درخت حوزه‌های تخصصی

Despite the increasing importance of data and information quality, current research related to Big Data quality is still limited. It is particularly unknown how to apply previous data quality models to Big Data. In this paper we review Big Data quality research from several perspectives and apply a known quality model with its elements of conformance to specification and design in the context of Big Data. Furthermore, we extend this model and demonstrate it utility by analyzing the impact of three Big Data characteristics such as volume, velocity and variety in the context of smart cities. This paper intends to build a foundation for further empirical research to understand Big Data quality and its implications in the design and execution of smart service ecosystems.

The purpose of this paper is to identify and prioritise mobile wallet (m-wallet) key adoption factors (KAFs). 9 KAFs are proposed by authors on the basis of a systematic literature review. Authors have proposed one novel factor influencing adoption called 'contactless transactions' due to pandemic and new normal post-Covid-19. This has resulted in a total of 10 KAFs. The fuzzy TOPSIS approach is proposed to rank these key adoption factors (KAFs). Sensitivity analysis has also been conducted to check the robustness of the study. Examining the literature indicates that this study is among the first attempts to prioritise key adoption factors (KAFs) using fuzzy TOPSIS. The results show that perceived security, trust, performance expectancy, perceived ease of use and contactless transactions are among the top 5 adoption factors. The findings of this research will be beneficial for both academicians and practitioners. The key adoption factors (KAFs) proposed in the paper will help practitioners develop strategies for building a wider acceptance of m-wallet among customers. Moreover, the fuzzy TOPSIS technique discussed in this paper will apprise managers about critical factors to be focused upon. This study will provide an integrated framework for academicians to carry out further research in the field of mobile wallets.

Purpose: Economic and social status play a prominent role in many human activities and their  function is accentuated in the theory of the knowledge gap. According to the idea, the knowledge of the people with higher socio-economic status increases compared to those with lower socio-economic status. The purpose of this study was to determine the role of socio-economic status (based on knowledge gap theory) in the information-seeking behavior of fellow members of staff at  Qom University.Method: The study was an applied research in terms of purpose and in terms of strategy and data collection was correlational. The population consisted of 761 university employees. Based on Cochran’s formula the sample of the study included 255 employees. A researcher-made questionnaire was used to collect data. Spearman and X2 statistical tests were applied to analyze data.Findings: People who have a higher socio-economic status (with higher employment, income and education levels) are more motivated to search and obtain information, and there is a significant relationship between the components of individuals' socio-economic status and the type of the used information resources. Socio-economic status affects the criteria for evaluating information resources, and people with higher rate use various evaluation criteria while assessing the information. People with socio-economic status use various and different channels to obtain information, thus, there is a positive and significant relationship between the use of search engines and meta-search engines, internal and external databases, conference papers, library RSS, specialized social networks, consultation with librarians and technical blogs, and their socio-economic status.Conclusion: The social and economic status explains and predicts the information-seeking behavior of the staff and the results confirmed the theory of knowledge gap. Prediction of the facilities required for searching and seeking information in organizations and making them accessible to all human resources can help provide fair access to information for the better part of society and reduce the knowledge gap.

Cloud computing technology could bring about cost-effectiveness, scalability, usage easiness, and flexibility against environmental changes. Despite several advantages of this technology, the acceptance and movement to the cloud computing environment occurs slowly, particularly in several organizations in developing countries. Cloud computing allows an individual to share distributed sources and services. This study aims to identify the optimal security framework in cloud computing, focusing on the Infrastructure Communications Company as a case study. The method used in this study is descriptive (non-test) and the correlative research scheme is PLS (partial least squares). The participants of the current study were selected among the Tehran Communication Infrastructure Company employees. Based on the Cochran formula and the research population which was 600, 234 were selected using the random sampling method. To measure the security framework in cloud computing, the questionnaires related to Joils and Opria (2017), Tari (2014), Qio and Gayi (2017), and Sing et al. (2016) were used. Findings indicate that the impacts of technological and technical factors, experienced human resources, financial resource provision and secure infrastructures on information technology security were significant (0.01). Moreover, information technology management and supporting regulations on security risk assessment have significant effects. The assessment of security risk has a significant effect on information security. Additionally, information security management and supporting regulations have a significant effect on Goal setting (0.01). Goal setting has a significant effect on environmental and physical security. Based on the results, the evaluated model of the research could explain 0.53 of information security management, 0.50 of security evaluation, 0.36 of goal setting, 0.55 of information security, and 0.35 of environmental security.

The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.

The article presents the results of the analysis of the indicators of the level of the shadow economy in Ukraine in the period from 2010 to 2020. The level of shadow economy calculated on the basis of such methods as: unprofitable enterprises, monetary, population expenditures - retail trade - services and electricity was used for the analysis. The causes and consequences of shadow economic activity in Ukraine are given. The study found that the downward trend in the shadow economy persists despite the spread of the negative effects of the COVID - 19 pandemic and declining real GDP. In particular, three of the four methods used to assess the level of the shadow economy recorded a decrease in the level of the shadow economy (the method of "population expenditure - retail trade and services"; the electric method; the monetary method). At the same time, the method of enterprise losses showed an increase in the shadow economy, which is largely due to a significant deterioration in the financial situation of enterprises under the restrictions imposed to prevent the rapid spread of the coronavirus pandemic in the world and Ukraine, as well as logistical problems. The practical value of the results is determined by the fact that the conclusions and proposals can be used to more accurately and objectively calculate the level of the shadow economy, which in turn can be the basis for effective decisions to de-shadow and legalize Ukraine's economy.