درخت حوزه‌های تخصصی

Enterprise Social Media (ESM) has been normally embraced by companies to boost team performance and agility for workers. The goal of this study is to investigate the mediating effect of workplace isolation on the relationships among usage ESM, employee agility and Team Performance along with exploration of the moderating influence of workplace Integrational study model. This research adds to corporate awareness in illustrating the impact of ESM use on team performance and employee agility based on theory of social exchange, theory of information processing and the theory of transactive memory. Cross-sectional survey was employed to collect data from telecommunication firms (public & private). 400 respondents were selected through purposive sampling technique and given close ended questionnaires, 348 questionnaires were selected for further analysis; through a number of statistical tools, after screening out the filled responses. It resulted in Suggesting ESM has a favorable effect on Employee Agility and Team Performance, but the negative relationships were observed among workplace isolation and employee agility and team performance. Further, Workplace Isolation mediated the relationship among ESM, Employee Agility and Team performance. Additionally, Workplace Integration strongly moderated the relationship between ESM and Workplace Isolation.  Experts and/or administrators should pay consideration to the impact of using ESM on agility and team performance of the workers. In addition, when implementing ESM to increase team performance they should concentrate on the extent of team diversity. By presenting the relationship between use of ESM, isolation in the workplace, workplace integration, agility of workers and performance of teams; it enriches the ESM use works by exploring the moderating functions of workplace integration while describing the beneficial consequences of workplace integration.

This study aimed to identify the impact of strategic vigilance (SV)on the useful application of electronic management in the National Railway Transport Company (SNTR), and to achieve the objectives of the study; a survey was designed and distributed to a simple random sample of 200 individuals from the National Railway Transport Company (SNTR) ), From which 180 questionnaires were retrieved, The results obtained indicate Spanish the respondents' perception of both strategic vigilance with its dimensions (competitive vigilance and technological vigilance, commercial vigilance and environmental vigilance) and electronic management in the researched company, The findings also revealed positive effect of strategic vigilance in the practical application of electronic management in the company National Rail Transport (SNTR).

The influence of disintegration processes on the development of regional trade agreements is revealed. Opportunities and threats to cooperation between Ukraine and the EU within the Deep and Comprehensive Free Trade Area at the state level, for enterprises and the population have been identified. To achieve the aim of the research, the method of hypotheses, the method of developing search questions and questionnaires, the method of expert questionnaire survey of government officials, business community and the scientific community were applied in combination with statistical methods of primary information processing and the software SPSS Statistics 23. The aim of article is to identify threats and opportunities of the Ukraine - EU Free Trade Area and priority forms of cooperation. Ukraine is exposed to disintegration tendencies and destabilizing political processes, influence of loss of control over the most industrially developed eastern territories, disruption and severance of established internal economic ties. The efficiency of cooperation forms in ensuring the stability of international economic relations is estimated. Based on results of the study, practical recommendations were developed for both enterprises (micro-level of international cooperation) and for the government (macro-level). In the context of digitalization and informatization in the global environment and the dynamic growth of the IT sector, international cooperation in this area is becoming especially important. According to the results of the study, Ukraine and the EU have mutual economic interests to develop cooperation in the IT field, which requires support and involvement of both parties in improving regulatory conditions and integration mechanisms.

Equity is the basic structural component of the development of any business, so it is important for an industrial enterprise to develop tools to determine its effective management. It it is impossible without conducting qualitative financial analysis, timely and effective adaptation of valuation approaches in the modern conditions of functioning of enterprises. The effective functioning of enterprises is impossible without the use of modern complex methods, which include not only a methodology, a system of indicators, but also modern technologies for their assessment, planning and control. Information management is one of these technologies. To solve the problems of the study we used the method of structural-logical analysis, methods of theoretical generalization and comparative analysis, synthesis and method of grouping of absolute and relative values, graphical method and information management methods. The result of the study is the formation of a comprehensive approach to the financial analysis of the equity of the enterprise on the formed system of four groups of indicators. These indicators take into account the state of equity, its efficiency, ensuring risks in the process of the enterprise and directions of financial analysis.

The article focuses on the relevance of the implementation  of information and analytical support mechanisms in the activities of local state administrations. Information resources and information processes in general become the main prerequisites for the effectiveness of public administration and local governments. This requires public authorities to implement systems and structures of information and analytical support of government activities, new forms and technologies of information use, new technologies for its collection, processing and analysis, creation and interaction of information databases. Theoretical bases of functioning of information and analytical maintenance mechanisms of local  administrations activity are substantiated; practical offers concerning the improvement of processes of their formation and functioning in system of public administration are generalized and developed.

Object Detection has been one of the areas of interest of research community for over years and has made significant advances in its journey so far. There is a tremendous scope in the applications that would benefit with more innovations in the domain of object detection. Rapid growth in the field of machine learning has complemented the efforts in this area and in the recent times, research community has contributed a lot in real time object detection. In the current work, authors have implemented real time object detection and have made efforts to improve the accuracy of the detection mechanism. In the current research, we have used ssd_v2_inception_coco model as Single Shot Detection models deliver significantly better results. A dataset of more than 100 raw images is used for training and then xml files are generated using labellimg. Tensor flow records generated are passed through training pipelines using the proposed model. OpenCV captures real-time images and CNN performs convolution operations on images. The real time object detection delivers an accuracy of 92.7%, which is an improvement over some of the existing models already proposed earlier. Model detects hundreds of objects simultaneously. In the proposed model, accuracy of object detection significantly improvises over existing methodologies in practice. There is a substantial dataset to evaluate the accuracy of proposed model. The model may be readily useful for object detection applications including parking lots, human identification, and inventory management.

The data stored in data warehouse is used for making strategic decisions by integrating heterogeneous data from multiple sources at a single storage place, where data is used for querying and analysis purposes. With the advancement in the technology, Business Analytics and Business intelligence are being increasingly used in the financial sector for forecasting business decisions. Many On-Line Analytical Processing (OLAP) tools are being largely explored that can contribute to business decision making. Banking operation handles a lot of data as they operate daily. Subsequently, preparing of this tremendous volume of information requires instant and quick tools that can process the information at high processing speeds. Through this research paper, we represent the OLAP cube as one of the tools which can be used for business analysis. A case study of a bank and loan approval process is considered as one of the areas for implementation and analysis of business decisions using business intelligence which can serve as a key factor for increasing intelligence in the banking sector to make reliable business decisions. Higher management can forecast and predict various outcomes from the bank data warehouse using On-Line Analytical Processing technology which provided a multidimensional view of the data. Analysts can make business decisions by analyzing the reports and pattern trends in the graphs. Management can modify existing policies and procedures to increase the growth of the bank and can have a healthy competition with their competitors.

Due to enchantment in network technology, the worldwide numbers of internet users are growing rapidly. Most of the internet users are using online purchasing from various sites. Due to new online shopping trends over the internet, the seller needs to predict the online customer’s choice. This field is a new area of research for machine learning researchers. A random forest (RF) machine learning method is a widely used classification method. It is mainly based on an ensemble of a single decision tree. Online e-commerce websites accumulate a massive quantity of data in large dimensions. A Random Forest is an efficient filter in high-dimensional data to reliably classify consumer behaviour factors. This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. The weighted random forest algorithm incorporates the C4.5 method named a “Hybrid Weighted Random Forest” (HWRF) to forecast online consumer purchasing behaviour. The experimental results influence the quality of the proposed method in the prediction of the behaviour of online buying customers over existing methods.

The Special Issue of the Journal of Information Technology Management (JITM) is publishing very selective papers on information management, Internet of Things (IoT), Algorithms, Quality of Service (QoS),Tourists Perception , Technology in higher education, integrated systems, enterprise management, Self-Service Technology (SST) , cultural thoughts, strategic contributions, management information systems, and cloud computing. We received numerous papers for this special issue but after an extensive peer-review process, eight papers were finally selected for publication. In the digital age, the management of electronic archives became a trend as well as the focus of management development in many institutions.

Globalization is one of the important elements of external environment of the enterprises, that is why it is defined to be the main object of this study. The main signs of globalization in international trade and the qualitative / quantitative changes caused are studied, in particular, attention is paid to the mutual exchange of resources to solve international problems, including environmental ones. The transformation of competitive / monopoly relations under the influence of globalization in the areas of levels of cooperation, the ratio of competition / rivalry, the dependence of competition on innovation, models of competitive behavior are analyzed. The impact of globalization on economic processes of influences redistribution in the markets between residents and nonresidents is investigated, the factors that cause changes in investment activity of nonresidents are identified, namely the direct relationship between changes in the index of economic globalization and the number of foreign enterprises in Ukraine. Based on the research, the identified exogenous factors are complemented by such factors as protection of intellectual property rights and prevention of abuse of intellectual property rights, and endogenous - as a relationship of decisive influence on businesses in specific markets, management awareness of the impact of their transactions on the market and others. It is concluded that globalization does not take into account the national characteristics of individual economies, the resource potential of development, but involves the use of existing benefits, respectively, those who want to become part of it must acquire certain exclusivity, disseminate relevant information, introduce innovation in enterprise management systems, show interest in cooperation with the relevant participant for the development of digitalization, social and economic transformations.

One of the most important risks that the banks and financial institutes face, is credit risk which is related to not-paid instalments or the instalments paid with delay by borrowers. Banks use credit scoring models In order to prevent this type of risk. The goal of this research is to investigate the joint effect of economic time cycles and the industry sector on credit scoring models we are seeking to answer the key question: “when should bank change their credit scoring models based on economic time cycles and for which industry sectors?”. The dataset of the research involves all companies that were applied for a loan in one of the Iranian major banks during the years 2008-2011. The companies have been divided into four industry sectors including “Industry and Mine”, “Oil and chemical”, “Service and Infrastructure” and finally “Agriculture”. Based on the sector of the industry and year, 54 explanatory variables, both financial and non-financial, 12 distinct industry sectors and time-specific data sets are built then classification methods were used to classify customers into two groups of defaults and non-defaults. Finally, we compared the results by Wilcoxon Test. The results show that the companies that are in the groups of Industry and Mine and Agriculture, need their own special credit scoring based on industry type model and time but two other groups don’t need of course in the studies dataset duration. Finally, the study concluded by introducing the credit scoring strategies for different four-cycle of economies