Search results

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management (CRM) investments in modern customer service. The purpose of this paper is to develop an analytic hierarchy planning framework to establish criteria weights and to develop a general self-assessment model for determining the most important factors influencing the IoT and BD investment in CRM. The authors found that most studies have focused on conceptualizing the impact of IoT without BD and with limited empirical studies and analytical models. This paper sheds further light on the topic by presenting both IoT and BD aspects of future CRM.

The analytic hierarchy process (AHP) methodology is used to weight and prioritize the factors influencing the IoT and BD investment in modern CRM in the service industry. The AHP framework resulted in a ranking of 21 sustainability sub-factors based on evaluations by experienced information technology and customer service professionals.

The paper provides significant insight on the new frontier of CRM, focusing on the use of IoT and BD and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing and implementing IoT and BD in big businesses by identifying the connecting link between firms and customers.

The understanding of new frontier of CRM connective via IoT and BD can solve the dilemmas and challenges linked to the practice of implement IoT and BD in the information systems field. The study provides valuable information and critical analysis of IoT and BD with regard to the integration of CRM. Finally, this study further provides directions for future researchers.

IoT and BD are a growing phenomenon, which business decision-makers and information professionals need to consider seriously to properly ascertain the modern CRM dimensions in the digital economies. They also should embrace the proper CRM innovation, which is powered by IoT and BD, and discover how IoT and BD can bring the next level of maturity to CRM “CRM of everything.”

The purpose of this study is to provide insights into the way in which understanding and implementation of disruptive technology, specifically big data analytics and the Internet of Things (IoT), have changed over time. The study also examines the ways in which research in supply chain and related fields differ when responding to and managing disruptive change.

This study follows a four-step systematic review process, consisting of literature collection, descriptive analysis, category selection and material evaluation. For the last stage of evaluating relevant issues and trends in the literature, the latent semantic analysis method was adopted using Leximancer, which allows more rapid, reliable and consistent content analysis.

The empirical analysis identified key research trends in big data analytics and IoT divided over two time-periods, in which research demonstrated steady growth by 2015 and the rapid growth was shown afterwards. The key finding of this review is that the main interest in recent big data is toward overlapping customer service, support and supply chain network, systems and performance. Major research themes in IoT moved from general supply chain and business information management to more specific context including supply chain design, model and performance.

In addition to providing more awareness of this research approach, the authors seek to identify important trends in disruptive technologies research over time.

This paper aims to provide guidance so firms can enter the Internet of Things (IoT) era today – and realize its data-driven benefits – by using IoT “dark data” already generated by their operations.

This study draws upon data from original expert interviews and an extensive study of over 1,200 research articles and white papers to provide managerial guidance for exploiting IoT dark data.

Many companies are held back from entering the IoT era today, not by technological issues, but by matters addressable by managerial and strategic leadership. Executives must build dark data awareness among their employees and use non-traditional measures to predict return on investment. The study shares expert advice for accomplishing both of these efforts.

Only 3 out of 1,202 research articles addressed IoT dark data. This paper helps fill this gap in understanding.

This study provides normative guidelines for managers and executives to increase awareness of the dark IoT data that exist within their organizations and to motivate the investments needed to exploit this data to improve business performance.

This research provides guidance for companies to benefit from the IoT today. This study provides an alternate, pragmatic view of Industry 4.0 that focuses on current business reality rather than futurist visions.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

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。

In data grids, replication has been regarded as a crucial optimization strategy. Computing tasks are performed on IoT gateways at the cloud edges to obtain a prompt response. So, investigating the data replication mechanisms in the IoT is necessary. Henceforth, a systematic survey of data replication strategies in IoT techniques is presented in this paper, and some suggestions are offered for the upcoming works. In two key classifications, various parameters dependent on the analysis of the prevalent approaches are considered. The pros and cons associated with chosen strategies have been explored, and the essential problems of them have been presented to boost the future of more effective data replication strategies. We have also discovered gaps in papers and provided solutions for them.

Progress in Information Technology (IT) growth has brought the Internet of Things (IoT) into life to take a vital role in our everyday lifestyles. Big IoT-generated data brings tremendous data processing challenges. One of the most challenging problems is data replication to improve fault-tolerance, reliability, and accessibility. In this way, if the primary data source fails, a replica can be swapped in immediately. There is a significant influence on the IoT created by data replication techniques, but no extensive and systematic research exists in this area. There is still no systematic and full way to address the relevant methods and evaluate them. Hence, in the present investigation, a literature review is indicated on the IoT-based data replication from papers published until 2021. Based on the given guidelines, chosen papers are reviewed. After establishing exclusion and inclusion criteria, an independent systematic search in Google Scholar, ACM, Scopus, Eric, Science Direct, Springer link, Emerald, Global ProQuest, and IEEE for relevant studies has been performed, and 21(6 paper analyzed in section 1 and 15 paper analyzed in section 3) papers have been analyzed.

The results showed that data replication mechanisms in the IoT algorithms outperform other algorithms regarding impressive network utilization, job implementation time, hit ratio, total replication number, and the portion of utilized storage in percentage. Although a few ideas have been suggested that fix different facets of IoT data management, we predict that there is still space for development and more study. Thus, in order to design innovative and more effective methods for future IoT-based structures, we explored open research directions in the domain of efficient data processing.

The present investigation encountered some drawbacks. First of all, only certain papers published in English were included. It is evident that some papers exist on data replication processes in the IoT written in other languages, but they were not included in our research. Next, the current report has only analyzed the mined based on data replication processes and IoT keyword discovery. The methods for data replication in the IoT would not be printed with keywords specified. In this review, the papers presented in national conferences and journals are neglected. In order to achieve the highest ability, this analysis contains papers from major global academic journals.

To appreciate the significance and accuracy of the data often produced by different entities, the article illustrates that data provenance is essential. The results contribute to providing strong suggestions for future IoT studies. To be able to view the data, administrators have to modify novel abilities. The current analysis will deal with the speed of publications and suggest the findings of research and experience as a future path for IoT data replication decision-makers.

In general, the rise in the knowledge degree of scientists, academics, and managers will enhance administrators' positive and consciously behavioral actions in handling IoT environments. We anticipate that the consequences of the present report could lead investigators to produce more efficient data replication methods in IoT regarding the data type and data volume.

This report provides a detailed literature review on data replication strategies relying on IoT. The lack of such papers increases the importance of this paper. Utilizing the responses to the study queries, data replication's primary purpose, current problems, study concepts, and processes in IoT are summarized exclusively. This approach will allow investigators to establish a more reliable IoT technique for data replication in the future. To the best of our understanding, our research is the first to provide a thorough overview and evaluation of the current solutions by categorizing them into static/dynamic replication and distributed replication subcategories. By outlining possible future study paths, we conclude the article.

The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the IoT-enabled Context-aware BPM (IoT-CaBPM) framework to bridge from the IoT infrastructure to context-aware business processes.

Motivated by the “Three Waves” of BPM research, IoT-enabled context-awareness is, therefore, expected to be achieved for enhancing the business process design, which pilots a new wave of BPR (Business Process Redesign/Reengineering) to enable the business process coevolve with IoT and analytics. This paper reports an illustrative case study of BPR in a Chinese bulk port, one of the hub seaports that widely adopted IoT technologies over the last few years.

The IoT implementation and data analytics has increased the efficiency and improve the monitoring effectively. The proposed IoT-CaBPM framework availably helps to identify and match nodes of IoT devices, business decisions and analytic models in order to redesign a business process towards context-aware variability. As IoT is rapidly becoming the new dominant IT paradigm is moving towards mature implementation in various industries, the corresponding BPR must be planned and executed strategically for achieving better benefits.

Despite some research extend BPM standard by integrating IoT devices as a sort of resources or report generically that the ports operations are affected by IoT, there is still a lack of layers from the IoT infrastructure to context-aware business processes. An industrial BPR case with business models in detail is also a lack for presenting the specific implications and effectiveness of the adoption of such technologies. This paper fills in this gap.

The technology used by an organization is significantly influenced by the organization’s preferred competitive capabilities. The Internet of things (IoT) is an important technology, which is implemented by most prominent business organizations. The purpose of this paper is to investigate the relationship between an organization’s strategies and the IoT architectures implemented by the organization.

This study has been carried out on primary data collected with the help of a structured questionnaire. The data have been analyzed by statistical techniques like cluster analysis and discriminant analysis through SPSS.

The empirical investigation of data revealed that there is a relationship between organizational strategy and IoT architectures. The three-layered architecture of the IoT is most suitable for caretakers; the three-, four- or five- layered architectures are suitable for marketeers; whereas innovators find it more suitable to use five- or more-layered architecture of the IoT. This paper draws the conclusion based on maximum likelihood rather than using statistical analyses like ANOVA. The idea behind using the maximum likelihood estimate is that there are many subjective parameters in deciding the architectures of the IoT. These subjective parameters are difficult to quantify, so it is not possible to apply ANOVA on these parameters.

This study considers three organizational strategies; the relationship between other organizational strategies and IoT architecture will be studied in future.

This study offers multiple opportunities to practitioners and consulting firms of the IoT to adopt a suitable IoT architecture according to the organizational strategy. This study equips IoT development engineers to select suitable technology for data capturing, data transmission, and data management and access for an IoT architecture.

Although a lot of work has already been done on the architecture of IoT for different industries and businesses, to the best of our knowledge, this is the first study that relates organizational strategies to IoT architectures. This study applies to all the major industry types.

The purpose of this paper is to investigate the implications for supply chain risk management (SCRM) by applying internet of things (IoT). Therefore, the impact and effects on the SCRM process, as well as the internal and external pathway and the outcome of SCRM are examined.

This study adopts a multiple case study methodology with twelve companies from the manufacturing industry. This study is guided by the information processing theory (IPT) and a theory-grounded research framework to provide insights into information requirements and information processing capabilities for IoT-supported SCRM.

The studied cases demonstrate an increase in data availability in the companies that contribute to improved process transparency and process management. Furthermore, the process steps, risk transparency, risk knowledge and risk strategies have been enhanced, which enabled improved SCRM performance by fitting information requirements and information processing capabilities, thus allowing for competitive advantage.

This study offers in-depth insights for SCRM managers into the structure of IoT systems, primary use cases and changes for the process itself. Furthermore, implications for employees, incentives and barriers are identified, which could be used to redesign SCRM.

This study addresses the requirement for additional empirical research on technology-enhanced SCRM, supported by IPT as a theoretical foundation. The radical change of SCRM by IoT is demonstrated while discussing the human role, implications for SCRM strategies and identifying relevant topics for future development.

Particular attention to the issue of information management will be required to meet the expected growth in IoT-devices and the data they generate. As government agencies start collecting and using such information, they must also deal with the issue of privacy, to comply with laws and regulations. The approach discussed here shows that record-keeping principles may form part of a solution to the issue of managing IoT-data for government agencies.

This study uses the generally accepted record-keeping principles as a basis for a high-level discussion on how IoT-data can be managed. This is followed by a presentation and discussion on how the Norwegian record-keeping standard, Noark, can be extended to highlight practical issues.

Record keeping has principles that are relevant to the management of IoT-data. Further an implementation of the chosen use-cases is possible based on an existing record keeping standard. Record keeping is one of many information science approaches that can manage IoT-data.

The main limitations are that the discussion cannot cover all types of IoT-devices, nor can all issues be captured with a limited choice of examples. The results should be seen within the context of the types of devices discussed and limited to the chosen use-cases. However, the level of abstraction used means the results may be applicable to similar scenarios.

The approach shows that record-keeping principles may be used as an approach to manage IoT-data. This discussion is useful when compared with other information science approaches, e.g. big-data or semantic Web approaches. The practicalities of a record-keeping approach are also discussed and relevant strengths and weaknesses are showed.