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

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Predicting Startup Success Through a New Graph Convolutional Neural Network Approach 23rd

Predicting Startup Success Through a New Graph Convolutional...

引用

23rd Wuhan International Conference on E-business (WHICEB)

作者： Zhang, Yue Tang, Xiaoyi Yang, Hu Cent Univ Finance & Econ Sch Informat Beijing 100098 Peoples R China

ISBN: (纸本)9783031603266;9783031603242

Venture capital (VC) is a high-risk, high-return capital injection for emerging or small and medium-sized enterprises with growth potential. Accurately predicting the success of startup is critical for venture capital institutions. Previous studies have used data-driven approaches to explore the many factors that influence startup success, but have often failed to delve deeper into the heterogeneous topological information in investment relationships. In fact, graph convolutional neural networks have been shown to be effective for binary classification problems. In this paper, to model the relational embedding of co-investment networks and investment relationship networks, a novel graph convolutional neural network approach, named VC-HGCN, is employed to effectively capture the complex interactions in investment networks by integrating the learned node attributes and network topology information. The results show that VC-HGCN performs better in predicting startup success compared to the benchmark model, and also demonstrates the value of using the two investment networks in combination. Our study improves the accuracy of startup success prediction and provides a powerful tool for venture capitalists to find high-potential startups.

关键词： Venture Capital Prediction Graph Neural Networks Startups

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Towards Model-driven Enhancement of Safety in Healthcare Robot Interactions 23rd

Towards Model-driven Enhancement of Safety in Healthcare Rob...

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23rd International Conference on Perspectives in business Informatics Research (BIR)

作者： Koutsopoulos, Georgios Ioannidou, Penelope Matsopoulos, George K. Koutsouris, Dimitrios D. Stockholm Univ Dept Comp & Syst Sci Borgarfjordsgatan 12 S-16407 Stockholm Sweden Natl Tech Univ Athens Sch Elect & Comp Engn Biomed Engn Lab Heroon Polytech 9 Athens 15780 Greece

ISBN: (纸本)9783031713323;9783031713330

In the continuously evolving landscape of healthcare technology, the evolution of robotics has revolutionized awide spectrum of services. This situation created a variety of opportunities and challenges. One of the main challenges concerns the interaction of robots with human users and other robots, along with the safety aspect of such interactions. The current paper introduces a project aiming to tackle this challenge, initially via a literature review aiming to explore and structure the domain of robotic interactions in healthcare. Subsequently, the results are conceptualized in a domain meta-model, aiming to establish the foundation for an information system, based on a multi-view modeling approach, with the capabilities to support by documenting and facilitating safer interactions between healthcare robots and external agents. The current study focuses on the safety viewpoint of robotic interaction. The developed model is suitable for initiating the development of the abovementioned system that will use multi-view modeling principles. It is demonstrated in a use case derived from the associated ENDORSE EU project.

关键词： Healthcare robot Multi-view modeling Instantiation Interaction Communication Collaboration Safety

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How Do Token Rewards Motivate User-Generated Content? Token Price Volatility and Peer Contribution Moderate the Effects of Token Rewards 23rd

How Do Token Rewards Motivate User-Generated Content? Token ...

引用

23rd Wuhan International Conference on E-business (WHICEB)

作者： Tang, Hongting Yao, Jiachuan Zhang, Yanlin Guangdong Univ Technol Sch Management Guangzhou 510520 Guangdong Peoples R China

ISBN: (纸本)9783031602634;9783031602641

This article elucidates the role of token rewards in influencing user contributions, proposing that token rewards can engender incentivizing effects on user contributions. Furthermore, it delves into the moderating effects of token price volatility and peer contribution on the relationship between token rewards and user contributions. Empirical research utilizing real data from Steemit is employed in this study. The results indicate that token rewards positively impact both the quantity and quality of user-generated content. Moreover, token price volatility positively/negatively moderates the positive effects of token rewards on the quantity/quality of user-generated content. Peer contribution negatively moderates the incentivizing effects of token rewards on user contributions. This article expands our understanding of blockchain-based online communities and provides management insights for such communities.

关键词： User-generated content Blockchain Token rewards Price volatility Peer contribution

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Model-Independent Error Bound Estimation for Conformance Checking Approximation

Model-Independent Error Bound Estimation for Conformance Che...

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21st International Conference on business Process Management (BPM)

作者： Sani, Mohammadreza Fani Kabierski, Martin van Zelst, Sebastiaan J. van der Aalst, Wil M. P. Rhein Westfal TH Aachen Proc & Data Sci Chair Aachen Germany Microsoft Dev Ctr Copenhagen Copenhagen Denmark Humboldt Univ Dept Comp Sci Berlin Germany Fraunhofer FIT St Augustin Germany

ISBN: (纸本)9783031509735;9783031509742

Conformance checking techniques quantify correspondence between a process's execution and a reference process model using event data. Alignments, used for conformance statistics, are computationally expensive for complex models and large datasets. Recent studies show accurate approximations can be achieved by selecting subsets of model behavior. This paper presents a novel approach deriving error bounds for conformance checking approximation based on arbitrary activity sequences. The proposed approach allows for the selection of relevant subsets for improved accuracy. Experimental evaluations validate its effectiveness, demonstrating enhanced accuracy compared to traditional alignment methods.

关键词： Process mining Conformance checking approximation Alignments Edit distance Instance selection Sampling

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Monitoring Value Chains of Organic Beverages

Monitoring Value Chains of Organic Beverages

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Enterprise Design, Operations, and Computing (EDOC) Forum / IDAMS Workshop / SoEA4EE Workshop / IRESEARCH Workshop / MIDas4CS Workshop

作者： Santos, Hugo D. Silva, Patricio de A. Cintra, Marcos E. Mendes Neto, Francisco M. Bukhsh, Faiza A. Fed Univ Semiarid Mossoro RN Brazil Fed Univ Espirito Santos Sao Mateus ES Brazil Univ Twente Enschede Netherlands

ISBN: (纸本)9783031547119;9783031547126

The outflow of manufactured organic products needs to prevent damage to the goods. There are specifications of models of value networks with blockchain services for monitoring transactions. This paper general objective is to provide strategic models to monitor supply chains of organic beverages. The design of this network was based on the Design Science methodology, including the process of investigating the problem, proposing an artifact to tackle it, and validating its construction. A systematic literature review was made and strategic models were proposed to monitor networks with blockchain with validation by empiric evaluation and assessment with a selected company for a single case study. To construct the models, information obtained with the literature review was used, as well as information provided by the company via meetings and surveys. In the design, the e3 value editor tool of the e 3 value framework was used. Three models were produced based on these scenarios: regional, national and international. The models were validated and positively assessed by the participating company, which answered a survey to assess the proposal according to their needs and the feasibility of implementing that technology.

关键词： Preventive Monitoring Food Supply Chain Blockchain technology Value Networks

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Selling in Prompt Marketplace: An Empirical Study on the Joint Effects of Linguistic and Demonstration Signals on Prompt Sales 23rd

Selling in Prompt Marketplace: An Empirical Study on the Joi...

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23rd Wuhan International Conference on E-business (WHICEB)

作者： Cao, Cuicui Zhao, Ling Li, Yuni Xie, Chongyang Hubei Univ Econ Wuhan 430205 Peoples R China Huazhong Univ Sci & Technol Wuhan 430074 Peoples R China China Univ Geosci Wuhan Wuhan 430074 Peoples R China

ISBN: (纸本)9783031602597;9783031602603

The proliferation of generative artificial intelligence (GAI) spawns a new type of freelance digital platform: prompt marketplace, on which prompt engineers upload their prompts and sell them to potential buyers. As only freelancers themselves know about the prompt in detail and they can only provide limited textual information, great information asymmetry exists that may hinder exchange. Besides, one distinct feature of prompt marketplace is that prompt engineers can display part of their prompt to potential buyers. Thus, drawing on the signaling theory, this study investigates the joint effects of linguistic and demonstration signals on prompt sales. Data from 16,890 prompts were collected and analyzed. Results show that linguistic signals and their interaction with demonstration signals significantly influence prompt sales. Interestingly, we found the negative direct influence of demonstration signals on prompt sales. Our study has theoretical contributions to freelance digital platform literature and extends signaling theory to prompt marketplace. This study can also provide practical suggestions to platforms and freelancers alike.

关键词： Prompt Engineering Prompt Sales informational Signal Affective Signal Demonstration Signal

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EA ModelSet - A FAIR Dataset for Machine Learning in Enterprise Modeling 16th

EA ModelSet - A FAIR Dataset for Machine Learning in Enterpr...

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16th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM) - Enterprise Modeling in the Circular Economy

作者： Glaser, Philipp-Lorenz Sallinger, Emanuel Bork, Dominik TU Wien Business Informat Grp Vienna Austria TU Wien Database & Artificial Intelligence Grp Vienna Austria

ISBN: (纸本)9783031485824;9783031485831

The conceptual modeling community and its subdivisions of enterprise modeling are increasingly investigating the potentials of applying artificial intelligence, in particularmachine learning (ML), to tasks like model creation, model analysis, and model processing. A prerequisiteand currently a limiting factor for the community-to conduct research involving ML is the scarcity of openly available models of adequate quality and quantity. With the paper at hand, we aim to tackle this limitation by introducing an EA ModelSet, i.e., a curated and FAIR repository of enterprise architecture models that can be used by the community. We report on our efforts in building this data set and elaborate on the possibilities of conducting ML-based modeling research with it. We hope this paper sparks a community effort toward the development of a FAIR, large model set that enables ML research with conceptual models.

关键词： Enterprise modeling Machine learning FAIR Enterprise architecture Data set

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Backer Preference Modeling and Prediction of Crowdfunding Campaign Success 1

引用

23rd Wuhan International Conference on E-business (WHICEB)

作者： Feng, Sijia Wang, Nianxin Qiu, Yan Jiangsu Univ Sci & Technol Zhenjiang 212100 Jiangsu Peoples R China

ISBN: (数字)9783031602603

ISBN: (纸本)9783031602597;9783031602603

Crowdfunding market has witnessed rapid growth;however, the overall success rate remains relatively low. Therefore, predicting crowdfunding success has garnered significant attention, offering benefits for backers, platforms, and campaign creators in terms of risk reduction and optimized resource allocation. Departing from the traditional campaign-centric perspective, we proposed a novel backer-centric approach for predicting crowdfunding success: Modeling backer preference based on their pledge history and aggregating preference of active backers within categories for predicting crowdfunding success. To validate the performance of this approach, we identified backers who participated in the discussion of recently popular campaigns on Indiegogo platform. A total of 7895 backers were captured along with the 91299 campaigns they either followed or contributed to. Additionally, we gathered 73581 campaigns for training and testing predictive models. Results indicate that considering backer preferences significantly enhances that accuracy of crowdfunding success prediction models. Further, we observed that modeling backer preferences based on higher activity level can further enhance the performance of the predictive model.

关键词： Crowdfunding Backers' Preference Success Prediction

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Bridging Technostress and Perceived Value: Why Middle-Aged and Elderly People Resist Using Chronic Diseases Management Apps 1

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23rd Wuhan International Conference on E-business (WHICEB)

作者： Zhao, Ying Liao, Hongyu Zhou, Liang Sichuan Univ Sch Publ Adm Chengdu 610065 Peoples R China North China Inst Sci & Technol Sch Econ & Management Langfang 065201 Peoples R China

ISBN: (数字)9783031602641

ISBN: (纸本)9783031602634;9783031602641

This paper aims to explore the causes of resistance to using chronic disease management APPs in middle-aged and elderly people. By integrating technostress theory and status quo bias (SQB) theory, a conceptual model was proposed to explore the resistance of information system users. A total of 290 questionnaires were collected in the middle-aged and elderly population, and the CB-Structural Equation Model was used to test the hypotheses. We found that both technology anxiety and perceived value can directly affect the resistance intention, while technology anxiety can also indirectly affect the resistance intention by significantly affecting the perceived value. We also found that switching cost has no significant impact on perceived value. The paramount contribution is the combination of technostress theory and the status quo bias theory in the study of system resistance intention and the in-depth discussion of the functional relationship between the two.

关键词： Chronic diseases elderly Resistance intention Technology anxiety Perceived value

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A Human-Computer Automated Negotiation Model Based on Opponent's Emotion and Familiarity 23rd

A Human-Computer Automated Negotiation Model Based on Oppone...

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23rd Wuhan International Conference on E-business (WHICEB)

作者： Cao, Mukun Xian, Lei Xiamen Univ Siming South Rd 422 Xiamen 361005 Peoples R China

ISBN: (纸本)9783031602634;9783031602641

In e-commerce transactions, agent-based automated negotiation systems combine the advantages of artificial intelligence and bring great convenience to enterprises. However, few studies in agent-based model have considered the social characteristics of human interactions. In this paper, we propose a model with opponent's emotion and familiarity. Also use a capsule network to predict the type of an opponent based on bidding. We use opponent type, emotion, and familiarity as inputs to the improved TD3 to predict opponent' next round bidding. Through comparative experiments, our proposed model achieves better results in the transaction price, seller's utility, satisfaction, negotiation process and the negotiation rounds.

关键词： Online Transaction Emotion Familiarity Negotiation

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