Research on the enterprise online marketing mode based on data mining

With the development and popularity of mobile networks, online shopping has gradually become a trend. For enterprises, the traditional marketing mode has been difficult to play an effective role when facing the emerging online shopping mode. This study aims to improve the revenue benefits of online shopping. This paper first introduces the traditional marketing mode and then selects the data mining model used for consumption preference segmentation to build an online marketing mode. An example analysis was conducted on a book sales company and a real estate company. The results showed that more users in this community preferred five types of books, and the percentages from high to low were teaching and learning materials, modern novels, popular science books, historical literature, and classical novels; more customers preferred online platforms among the channels for collecting information on home purchase. No matter it was the book sales company or the real estate company, compared with no fluctuation in the company’s turnover under the traditional marketing mode, the turnover of the company increased month by month after adopting the online marketing mode.

Augmenting Customer Support with an NLP-based Receptionist

In this paper, we show how a Portuguese BERT model can be combined with structured data in order to deploy a chatbot based on a finite state machine to create a conversational AI system that helps a real-estate company to predict its client's contact motivation. The model achieves human level results in a dataset that containts 235 unbalanced labels. Then, we also show its benefits considering the business impact comparing it against classical NLP methods.

The Effect of Auditor Quality, Liquidity, Profitability, and Solvency on Going Concern Audit Opinions on Property and Real Estate Companies Listed on IDX in 2016-2020

This is document gives formatting instructions for authors preparing papers for publication in the Recent Science Journals. The authors must follow the instructions given in the document for the papers to be published. You can use this document as both an instruction set and as a template into which you can type your own text. In this study, it is about assessing how the influencer or impact of an auditor's quality, liquidity, profitability, and solvency either partially or partially or simultaneously or simultaneously, on the audit opinions of property and real estate companies that are already on the IDX list between 2016 and 2020 Changes in the audit report indicates that the auditor believes there is a possibility that the auditor may be able to leave the company. Various variables, both financial and non-financial, can affect the assessment of a company's capacity to continue its operations. This research involved 65 real estate building companies that can be listed on the IDX from 2016 to 2020, with a total of 195 units of analysis. Multiple linear regression analysis methods are used in the research procedure. Based on the findings, auditor quality, liquidity and profitability have little effect on the audit view of a property and real estate company listed on the IDX between 2016 and 2020. Between 2016 and 2020, the solvency variable has minimal impact. Immobility and a property company have been listed on the IDX. Variables such as the ability to audit, liquidity, profitability, and solvency have an impact on the audit opinion so that property and real estate companies can be listed on the IDX in 2016-2020.

Housing-Price Prediction in Colombia using Machine Learning

It is a common practice to price a house without proper evaluation studies being performed for assurance. That is why the purpose of this study provide an explanatory model by establishing parameters for accuracy in interpretation and projection of housing prices. In addition, it is intentioned to establish proper data preprocessing practices in order to increase the accuracy of machine learning algorithms. Indeed, according to our literature review, there are few articles and reports on the use of Machine Learning tools for the prediction of property prices in Colombia. The dataset in which the research is built upon was provided by an existing real estate company. It contains near 940,000 items (housing advertisements) posted on the platform from the year 2018 to 2020. The database was enriched using statistical imputation techniques. Housing prices prediction was performed using Decision Tree Regressors and LightGBM methods, thus deriving in better alternatives for house price prediction in Colombia. Moreover, to measure the accuracy of the proposed models, the Root Mean Squared Logarithmic Error (RMSLE) statistical indicator was used. The best cross validation results obtained were 0.25354±0.00699 for the LightGBM, 0.25296 ±0.00511 for the Bagging Regressor, and 0.25312±0.00559 for the ExtraTree Regressor with Bagging Regressor, and it was not found a statistical difference between their performances.

Pengaruh Kepuasan Kerja Terhadap Kinerja Karyawan Dengan Stres Kerja Sebagai Variabel Mediasi

This study aims to determine the effect of job satisfaction on employee performance with job stress as a mediating variable. The subjects used in this study were employees at PT. XYZ. PT. XYZ is a multinational real estate company. The number of samples taken in this study were 75 respondents. The data obtained was carried out from the results of distributing questionnaires through google form using purposive sampling technique. Processing of the collected data is carried out with the SmartPLS program. Based on the results of data analysis, it can be concluded that job satisfaction has a significant negative effect on job stress, and job stress has a significant negative effect on employee performance. Also, job satisfaction has no effect on employee performance. However, job stress can mediate the effect of job satisfaction on employee performance. This research shows that in order to improve employee performance, companies need to pay attention to employee job satisfaction in order to reduce employee work stress levels. Penelitian ini bertujuan untuk mengetahui pengaruh Kepuasan Kerja terhadap Kinerja Karyawan dengan Stres Kerja sebagai variabel mediasi. Subjek yang digunakan dalam penelitian ini adalah karyawan pada PT. XYZ. PT. XYZ merupakan perusahaan di bidang real estate berskala multinasional. Jumlah sampel yang diambil dalam penelitian ini sebanyak 75 responden. Data yang diperoleh dilakukan dari hasil penyebaran kuesioner melalui google form dengan menggunakan teknik pengambilan sampel purposive sampling. Pengolahan data yang telah terkumpul dilakukan dengan program SmartPLS. Berdasarkan hasil analisis data, maka dapat disimpulkan bahwa Kepuasan Kerja berpengaruh negatif signifikan terhadap Stres Kerja, dan Stres Kerja berpengaruh negatif signifikan terhadap Kinerja Karyawan. Serta, Kepuasan Kerja tidak berpengaruh terhadap Kinerja Karyawan. Akan tetapi, Stres Kerja dapat memediasi pengaruh Kepuasan Kerja terhadap Kinerja Karyawan. Dari penelitian ini menunjukkan bahwa untuk dapat meningkatkan Kinerja Karyawan, perusahaan perlu memperhatikan Kepuasan Kerja karyawan agar dapat menurunkan tingkat Stres Kerja karyawan.

Modelling the Impact of Different COVID-19 Pandemic Waves on Real Estate Stock Returns and Their Volatility Using a GJR-GARCHX Approach: An International Perspective

This paper aims to investigate the impact of various COVID-19 pandemic waves on real estate stock returns and their volatility in developed (US, Australia), emerging (Turkey, Poland), and frontier (Morocco, Jordan) markets. A study using a GJR-GARCHX model revealed that the pandemic outbreak had a limited impact on real estate company stocks. The first pandemic wave only in the US caused a decline in stock returns. In turn, this was the case in Poland and Jordan during the second and third waves. Furthermore, in the aftermath of the pandemic development, an increase in the volatility of stock returns can be observed in the Polish financial market. However, this effect mainly applies to the period of the first disease wave.

The Influence of E-Marketing on Performance of Real Estate Enterprises: Based on Super-Efficiency DEA and Grey Entropy Methods

E-marketing is an important tool for real estate enterprises. We evaluate 3 online marketing channels of 44 Chinese real estate companies. Super-efficiency DEA and grey entropy methods are applied to analyse the influence of E-marketing on the performance of real estate enterprises. We find that E-marketing will affect the business performance of real estate companies. Real estate company managers should adopt more strategies to improve corporate performance.

Value Creation of Real Estate Company Spin-off Property Service Company Listing

The paper took 12 groups of parent companies and subsidiaries as the samples, in which the property service companies, spun from the real estate companies, have successfully on the capital market. The research showed that the average abnormal return (AAR) of real estate companies’ stocks was positive on the first announcement date of possible spin-off listing, while the cumulative average abnormal return (CAAR) remained positive for 21 days during the (–11, 9) days around the first announcement of possible spin-off and listing. Further, the changes in operating performance of real estate companies and property service companies were analysed after the successful spin-off for 3 consecutive years, compared with the year before the spin-off and listing. The results showed that after the spin-off and listing, real estate companies and property service companies have greatly improved their performance. Therefore, the fact that real estate companies spun off property service companies created positive values for shareholders.