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检索条件"丛书名=Lecture Notes in Business Information Processing"

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The Role of Actors in Platform Ecosystems: A Systematic Literature Review and Comparison Across Platform Types 13th

The Role of Actors in Platform Ecosystems: A Systematic Lite...

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13th International Conference on Software business

作者： Kauschinger, Martin Schreieck, Maximilian Krcmar, Helmut Tech Univ Munich Munich Germany Univ Innsbruck Innsbruck Austria

ISBN: (纸本)9783031207051;9783031207068

The information systems literature has acknowledged the importance of external actors for the success of platform ecosystems. Thus far, these actors have either been studied on a particular platform type or have been generalized across multiple platform types. We see opportunities in scrutinizing the varying roles that actors play on platforms of different types. For instance, actors who develop third-party applications are hardly comparable to actors that sell physical goods on an electronic marketplace. We conducted a systematic literature review and compared actors and their activities across different platform types. Specifically, we analyzed 68 scientific studies and distilled five platform types: social media platforms, e-commerce platforms, sharing platforms, crowdsourcing platforms, and software platforms. Next, we analyzed the actors that engage on those platforms and found that each platform type is associated with a specific set of actors: e-commerce platforms involve sellers and buyers, sharing platforms involve lenders and borrowers, crowdsourcing platforms involve workers and crowdsourcers and software platforms involve application developers and users. On social media platforms, actors occupy a double role as prosumers. Additionally, we investigated the interactions between these actor types and found that same-side interactions are especially prevalent among application developers who share knowledge with one another. The main contribution of our study is a comparative overview on platform types, actors and activities.

关键词： Platform ecosystem Platform governance Platform typology Actor engagement Actor typology Complementor

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Bridging the Gap Between Process Mining Methodologies and Process Mining Practices Comparing Existing Process Mining Methodologies with Process Mining Practices at Local Governments and Consultancy Firms in the Netherlands

Bridging the Gap Between Process Mining Methodologies and Pr...

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20th International Conference on business Process Management (BPM) / business Process Management (BPM) Forum

作者： Zuidema-Tempel, Evelyn Effing, Robin van Hillegersberg, Jos Univ Twente Drienerlolaan5 NL-7522 NB Enschede Netherlands Sax Univ Appl Sci Handelskade 75 NL-7417 DH Deventer Netherlands Jheronimus Acad Data Sci Sint Janssingel 92 NL-5211 DA Shertogenbosch Netherlands

ISBN: (纸本)9783031161711;9783031161704

This study aims at identifying the differences and similarities between existing process mining methodologies and process mining practitioner experiences. Four existing process mining methodologies are critically reviewed and compared with process mining project elements derived from process mining practitioner experiences and available literature on process mining challenges and enablers. In total 27 interviews with process mining experts of consultancy firms and professionals at local governments have been conducted. Results show that overall existing process mining methodologies lack focus on stakeholder involvement, quantifying and selecting improvement actions, communicating quick wins and results. Also considering organizational commitment and data availability as prerequisites for process mining projects, process selection, vendor- and tool selection, acting on low familiarity with process mining is lacking in various methodologies. Finally, creating a dashboard with flexibility to include self-selected KPIs and metrics, and applying process mining on a continuous basis is considered important by interviewees while is lacking in methodologies. In future research on process mining methodologies it is recommended to take these elements into account. This is expected to give process mining practitioners guidance and support in applying process mining in organizations and stimulate the adoption of process mining in organizations.

关键词： Process mining Process mining methodology Gap analysis BPM

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Recommending Next Best Skill in Conversational Robotic Process Automation 1

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20th International Conference on business Process Management (BPM) / business Process Management (BPM) Forum

作者： Yaeli, Avi Shlomov, Segev Oved, Alon Zeltyn, Sergey Mashkif, Nir IBM Res Haifa Haifa Israel

ISBN: (数字)9783031161681

ISBN: (纸本)9783031161681;9783031161674

In recent years, Robotic Process Automation (RPA) has been widely adopted across the industry as an important enabler for business process automation and digital transformation. Recent advancements suggest that next generation RPA will require advanced humanrobot collaboration capabilities for providing a more natural conversational interface and supporting more complex automation orchestration needs. Our work focuses on the nascent field of conversational RPA bots that are able to dynamically orchestrate automation tasks through natural language. In this context, recommending possible utterances and next steps to the user is an important capability to enhance humanbot collaboration. We take an exploratory approach to the problem of next-best-skill recommendation in human-robot collaboration. We highlight key characteristics of this problem, examine existing approaches, and call out specific challenges in implementing a solution. We suggest that this problem calls for an integrated strategy for recommendation, and illustrate a possible implementation architecture that can integrate multiple recommendation strategies.

关键词： Intelligent process automation Robotic process automation Prescriptive process monitoring Multi-agent orchestration Collaborative RPA Conversational interfaces for RPA

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Exploring Gated Graph Sequence Neural Networks for Predicting Next Process Activities 5th

Exploring Gated Graph Sequence Neural Networks for Predictin...

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International Conference on business Process Management (BPM)

作者： Weinzierl, Sven Friedrich Alexander Univ Erlangen Nurnberg Inst Informat Syst Further Str 248 D-90429 Nurnberg Germany

ISBN: (纸本)9783030943431;9783030943424

A current trend in predictive business process monitoring is to construct predictive models using deep neural networks (DNNs), especially long short-term memory neural networks, convolutional neural networks, or multilayer perceptron neural networks. While these DNN types typically require data defined on the Euclidean space (e.g., grids), graph neural networks (GNNs), a relatively new type of DNNs, can compute data defined on the non-Euclidean space (e.g., graphs). Because GNNs can directly compute graph-oriented data inputs, generally structured into nodes and edges, they can explicitly model event relationships. This paper investigates gated graph sequence neural networks (GGNNs) for the next activity prediction. First results with two real-life event logs show that GGNNs can outperform traditional DNNs regarding predictive quality, especially if nodes of an input graph are assumed as events, and the graph's adjacency matrix only describes event relationships of a process instance prefix.

关键词： Predictive business process monitoring Graph neural networks Deep learning Machine learning

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Requirements Engineering for Collaborative Artificial Intelligence Systems: A Literature Survey 16th

Requirements Engineering for Collaborative Artificial Intell...

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16th International Conference on Research Challenges in information Sciences (RCIS)

作者： Odong, Lawrence Araa Perini, Anna Susi, Angelo Univ Trento Via Calepina 14 I-38122 Trento TN Italy Fdn Bruno Kessler Trento Italy

ISBN: (纸本)9783031057601;9783031057595

Artificial Intelligence (AI) systems are pervasively exploited to manipulate large sets of data, support data-driven decisions, as well as to replace or collaborate with humans in performing boring tasks that require high level precision. Awareness of the need of engineering approaches that align with ethical principles is increasing and motivates attention by diverse research communities, such as AI research and Software Engineering research communities. In our research, we focus on Requirements Engineering (RE) for Collaborative Artificial Intelligence Systems (CAIS), such as robot arms that collaborate with human operators to perform repetitive and tiring tasks. A systematic literature review was conducted to assess the state of research, which resulted in the analysis of 41 research publications. Among the main findings, a set of challenges pointed out by researchers, such as the lack of a well-structured definition for CAIS requirements and the inadequacy of current standards. A discussion of these challenges and of recommendations for addressing them is proposed, taking into account similar results from recent related work. Similarly, the requirements types mentioned in the analysed literature are analysed according to categories proposed in related work.

关键词： Collaborative Artificial Intelligence Systems Requirements Engineering Machine learning Collaborative robots

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On the Systematic Analysis of Process Landscape Method Implementation Using Grounded Theory 5th

On the Systematic Analysis of Process Landscape Method Imple...

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International Conference on business Process Management (BPM)

作者： Gonzalez-Lopez, Fernanda Munoz-Gama, Jorge Fabia, Paolo Jara, Alberto Pontificia Univ Catolica Chile Santiago Chile

ISBN: (纸本)9783030943431;9783030943424

Process Landscapes are critical elements towards the systematic management of a process portfolio, representing its process architecture from a high-level perspective. Consequently, a wide range of methods to generate Process Landscapes is available in the literature, whose effectiveness has been extensively validated, mostly through case studies. However, little is known or reported about the implementation of landscape methods with the human team, e.g. facilitators, common pitfalls, or lessons learned. To fill this research gap, this article proposes the Landscape Method Implementation Grounded Theory based evaluation (LanMI-GT) procedure for the systematic analysis of a landscape method implementation through Grounded Theory. This was generated using a Design Science Research approach. The contribution of this work is twofold. First, the proposed procedure would enable practitioners to systematically analyze the implementation with a human team of a specific landscape method. Second, the procedure is demonstrated by analyzing a well-known Process Landscape Method in a real context, and the findings thereof are discussed in the paper.

关键词： Process Landscape Modeling Grounded Theory business Process Management Socio-technical Context

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The Use of Mixed-Reality Sport Platforms in Social Media Sentiment Analysis during COVID-19 21st

The Use of Mixed-Reality Sport Platforms in Social Media Sen...

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21st International Conference on Perspectives in business Informatics Research (BIR) - business Informatics for Sustainable Innovation

作者： Domok, Laszlo Fodor, Szabina Corvinus Univ Budapest Fovam Ter 13-15 H-1093 Budapest Hungary

ISBN: (纸本)9783031169465;9783031169472

Sport and physical activity are very closely related to people's health. The COVID-19 pandemic has made everyone aware of the importance of maintaining regular physical activity. The lockdowns and mandatory social distancing experienced during the epidemic underlined the importance of new sports platforms that bring traditional sports, such as cycling, to the virtual world. This work focuses on the ZWIFT cycling application as an exemplary mixed-reality sport platform. Sentiment analysis (or opinion mining) aims to explore the emotions behind the opinions expressed in texts on different topics. We used sentiment analysis of social media platforms (Twitter and Reddit) to provide valuable information on the culture surrounding mixed reality sports platforms.

关键词： Mixed reality Virtual sports Sentiment analysis Social network COVID-19

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Analysis of the Structure of Germany's Energy Sector with Self-organizing Kohonen Maps 24th

Analysis of the Structure of Germany's Energy Sector with Se...

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24th International Conference on business information Systems (BIS)

作者： Potapenko, Irina Kukartsev, Vladislav Tynchenko, Vadim Mikhalev, Anton Ershova, Evgeniia Reshetnev Siberian State Univ Sci & Technol Krasnoyarsk Russia Siberian Fed Univ Krasnoyarsk Russia Russian Acad Sci Inst Marine Hydrophys Sevastopol Russia

ISBN: (纸本)9783031042164;9783031042157

The purpose of the research in this article is to analyze the structure of energy in Germany and compare the obtained data with events occurring in the country and the world. The article reviews the world energy sector and considers the rating of regions by gross energy production. The analysis helps to identify the leading regions in terms of energy production: Asia and Oceania, North America and Europe. The German economy and energy sector were considered, as well as the development of nuclear power in particular and the gradual abandonment from nuclear power plants because of the occurred radiation accidents in the world. It also describes the relevance of data analysis in the energy sector, especially in working with renewable energy sources due to their instability and unpredictability. Using self-organizing Kohonen maps, the data on German energy indicators was analyzed. Basing on the analysis it was concluded that these maps correspond to the changes in the energy policy of Germany.

关键词： Energy Germany Kohonen maps Neural networks Intellectual analysis Clustering

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Process Mining for Process Improvement - An Evaluation of Analysis Practices 16th

Process Mining for Process Improvement - An Evaluation of An...

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16th International Conference on Research Challenges in information Sciences (RCIS)

作者： Kubrak, Kateryna Milani, Fredrik Nolte, Alexander Univ Tartu Tartu Estonia Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9783031057601;9783031057595

Organizations have a vital interest in continuously improving their business processes. Process analysts can use process mining tools that provide data-driven discovery and analysis of business processes to achieve this. Current research has mainly focused on creating and evaluating new tools or reporting process mining case studies from different domains. Although usage of process mining has increased in industry, insights into how analysts work with such methods to identify improvement opportunities have consequently been limited. To reduce this gap, we conducted an exploratory interview study of seven process analysts from different domains. Our findings indicate that process analysts assess improvement opportunities by their impact, the feasibility of required implementation, and stakeholders' input. Furthermore, our results indicate that process mining tools, when used to identify improvement opportunities, do not provide sufficient support for analysis, requiring process analysts to use additional tools. Lastly, analysts use storytelling to frame and communicate their findings to various stakeholders.

关键词： Process mining business process analysis business process improvement

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Adaptive Enterprise Architecture: Complexity Metrics in a Mixed Evaluation Method 23rd

Adaptive Enterprise Architecture: Complexity Metrics in a Mi...

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23rd International Conference on Enterprise information Systems (ICEIS)

作者： Daoudi, Wissal Doumi, Karim Kjiri, Laila ENSIAS Mohammed V Univ Rabat AlQualsadi Team Rabat Morocco

ISBN: (纸本)9783031089657;9783031089640

Classically, enterprises future is intertwined with the needs and demands of society. Nowadays, in addition to those two elements, challenges are becoming more and more numerous and unavoidable. Saying a few, global warming, social responsibilities, Covid 19, digital transformation. We are living in a new era that is highly volatile and unpredictable. We don't have anymore the privilege to choose threats and opportunities that we want to adapt to. In fact adaptation becomes a necessity to survive in this highly competitive and dynamic environment. Factors coming from those challenges externally on top of internal ones can impact various parts of the enterprise in the form of changes. Thus, Adaptive Enterprise Architecture (EA) is leveraged to assist the continuous adaptation to the evolving transformation. On the other hand, one of the criteria of Adaptive EA is the ability to monitor and control the complexity of changes. In this paper, we suggest a mixed approach of EA complexity measurement based on quantitative and qualitative analysis. First, we begin with a recap of the criteria shaping our Adaptive Enterprise Architecture approach and we give an overview of the model that we worked on in previous work. Then we investigate related work about complexity and subjective measurement. Finally, we describe our mixed approach of assessment of complexity and we focus on the calculation of some objective and subjective metrics.

关键词： Adaptation Complexity Dynamic environments Enterprise architecture

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