The CAiSE’24 organization calls for full papers with a special emphasis on the theme of Information Systems in the Age of Artificial Intelligence. Artificial Intelligence (AI) has emerged as a transformative technology, revolutionizing various industries, and its significance in Information Systems cannot be overstated. AI-powered systems have the potential to streamline operations, enhance decision-making processes, and drive innovation across organizations. From data analysis to automated processes, AI is reshaping the way we leverage information in the digital age. The relevance of AI in IS extends beyond internal operations. AI-powered predictive analytics enables organizations to forecast trends, anticipate customer needs, and optimize resource allocation. This empowers businesses to adapt swiftly to changing market dynamics, gain a competitive edge, and make proactive decisions. AI algorithms can also detect anomalies and patterns that indicate potential security breaches, contributing to robust cybersecurity measures in information systems. However, while acknowledging the benefits, it is essential to consider the ethical implications of AI in information systems. Ensuring data privacy, addressing bias in algorithms, and maintaining transparency are vital aspects that need to be carefully managed and regulated to foster trust and accountability.

In addition to offering an exciting scientific program, CAiSE’24 will feature a best paper award, a journal special issue, and a PhD-thesis award: 

    Best Paper Award‚ prize EUR 1000 (sponsored by Springer)
    A small selection of best papers will be invited to submit enhanced versions for consideration in a special issue of Elsevier Information Systems journal dedicated to this conference.
    PhD-Thesis Award
    Best PhD thesis of a past CAISE Doctoral Consortium author (co-sponsored by the CAiSE Steering Committee and Springer)

Papers should be submitted in PDF format. Submissions must conform to Springer‚ LNCS format and should not exceed 15 pages, including all text, figures, references, and appendices. Submissions not conforming to the LNCS format, exceeding 15 pages, or being obviously out of the scope of the conference, will be rejected without review. See the guidelines here: https://www.springer.com/comp/lncs/authors.html

The results described must be unpublished and must not be under review elsewhere. Three to five keywords characterizing the paper should be listed at the end of the abstract. Each paper will be reviewed by at least two program committee members and, if positively evaluated, by one additional program board member. The selected papers will be discussed among the paper reviewers online and during the program board meeting. As the review process is not blind, please indicate your name and affiliation on your submission. Accepted papers will be presented at CAiSE’24 and published in the Springer Lecture Notes in Computer Science (LNCS) conference proceedings. 

We invite three types of original and scientific papers. The type of submission must be indicated in the submission system. Each contribution should explicitly address the engineering or the operation of information systems, clearly identify the information systems problem addressed, the expected impact of the contribution to information system engineering or operation, and the research method used. We strongly advise authors to clearly emphasize these aspects in their paper, including the abstract. 

Technical papers describe original solutions (theoretical, methodological or conceptual) in the field of IS Engineering. A technical paper should clearly describe the situation or problem tackled, the relevant state of the art, the position or solution suggested and its potential‚ as well as demonstrate the benefits of the contribution through a rigorous evaluation.

Empirical papers evaluate existing problem situations including problems encountered in practice, or validate proposed solutions with scientific means, i.e., by empirical studies, experiments, case studies, experience reports, simulations, etc. Scientific reflection on problems and practices in industry also falls into this category. The topic of the evaluation presented in the paper as well as its causal or logical properties must be clearly stated. The research method must be sound and appropriate.

Exploratory papers describe completely new research positions or approaches, in order to face a generic situation arising because of new ICT tools, new kinds of activities, or new IS challenges. They must precisely describe the situation and demonstrate why current methods, tools, ways of reasoning, or meta-models are inadequate. They must also rigorously present their approach and demonstrate its pertinence and correctness in addressing the identified situation.