Workflow Management Systems and ERP Systems: Differences, Commonalities, and Applications

Two important classes of information systems, Workflow Management Systems(WfMSs) and Enterprise Resource Planning (ERP) systems, have been used to support e-business process redesign, integration, and management. While both technologies can help with business process automation, data transfer, and information sharing, the technological approach and features of solutions provided by WfMS and ERP are different. Currently, there is a lack of understanding of these two classes of information systems in the industry and academia, thus hindering their effective applications. In this paper, we present a comprehensive comparison between these two classes of systems. We discuss how the two types of systems can be used independently or together to develop intra- and inter-organizational application solutions. In particular, we also explore the roles of WfMS and ERP in the next generation of IT architecture based on web services. Our findings should help businesses make better decisions in the adoption of both WfMS and ERP in their e-business strategies

A survey on context awareness in big data analytics for business applications

The concept of context awareness has been in existence since the 1990s. Though initially applied exclusively in computer science, over time it has increasingly been adopted by many different application domains such as business, health and military. Contexts change continuously because of objective reasons, such as economic situation, political matter and social issues. The adoption of big data analytics by businesses is facilitating such change at an even faster rate in much complicated ways. The potential benefits of embedding contextual information into an application are already evidenced by the improved outcomes of the existing context-aware methods in those applications. Since big data is growing very rapidly, context awareness in big data analytics has become more important and timely because of its proven efficiency in big data understanding and preparation, contributing to extracting the more and accurate value of big data. Many surveys have been published on context-based methods such as context modelling and reasoning, workflow adaptations, computational intelligence techniques and mobile ubiquitous systems. However, to our knowledge, no survey of context-aware methods on big data analytics for business applications supported by enterprise level software has been published to date. To bridge this research gap, in this paper first, we present a definition of context, its modelling and evaluation techniques, and highlight the importance of contextual information for big data analytics. Second, the works in three key business application areas that are context-aware and/or exploit big data analytics have been thoroughly reviewed. Finally, the paper concludes by highlighting a number of contemporary research challenges, including issues concerning modelling, managing and applying business contexts to big data analytics. © 2020, Springer-Verlag London Ltd., part of Springer Nature

The Impact of EHR Usability Issues on the Perceived Efficiency of Non-Clinical Hospital-Based EHR Users

A survey-based study of the impact of the EHR systems usability issues on the perceived efficiency of work among non-clinical users in the hospital settings was performed June 20th to July 24th 2015. There were 160 valid responses. The results were processed in SPSS (IBM statistical application) and I determined the usability dimensions with the greatest impact on efficiency, for all EHRs and for the major EHRs (Meditech, Epic and Cerner). Helpfulness was the most frequent problem for users of all EHRs. The survey is experimental and cross-sectional. The format was 20 Likert-type questions, along with screening and demographic questions. Due to the nature of data collected (ordinal) the non-parametric analysis was performed in SPSS. The goal of the study was to figure out the main usability issues among non-clinical users of the EHR systems and to generate actionable insights for designers and developers of EHR systems

Vers une plateforme dédiée à la composition automatique et l'exécution de services : Applications E-Tourisme

Recently, distributed computing systems based on context awareness have been proposing in several domains such as healthcare, logistics and tourism. The study described in this thesis is a part of a broader project of E-Tourism system that provides nomad user, context-aware personalized services. The work of this thesis focuses on the issues raised by web service composition and execution. Web service composition brings benefits of reusing existing services to synthesize the new resulting service that meets users needs. The way to create web service composition normally happens at design time, but this limits choices of services. This thesis presents a novel approach of automated web service composition and execution framework. Our approach aims to compose service operations that fulfill mobile users' requirements expressed in propositional logic and execute the resulting service based on aggregating multi service components. In the proposed framework, we have introduced our planning algorithm based on abstract goal states to search and connect to service operations, by mean of service operation annotations, for an abstract plan. The abstract plan is expected for workflow model of sequencing, paralleling and conditioning among service operations. However, the generated workflow is not in an executable form, this is why we perform the transformation of the workflow into an executable business process. To achieve the business process execution, we defined context based BPMN model for mapping the abstract plan to BPMN semantics. We also propose a new validation algorithm and exploited planning-as-model-checking approach to validate the semantic BPMN model whether it is Well-formed and Well-defined BPMN process. Finally, we implemented the automated service composition and execution framework system in Java platform as a proof of concept. We developed the logical composition and, transformation and validation BPMN algorithms written in Prolog. We have integrated these algorithms into the whole system. From the perspective, we plan to extend our current work and take into account more complex user's scenarios that explicitly and implicitly express other pattern controls and we will also consider the scenarios required for stateful web servicesLes systèmes de services contextualisés ont connu un grand essor ces dernières années dans des domaines variés tels que la santé, la logistique ou bien le tourisme. Cette thèse s'intègre dans un projet plus global, nommé E-Tourism, qui vise à réaliser une plateforme de fourniture de services sensibles au contexte à des utilisateurs en situation de mobilité. Le travail de cette thèse se focalise sur la problématique de composition de services web et de leur exécution. La composition de services web permet la réutilisation de services existants afin d'en faire une synthèse répondant au besoin de l'utilisateur. Cette composition se fait en général au niveau de la phase conceptuelle ce qui limite le choix de services potentiels. Cette thèse présente une nouvelle approche de la composition de services Web automatisé et une plateforme d'exécution. Notre approche vise à composer les opérations de services qui répondent aux besoins des utilisateurs mobiles exprimées dans une logique propositionnelle et exécuter le service composé en agrégeant plusieurs services composants. Nous avons proposé une plateforme d'exécution de services et nous avons introduit un nouvel algorithme de planification intégré à cette plateforme. Nous avons défini un contexte basé sur le modèle BPMN. Afin de valider notre modèle sémantique nous avons utilisé une approche de type « model-checking » . Enfin, nous avons réalisé un prototype sous forme d'une plateforme de composition de services et d'exécution automatique en Java. Nous avons implémenté les règles d'inférence et les modèles BPMN en prolog. Enfin, nous avons intégré ces algorithmes dans l'ensemble du système. En perspectives, nous prévoyons d'étendre notre travail actuel et prendre en compte des scénarios plus complexes nécessitant des services web dynamiques

The First 25 Years of the Bled eConference: Themes and Impacts

The Bled eConference is the longest-running themed conference associated with the Information Systems discipline. The focus throughout its first quarter-century has been the application of electronic tools, migrating progressively from Electronic Data Interchange (EDI) via Inter-Organisational Systems (IOS) and eCommerce to encompass all aspects of the use of networking facilities in industry and government, and more recently by individuals, groups and society as a whole. This paper reports on an examination of the conference titles and of the titles and abstracts of the 773 refereed papers published in the Proceedings since 1995. This identified a long and strong focus on categories of electronic business and corporate perspectives, which has broadened in recent years to encompass the democratic, the social and the personal. The conference\u27s extend well beyond the papers and their thousands of citations and tens of thousands of downloads. Other impacts have included innovative forms of support for the development of large numbers of graduate students, and the many international research collaborations that have been conceived and developed in a beautiful lake-side setting in Slovenia

THE RISE OF AI IN CONTENT MANAGEMENT: REIMAGINING INTELLIGENT WORKFLOWS

As content management systems (CMS) become indispensable for managing digital experiences, AI integration promises to bring new levels of automation and intelligence to streamline workflows. This paper surveys how AI techniques like machine learning, natural language processing, computer vision, and knowledge graphs are transforming CMS capabilities across the content lifecycle. We analyze key use cases like automated metadata tagging, natural language generation, smart recommendations, predictive search, personalized experiences, and conversational interfaces. The benefits include enhanced content discoverability, accelerated creation, improved optimization, simplified governance, and amplified team productivity. However, adoption remains low due to challenges like opaque AI, poor workflow integration, unrealistic expectations, bias risks, and skills gaps. Strategic priorities include starting with focused pilots, evaluating multiple AI approaches, emphasizing transparent and fair AI models, and upskilling teams. Benefits are maximized through hybrid human-AI collaboration vs full automation. While AI integration is maturing, the outlook is cautiously optimistic. Leading CMS platforms are accelerating development of no-code AI tools. But mainstream adoption may take 2-5 years as skills and best practices evolve around transparent and ethical AI. Wise data practices, change management, and participatory design will be key. If implemented thoughtfully, AI can reimagine workflows by expanding human creativity, not replacing it. The future points to creative synergies between empowered users and AI assistants. But pragmatic pilots, continuous improvement, and participatory strategies are necessary to navigate the hype and deliver value. The promise warrants measured experimentation

QoS-Aware Middleware for Web Services Composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming