Towards a method and a guiding tool for conducting process mining projects

Due to the increased use of information systems by organizations, information on the execution of processes is recorded. This enables using process mining as a tool for improving process performance. Process mining allows gaining insights regarding actual processes by extracting and processing data from existing systems. Many projects have been conducted for process discovery, conformance checking, etc. Despite of the existence of general methods for data analysis, there’s a lack of specific methods to support process mining projects. Thus, completions of such projects are often dependent on expertise of the analysts. This paper presents a detailed method for conducting process mining projects and a tool for supporting its execution and retaining the outcomes of each step. A case is analysed for evaluating them. Organizations seeking process performance improvement can get benefit from a method that states how process mining techniques can be used in process mining projects

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Four Shades of Customer: How Value Flows in Fintech Ecosystems

The financial sector is undergoing a massive transformation, with new technology-driven players challenging established mechanisms and transforming the sector into a fast-moving market. With the gradual transition from a scale economy to a platform-driven network economy, enterprise networks are gaining strategic importance. Despite the growing interest in fintech’s, research has so far lacked a conceptualization of value creation in fintech ecosystems. Therefore, this research paper aims to analyze key players, value creation activities, and value streams based on the analysis of the business models of payment services, personal financial management, robo-advisory, peer-to-peer lending, trading, and cryptocurrency. We present a holistic value network for the fintech ecosystem based on structured literature review and analysis of 171 fintech companies. We were able to show that fintech platform orchestrates multiple market sides and that customers take four distinct roles at the center of the ecosystem when using fintech services

Does Canada Have a Problem with Occupational Fraud?

Small and medium-sized enterprises (SMEs) are an important collective force in the Canadian economy, however the visibility and economic power of small businesses suffer due to their size and frequent turnover. When it comes to the issue of businesses being subject to occupational fraud, the moderate visibility of SMEs only contributes to the challenge of assessing the real scope of the problem. This paper seeks to examine the prevalence and types of occupational fraud experienced by Canadian SMEs as well as gathers information on prevention and detection methods used to safeguard against occupational fraud. That is done based on data compiled from a survey of 802 SMEs across Canada. The analysis shows that a substantial proportion of SMEs experience incidents of occupational fraud; however, the majority of SMEs are not fully prepared to respond to fraud. Furthermore, SMEs’ experience with and attitudes toward fraud vary noticeably with company characteristics, although a large proportion of SMEs believe risk to occupational fraud is low.Occupational fraud, fraud prevention, fraud detection, types of occupational fraud, Canadian small and medium businesses, employee fraud, internal fraud

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

[EN] The study presents some results of customer paths¿ analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men¿s bathroom or women¿s bathroom. Since the study has a comprehensive scope, we focused on male and female customers¿ behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.Dogan, O.; Bayo-Monton, JL.; Fernández Llatas, C.; Oztaysi, B. (2019). Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application. Sensors. 19(3):1-20. https://doi.org/10.3390/s19030557S120193Oosterlinck, D., Benoit, D. F., Baecke, P., & Van de Weghe, N. (2017). Bluetooth tracking of humans in an indoor environment: An application to shopping mall visits. Applied Geography, 78, 55-65. doi:10.1016/j.apgeog.2016.11.005Merad, D., Aziz, K.-E., Iguernaissi, R., Fertil, B., & Drap, P. (2016). Tracking multiple persons under partial and global occlusions: Application to customers’ behavior analysis. Pattern Recognition Letters, 81, 11-20. doi:10.1016/j.patrec.2016.04.011Wu, Y., Wang, H.-C., Chang, L.-C., & Chou, S.-C. (2015). Customer’s Flow Analysis in Physical Retail Store. Procedia Manufacturing, 3, 3506-3513. doi:10.1016/j.promfg.2015.07.672Dogan, O., & Öztaysi, B. (2018). In-store behavioral analytics technology selection using fuzzy decision making. Journal of Enterprise Information Management, 31(4), 612-630. doi:10.1108/jeim-02-2018-0035Hwang, I., & Jang, Y. J. (2017). Process Mining to Discover Shoppers’ Pathways at a Fashion Retail Store Using a WiFi-Base Indoor Positioning System. IEEE Transactions on Automation Science and Engineering, 14(4), 1786-1792. doi:10.1109/tase.2017.2692961Abedi, N., Bhaskar, A., Chung, E., & Miska, M. (2015). Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses. Transportation Research Part C: Emerging Technologies, 60, 124-141. doi:10.1016/j.trc.2015.08.010Mou, S., Robb, D. J., & DeHoratius, N. (2018). Retail store operations: Literature review and research directions. 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An Analysis of Visitors’ Behavior in the Louvre Museum: A Study Using Bluetooth Data. Environment and Planning B: Planning and Design, 41(6), 1113-1131. doi:10.1068/b130047pDe Leoni, M., van der Aalst, W. M. P., & Dees, M. (2016). A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs. Information Systems, 56, 235-257. doi:10.1016/j.is.2015.07.003Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Arroyo, R., Yebes, J. J., Bergasa, L. M., Daza, I. G., & Almazán, J. (2015). Expert video-surveillance system for real-time detection of suspicious behaviors in shopping malls. Expert Systems with Applications, 42(21), 7991-8005. doi:10.1016/j.eswa.2015.06.016Popa, M. C., Rothkrantz, L. J. M., Shan, C., Gritti, T., & Wiggers, P. (2013). Semantic assessment of shopping behavior using trajectories, shopping related actions, and context information. Pattern Recognition Letters, 34(7), 809-819. doi:10.1016/j.patrec.2012.04.015Kang, L., & Hansen, M. (2017). Behavioral analysis of airline scheduled block time adjustment. Transportation Research Part E: Logistics and Transportation Review, 103, 56-68. doi:10.1016/j.tre.2017.04.004Rovani, M., Maggi, F. M., de Leoni, M., & van der Aalst, W. M. P. (2015). Declarative process mining in healthcare. Expert Systems with Applications, 42(23), 9236-9251. doi:10.1016/j.eswa.2015.07.040Fernández-Llatas, C., Benedi, J.-M., García-Gómez, J., & Traver, V. (2013). Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes. Sensors, 13(11), 15434-15451. doi:10.3390/s131115434Van der Aalst, W. M. P., Reijers, H. A., Weijters, A. J. M. M., van Dongen, B. F., Alves de Medeiros, A. K., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732. doi:10.1016/j.is.2006.05.003M. Valle, A., A.P. Santos, E., & R. Loures, E. (2017). Applying process mining techniques in software process appraisals. Information and Software Technology, 87, 19-31. doi:10.1016/j.infsof.2017.01.004Juhaňák, L., Zounek, J., & Rohlíková, L. (2019). Using process mining to analyze students’ quiz-taking behavior patterns in a learning management system. Computers in Human Behavior, 92, 496-506. doi:10.1016/j.chb.2017.12.015Sedrakyan, G., De Weerdt, J., & Snoeck, M. (2016). Process-mining enabled feedback: «Tell me what I did wrong» vs. «tell me how to do it right». Computers in Human Behavior, 57, 352-376. doi:10.1016/j.chb.2015.12.040Schoor, C., & Bannert, M. (2012). Exploring regulatory processes during a computer-supported collaborative learning task using process mining. 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The Value of Integrated Information Systems for U.S. General Hospitals

Each year, huge investments into healthcare information systems (HIS) are being made all over the world. Despite the enormous cost for the hospitals, the overall benefits and costs of the healthcare information systems have not been deeply assessed. In recent years, much previous research has investigated the link between the implementation of Information Systems and the performance of organizations. Although the value of Healthcare Information System or Healthcare Information Technology (HIS/HIT) has been found in many studies, some questions remain unclear. Do HIS/HIT systems influence different hospitals the same way? How to understand and explain the mechanism that HIS/HIT improves the performance of hospitals? To address these questions, our research will: 1) Identify the bottlenecks of the current healthcare system which affects the operation efficiency (mismatch between demand and service provided); 2) Adopt the institutional theory to explain the process of implementing HIS/HIT and the possible outcomes; 3) Conduct an empirical study, to expose issues of current healthcare system and the value of the HIS/HIT, and to identify the factors that affect the performance of different hospitals; and 4) Design a decision support system for hospitals. Based on institutional theory, we explain the empirical findings from 2014 HIMSS database. To solve the mismatch between the patient needs and doctor’s schedule, we will propose a business model for a new integrated information management system. It gives the physicians and patients a comprehensive picture needed to understand the type of different patients. A classification schema will be designed to provide recommendations for scheduling decision, and it is supported by the interactive system

Policy analysis and policy analytics

Working from a description of what policy analysis entails, we review the emergence of the recent field of analytics and how it may impact public policy making. In particular, we seek to expose current applications of, and future possibilities for, new analytic methods that can be used to support public policy problem-solving and decision processes, which we term policy analytics. We then review key contributions to this special volume, which seek to support policy making or delivery in the areas of energy planning, urban transportation planning, medical emergency planning, healthcare, social services, national security, defence, government finance allocation, understanding public opinion, and fire and police services. An identified challenge, which is specific to policy analytics, is to recognize that public sector applications must balance the need for robust and convincing analysis with the need for satisfying legitimate public expectations about transparency and opportunities for participation. This opens up a range of forms of analysis relevant to public policy distinct from those most common in business, including those that can support democratization and mediation of value conflicts within policy processes. We conclude by identifying some potential research and development issues for the emerging field of policy analytics