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Journal articles on the topic 'Business Process Monitoring'

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1

Santoso, Ario, and Michael Felderer. "Specification-driven predictive business process monitoring." Software and Systems Modeling 19, no. 6 (November 2, 2019): 1307–43. http://dx.doi.org/10.1007/s10270-019-00761-w.

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Abstract Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a means for properly specifying the desired prediction tasks, and a mechanism to deal with these various prediction tasks. Although there have been many studies in this area, they mostly focus on a specific prediction task. This work introduces a language for specifying the desired prediction tasks, and this language allows us to express various kinds of prediction tasks. This work also presents a mechanism for automatically creating the corresponding prediction model based on the given specification. Differently from previous studies, instead of focusing on a particular prediction task, we present an approach to deal with various prediction tasks based on the given specification of the desired prediction tasks. We also provide an implementation of the approach which is used to conduct experiments using real-life event logs.
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Kien Sia, Siew, and Boon Siong Neo. "Business process reengineering, empowerment and work monitoring." Business Process Management Journal 14, no. 5 (September 12, 2008): 609–28. http://dx.doi.org/10.1108/14637150810903020.

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Spree, Florian. "Business Process Models in the Context of Predictive Process Monitoring." Revista de Informática Teórica e Aplicada 28, no. 1 (January 19, 2021): 39–46. http://dx.doi.org/10.22456/2175-2745.106828.

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Predictive process monitoring is a subject of growing interest in academic research. As a result, an increased number of papers on this topic have been published. Due to the high complexity in this research area a wide range of different experimental setups and methods have been applied which makes it very difficult to reliably compare research results. This paper's objective is to investigate how business process models and their characteristics are used during experimental setups and how they can contribute to academic research. First, a literature review is conducted to analyze and discuss the awareness of business process models in experimental setups. Secondly, the paper discusses identified research problems and proposes the concept of a web-based business process model metric suite and the idea of ranked metrics. Through a metric suite researchers and practitioners can automatically evaluate business process model characteristics in their future work. Further, a contextualization of metrics by introducing a ranking of characteristics can potentially indicate how the outcome of experimental setups will be. Hence, the paper's work demonstrates the importance of business process models and their characteristics in the context of predictive process monitoring and proposes the concept of a tool approach and ranking to reliably evaluate business process models characteristics.
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4

Sucharittham, Nanthawadee, Choochart Haruechaiyasak, Hieu Chi Dam, and Thanaruk Theeramunkong. "Multidimensional Sentiment Cube Mining for Process Monitoring." Trends in Sciences 19, no. 9 (April 9, 2022): 3682. http://dx.doi.org/10.48048/tis.2022.3682.

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Process monitoring is essential for quality improvement because it is necessary to find the answers to which business issues need to be understood. In the era of social media, many critiques concern the business domain, including life insurance, which is one of the significant business sectors in Thailand. To utilize this useful cloud corpus for the business improvement process, we propose a novel methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining to raise usefulness with the business process model notation (BPMN). As the ability of MDC raise unlimited analysis perspectives merge with sentiment analysis (MDSC), this method can provide more sets of data for association rules mining and meet the needs to be analyzed. The cube analysis scenario, which uses association rules mining results, can reveal a significant hidden issue among aspects and sub-aspects associated under our design with their measurements. The results can be used for monitoring, which presents the customer's sentiment from social media in the real business case and identifying in the real process model. HIGHLIGHTS A methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining raise the usefulness of the business process model notation (BPMN) by utilizing the corpus for the business improvement process This method can provide more sets of data for association rules mining as the ability of MDC raise unlimited analysis perspectives to merge with sentiment analysis (MDSC) The results can monitor the customer’s sentiment from social media in the real business case and identify in the real process model GRAPHICAL ABSTRACT
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Oksanych, I., I. Shevchenko, O. Kaliuzhnyi, P. Savushkin, and V. Mizin. "ARCHITECTURE OF BUSINESS PROCESS MONITORING AND DISPATCHING SYSTEM." Transactions of Kremenchuk Mykhailo Ostrohradskyi National University 3 (June 23, 2020): 106–13. http://dx.doi.org/10.30929/1995-0519.2020.3.106-113.

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Metzger, Andreas, Philipp Leitner, Dragan Ivanovic, Eric Schmieders, Rod Franklin, Manuel Carro, Schahram Dustdar, and Klaus Pohl. "Comparing and Combining Predictive Business Process Monitoring Techniques." IEEE Transactions on Systems, Man, and Cybernetics: Systems 45, no. 2 (February 2015): 276–90. http://dx.doi.org/10.1109/tsmc.2014.2347265.

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Kang, Dongwoo, Sunjae Lee, Kwangsoo Kim, and Jae Yeol Lee. "An OWL-based semantic business process monitoring framework." Expert Systems with Applications 36, no. 4 (May 2009): 7576–80. http://dx.doi.org/10.1016/j.eswa.2008.09.027.

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Knuplesch, David, Manfred Reichert, and Akhil Kumar. "A framework for visually monitoring business process compliance." Information Systems 64 (March 2017): 381–409. http://dx.doi.org/10.1016/j.is.2016.10.006.

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Przemyslaw, Dadel, Balawajder Mariusz, Radziszowski Dominik, and Zielinski Krzysztof. "Adaptive SOA Stack-Based Business Process Monitoring Platform." Computer Science 15, no. 2 (2014): 173. http://dx.doi.org/10.7494/csci.2014.15.2.173.

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Fardbastani, Mohammad Ali, Farshad Allahdadi, and Mohsen Sharifi. "Business process monitoring via decentralized complex event processing." Enterprise Information Systems 12, no. 10 (September 22, 2018): 1257–84. http://dx.doi.org/10.1080/17517575.2018.1522453.

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Comuzzi, Marco, and Samuil Angelov. "Patterns and tools for business process monitoring customization." Service Oriented Computing and Applications 10, no. 3 (November 16, 2015): 253–71. http://dx.doi.org/10.1007/s11761-015-0185-y.

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Maamar, Zakaria, Noura Faci, Mohamed Sellami, Khouloud Boukadi, Fadwa Yahya, Ahmed Barnawi, and Sherif Sakr. "On business process monitoring using cross-flow coordination." Service Oriented Computing and Applications 11, no. 2 (March 23, 2017): 203–15. http://dx.doi.org/10.1007/s11761-017-0206-0.

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13

Amali, Lanto Ningrayati, Muhammad Rifai Katili, Sitti Suhada, and Tri Alfandra Labuga. "Business process monitoring system in supporting information technology governance." Bulletin of Electrical Engineering and Informatics 10, no. 5 (October 1, 2021): 2884–91. http://dx.doi.org/10.11591/eei.v10i5.3147.

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Information technology (IT) is essential in supporting an organization's business sustainability and growth, making it critically dependent on IT. Therefore, a focus on IT governance, consisting of leadership, organizational structure, and process ensuring that IT organization supports and expands the organizational strategies and goals is required. When the business supports the strategic significance of IT investment, the implementation of an IT strategy will lead to the adoption of an IT governance model. It will support and help the description of the benefit roles and responsibilities from IT systems and infrastructure. This paper aims to develop a business process monitoring system to support IT governance in improving user service and measuring organizational performance. The research method was the system development method with the Waterfall model. To measure the performance of the business process, the self-assessment method with performance matrix tools was applied. The study resulted in a business process monitoring system that can enhance the organization’s primary business process in services, supporting the said organization’s performance.
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Turisová, Renáta, Michal Tkáč, and Miloš Pachta. "Monitoring of process performance by means of financial indicators." Problems and Perspectives in Management 16, no. 3 (September 25, 2018): 477–87. http://dx.doi.org/10.21511/ppm.16(3).2018.38.

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The paper deals with problematic nature of measuring of process performance. It includes a designed procedure of process performance monitoring, evaluation of logistic processes quality, and also measuring of the impact of marketing activities on the profitability of process output, i.e. a product, by means of appropriate indicator.There are several performance indicators that companies use to monitor the performance of their processes and business strategies with respect to their objectives. To monitor these indicators, enterprises rely on dashboards that present one or more indicators along with contextual information to help decision makers identify deviations and their root causes. Associated benefits related to the process performance measurement system can be seen, for example, in better decision-making, flexible human resource management and process management structures. By using rolled steel sheets in a large metallurgical plant as an example, there will be shown how the performance of the rolling process can be improved by monitoring the tangible financial indicator. Subsequently, the experience was from case management companies presented to further incorporate a practical view of implementation and related issues. Finally, the reasons why the organization prefers the observed indicator during implementation of the process performance of measurement system is explored in order to understand the causes and consequences.
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Owczarek, Tomasz, and Piotr Janke. "Predictive Business Process Monitoring with Tree-based Classification Algorithms." Logistics and Transport, no. 40 (2018): 73–82. http://dx.doi.org/10.26411/83-1734-2015-4-40-10-18.

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Predictive business process monitoring is a current research area which purpose is to predict the outcome of a whole process (or an element of a process i.e. a single event or task) based on available data. In the article we explore the possibility of use of the machine learning classification algorithms based on trees (CART, C5.0, random forest and extreme gradient boosting) in order to anticipate the result of a process. We test the application of these algorithms on real world event-log data and compare it with the known approaches. Our results show that.
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16

Kang, Bokyoung, Jae‐Yoon Jung, Nam Wook Cho, and Suk‐Ho Kang. "Real‐time business process monitoring using formal concept analysis." Industrial Management & Data Systems 111, no. 5 (May 24, 2011): 652–74. http://dx.doi.org/10.1108/02635571111137241.

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Kang, Bokyoung, Dongsoo Kim, and Suk‐Ho Kang. "Periodic performance prediction for real‐time business process monitoring." Industrial Management & Data Systems 112, no. 1 (January 27, 2012): 4–23. http://dx.doi.org/10.1108/02635571211193617.

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18

Jiang, Wei, Tom Au, and Kwok-Leung Tsui. "A statistical process control approach to business activity monitoring." IIE Transactions 39, no. 3 (March 2007): 235–49. http://dx.doi.org/10.1080/07408170600743912.

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19

AlMahmoud, Abdelrahman, Maurizio Colombo, Chan Yeob Yeun, and Hassan Al Muhairi. "Secure communication protocol for real-time business process monitoring." International Journal of Internet Technology and Secured Transactions 5, no. 3 (2014): 223. http://dx.doi.org/10.1504/ijitst.2014.065183.

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Comuzzi, Marco, Irene Vanderfeesten, and Tingting Wang. "Optimized cross-organizational business process monitoring: Design and enactment." Information Sciences 244 (September 2013): 107–18. http://dx.doi.org/10.1016/j.ins.2013.04.036.

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Hao, Yong Ping, Wei Ping Shao, and Li Lun He. "Research of Workflow Modeling System for Business Process Management." Applied Mechanics and Materials 16-19 (October 2009): 219–23. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.219.

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Establish an environment-independent process flow definition for Business Process Management that can realize the common flow chart conversion with the help of flow engine. It adopts a browser-based client-side development mode to realize friendly flow user interface, and has the role-based task allocation mode and the user’s allocation-based task allocation mode, which can implement the system with the datasheet-based flow monitoring and the graphics-based flow monitoring.
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22

AIELLO, MARCO, and ALEXANDER LAZOVIK. "MONITORING ASSERTION-BASED BUSINESS PROCESSES." International Journal of Cooperative Information Systems 15, no. 03 (September 2006): 359–89. http://dx.doi.org/10.1142/s0218843006001396.

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Business processes that span organizational borders describe the interaction between multiple parties working towards a common objective. They also express business rules that govern the behavior of the process and account for expressing changes reflecting new business objectives and new market situations. We developed a service request language and support framework that allow users to formulate their requests against standard business processes.19 In this paper, we extend the approach by presenting a framework capable of automatically associating business rules with relevant processes involved in a user request. This framework plans and monitors the execution of the request and assertions against services underlying these processes. Definitions and classifications of business rules (named assertions in the paper) are given together with an assertion language for expressing them. The framework is able to handle the non-determinism typical for service-oriented computing environments and it is based on the interleaving of planning and execution. Interestingly, the language is able to express both functional and non-functional aspects of the assertions.
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Soegoto, E. S., and R. Sani. "Development of Information Technology Structural Scheme For Monitoring Business Process." IOP Conference Series: Materials Science and Engineering 407 (September 26, 2018): 012001. http://dx.doi.org/10.1088/1757-899x/407/1/012001.

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24

Dominguez, Eladio, Beatriz Perez, Angel L. Rubio, Maria A. Zapata, Juan Lavilla, and Alberto Allue. "Occurrence-Oriented Design Strategy for Developing Business Process Monitoring Systems." IEEE Transactions on Knowledge and Data Engineering 26, no. 7 (July 2014): 1749–62. http://dx.doi.org/10.1109/tkde.2013.166.

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Macedo, Julio, R. Ruiz Usano, and J. Framifiñan Torres. "A Real Time Cost Monitoring System for Business Process Reengineering." IFAC Proceedings Volumes 30, no. 1 (February 1997): 411–16. http://dx.doi.org/10.1016/s1474-6670(17)44667-2.

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Koetter, Falko, and Monika Kochanowski. "A model-driven approach for event-based business process monitoring." Information Systems and e-Business Management 13, no. 1 (January 18, 2014): 5–36. http://dx.doi.org/10.1007/s10257-014-0233-8.

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Meroni, Giovanni, Luciano Baresi, Marco Montali, and Pierluigi Plebani. "Multi-party business process compliance monitoring through IoT-enabled artifacts." Information Systems 73 (March 2018): 61–78. http://dx.doi.org/10.1016/j.is.2017.12.009.

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Di Francescomarino, Chiara, Marlon Dumas, Marco Federici, Chiara Ghidini, Fabrizio Maria Maggi, Williams Rizzi, and Luca Simonetto. "Genetic algorithms for hyperparameter optimization in predictive business process monitoring." Information Systems 74 (May 2018): 67–83. http://dx.doi.org/10.1016/j.is.2018.01.003.

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Comuzzi, Marco, Jochem Vonk, and Paul Grefen. "Measures and mechanisms for process monitoring in evolving business networks." Data & Knowledge Engineering 71, no. 1 (January 2012): 1–28. http://dx.doi.org/10.1016/j.datak.2011.07.004.

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Eldin Adam Hamza, Salah. "Monitoring and controlling design process using control charts and process sigma." Business Process Management Journal 15, no. 3 (June 5, 2009): 358–70. http://dx.doi.org/10.1108/14637150910960611.

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31

Varol, Cihan, and Henry Neumann. "Real-Time Data Quality Monitoring System for Data Cleansing." International Journal of Business Intelligence Research 3, no. 1 (January 2012): 83–93. http://dx.doi.org/10.4018/jbir.2012010106.

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To assist business intelligence companies dealing with data preparation problems, different approaches have been developed to handle the dirty data. However, these data cleansing approaches do not have real-time monitoring capabilities. Therefore, business intelligence companies and their clients are not able to predict the final outcome before running all business process. This yields an extra cost for the company if the data are highly corrupted. Therefore, to reduce cost for these types of businesses, the authors design a framework that monitors the quality attributes during the data cleansing process. Moreover, the system provides feedback to the user and allows the user to restructure the workflow based on quality attributes. The main concept of the framework is based on client-server architecture that uses multithreading to allow real-time monitoring of the process. A child thread is dedicated to run and another is dedicated to monitor the processes and give feedback to the user. The real-time monitoring system not only displays the cleansing process done on the data set, but also estimates the risk propagation probabilities in the data cleansing process. De-duplication elimination, address normalization, spelling correction for personal names, and non-ASCII character removal techniques are employed.
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Zelt, Sarah, Jan Recker, Theresa Schmiedel, and Jan vom Brocke. "A theory of contingent business process management." Business Process Management Journal 25, no. 6 (September 17, 2019): 1291–316. http://dx.doi.org/10.1108/bpmj-05-2018-0129.

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Purpose Many researchers and practitioners suggest a contingent instead of a “one size fits all” approach in business process management (BPM). The purpose of this paper is to offer a contingency theory of BPM, which proposes contingency factors relevant to the successful management of business processes and that explains how and why these contingencies impact the relationships between process management and performance. Design/methodology/approach The authors develop the theory by drawing on organizational information processing theory (OIPT) and applying an information processing (IP) perspective to the process level. Findings The premise of the model is that the process management mechanisms such as documentation, standardization or monitoring must compensate for the uncertainty and equivocality of the nature of the process that has to be managed. In turn, managing through successful adaptation is a prerequisite for process performance. Research limitations/implications The theory provides a set of testable propositions that specify the relationship between process management mechanisms and process performance. The authors also discuss implications of the new theory for further theorizing and outline empirical research strategies that can be followed to enact, evaluate and extend the theory. Practical implications The theory developed in this paper allows an alternative way to describe organizational processes and supports the derivation of context-sensitive management approaches for process documentation, standardization, monitoring, execution and coordination. Originality/value The theoretical model is novel in that it provides a contextualized view on BPM that acknowledges different types of processes and suggests different mechanisms for managing these. The authors hope the paper serves as inspiration both for further theory development as well as to empirical studies that test, refute, support or otherwise augment the arguments.
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Glykas, Michael, George Valiris, Angelika Kokkinaki, and Zoi Koutsoukou. "Banking Business Process Management Implementation." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (January 2018): 50–69. http://dx.doi.org/10.4018/ijpmat.2018010104.

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Scholars and practitioners in the fields of Business Process Management (BPM), performance measurement and business information systems tend to use different approaches for implementing BPM Programs without arguing about the quality strategy set to ensure successful implementation and adoption. This lack of quality standards makes it difficult for researchers and practitioners to build on each other's work. The purpose of this article is to present a model for a BPM Program implementation in the banking sector. The authors' four steps implementation model is based on a quality strategy monitoring the different phases of the entire procedure. Through this work, they aim to identify the key characteristics of a BPM system as well as open a debate on what are the necessary and sufficient conditions for the full implementation of a BPM Program. The authors review the relevant literature and present their BPM implementation approach. Based on their research, they presented a case study on the implementation of a BPM program in a Greek bank. Some of the subjects discussed included the integration plans for the projects, Human Resources management issues, and other concepts for the improvement of the bank's processes. The main part of the case study was the integration themes that the bank in question had identified and separated in order to produce a viable and continuous plan for the full implementation of the projects. The analysis in this paper provides an approach that researchers could use as a reference framework in their efforts for implementing BPM Programs in general and more specifically in banking sector.
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SRDIC, GREGOR, and MATJAZ B. JURIC. "MODEL FOR INTEGRATED MONITORING OF BPEL BUSINESS PROCESSES." International Journal of Cooperative Information Systems 22, no. 02 (June 2013): 1350008. http://dx.doi.org/10.1142/s0218843013500081.

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Business process execution language (BPEL) does not provide a native support for defining data and metrics, required to perform business activity monitoring (BAM). Existing industry solutions are vendor-specific while platform-independent scientific approaches separate tightly coupled monitoring definitions from the core BPEL processes into external descriptors, thus increasing the complexity of the development, packaging and deployment processes. Furthermore, existing monitoring solutions reuse platform-specific audit trail events. This requires monitor model developers to be familiar with the details of the process implementation and the custom BPEL engine meta-model. To overcome these issues, this paper presents bpelx4bam — a new approach to defining monitoring data and metrics within BPEL processes, based on BPEL extensions. The bpelx4bam promotes these definitions into the first class citizens of the BPEL specification in order to unify and fully integrate BAM into the BPM lifecycle. It enables a cross-platform migration of BAM-enabled business processes, removes the need for separate models and specifications, eases development, packaging and deployment processes, aligns the separation of concerns with actual process roles and introduces BAM-specific and optimized events. Therefore, it presents a solid ground for a future specification or a standard in this area.
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Korobeynikova, Svetlana, and Ludmila Dukanich. "PROCESS MANAGEMENT IN RUSSIAN BUSINESS EDUCATION." CBU International Conference Proceedings 1 (June 30, 2013): 188–95. http://dx.doi.org/10.12955/cbup.v1.33.

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The current management system in Russian business education is predominantly based on the principle of functional management, which in turn does not comprehensively address the emerging objectives and terms of modern-day education providers in Russia. The countries’ business schools are of the particular concern of the issue, considering the factors of their recent establishment and revenue-based financing. Presented in this paper is the outcome of implementation of the process-orientated approach to business education based on the experience of one of the leading Russian business schools. The implementation of the process-orientated approach into the management system of the business school has resulted in an array of advantages: a significant improvement in the speed of the management process; a horizontal and vertical compaction of processes due to employees making independent decisions, reduction in the number of errors, delays and alterations, an increase in the quality of tasks executed by the personnel, a decrease in the need of employee monitoring; reduction of costs associated with employee wages and equipping workplaces; development of the basis for automation of educational and supporting business processes and delegation of particular elements of business processes to external.
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Baek, Su-Jin, and Young-Jae Song. "Process Evaluation Model based on Goal-Scenario for Business Activity Monitoring." Journal of information and communication convergence engineering 9, no. 4 (August 31, 2011): 379–84. http://dx.doi.org/10.6109/jicce.2011.9.4.379.

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Kim, Min-Soo, and Young-Seok Ock. "Business Process Monitoring under Extended-GMA Environment with Complex Event Handling." Journal of the Korea Academia-Industrial cooperation Society 11, no. 6 (June 30, 2010): 2256–62. http://dx.doi.org/10.5762/kais.2010.11.6.2256.

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Proboyekti, Umi, Charoline Septa, and Budi Susanto. "Implementasi Business Process Modeling dalam Workflow Aplikasi Monitoring Electronic Data Capturer." Jurnal Terapan Teknologi Informasi 6, no. 1 (April 30, 2022): 75–82. http://dx.doi.org/10.21460/jutei.2022.61.208.

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Business Process Modeling (BPM) adalah representasi visual berbasis data untuk memodelkan alur kerja bisnis untuk mengoptimalkan proses bisnis. Notasi BPM membuat model mudah dipahami oleh semua pemangku kepentingan yang berperan dalam mengembangkan proses bisnis. Makalah ini akan menjelaskan penerapan BPM dalam alur kerja Electronic Data Capturer (EDC) Monitoring Application (EDCMA). Proses pemodelan alur kerja menggunakan perangkat lunak Bonitasoft yang mencakup pembuatan proses bisnis untuk antarmuka pengguna dan mesin proses. EDCMA merupakan proses untuk menyelesaikan permasalahan pada proses perbaikan terminal EDC dan pengajuan sebagai merchant baru. Berdasarkan prosedur manual EDCMA yang ada, model proses EDCMA yang baru menggunakan bentuk elektronik dan pemrosesan semi-otomatis yang mengimplementasikan beberapa fitur Bonitasoft BPM untuk mengembangkan prototipe aplikasi dengan ketelitian tinggi. Dalam proses evaluasi, kami mengembangkan beberapa skenario dengan pengujian data yang terjadi pada prosedur manual. Berdasarkan evaluasi, prototype telah berhasil merepresentasikan seluruh proses yang terjadi pada setiap fitur. Di masa depan, pengembangan EDCMA yang menggunakan kerangka kerja aplikasi web dan seluler akan menyediakan sistem EDCMA untuk pengguna akhir.
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Jalayer, Abdulrahman, Mohsen Kahani, Asef Pourmasoumi, and Amin Beheshti. "HAM-Net: Predictive Business Process Monitoring with a hierarchical attention mechanism." Knowledge-Based Systems 236 (January 2022): 107722. http://dx.doi.org/10.1016/j.knosys.2021.107722.

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Bauman, Yu I., and S. T. Tsaplin. "COMPARATIVE ANALYSIS OF BUSINESS PROCESS MONITORING TOOLS IN THE FINANCIAL SECTOR." Вестник Московского финансово-юридического университета, no. 3 (2021): 92–103. http://dx.doi.org/10.52210/2224669x_2021_3_92.

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Kim, Jongchan, and Marco Comuzzi. "A diagnostic framework for imbalanced classification in business process predictive monitoring." Expert Systems with Applications 184 (December 2021): 115536. http://dx.doi.org/10.1016/j.eswa.2021.115536.

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42

Barnawi, Ahmed, Ahmed Awad, Amal Elgammal, Radwa El Shawi, Abdullah Almalaise, and Sherif Sakr. "Runtime self-monitoring approach of business process compliance in cloud environments." Cluster Computing 18, no. 4 (October 13, 2015): 1503–26. http://dx.doi.org/10.1007/s10586-015-0494-0.

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Pérez-Álvarez, José Miguel, Alejandro Maté, María Teresa Gómez-López, and Juan Trujillo. "Tactical Business-Process-Decision Support based on KPIs Monitoring and Validation." Computers in Industry 102 (November 2018): 23–39. http://dx.doi.org/10.1016/j.compind.2018.08.001.

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Comuzzi, Marco. "Alignment of process compliance and monitoring requirements in dynamic business collaborations." Enterprise Information Systems 11, no. 6 (January 18, 2016): 884–908. http://dx.doi.org/10.1080/17517575.2015.1135482.

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Loreti, Daniela, Federico Chesani, Anna Ciampolini, and Paola Mello. "A distributed approach to compliance monitoring of business process event streams." Future Generation Computer Systems 82 (May 2018): 104–18. http://dx.doi.org/10.1016/j.future.2017.12.043.

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46

Shevchenko, Ihor, Denys Vasyliev, Serhii Prytchyn, and Andrii Samoilov. "Business processes monitoring based on fuzzy cognitive maps." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 3 (October 4, 2022): 110–20. http://dx.doi.org/10.32620/reks.2022.3.08.

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The subject matter of the article is a toolkit and monitoring processes of weakly structured business processes using fuzzy cognitive maps (FCMs). The goal is to create a model for monitoring and forecasting the course of business processes based on the FCMs, which provide flexibility and the ability to adapt to the conditions of changing circumstances in the process to be monitored, as well as insurance of the possibility of applying unstable FCM.s The task is to develop a formal monitoring system model; develop a computational FCM model; develop a method of using unstable FCMs: to develop a method for creating and using an FCM model. The methods used are graph modeling methods and computational experiment methods. The following results were obtained. A formal model of the system of monitoring and coordination of decisions regarding the course of business processes has been developed. A model of a weighted semantic graph was developed, which includes three types of vertices, namely, input vertices that will receive subjective evaluations of users regarding the course of the process, intermediate vertices that correspond to factors important from the perspective of the decision-maker, and final vertices that reflect integral evaluations of the quality of business process execution. A computational FCM model has been developed, which can adapt to the specifics of business logic due to the flexible adjustment of memory parameters and connections between FCM nodes. A method of using unstable FCMs has been developed. A methodology for creating and using FCMs designed for monitoring weakly structured business processes has been developed. Conclusions. The scientific novelty of the work is as follows: the model for monitoring and forecasting the course of business processes due to the use of a fuzzy cognitive map, in which the parameters of the importance and node memory and connections provide additional flexibility and the possibility of coordination and adaptation in the conditions of changing circumstances in the process to be monitored has been improved; a method of using unstable FCMs by setting limits on the values of the nodes excitation and using as a measure of excitation not only stable excitation values of FCM nodes but also the rate of growth of excitation values as an indicator of trends, which allows monitoring and forecasting the course of business processes has been proposed.
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47

Kubrak, Kateryna, Fredrik Milani, Alexander Nolte, and Marlon Dumas. "Prescriptive process monitoring: Quo vadis?" PeerJ Computer Science 8 (September 29, 2022): e1097. http://dx.doi.org/10.7717/peerj-cs.1097.

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Prescriptive process monitoring methods seek to optimize a business process by recommending interventions at runtime to prevent negative outcomes or address poorly performing cases. In recent years, various prescriptive process monitoring methods have been proposed. This article studies existing methods in this field via a systematic literature review (SLR). In order to structure the field, this article proposes a framework for characterizing prescriptive process monitoring methods according to their performance objective, performance metrics, intervention types, modeling techniques, data inputs, and intervention policies. The SLR provides insights into challenges and areas for future research that could enhance the usefulness and applicability of prescriptive process monitoring methods. This article highlights the need to validate existing and new methods in real-world settings, extend the types of interventions beyond those related to the temporal and cost perspectives, and design policies that take into account causality and second-order effects.
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Künzle, Vera, Barbara Weber, and Manfred Reichert. "Object-Aware Business Processes." International Journal of Information System Modeling and Design 2, no. 2 (April 2011): 19–46. http://dx.doi.org/10.4018/jismd.2011040102.

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Despite the increasing maturity of process management technology not all business processes are adequately supported by it. Support for unstructured and knowledge-intensive processes is missing, especially since they cannot be straight-jacketed into predefined activities. A common characteristic of these processes is the role of business objects and data as drivers for process modeling and enactment. This paper elicits fundamental requirements for effectively supporting such object-aware processes; i.e., their modeling, execution, and monitoring. Imperative, declarative, and data-driven process support approaches are evaluated and how well they support object-aware processes are investigated. A tight integration of process and data as major steps towards further maturation of process management technology is considered.
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Yanti, Yanti. "MODEL RANCANGAN SISTEM INFORMASI PROJECT MONITORING." CommIT (Communication and Information Technology) Journal 3, no. 2 (October 31, 2009): 59. http://dx.doi.org/10.21512/commit.v3i2.515.

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Economic development makes the property industry growing very rapidly. The property development is supported by the development of contractor’s company that conducts property development. Inside the contracting company doing business can not perform their own procurement because of the many items that must be provided. For the purposes of the construction company entered into an agreement with the subcontractor as vendor conduct procurement in accordance with the needs of contracting companies. To simplify the procurement process, generally conducted by a process called a tender / auction. This is done by contracting companies to get quality and price in accordance with the desired budget. The company’s commitment subcontractors as the procurement of goods to be one key to successful contracting company doing business development process. Therefore, the subcontractor companies are required to have a good commitment. Therefore we need a project monitoring system that can monitor business processes running on those sub contractor company. The purpose of this research is to design a project monitoring information system in accordance with company requirements to operational activities more effective and efficient company.Keywords: project monitoring, design model, subcontractor
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Wiratama, Jansen. "Analysis and Design of Production Monitoring Information Systems on Label Shoe Manufacturing Companies." Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika 20, no. 1 (December 2, 2022): 12–23. http://dx.doi.org/10.33751/komputasi.v20i1.6075.

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Digital technology can be used to solve problems that arise from business activity. One company that has not optimally used digital technology is PT Tiga Tapak Mutiara, which is engaged in manufacturing shoe labels. In its business process, each related division collects data, and the data collection results will be reported to the manager to unify work activities. The production data collection process has not been carried out optimally by the relevant divisions because the conventional recording is still carried out using a spreadsheet application which can slow down the reporting process to be monitored by the leadership. As a result, a slow process can impact not completing production on time. In addition to the problem of data collection, another problem is that the completion of orders received earlier is not compared to the orders received last. The aim and contribution of this research are to integrate business processes to overcome these problems in data collection, monitoring, and order completion activities. It is necessary to design a web-based monitoring information system with the Rapid Application Development (RAD) method and the application of the First In, First Out (FIFO) method so that the ordering process can run according to the time of order. The result of this research is a web-based information system that is useful for integrating business processes to monitor and optimize production activities to be completed on time. This web-based information system has also passed the functionality test using black box testing and is following the company's needs.
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