This Friday, Feb 24, 12:30h, in Pav. K16., Samaneh Bagheri presents her recent work on knowledge transfer issues in service-oriented value networks. The title and abstract are shown below.
Title: Toward understanding knowledge transfer issues within value networks from SMEs perspectives: insights from multiple case studies
Abstract: In today’s interconnected global marketplace, where customers have become increasingly knowledgeable and empowered, a customer-centric view is becoming a prominent differentiating strategy of firms. Accordingly, firms in collaboration with multiple service providers and customers, in the context of service-oriented value network (VN), strive to offer co-created integrated solutions. In this context, knowledge is regarded as a main source in integrated solution provision with the ultimate aim of enhancing the customer experience. This implies the importance of effective knowledge transfer within the context of VN. Addressing issues that might hinder effective knowledge transfer is therefore relevant. Previous research on integrated solutions has not really examined knowledge transfer issues within a VN setting (VN-KTIs). This is even scarcer when focusing on small and medium sized enterprises (SMEs) in such studies. To address these research gaps, this study aims to determine the issues that VN encounters during the knowledge transfer process from the perspective of SMEs. To do so, a multiple case study is conducted. The results of this study give us context-speciﬁc explanations on the actual issues, faced by VNs, related to the knowledge transfer process. Based on the results we identify 28 relevant issues- list in the VN-KTIs framework- hinder knowledge transfer processes within VNs from the perspective of SMEs.
Actors of a VN can apply the VN-KTIs framework as an analysis support to understand which issue will most likely inhibit knowledge transfer across a VN. Accordingly, they will be prepared to solve such issues and manage the effects of them on their knowledge transfer initiatives.
On January 27 we had an internal meeting of the Smart Mobility cluster meeting.
Due to holidays, there is no meeting Friday December 23. Next meeting is January 27.
In the next SmartMobility cluster meeting this Friday (Oct 28), 12:30-13:30h, in Pav. K16, Sander Peters will give a talk about his recently finished graduation project; see below for the abstract.
Title: Throughput time and time window estimation for business processes using historical data
Abstract: Throughput time prediction is important for companies to plan resources or provide customers with an estimated completion time of their case. In order to increase the reliability of these estimates the new developed technique generates empirical probability distributions that describe when each event in the process occurs, based upon historical data. These empirical distributions are combined into a new empirical distribution to estimate the throughput time for a certain event. Using these empirical distributions time window estimates are derived with a certain precision.
Based upon the related work in the field of throughput time prediction a gap in literature on statistical techniques for throughput time prediction is found. The gap consists of the lack of the ability to use statistical techniques to obtain time window estimates. The new technique is first evaluated on an artificially generated dataset and outperforms the existing techniques for this dataset. A case study at Van Opzeeland is performed to evaluate the new technique on processes, in which there is a single possible execution path without choices, on a real-life dataset. The throughput time estimates are about 50 percent improved compared to the existing techniques and in 70 percent of the cases the time range wherein a certain even is finished is smaller with the same precision compared to the existing techniques. In order to also handle processes in which choices can be made an extension has been developed to the new technique. This extension uses the probabilities of each variant to estimate throughput times and provide estimates for time windows. The extension has been verified on a case study using the real-life dataset from the BPI 2015 challenge. For the case study the new technique performs less well than the average value for the throughput time estimates. Also the time range is larger than the average value with a markup value added to it. This might be an issue of the technique or could be caused by the assumption that each process time of an activity is independent of the previous activities. The new technique provides statistically reliable time windows and therefore can improve, for example, resource scheduling, since reliable estimates provide indicators when a resource is needed for a specific case.
In the SmartMobility cluster meeting of Friday Sep 23, 12:30-13:30h, in Pav. K16, Mohammad Rasouli gives a talk about Process-Aware Information Systems in Support of Agility in Relief Operations; see below for the abstract.
Title: Process-Aware Information Systems in Support of Agility in Relief Operations
Abstract: Due to the rise of frequency and intensity of disasters, relief operations receive an increasing attention in recent research. Relief operations address all activities within a value chain that intends to aid people in their survival during disasters. Agility is a key characteristic in relief operations, as rapidly respond to needs is a crucial requirement to survive people during disasters. An agile relief operation should be able to rapidly handle all related demand chain a supply chain activities. More precisely, it should be able to sense expected relief services in different affected points and rapidly orchestrate relevant resources – including material, food, equipment, and rescue personnel- to provide expected services.
Shaping agility in relief operations requires handling dynamic inter-operations among different parties that collaborate within virtual organizations. This necessitates using relevant information systems that support agility by providing information and process reach and richness to manage dynamic inter-operations. Process-aware information systems (PAISs), which have been evolved to support flexibility and dynamism for business processes, can support agility in relief operations. This presentation intends to address how a PAIS can support agile relief operations.
In the SmartMobility cluster meeting of Friday May 27, 12:30-13:30h, Pav. K16, Shaya Pourmirza presents his research on GET Controller and UNICORN: Event-driven Process Execution and Monitoring in Logistics; see below for the abstract.
Especially in logistics processes, cases often interact with their real-world environment during execution. This is challenging due to the fact that events from this environment are often distributed and heterogeneous, and consequently, their import and visualization in traditional business process management systems (BPMSs) is not sufficiently supported. To address these challenges, we implemented GET Controller(http://is.ieis.tue.nl/research/getservice) and UNICORN(http://bpt.hpi.uni-potsdam.de/GETAggregationWebService) in the context of GET Service project (http://getservice-project.eu), two systems that together enable event-driven process execution and monitoring. Their application is shown for a logistics scenario.
In the SmartMobility cluster meeting of Friday Apr 22, 12:30-13:30h, in Pav. K16, Elena Tufan will present her LMS project on Service-dominant business design for the logistics service platform of Portbase; see below for the abstract.
Service-dominant business design for a logistics service platform
In the Port of Rotterdam and the other Dutch ports, coordination and exchange of logistics information take place easily via the services provided by the Port Community System of Portbase. In designing and developing solutions, Portbase deals with an ongoing change in customer requirements, technologies and systems. To keep pace with these dynamic changes, Portbase envisions making the transition in its innovation approach from a technology-push view to a customer-oriented pull view, i.e. a service-dominant business design.
The current design project helps Portbase to flexibly design and offer customer-centric solutions by using the BASE/X framework. To this end, the project analyzes the business strategy and the business services in the service-dominant context. The results of this analysis show that the current business services do not fit the business goals of Portbase. Therefore, the business service catalog and business services are redesigned enabling Portbase to operationalize service-dominant business models in service compositions. For a proper usage of the business service catalog, a user manual and an automated repository (i.e., a database) are further developed.
As a whole, the project provides Portbase a structured method for successfully implementing the service-dominant business design. From a managerial point of view, the design provides a holistic approach to align the organization capabilities with the required capabilities of the
In the SmartMobility cluster meeting of Friday Feb 26, 12:30-13:30h, in Pav. K16, Jos Trienekens leads the discussion about the attached paper by Cuenca, Boza, Ortiz, Trienekens, “Conceptual Interoperability Barriers Framework (CIBF) – A Case Study of Multi-organizational Software Development”, In Proc. ICEIS 2015, vol. 2, pp. 521 -531, 2015; see below for the abstract.
Abstract: This paper identifies conceptual barriers to enterprise interoperability and classifies them along interoperability levels of concern. The classification is based on the enterprise interoperability framework by Interop NoE and introduces the concepts of horizontal and vertical interoperability. From the initial classification a new conceptual interoperability barriers framework is proposed. The goal of the framework is to present generic conceptual barriers to interoperability and show where they are interrelated. The proposal has been validated in a case study of multi-organizational software development.
This Friday (Jan 22) Jonnro Erasmus will introduce the recently started EU project HORSE in which our group participates; see below for the abstract.
Mass customization and personalization is approaching a state where every instance of a product is different from all other instances of that same product. This variation in the product specifications clearly has manufacturing implications. It is an exceedingly laborious and expensive task to adjust manufacturing systems for different product variations. To keep cost down while reaching for more individualised products, manufacturers want to do more with less equipment and operating personnel. This dilemma represents a system optimisation problem in which the input into the process constantly changes, the service stations are not fixed and the process steps are dependant on the product requirements. TU/e is one of the 15 partners in the HORSE project, which aims to develop techologies for the smart factories of the future. Jonnro will present an overview of the project and give some detail about the role of TU/e.
[Same topic as Sep 25 meeting, since that meeting was canceled due to lack of attendance] Nov 27, 12:30h, Shaya Pourmirza will lead the discussion about a paper by Metzger et al. ” Predictive Monitoring of Heterogeneous Service-oriented Business Networks:The Transport and Logistics Case”, Service Research and Innovation Institute Global Conference, pp. 313 -322, 2012; see below for the abstract.
Future service technology will provide an unprecedented access to operational data, which opens up novel opportunities for monitoring, controlling and managing service- oriented business processes. Amongst these opportunities, we consider predictive monitoring to be a major lever for increased efficiency, effectiveness and sustainability in future business networks. Predictive monitoring means that critical events, potential deviations and unplanned situations can be anticipated and proactively managed and mitigated along the execution of business processes. This paper demonstrates the potential of predictive monitoring in practice. We focus on transport & logistics as a major industry sector — accounting for between 10% to 20% of a country’s Gross Domestic Product. Based on widely adopted standards and real operational data, we empirically support the relevance of key issues faced in that industry sector, such as late cancellations of transport bookings and delayed deliveries. As a solution, we describe the design of a novel, cloud- and services-based collaboration and integration platform. Based on this platform we develop short-term prediction capabilities allowing to proactively manage and mitigate the identified issues in the transport & logistics industry, thus promising to increase business efficiency and sustainability.