performance of Islamic banking in Indonesia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Ayoub Ledhem
Keyword(s):  
Data Mining ◽  
Financial Performance ◽  
Banking Sector ◽  
Capital Adequacy ◽  
Future Research ◽  
Islamic Banking ◽  
Accuracy Score ◽  
Content Type ◽  
Data Mining Techniques ◽  
Using Data

Purpose The purpose of this paper is to apply various data mining techniques for predicting the financial performance of Islamic banking in Indonesia through the main exogenous determinants of profitability by choosing the best data mining technique based on the criteria of the highest accuracy score of testing and training. Design/methodology/approach This paper used data mining techniques to predict the financial performance of Islamic banking by applying all of LASSO regression, random forest (RF), artificial neural networks and k-nearest neighbor (KNN) over monthly data sets of all the full-fledged Islamic banks working in Indonesia from January 2011 until March 2020. This study used return on assets as a real measurement of financial performance, whereas the capital adequacy ratio, asset quality and liquidity management were used as exogenous determinants of financial performance. Findings The experimental results showed that the optimal task for predicting the financial performance of Islamic banking in Indonesia is the KNN technique, which affords the best-predicting accuracy, and gives the optimal knowledge from the financial performance of Islamic banking determinants in Indonesia. As well, the RF provides closer values to the optimal accuracy of the KNN, which makes it another robust technique in predicting the financial performance of Islamic banking. Research limitations/implications This paper restricted modeling the financial performance of Islamic banking to profitability through the main determinants of return of assets in Indonesia. Future research could consider enlarging the modeling of financial performance using other models such as CAMELS and Z-Score to predict the financial performance of Islamic banking under data mining techniques. Practical implications Owing to the lack of using data mining techniques in the Islamic banking sector, this paper would fill the literature gap by providing new effective techniques for predicting financial performance in the Islamic banking sector using data mining approaches, which can be efficient tools in business and management modeling for financial researchers and decision-makers in the Islamic banking sector. Originality/value According to the author’s knowledge, this paper is the first that provides data mining techniques for predicting the financial performance of the Islamic banking sector in Indonesia.

scholarly journals The role of digital marketing in mediating the effect of the COVID-19 pandemic and the intensity of competition on business performance

2022 ◽  
Vol 6 (1) ◽  
pp. 217-232 ◽  
Author(s):  
I Gusti Ayu Ketut Giantari ◽  
Ni Nyoman Kerti Yasa ◽  
Herkulanus Bambang Suprasto ◽  
Putu Laksmita Dewi Rahmayanti
Keyword(s):  
Financial Performance ◽  
Business Performance ◽  
Analytical Tool ◽  
Digital Marketing ◽  
Purposive Sampling ◽  
Intensity Of Competition ◽  
Sampling Approach

This study aims to explain the role of digital marketing adoption in mediating the effect of the COVID-19 pandemic and the intensity of competition on business performance, which is seen from the perspective of financial performance and non-financial performance. This research was conducted on the culinary sector SMEs in Bali. The size of the sample used is 210 culinary sector SMEs with a purposive sampling approach, namely the culinary sector SMEs that have adopted digital marketing. The analytical tool used is SEM-PLS. The results of the study show that the effect of the COVID-19 pandemic and the intensity of competition has a negative and significant effect on business performance, both financial and non-financial performance. The adoption of digital marketing was unable to mediate the effect of the COVID-19 pandemic and the intensity of competition on financial performance, but the adoption of digital marketing was capable in mediating the effect of the COVID-19 pandemic and the intensity of competition on non-financial performance. Therefore, the adoption of digital marketing needs to be re-optimized to improve business performance, both financial and non-financial performance.

scholarly journals Pengaruh Market to Book Value of Equity, Debt to Equity Ratio dan Dividend Payout Ratio terhadap Net Profit Margin dimoderasi Jumlah Dewan Komisaris

2021 ◽  
Vol 19 (1) ◽  
pp. 90
Author(s):  
Ainun Jariah
Keyword(s):  
Financial Performance ◽  
Financial Management ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Profit Margin ◽  
Dividend Payout ◽  
Book Value ◽  
Financial Decisions ◽  
Net Profit ◽  
Equity Ratio

Financial performance an analysis carried out to see the extent which a company has financial implementation rules. The financial performance really depends on manages the company's finances and carries out the activities, therefore is required improve its ability to manage. Financial performance can be achieved by implementing financial management which involves the completion of important decisions taken by the company, investment and funding decisions, dividend policies. To implement financial decisions properly requires the role of good corporate governance. Research aims to determine the effect of market to book value of equity (MVE/BE), debt to equity ratio (DER), and dividend payout ratio (DPR), partially or simultaneously on net profit margin (NPM) and numbers of commissioners as moderating. By multiple linear regression analysis and moderation, the results MVE/BVE and DER have a significant effect on NPM and number of commissioners. MVE/BVE, DER, and DPR simultaneously a significant effect on NPM and number of commissioners. Number of commissioners moderates the effect of DPR on NPM.

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