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For aiding computer security experts in their study, log files are a crucial piece of information. Especially the time domain is very important for us because in most cases, timestamps are the only linking points between events caused by attackers, faulty systems or simple errors and their corresponding entries in log files. With the idea of storing and analyzing this log information in graph databases, we need a suitable model to store and connect timestamps and their events. This paper aims to find and evaluate different approaches how to store timestamps in graph databases and their individual benefits and drawbacks.

We analyse three different approaches, how timestamp information can be represented and stored in graph databases. For checking the models, we set up four typical questions that are important for log file analysis and tested them for each of the models. During the evaluation, we used the performance and other properties as metrics, how suitable each of the models is for representing the log files’ timestamp information. In the last part, we try to improve one promising looking model.

We come to the conclusion, that the simplest model with the least graph database-specific concepts in use is also the one yielding the simplest and fastest queries.

Limitations to this research are that only one graph database was studied and also improvements to the query engine might change future results.

In the study, we addressed the issue of storing timestamps in graph databases in a meaningful, practical and efficient way. The results can be used as a pattern for similar scenarios and applications.

The quality of interaction between learners and online content is one of the imperative factors in determining the efficacy of web-based teaching-learning towards the creation and maintenance of sustainable learning communities. Interaction with content is an internal dialogue of reflective thought that occurs between learner and the substance. Interaction is often triggered and supported by events in the learning environment – focusing on how the learner interacts with what is to be learned.

This paper looks at the difference in learners' interaction on the online Learning Management System (LMS) of undergraduate and postgraduate courses. Based on a framework developed for investigating learners' interaction with online content in Wawasan Open University, data from the LMS log and activity database was extracted. The data is then analyzed based on the pattern and behavior of learners' interaction with the online content of the courses. Further analysis is done by transcribing the discussions and exchanges of teacher and learners within the online forums, specifically investigating the dimension, depth and category of exchanges that occurred. Based on the findings, several recommendations are made to enhance the design and delivery of web-based content, aiming at maximizing the efficacy of the online learning environment of undergraduate and postgraduate courses in open distance learning (ODL).

This study aims to investigate customers’ churning out of Internet Protocol Television (IPTV) service, one of the most prevalent forms of IT convergence.

Based on the review of current literature, a research model is introduced to depict the effects of select independent variables on customer churning behavior. First of all, the two groups are compared in terms of predictor variables, including switching barriers, voice of customer (VOC), membership period and degree of contents usage. Then, a curvilinear regression was applied to understand the association relationship between the level of IPTV contents usage and variables of switching barriers, VOC and membership period. Third, a logit regression was performed to predict customer churning through the variables of switching barriers, VOC, membership period and level of IPTV contents usage.

Through the empirical analysis, this study analyzed the factors affecting customer churning behavior of IPTV service providers based on switching barriers, VOC and contents usage.

Although several studies on IPTV have been undertaken globally, they have largely depended on self-reporting surveys to examine dynamics between antecedent variables and IPTV performance in terms of customer satisfaction, usage intension and customer retention. This empirical study is performed to understand influential factors of IPTV service defection through the weblog analysis of 3,906 service users, who represented both service defectors and non-defectors during a specific month.

This article examines the links between average city size, fiscal decentralisation, and national economic growth in 33 Organisation for Economic Co-operation and Development (OECD) countries.

The data in this paper comprise an unbalanced panel dataset which contains economic growth indicators, average city size, fiscal decentralisation indicators and control variables in 33 OECD member countries from 1975 to 2015 in five-year intervals. Fixed-effects (FE) estimators are used for the analysis.

This research finds i) countries with larger weighted average city sizes have higher economic growth, ii) countries with greater fiscal decentralisation have higher economic growth, but iii) countries with larger weighted average city sizes with greater decentralisation have lower rates of economic growth.

The research highlights the importance of agglomerations and decentralised governance and management for economic growth. While the findings are consistent with previous evidence that larger city sizes and fiscal decentralisation are separately associated with higher rates of economic growth, the authors find countries which have larger cities and greater fiscal decentralisation experience lower rates of economic growth highlighting a need for caution on decentralisation agendas in such cases. The implications of this suggest policymakers should proceed with caution on decentralisation agendas in countries with large cities.

This paper aims to empirically verify the impact of the mandatory dividend law on the investment of publicly traded companies.

The sample includes 212,595 observations from publicly traded companies from 47 different countries over the period from 2000 to 2016. The authors estimated a regression model by panel data methods to show the impact of the mandatory dividend on firm’s investment, more specifically in their sensitivities of investment to cash flow and to growth opportunities. In addition, the average treatment effect on the treated was estimated through sample matching.

The results indicate that the mandatory dividend have a direct and indirect impact on corporate investment.

Legislators and economic agents can use the results of the present research to evaluate the continuity or implementation of this legal mechanism (mandatory dividend) to evaluate economic moments favorable to its use or to create different legal rules to smooth the impact of this mechanism on the investment of companies.

This paper analyses the research in Library and Information Science (LIS) and reports on (1) the status of LIS research in 2015 and (2) on the evolution of LIS research longitudinally from 1965 to 2015.

The study employs a quantitative intellectual content analysis of articles published in 30+ scholarly LIS journals, following the design by Tuomaala et al. (2014). In the content analysis, we classify articles along eight dimensions covering topical content and methodology.

The topical findings indicate that the earlier strong LIS emphasis on L&I services has declined notably, while scientific and professional communication has become the most popular topic. Information storage and retrieval has given up its earlier strong position towards the end of the years analyzed. Individuals are increasingly the units of observation. End-user's and developer's viewpoints have strengthened at the cost of intermediaries' viewpoint. LIS research is methodologically increasingly scattered since survey, scientometric methods, experiment, case studies and qualitative studies have all gained in popularity. Consequently, LIS may have become more versatile in the analysis of its research objects during the years analyzed.

Among quantitative intellectual content analyses of LIS research, the study is unique in its scope: length of analysis period (50 years), width (8 dimensions covering topical content and methodology) and depth (the annual batch of 30+ scholarly journals).

The paper aims to present a systematic literature review (SLR) showing the benefits, challenges and future research of blockchain technology (BT) for the supply chain (SC), also suggesting how the features of BT can change the organizational aspects of the SC.

An SLR has been conducted to detect papers that contained the word “Blockchain” in their titles, keywords or abstracts. Consequently, a second filter to analyze BT papers for the SC was applied.

This paper shows through 31 variables classified into positive, negative and future directions of technology for the SC. For instance, BT will reduce time consuming of operations management and payments using smart contracts. In addition, integrating BT with other technologies will allow product tracking and sustainable production management.

The selection of papers is limited to Scopus database and specifically to the Management Journal.

BT creates collaborative peer-to-peer and business-to-business markets. The technology automates several tasks such as order management, payment for goods, waste reduction and process control. Therefore, its use within the SCs will improve the productivity and profits of the participants.

This paper is focused on BT for the SC area with 60 articles analyzed. In addition, 13 variables on benefits, eight variables on challenges and 12 points on future research directions were analyzed. This work will help researchers and entrepreneurs to deepen about the changes that BT offers in SC.

The paper investigates the effects of global value chains (GVCs) and technological innovation on exports. The paper builds a new dataset from two database, the EORA and the OECD stan database. Using a pooled OLS and a two-stage quantile regression technique on a sample of 8 OECD countries, the results suggest that the effects of GVCs participation are heterogeneous across countries. We find that at the aggregate level, GVCs and forward participation are negatively associated with exports growth. However, we only find evidence of a positive effect of backward participation on exports in the case of France and Germany. At the disaggregated level, we find that: (a) an increase in GVCs participation in low technology intensive sectors is positively associated with exports’growth; (b) an increase in GVCs participation in high technology intensive sector is negatively correlated with exports’growth. The findings stress the importance of GVCs as a driving channel for subdue economic growth in low technological sectors.

Recent advancement in technological development has encouraged distance learning institutions to be more productive and creative in effectively utilizing the Learning Management System (LMS). Among the many measures employed is the integration of federated search engine into the LMS which allows for a more productive and wider scope of information retrieval through the provisions of library resources and services. The purpose of this paper is to report one such case study in Wawasan Open University exploring the integration of federated search engine (EBSCO Discovery Service (EDS) widget) into the learning spaces of LMS. Widgets resemble apps that enable the integration of EDS functionality in providing access for students to retrieve library learning resources from the convenience of the LMS, excluding the need to log onto the library.

This paper presents a discussion that highlights the development and conjectural implementation of a framework on the integration of the EDS widget into the University’s LMS. Data collection includes meta-analysis data from the micro- and macro-level infrastructure that make up the framework, namely, end-user layer, system layer and data management layer.

Findings from this study addressed significant importance to the library in promoting effective search and utilization of information needs. The findings will also make clear recommendations in developing effective collaborations between the library and faculties. Although the implementation of this framework is still in a developmental stage, this study still provides pertinent information in validating the integration of EDS into the University’s LMS.

While serious limitations are not anticipated, possible concerns do exist with programming algorithms in the integration of EDS into the LMS. These challenges will be reported in the paper as reference for future replications of study

One key implication is the increase in the usage of the library resources and the potential to reach a larger audience of remote library users.

The primary advantage is to minimize the need for multiple gateway login while ensuring the library to monitor relevant library databases activities throughout the system check of the LMS.

Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The purpose of this paper is to illustrate that process mining can do with events what spreadsheets can do with numbers.

The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example, the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes.

Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given.

Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, production, sales, education, and sports, process mining software can be used in a broad range of organizations.

The paper provides an original view on process mining by relating it to the spreadsheets. The value of spreadsheet-like technology tailored toward the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.