Search results

This paper aims to examine how multinational corporations respond to environmental turbulence by adopting a flexible supply chain (SC).

This study adopts a case study in the medical industry to identify effective strategic approaches by taking advantage of new business opportunities and navigating complex business partnerships. This study focuses on medical diagnostic equipment, including computed tomography, magnetic resonance imaging and X-ray, that involves the suppliers, channel partners and medical users.

(1) The market turbulence brought the SC leaders to adopt multiple partnership approaches, i.e. funnel-based and area-based partnerships. (2) Adopting a funnel-based partnership allows the SC to seize new market opportunities. Still, it brought a risk element of SC failure from the flawed selection process and professional misconduct. (3) SC leaders adopted flexible partnerships to help address the risk of professional misconduct and select partners for long-term collaboration.

This paper contributes to emergent literature on social exchange theory by exposing the global SC when the SC leaders set up agility approaches. This paper also extends the discussion on the industrial marketing and purchasing theory, which seeks to promote an active buyer–seller relationship.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

Is humanity heading to immortal living? If so, what areas of society are playing an active role in achieving this? In order to understand this, the study explores the relationship between immortality and the wellness and medical tourism industry to seek potential relationships between them and ultimately, asks difficult questions about the growth of these tourism sectors and the potential need for greater regulation of them.

Taking a pragmatic philosophical approach and through the examination of refined information from secondary sources and published material and reports, the study presents original theoretical knowledge and a model exploring tourism and human immortality.

This paper argues that continued growth in the wellness and medical markets today could lead to a world where transhumanists and cyborgs are present in our world, even taking over from Homo sapiens. The study presents a model highlighting the potential role of wellness and medical tourism markets, illustrating the potential for future consumer services that could further fuel the search for immortality. Thus, how such markets and consumer desires are (in)directly supporting humanities desire for (non-human) immortal existence.

Today, individuals are driven by wellness practices and medical and cosmetic desires and are willing to travel the globe in search of companies who are either capable of carrying out the desired procedures or seeking prices more affordable to them. This research offers novel insights into these complex relationships and maps the affiliation between wellness and medical practices and the concept of immortality.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

Applying both the dynamic capability and configuration theoretical perspectives, the paper showcases the role of network configuration and dynamics of hybrid offerings in both developed and emerging markets by high-tech firms.

The current paper uses an exploratory qualitative research methodology based on in-depth case studies of three Finnish high-tech firms operating in the medical technology industry globally.

The findings from the study showed that dynamic capabilities such as sensing and customer engagement along with internal coordination and adaptation capabilities are critical to the success of hybrid market offerings. Moreover, dynamic capabilities were found to be influential in those emerging and advanced international markets where case firms were less familiar with market dynamics. Moreover, the configuration of these capabilities within functional units and coordination of marketing and R&D activities can be effective for creating hybrid offerings in international markets. Ultimately, this was found to be the case even though target market selection for hybrid offerings was influenced by the level of convergence and fragmentation of the market.

Applying the configuration theory, this is one of the first studies to specifically analyze the differences in organizational network configuration changes in relation to hybrid market offerings in both developed economies and emerging economies. The findings contribute to hybrid market offering literature by pointing out that not only internal capabilities are important for enacting hybrid offerings, but the roles of ecosystems and knowledge centers are also extremely important to develop hybrid offerings. This paper also highlights the criticality of under-studied dynamic capabilities such as market sensing and customer engagement in the context of hybrid offerings in international markets. This showcases the wider role of ecosystems in enabling technology firms to develop hybrid offerings.

The future construction site will be pervasive, context aware and embedded with intelligence. The purpose of this paper is to explore and define the concept of the digital skin of the future smart construction site.

The paper provides a systematic and hierarchical classification of 114 articles from both industry and academia on the digital skin concept and evaluates them. The hierarchical classification is based on application areas relevant to construction, such as augmented reality, building information model-based visualisation, labour tracking, supply chain tracking, safety management, mobile equipment tracking and schedule and progress monitoring. Evaluations of the research papers were conducted based on three pillars: validation of technological feasibility, onsite application and user acceptance testing.

Technologies learned about in the literature review enabled the envisaging of the pervasive construction site of the future. The paper presents scenarios for the future context-aware construction site, including the construction worker, construction procurement management and future real-time safety management systems.

Based on the gaps identified by the review in the body of knowledge and on a broader analysis of technology diffusion, the paper highlights the research challenges to be overcome in the advent of digital skin. The paper recommends that researchers follow a coherent process for smart technology design, development and implementation in order to achieve this vision for the construction industry.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

There are over 40 million amputees globally with more than 185,000 Americans losing their limbs every year. For most of the world, prosthetic devices remain too expensive and uncomfortable. This paper aims to outline advancements made by a multidisciplinary research group, interested in advancing the restoration of human motion through accessible lower limb prostheses.

Customization, comfort and functionality are the most important metrics reported by prosthetists and patients. The work of this paper presents the design and manufacturing of a custom made, cost-effective and functional three-dimensional (3D) printed transtibial prosthesis monocoque design. The design of the prosthesis integrates 3D imaging, modelling and optimization techniques coupled with additive manufacturing.

The successful fabrication of a functional monocoque prosthesis through 3D printing indicates the workflow may be a solution to the worldwide accessibility crisis. The digital workflow developed in this work offers great potential for providing prosthetic devices to rural communities, which lack access to skilled prosthetic physicians. The authors found that using the workflow together with 3D printing, this study can create custom monocoque prostheses (Figure 16). These prostheses are comfortable, functional and properly aligned. In comparison with traditional prosthetic devices, the authors slowered the average cost, weight and time of production by 95%, 55% and 95%, respectively.

This novel digital design and manufacturing workflow has the potential to democratize and globally proliferate access to prosthetic devices, which restore the patient’s mobility, quality of life and health. LIMBER’s toolbox can reach places where proper prosthetic and orthotic care is not available. The digital workflow reduces the cost of making custom devices by an order of magnitude, enabling broader reach, faster access and improved comfort. This is particularly important for children who grow quickly and need new devices every few months or years, timely access is both physically and psychologically important.

In this manuscript, the authors show the application of digital design techniques for fabricating prosthetic devices. The proposed workflow implements several advantageous changes and, most importantly, digitally blends the three components of a transtibial prosthesis into a single, 3D printable monocoque device. The development of a novel unibody transtibial device that is properly aligned and adjusted digitally, greatly reduces the number of visits an amputee must make to a clinic to have a certified prosthetist adjust and modify their prosthesis. The authors believe this novel workflow has the potential to ease the worldwide accessibility crisis for prostheses.

The purpose of this paper is to identify the potential and the challenges for different firms in adopting an AI-first strategy. The study attempts to discern if any company can prioritize AI at the forefront of their strategic plans.

Drawing from illustrative examples from well-known AI-leaders like Netflix and Spotify, as well as from upcoming AI startups and industry incumbents, the paper explores the strategic role of AI in core business processes and customer value creation. It also discusses the advent and implications of generative AI tools since late 2022 to firms’ business strategies.

The authors identify three types of AI-first strategies, depending on firms’ starting points: digital tycoon, niche carver and asset augmenter. The authors discuss how each strategy can aim to achieve data, algorithmic and execution advantages, and what the strategic bottlenecks and risks are within each strategy.

To the best of the authors’ knowledge, this paper is the first to systematically describe how companies can form “AI-first” strategies from different starting points. This study includes actionable examples from known industry players to more emerging startups and industrial incumbents.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.