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The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare industry. It is of great significance to transport the medical resources to required places in an efficient way. However, it is difficult to exactly discover matched transportation resources and deliver to its destination due to the heterogeneity. This paper studies the medical transportation resource discovery mechanism, leading to efficiency improvement and operational innovation.

To solve the transportation resource semantic discovery problem under the novel cloud environment, the ontology modelling approach is used for both transportation resources and tasks information modes. Besides, medical transportation resource discovery mechanism is proposed, and resource matching rules are designed including three stages: filtering reasoning, QoS-based matching and user preferences-based rank to satisfy personalized demands of users. Furthermore, description logic rules are built to express the developed matching rules.

An organizational transportation case is taken as an example to describe the medical transportation logistics resource semantic discovery process under cloud medical service scenario. Results derived from the proposed semantic discovery mechanism could assist operators to find the most suitable resources.

The case study validates the effectiveness of the developed transportation resource semantic discovery mechanism, contributing to knowledge management innovation for the medical logistics industry.

To improve task-resource matching accuracy under cloud scenario, this study develops a transportation resource semantic discovery procedure from the viewpoint of knowledge management. The novel knowledge management practice contributes to operational management of the cloud medical logistics service by introducing ontology modelling and creative management.

This study aims to explore how knowledge management (KM) influences the intellectual capital (IC) of organizations operating in health care and how IC and knowledge-sharing (KS) can contribute to the achievement of sustainable development in health systems. Notably, this study focuses on telemedicine, investigating how relational capital contributes to KS in the context of remote care services.

To comply with the paper’s aim, the authors use a qualitative research method based on a polar case study suitable for IC in health-care studies. More precisely, this study analyzes a nonprofit organization that, for over 15 years, has offered a free multispecialist teleconsultation service to answer medical questions from the most disadvantaged places in the world.

The findings show that the KM significantly contributes to the IC of organizations. Indeed, it improves the data management and transmission system, it increases performance flexibility in times of resource scarcity without compromising business objectives and it can attract new human resources even when not motivated by selfish goals (volunteer physicians).

This research contributes to studies on IC in health care by focusing on the contribution of telemedicine to the creation of IC. In particular, this work emphasizes the ability of telemedicine to develop and share knowledge in disadvantaged areas of the world. Moreover, in the current context, still strongly permeated by the health emergency generated by the pandemic and recently by the war in Eastern Europe, the importance of such assistance and diagnosis grows.

The conclusions the research findings lead may guide policymakers toward a policy supporting telemedicine. It would alleviate general health-care costs and completely revolutionize light health care’s role. Moreover, reducing socioeconomic distances, improving access to care and applying innovative technologies for sharing outcomes foster balanced socioeconomic development and knowledge dissemination.

This research has shown how telemedicine represents a new successful business model even in times of crisis. The organizational model makes it possible to offer cutting-edge specialized care, contain costs, easily reach disadvantaged areas of the planet, strengthen the skills and autonomy of the most backward countries through a process of KS and push the structures operating there to interact with those in advanced countries.

The main goal of this paper is to study the cloud service discovery mechanisms. In this paper, the discovery mechanisms are ranked in three major classes: centralized, decentralized, and hybrid. Moreover, in this classification, the peer-to-peer (P2P) and agent-based mechanisms are considered the parts of the decentralized mechanism. This paper investigates the main improvements in these three main categories and outlines new challenges. Moreover, the other goals are analyzing the current challenges in a range of problem areas related to cloud discovery mechanisms and summarizing the discussed service discovery techniques.

Systematic literature review (SLR) is utilized to detect, evaluate and combine findings from related investigations. The SLR consists of two key stages in this paper: question formalization and article selection processes. The latter includes three steps: automated search, article selection and analysis of publication. These investigations solved one or more service discovery research issues and performed a general study of an experimental examination on cloud service discovery challenges.

In this paper, a parametric comparison of the discovery methods is suggested. It also demonstrates future directions and research opportunities for cloud service discovery. This survey will help researchers understand the advances made in cloud service discovery directly. Furthermore, the performed evaluations have shown that some criteria such as security, robustness and reliability attained low attention in the previous studies. The results also showed that the number of cloud service discovery–related articles rose significantly in 2020.

This research aimed to be comprehensive, but there were some constraints. The limitations that the authors have faced in this article are divided into three parts. Articles in which service discovery was not the primary purpose and their title did not include the related terms to cloud service discovery were also removed. Also, non-English articles and conference papers have not been reviewed. Besides, the local articles have not been considered.

One of the most critical cloud computing topics is finding appropriate services depending on consumer demand in real-world scenarios. Effective discovery, finding and selection of relevant services are necessary to gain the best efficiency. Practitioners can thus readily understand various perspectives relevant to cloud service discovery mechanisms. This paper's findings will also benefit academicians and provide insights into future study areas in this field. Besides, the drawbacks and benefits of the analyzed mechanisms have been analyzed, which causes the development of more efficient and practical mechanisms for service discovery in cloud environments in the future.

This survey will assist academics and practical professionals directly in their understanding of developments in service discovery mechanisms. It is a unique paper investigating the current and important cloud discovery methods based on a logical categorization to the best of the authors’ knowledge.

Knowledge management (KM) is widely adopted by organisations to improve their performance and make informed decisions. Prior research has confirmed that Information Systems (IS) play a critical role in effective KM. The purpose of this study is to examine the existing literature on the role of cloud-based KM systems (C-KMS) in small- and medium-sized enterprise (SMEs) by understanding its impact on the five KM processes: knowledge acquisition, creation, storage, sharing and usage.

This study conducted a systematic literature review by examining 133 journal articles and 24 conference papers from 2010 to 2021 on the role of cloud computing in KM for SMEs.

This study revealed that there are numerous empirical analyses on KM processes and tools in SMEs; however, only few studies demonstrate how the whole gamut of KM processes can adopt cloud computing in SMEs. Therefore, SMEs are ineffective at KM with limited IS intervention. This paper offers a proposition on how C-KMS can impact all five KM process, thereby increasing its effectiveness of KM in SMEs. This study analysed the benefits of C-KMS that brings to SMEs in terms of availability, scalability, reliability, security and cost.

This systematic review is restricted to certain databases (ScienceDirect, Sage journals, Scopus and Emerald Insight) and specific IS conference proceedings to source articles. The selection of search criteria and time frame is based on this study’s assessment and choice. This study adds value to our understanding of the role of KM in SMEs, and it reinforces the role of cloud computing in effectively managing knowledge in SMEs. The proposal of C-KMS for the enhancement of KM has significant implications for SMEs to effectively use knowledge for their survival and superior performance.

This study suggests three practical implications. First, adopting and using C-KMS provide a strong foundation to manage knowledge for SMEs in a cost-effective way. Second, C-KMS improves the effectiveness of KM by increasing availability of knowledge artifacts, which in turn aids SMEs’ growth. Third, C-KMS is useful to codify SME’s knowledge, and accordingly supports employees to acquire and use knowledge based on their requirements.

This study discussed C-KMS with contemporary social issues, such as the COVID-19 pandemic challenges for SMEs and demonstrated how C-KMS can support SMEs to handle such crises by managing knowledge effectively.

This research highlights the importance of the implementation of a C-KMS for the enhancement of KM in SMEs. The review provides empirical evidence on the challenges faced by SMEs regarding KM, as they often only have enough resources to focus on a single KM process, predominantly knowledge sharing. Consequently, a holistic approach to KM cannot be realised by SMEs. In this context, the findings of this study offer theoretical and practical insights into the role of cloud computing by addressing the challenges of KM in SMEs.

This study aims to map out the ways in which the intellectual structure and research trends of scientific publications come together in business-to-business (B2B) marketing strategies in the health-care sector. More specifically, it aims first to identify the fundamental contributions of research in this area of knowledge and second to determine the lines of research that constitute the most prominent intellectual contribution to the development of a solid future research agenda.

The statistical and analytical methods include bibliometric, co-citation and cluster analysis techniques. To identify useful patterns of information within the paper, this study sought paid special attention to scholarship that was jointly cited. This study then applied hierarchical cluster analysis to the totality of the co-cited paper and then grouped the interrelated paper into distinct sets.

This study were able to systematically identify and classify various theoretical perspectives of B2B marketing strategies within the health-care sector into four main approaches, namely, decision-making strategies; relational marketing; co-creation; new challenges.

By systematically identifying, exploring and analyzing the key priorities of B2B marking within the health-care sector, this study contributes positively to the existing literature. The added value is that the work will help to further improve the international standards of excellence within the health-care sector and its marking apparatuses.

The purpose of this paper is to find the key innovative principles for evaluating the long-term care (LTC) cloud system by exploring contradictory and complex points in its development.

The theory of inventive problem solving (TRIZ) and the decision-making trial and evaluation laboratory (DEMATEL) approaches are integrated to resolve complex contradictions in the system. The heuristic reasoning of TRIZ is applied to obtain innovation principles for an LTC cloud mining system. However, the importance and feasibility of these innovative principles require further assessment. In this study, DEMATEL is employed to clarify the complex relationships among the principles and evaluate their key influences.

This paper identifies six primary contradictions and derives 25 innovative principles for the resolution of these conflicts. Further analysis confirms three key innovative principles. First, the government should consider the overall planning of the cloud system platform, followed by the participation of other medical and LTC institutions. Second, the information capability of LTC institutions should be unified by recording the pathology data of care recipients to create an information exchange system. Third, LTC institutions should act in cooperation with medical institutions to provide professional medical capabilities.

The contributions of this paper are two-fold. First, this study provides an integrated methodology integrating the TRIZ and DEMATEL approaches to resolve LTC problems. Second, this research identifies the key innovative principles for developing an LTC cloud system in Taiwan.

Increasing academic communities and practitioners begin to explore a novel method to reduce environmental pollution and realize green logistics delivery. Additionally, China's Statistical Yearbook shows that the number of private cars has reached 165 million in China. Under this background, this study proposes a green delivery method by the combination of sharing vehicle (private cars) and IoT (Internet of things) from the perspective of vehicle energy efficiency and aims to improve the energy efficiency of social vehicles and provides more convenient delivery services.

This study builds an IoT architecture consisting of customer data layer, information collection layer, cloud optimization layer and delivery task execution layer. Especially in the IoT architecture, a clustering analysis method is used to determine the critical value of customers' classification and shared delivery, a routing optimization method is used to solve the initial solution in could layer and shared technology is used in the implementation of shared delivery.

The results show that the delivery method considering shared vehicles has a positive effect on improving the energy utilization of vehicles. But if all of delivery tasks are performed by the shared vehicle, the application effect may be counterproductive, such as delivery cost increases and energy efficiency decreases. This study provides a good reference for the implementation of green intelligent delivery business, which has a positive effect on the improvement of logistics operation efficiency.

This study designs a novel method to solve the green and shared delivery issues under the IoT environment, which integrates the IoT architecture. The proposed methodology is applied in a real case in China.

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.

Purpose: Green computing is a way of using the computer resource in an eco-friendly while maintaining and decreasing the harmful environmental impact. Minimising toxic materials and reducing energy usage can also be used to recycle the product.

Need for the Study: The motivation of the study is to use green computing resources to decrease carbon emissions and their adverse effect on the environment.

Methodology: The study uses a qualitative method of collecting resources and data to address the opportunities, challenges, and future trends in green computing for Sustainable Future Technologies. The study focusses on multiple kinds of cloud computing services collected and executed into single remote servers. The service demand processor offers these services to the client per their needs. The simultaneous requests to access the cloud services, processing and expertly managing these requests by the processors are discussed and analysed.

Findings: The findings suggest that green computing is an upcoming and most promising area. The number of resources employed for green computing can be beneficial for lowering E-waste so that computing can be environmentally friendly and self-sustainable.

Practical Implications: Green computing applies across all industries and service sectors like healthcare, entertainment, tourism, and education. The convergence of technologies like Cloud Computing, AI, and Internet of Things (IoT) is greatly impacting Green Supply Chain Management (GSCM) market.