Search results

In this paper we present a CDN‐based system, namely the COMODIN system, which is a media on‐demand platform for synchronous cooperative work which supports an explicitly‐formed cooperative group of distributed users with the following integrated functionalities: request of an archived multimedia session, sharing of its playback, and collaboration through questioning. The server‐side architecture of the COMODIN system is organized into two integrated planes: the Base plane, which consists of a streaming CDN providing media streaming, and the Collaborative plane, which provides the collaborative playback service. At the client‐side, the system centers on a Java‐based application which interfaces the cooperative group of users.

The convergence of multimedia, virtual reality and the Internet is promoting low‐cost multimedia virtual environments which are easily accessible to large network communities. These environments, which facilitate usability and enhance user experience, are very suitable for supporting user‐oriented application domains such as e‐learning and entertainment. This paper presents a multimedia virtual environment, namely the Virtual Video Gallery, an advanced, distributed media on‐demand system which is browsable through a virtual world. By taking a virtual walk inside the gallery, the user can interactively select, preview, watch and control multimedia sessions. While the user‐centred design of the system relies on UML‐based modelling techniques, system implementation is obtained by the integration of Java, VRML and Web‐based technologies. In order to evaluate the user‐oriented effectiveness of the Virtual Video Gallery and compare it to currently available Internet‐based MoD systems, the usability testing of the system was established for deriving both summative and formative usability data.

To date e‐Learning material has usually been accessed and delivered through a central web server. As the number of users, the amount of information, the frequency of accesses and the volume of data increase, together with the introduction of multimedia streaming applications, a decentralized content distribution architecture is necessary. In this paper we propose the adaptation of the well‐known scalable Content Distribution Networks (CDN) schema for media streaming supported e‐Learning using a novel architecture named COMODIN SCDN (COoperative Media On‐Demand on the InterNet ‐ Streaming Content Distribution Network). COMODIN SCDN utilises surrogates as edge content delivery nodes, incorporates a redirection mechanism able to route requesting clients to the closest copy of the content, encompasses distributed content delivery and management mechanisms to improve the speed, reliability, and scalability of user access to prevent flash‐crowds. Preliminary results in testbeds have shown that COMODIN SCDN increases the efficacy of information distribution through intra and inter‐campus area netwoks. This overlay network will provide learners and educators a scalable, balanced and expeditious access to e‐Learning contents.

The issue of trust in Industry 4.0 is extremely important from an organization’s perspective. The dynamic development of 4.0 technologies implies wide-ranging changes, which, in order to be implemented effectively, require cooperation based on trust. The purpose of this literature analysis is to identify key research areas regarding trust in Industry 4.0 and to identify further research directions.

Based on a comprehensive literature analysis, the most prominent areas of research on trust issues in Industry 4.0 will be presented (k=36). This chapter will also identify and discuss directions for further research.

The results of the analysis enable to illustrate the trends of science development in the area of Industry 4.0, as well as to identify key issues related to trust. Moreover, the research problems for further studies on the analyzed issue will also be indicated.

The research presented here identifies key Industry 4.0 technologies that are based on trust.

The review provides a valuable resource for practitioners regarding the critical aspects of implementing Industry 4.0 with respect to trust.

This is the first comprehensive literature review diagnosing research areas, technologies, and directions for future research on trust in Industry 4.0.

The purpose of this study is to explore the use of Internet of Things (IoT) in hospitality and examine its relationship with Big Data. Drawing upon theoretical and practical considerations, it lays a foundation for its adoption in practice and future research.

This paper uses a conceptual approach. It demonstrates the use of IoT and its impact on Big Data in hospitality through exemplars. The paper further explores the convergence of IoT, Big Data and hospitality in the context of the literature, value attributes and vendor offerings. Theoretical models from information systems and business are used to support the concepts proposed.

The study compiles and contextualizes the applications of IoT in hospitality by applying an input–process–output model, demonstrating the link to Big Data. The resulting value dimensions are represented by the IoT–Big Data triple impact intensity model.

An outlook toward the future trajectory of IoT adoption is provided by proposing to extend the prevalent social, mobile, analytics and cloud framework with an IoT component.

Practical implications of the use of IoT and Big Data in hospitality on information technology infrastructure, business models, security and standardization highlight the scope for further empirical research.

By synthesizing IoT applications in hospitality and by bringing to light their relationship with Big Data, the study demonstrates how IoT, Big Data and hospitality converge – a synthesis that has thus far been largely unexplored. This study lays the groundwork for increased deployment of IoT and Big Data in hospitality and future academic research in this area.

本论文开发了酒店管理中的物联网（IoT）的使用, 并且检验了其与大数据的关系。根据其理论和实际考虑, 这方面的科技缺乏应用理论基础和未来研究方向。

本论文采用理论讲述的方式, 通过例子来阐述IoT的应用和大数据对于酒店管理的影响。本论文还拓展了IoT、大数据、以及酒店管理在文献范畴、价值属性、以及供应商考量中的认识。本论文借鉴了信息系统和商业管理中的理论模型以支撑提出的理论概念。

本论文综合审视了IoT在酒店管理中的应用, 提出了一个输入-处理-输出的模型, 指出了其与大数据的关联。其相关价值维度通过IoT-大数据三重影响强度模型来显示。

本论文提出了对IoT使用的未来展望, 拓展了著名的SMAC模型（social, mobile, analytics, cloud）, 加入了IoT成分。

本论文对IoT和大数据在酒店IT架构、商业模型、安保和标准化等方面的使用, 强调了其未来应用研究的方向。

本论文通过酒店管理中的IoT应用综述, 以及其与大数据分析的关联, 展示了IoT、大数据、酒店覆盖等概念如何融合, 这方面的研究还未真正被开发。本论文对于酒店领域中的IoT和大数据应用以及相关领域的未来研究, 有着奠基作用。

Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.

The rapid proliferation of Internet of Things (IoT) devices across various domains has created a demand for real-time computing resources that traditional cloud computing models struggle to meet. Fog computing, which brings computation resources closer to IoT devices, has emerged as a promising solution. An automatic service placement framework is needed to use fog computing resources efficiently.

In this study, first a three-layer independent service framework is introduced to define relationships between IoT devices and fog layers, facilitating automatic application deployment. Next, an enhanced version of the equilibrium optimizer (EO) algorithm, inspired by physics, is designed for service placement in fog computing environments.

Simulations reveal that the proposed approach surpasses existing methods, achieving a 99% success rate compared to the closest alternative’s 93%. The algorithm also significantly reduces waiting and planning times for service placement, proving its efficiency and effectiveness in optimizing IoT service deployment in fog computing.

One of the primary limitations is the computational complexity involved in dynamically adjusting to real-time changes in network conditions and IoT workloads. Although improved EO offers improvements in placement efficiency, it may not be fully optimized for highly fluctuating environments. Another important limitation is the uncertainty in node resources. Fog computing environments often face unpredictable changes in the availability and capacity of resources across nodes. This uncertainty can affect the algorithm’s ability to consistently make optimal decisions for IoT service placement.

From a practical perspective, the implementation of the proposed framework and the improved EO algorithm can drastically enhance the efficiency of IoT service deployment in fog computing systems. Organizations that rely on IoT networks, particularly those with critical real-time requirements, can benefit from reduced service placement times and lower failure rates. This can lead to better resource utilization, reduced operational costs and improved overall performance of IoT systems. The commercial impact is evident in industries such as smart cities, healthcare, where fast data processing is crucial.

Our proposed framework has important implications for real-world IoT applications, particularly in areas requiring low latency processing, such as healthcare, smart cities. By reducing service delays and optimizing resource allocation, the framework can significantly improve the quality and reliability of services. Additionally, improved resource management leads to cost savings and better system efficiency, making the technology accessible to a wider range of applications.

Existing resource placement strategies have shown inadequate performance, highlighting the need for more advanced algorithms. This study introduces a three-layer automatic framework for enhancing the application deployment of a fog system beside a novel improved EO algorithm to offer a robust solution for assigning IoT applications to fog nodes.

Smart cities and their internationalization process and efforts in order to gain the competitive advantage in the international arena have received a great deal of attention by marketing scholars and practitioners alike. Yet, the growing number of studies focused on this topic has led to considerable fragmentation and theoretical confusion.

To move the domain forward, this study applies the systematic review methodology and reviews 41 peer-reviewed articles published in highly esteemed publication outlets.

Building on the antecedents–phenomenon–consequences framework, the authors discuss the antecedents and consequences of the various innovative marketing strategies that smart cities adopt for their internationalization and development of an international competitive advantage. In the process of doing so, the authors synthesize the findings of the studies as well as literature gaps that provide fruitful avenues for future research.

This article offers a systematic review of extant marketing research on smart cities and their efforts to internationalize. In particular, this study advances the conceptual development of smart city internationalization and innovation by a marketing lens, provides an integrative, international-oriented framework that maps the extant literature across disciplines and countries, expands the boundaries of this research domain into new research paths and offers implications for policy and practice.

The effect of digital transition on knowledge management (KM) processes is becoming relevant for companies operating in different industries and the body of literature examining this impact is rapidly growing. This paper aims to critically analyse the literature on the impact of digital transition on KM by rethinking the SECI model proposed by Nonaka and proposing the WISED model for the digital knowledge-creating company.

The systematisation of existing studies on the topic and the analysis of the evolution of knowledge creation process in the era of digital transition was carried out through a bibliometric approach.

According to the traditional epistemological and ontological dimensions and considering the innovative KM processes identified by this study (i.e. webification, informalisation, systematisation, explicitation and digitalisation), the results highlight how the proposed WISED model can be adopted by organizations to manage knowledge through the use of digital technologies.

Digital transition seems to open up new horizons that can expand the potential use of the WISED model for organisations and society.

The study aims to investigate the integration of human and machine intelligence in Industry 4.0 (I4.0), particularly in the convergence of industrial revolutions 4.0 (IR4.0) and 5.0. It seeks to identify employee competencies aligned with industry 5.0 (I5.0) and propose a framework for deep multi-level cooperation to improve human integration within the intelligence system.

This study uses bibliometric analysis to review 296 research papers retrieved from the Scopus database between 2002 and 2022. The prominence of the research is evaluated by analyzing the publication trend, sample statistics, theoretical foundation, commonly used keywords, thematic evolution, country-based contributions and top-cited documents.

The study observed that research in I5.0 has been limited in the past but has gained momentum since 2015. An analysis of research papers from 2002 to 2022 reveals a gradual shift toward human-centric practices. The literature on I4.0, the internet of things (IoT), artificial intelligence (AI), cloud manufacturing, blockchain and big data analysis has been increasingly highlighting the growing importance of digitalization in the future. An increase in the number of countries contributing to the field of study has also been observed.

This analysis offers valuable insights for managers, policymakers, information technology (IT) developers and stakeholders in understanding and implementing human-centric practices in I5.0. It emphasizes staying current with trends, embracing workforce empowerment through reskilling and upskilling, and prioritizing data privacy and security in adaptable systems. These strategies contribute to developing effective, inclusive and ethically sound approaches aligned with the principles of I5.0.