Exploring the remote work challenges in the era of COVID-19 pandemic: review and application model

PurposeRemote work (RW) literature is a megatrend in HRM literature, and the COVID-19 pandemic has highlighted the importance of RW as a concept and an organisational practice. Given the large number of papers being published on remote work, there is a need for a critical review of the extant literature using bibliometric analysis. This paper examines the literature on remote working to identify the factors crucial for managing a remote workforce. This study uses the complex adaptive systems theory as a foundation to build a framework that organisations can use to manage their remote workforce, focusing on three outcomes: employee engagement, collaboration and organisational agility.Design/methodology/approachBibliometric analysis was conducted on the research published in Scopus journal in the area of remote work, followed by critical literature analysis.FindingsThe bibliometric analysis identified five clusters that reflect five organisational factors which the management can align to achieve the desired outcomes of engagement, collaboration and agility: technology orientation, leadership, HRM practices, external processes and organisational culture. The present findings have important implications for managing the remote workforce.Originality/valueThe five factors were mapped to propose a conceptual model on engaging individual employees, fostering team collaboration and building organisational agility while working remotely. We also propose an application model for using technology to achieve the outcomes of engagement, collaboration and agility in the organisation. Practitioners could use this framework to focus on the factors that can create a conducive environment to improve work efficiency in a remote workforce.

Application of Decision Tree Intelligent Algorithm in Data Analysis of Physical Health Test

With the continuous development of China’s cultural industry, people’s health has become one of the topics of the highest concern. Therefore, all the application models of physical health test data in the actual analysis have become the current research focus and trend direction of healthy constitution. This paper summarizes the significant problems in the analysis of physical health test data, through the comprehensive analysis and investigation of physical health test data, combined with the measurement of the test indicators, through the analysis and processing system of youth physical health data, the use process of national youth group physical health standard data management software, and decision tree intelligent algorithm in physical health. The research steps of test data analysis and application model summarize the application characteristics of physical health test data in the application process. Based on this, a decision tree intelligent algorithm is proposed, and the corresponding functions and optimization formulas of the algorithm are substituted. In the process of actual sample checking calculation, each weight range and corresponding errors are inferred and analyzed by combining examples. This paper summarizes the application model and optimization model of health test data analysis based on decision tree intelligent algorithm. Through the repeated test of the research data, the feasible area and application scope of the algorithm are obtained, and the practical optimization scheme and application ideas under the algorithm are obtained.

Associations Between Pornography Consumption, Sexual Flexibility, and Sexual Functioning Among Austrian Adults

To date, only a few studies have examined the associations between pornography consumption and sexual functioning. The Acquisition, Activation, Application Model (3AM) indicates that the frequency of pornography consumption and the perceived realism of pornography may influence whether sexual scripts are acquired from viewed pornography. Having sexual scripts that are alternative to their preferred sexual behaviors may help people switch to alternative sexual behavior when sexual problems arise. The current study analyzed whether frequent pornography consumption was associated with greater sexual flexibility and greater sexual functioning. Additionally, the perceived realism of pornography consumption was tested as a moderator of those associations. At an Austrian medical university, an online cross-sectional questionnaire study was conducted among 644 medical students (54% women and 46% men; Mage = 24.1 years, SD = 3.8). The participants were asked about their pornography consumption, partnered sexual activity, sexual flexibility, perceived realism of pornography, and sexual functioning. Manifest path analyses revealed direct and indirect associations between frequent pornography consumption and greater sexual functioning through greater sexual flexibility in women but not in men. Perceived realism did not moderate those associations. In conclusion, our study was in line with previous studies that found no significant associations between men’s pornography consumption and sexual functioning in men. However, some women may expand their sexual scripts and learn new sexual behaviors from pornography consumption, which may help with their sexual functioning.

Para-Social Interaction Analysis of Valentino Virtual Spokesperson based on Weibo Data and Search Popularity

Brand image is one of the most important factors influencing the competitiveness of the commodity market. In order to reduce the negative impact of potential scandals of celebrity spokespersons, Valentino began to use a virtual spokesperson named noonoouri for promotion. In this context, we first describe the application model of Valentino's virtual spokesperson. Then, based on the Valentino Weibo data we collected and Google search popularity, we analyzed the impact of virtual spokespersons on the para-social interaction between brands and consumers. Finally, according to the analysis conclusion of the impact of Valentino's virtual spokesperson in the para-social interaction, a corresponding marketing-competitive brand image promotion proposal is put forward.

Empirical Analysis of Financial Statement Fraud of Listed Companies Based on Logistic Regression and Random Forest Algorithm

Financial supervision plays an important role in the construction of market economy, but financial data has the characteristics of being nonstationary and nonlinear and low signal-to-noise ratio, so an effective financial detection method is needed. In this paper, two machine learning algorithms, decision tree and random forest, are used to detect the company's financial data. Firstly, based on the financial data of 100 sample listed companies, this paper makes an empirical study on the fraud of financial statements of listed companies by using machine learning technology. Through the empirical analysis of logistic regression, gradient lifting decision tree, and random forest model, the preliminary results are obtained, and then the random forest model is used for secondary judgment. This paper constructs an efficient, accurate, and simple comprehensive application model of machine learning. The empirical results show that the comprehensive application model constructed in this paper has an accuracy of 96.58% in judging the abnormal financial data of listed companies. The paper puts forward an accurate and practical method for capital market participants to identify the fraud of financial statements of listed companies and has certain practical significance for investors and securities research institutions to deal with the fraud of financial statements.

Dashboard Monitoring Website Dosen Studi Kasus Universitas Bina Darma

The concept of dashboard performance is an information system application model provided for managers to present performance quality information, from a company or organizational institution, dashboards have been widely adopted by companies or businesses. In this study, the authors designed a dashboard that was used as a monitoring system for lecturer posting activities at Binadarma University, Palembang. The limitation of the dashboard in this study only displays data based on lecturer posts which will be developed in the form of a website. Dashboard design is more effective and efficient than viewing data manually, which requires managers to open a database to view data one by one from lecturers' posts. In making the lecturer website dashboard, the data taken is in the form of posting data stored in the lecturer database, the data that has been taken will be presented in the dashboard in the form of graphs, tables and dashboards.

Bounding the execution time of parallel applications on unrelated multiprocessors

Heterogeneous multiprocessors can offer high performance at low energy expenditures. However, to be able to use them in hard real-time systems, timing guarantees need to be provided, and the main challenge is to determine the worst-case schedule length (also known as makespan) of an application. Previous works that estimate the makespan focus mainly on the independent-task application model or the related multiprocessor model that limits the applicability of the makespan. On the other hand, the directed acyclic graph (DAG) application model and the unrelated multiprocessor model are general and can cover most of today’s platforms and applications. In this work, we propose a simple work-conserving scheduling method of the tasks in a DAG and two new approaches to finding the makespan. A set of representative OpenMP task-based parallel applications from the BOTS benchmark suite and synthetic DAGs are used to evaluate the proposed method. Based on the empirical results, the proposed approach calculates the makespan close to the exhaustive method and with low pessimism compared to a lower bound of the actual makespan calculation.