Practical Roadmap Research Articles

The Impact of Authentic Leadership on Employee Innovation Behavior and Work Engagement in Specialized, Fined, Peculiar and Innovative SMEs

Existing firms are undergoing rapid and substantial change as a result of digital transformation. Dealing with accelerating digital transformation is a difficult process for business leaders. The digital transformation process presents both an opportunity and a challenge. This paper examines how authentic leadership may contribute to increased work engagement and innovative behaviors during times of digital change, both theoretically and empirically. This study investigated data from an online survey of 305 current employees of enterprises in the fields of specialized, fined, peculiar and innovative SMEs, include information technology, media, and networking and so on. SPSS 21.0 and AMOS 23.0 were used to analyze the data. The findings indicate that authentic leadership positively impacts employee innovation behaviors and engagement, and that digital transformation moderates the relationship between authentic leadership and innovation behavior and engagement. Not only do these findings contribute to our understanding of digital transformation and extend and broaden applicable theories of authentic leadership, but they also open the way for corporate leaders to adopt appropriate behavioral techniques to encourage work engagement and innovation. Enhancing employee innovation performance, maximizing management leadership behaviors, and offering practical inspiration all contribute to the long-term success of the firm. The findings are conceptually significant and provide corporate leaders with a practical roadmap.

Transformation of Аnalytics of Large Databases in Procurement Management with the Development of Artificial Intelligence

The article offers an in-depth examination of the current state, as well as the growth trajectories, of the global market for big data analytics, with a specific focus on the subfield of procurement analytics. It goes beyond mere surface-level statistics to provide a nuanced understanding of market trends and potential future directions. This is explored not just in the context of the European Union but also extends to a detailed case study involving Ukraine, thereby offering a more global perspective. Furthermore, the article scrutinizes the various data sources that can be leveraged for making well-informed management decisions in the realm of procurement. It doesn’t stop at merely listing these sources but goes on to analyze their respective merits and limitations. In addition, the article provides real-world examples from Ukraine, showcasing the practical applications of data analytics in procurement processes, thereby grounding the theoretical discussions in empirical reality. The article also ventures into the burgeoning field of artificial intelligence (AI), outlining its transformative potential in procurement data analytics. It characterizes the myriad benefits that AI can bring to procurement management, from increased efficiency to more nuanced decision-making capabilities. To guide practitioners, the article proposes a detailed algorithmic workflow for employing AI in the analysis of data crucial for procurement decisions. This serves as a practical roadmap for organizations looking to integrate AI into their procurement strategies. However, the article is not blindly optimistic about the role of AI; it also brings to the fore the potential risks associated with employing artificial intelligence for the analysis of large and complex databases. This balanced approach adds a layer of caution to the otherwise optimistic narrative, making the article a comprehensive and nuanced contribution to the literature on procurement analytics and artificial intelligence. In sum, the article serves as a robust academic resource that traverses the landscape of procurement analytics, from market trends and macroeconomic impacts to the practicalities and potential pitfalls of AI integration.

ՏՆՏԵՍԱԳԻՏԱԿԱՆ ԿՐԹՈՒԹՅԱՆ ԱՐԴԻԱԿԱՆԱՑՈՒՄԸ։ ԱԿՏԻՎ ՈՒՍՈՒՄՆԱՌՈՒԹՅԱՆ ՄԵԹՈԴՆԵՐԻ (ՀԻՄՆԱԽՆԴՐԱՀԵՆՔ ՈՒՍՈՒՑՈՒՄ և ԻՐԱՎԻՃԱԿԱՅԻՆ ՎԵՐԼՈՒԾՈՒԹՅՈՒՆՆԵՐ) ԿԻՐԱՌՄԱՆ ԱՌԱՆՁՆԱՀԱՏԿՈՒԹՅՈՒՆՆԵՐԸ/MODERNIZATION OF ECONOMIC EDUCATION. FEATURES OF THE APPLICATION OF ACTIVE LEARNING METHODS (PROBLEM-BASED LEARNING AND CASE STUDIES)/МОДЕРНИЗАЦИЯ ЭКОНОМИЧЕСКОГО ОБРАЗОВАНИЯ. ОСОБЕННОСТИ ПРИМЕНЕНИЯ АКТИВНЫХ МЕТОДОВ ОБУЧЕНИЯ (ПРОБЛЕМНОЕ ОБУЧЕНИЕ И КЕЙС-СТАДИ)

Teaching economics in universities can be both creative and effective by incorporating various methods that engage students, promote critical thinking, and connect theory to real-world applications. Economics education at the university level is undergoing various transformations to meet the demands of a rapidly changing world, and to equip students with practical skills and a deep understanding of real-world economic phenomena. The relevance of the article is explained by the current challenges economics education is facing, such as passive learning, and the gap between theoretical knowledge and practical skills. This methodological article aims to identify the importance of innovative methods in economics education and to provide a practical roadmap for educators to make the learning process more effective and interesting, as well as to prepare students for modern economic challenges. The article examines the implementation of active learning methods, particularly problem-based learning (PBL) and case studies methods in university education for teaching economics. Active learning methods are widely used in higher education due to the ability to promote critical thinking, problem-solving, creativity, and other skills, as well as the possibility of practical application of theoretical knowledge. The article can serve as a comprehensive guide to the use of PBL and case analysis, offering examples and practical tasks for instructors who aim to implement innovative approaches in their courses.

Management of systemic sclerosis: British Society for Rheumatology guideline scope.

This guideline will provide a practical roadmap for management of SSc that builds upon the previous treatment guideline to incorporate advances in evidence-based treatment and increased knowledge about assessment, classification and management. General approaches to management as well as treatment of specific complications will be covered, including lung, cardiac, renal and gastrointestinal tract disease, as well as RP, digital vasculopathy, skin manifestations, calcinosis and impact on quality of life. It will include guidance related to emerging approved therapies for interstitial lung disease and account for National Health Service England prescribing policies and national guidance relevant to SSc. The guideline will be developed using the methods and processes outlined in Creating Clinical Guidelines: Our Protocol. This development process to produce guidance, advice and recommendations for practice has National Institute for Health and Care Excellence accreditation.

How to stretch system reliability exploiting mission constraints: A practical roadmap for industries

Reliability analysis can be committed to companies by customers willing to verify whether their products comply with the major international standards or simply to verify the design prior of market deployment. Nevertheless, these analyses may be required at the very preliminary stages of design or when the design is already in progress due to low organizational capabilities or simple delay in the project implementation process. The results sometime maybe be far from the market or customer target with a subsequent need to redesign the whole asset. Of course, not all the cases fall in the worst scenario and maybe with some additional consideration on mission definition it is possible to comply with the proposed reliability targets. In this paper the author will provide an overview on the approach which could be followed to achieve the reliability target even when the project is still on-going providing a practical case study.

Participatory research to improve medication reconciliation for older adults in the community.

Medication reconciliation, a technique that assists in aligning a care team's understanding of an individual's true medication regimen, is vital to optimize medication use and prevent medication errors. Historically, most medication reconciliation research has focused on institutional settings and transitional care, with comparatively little attention given to medication reconciliation in community settings. To optimize medication reconciliation for community-dwelling older adults, healthcare professionals and older adults must be engaged in co-designing processes that create sustainable approaches. Academic researchers, older adults, and community- and health system-based healthcare professionals engaged in a participatory process to better understand medication reconciliation barriers and co-design solutions. The initiative consisted of two participatory research approaches: (1) Sparks Innovation Studios, which synthesized professional expertise and opinions, and (2) a Community Consultation Studio with older adults. Input from both groups informed a list of possible solutions and these were ranked based on evaluative criteria of feasibility, person-centeredness, equity, and sustainability. Sparks Innovation Studios identified a lack of ownership, fragmented healthcare systems, and time constraints as the leading barriers to medication reconciliation. The Community Consultation Studio revealed that older adults often feel dismissed in medical encounters and perceive poor communication with and among providers. The Community Consultation Studio and Sparks Innovation Studios resulted in four highly-ranked solutions to improve medication reconciliation: (1) support for older adults to improve health literacy and ownership; (2) ensuring medication indications are included on prescription labels; (3) trainings and incentives for front-line staff in clinic settings to become champions for medication reconciliation; and (4) electronic health record improvements that simplify active medication lists. Engaging community representatives with academic partners in the research process enhanced understanding of community priorities and provided a practical roadmap for innovations that have the potential to improve the well-being of community-dwelling older adults.

Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling

General conditions for organic reactions are important but rare, and efforts to identify them usually consider only narrow regions of chemical space. Discovering more general reaction conditions requires considering vast regions of chemical space derived from a large matrix of substrates crossed with a high-dimensional matrix of reaction conditions, rendering exhaustive experimentation impractical. Here, we report a simple closed-loop workflow that leverages data-guided matrix down-selection, uncertainty-minimizing machine learning, and robotic experimentation to discover general reaction conditions. Application to the challenging and consequential problem of heteroaryl Suzuki-Miyaura cross-coupling identified conditions that double the average yield relative to a widely used benchmark that was previously developed using traditional approaches. This study provides a practical road map for solving multidimensional chemical optimization problems with large search spaces.

Asteroid interception and disruption for terminal planetary defense

Modern techniques for planetary defense from comets and asteroids involve the deflection of the bolide via kinetic, gravitational, ablative, or radiative means. While potentially effective, none of these methods are capable of operating in a terminal interdiction mode wherethe threat is discovered with little time prior to impact. We present a practical and effective method for planetary defense which enables extremely short interdiction time scales, but can also operate within longer time scales and can be effective for extremely large threats. Called PI (“Pulverize It”), the method makes use of an array of hypervelocity penetrators which uses the kinetic energy of the asteroid or comet to disrupt it. In the terminal interdiction mode, the fragments of maximum ∼10 m diameter disperse laterally as they continue towards the Earth, and then enter the Earth’s atmosphere where they burn up as a series of airburst events which spatially and temporally de-correlate the energy of the original parent bolide for any arbitrary observer on the ground in the form of acoustical shockwaves and optical pulses. We show that terminal interdiction modes ranging from 2 minutes prior to impact for 20-meter class bolides (such as the Chelyabinsk asteroid), 1 day prior to impact for 100 m-class asteroids, 10 days prior to impact for Apophis-class asteroids (∼370 m), and even 60 days prior to impact for 1 km-class threats are all possible, though longer warning times are always preferred. Using only technologies readily available today, the PI method allows for a cost-effective and practical roadmap towards robust planetary defense capability.

Assessment of ideal smart network strategies for logistics companies using an integrated picture fuzzy LBWA–CoCoSo framework

PurposeNowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues.Design/methodology/approachThis study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature.FindingsAccording to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry.Originality/valueThis study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem.

A systematic review of e-learning systems adoption before and during the COVID-19

PurposeThis systematic review aims to assess the studies collected by identifying factors influencing the acceptance of e-learning systems before and during the current propagation of the COVID-19 pandemic.Design/methodology/approachThis study undertook a literature review on the in-depth revision of studies published before 2021. The reviewed research papers meet the inclusion and exclusion criteria. A total of 97 out of 214 articles met the inclusion criteria and were subsequently used in this review.FindingsThe findings revealed that the survey questionnaire is the most common data collection instrument used regardless of the research objectives. 2019 was a remarkable year because of the emergence of the COVID-19 pandemic.Research limitations/implicationsThis systematic review relied on specific databases (ScienceDirect, Emerald, IEEE and Google Scholar) to search for the articles included in this paper. However, these databases may not comprehensively represent all papers published on e-learning using the technology acceptance model (TAM).Practical implicationsThis paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers. This research spotlights the significant factors influencing the acceptance and adoption of e-learning.Originality/valueThis research assessed articles that examined the TAM in e-learning and classified them according to their methodology, country of dissemination, context and distribution within the year of publication. This paper contributes to the body of knowledge in a way that will benefit stakeholders in an educational setting.

Mapping the extent, range and nature of research activity on value-based healthcare in the 15 years following its introduction (2006–2021): a scoping review

ObjectivesWe aimed to systematically map the extent, range and nature of research activity on value-based healthcare (VBHC), and to identify research gaps.DesignA scoping review with an additional cited reference search...

THE ETHICAL IMPLEMENTATION OF ALGORITHM-BASED DECISION-MAKING: AN ANALYTIC ROADMAP TO EXAMINE ACCOUNTABILITY AND RESPONSIBILITY OF DESIGNING AND IMPLEMENTING AUDIT DATA ANALYTICS

This essay aims to manage the ethical issues of data and analytics in data-driven solutions. The proposed analytic roadmap emphasizes identifying potential root causes throughout the design and implementation process, from data collection to analytics output. The study adopts a futuristic approach to take proactive actions to manage the ethical issues at the beginning of the design. It concerns consequential ethics highly related to the analytical context. The interaction between emerging technology and the business context intensifies the uncertainty of data analytics’ consequences. The study theorizes eleven potential ethical dimensions from the technology level, artifact level, and application level. Then, a four-phase ethics assessment map is developed to evaluate and deal with these moral problems. The four stages include assessing the data source, training data selection, the algorithm’s traceability, and the output’s interpretation. The assessment guides a detailed discussion about handling “ethical laziness” to decrease the evidence’s entropy. One contribution of this study is that it offers a practical roadmap to solve the ethical issue in algorithmic accounting analytics, from raw data through the analytic output deployment.

The Hemophilia Gene Therapy Patient Journey: Questions and Answers for Shared Decision-Making.

PurposeThe anticipated emergence of hemophilia gene therapy will present people with hemophilia (PWH) and treating clinicians with increasingly complex treatment options. It will be critical that PWH and their families be empowered to participate fully in decision-making through transparent communication and the development of targeted educational resources.MethodsThe Council of Hemophilia Community (CHC) convened across a series of roundtable meetings to define the patient journey for hemophilia gene therapy, and to develop a question-and-answer style resource to guide discussion between healthcare professionals (HCPs) and their patients. Patient groups were also consulted during the development of this tool.ResultsThe CHC defined 5 key stages in the hemophilia gene therapy patient journey: pre-gene therapy (information-seeking and decision-making), treatment initiation, short- and long-term post-gene therapy follow-up. PWH will have different questions and concerns at each stage of their journey, which should be discussed with their HCP to aid decision-making. The resulting patient journey infographic and Q&A resource (see Supplementary Materials) has been developed for HCPs and PWH to provide a novel and practical roadmap of key issues and considerations throughout all stages.ConclusionThese resources support a collaborative, patient-centric, shared decision-making approach to inform treatment decision discussions between HCPs and PWH. The value of such discussions will be influenced by the language adopted; health literacy is a particularly important consideration, and these discussions should be accessible and tailored to PWH. HCPs and PWH can benefit from awareness of the common questions and uncertainties as they progress together along the patient journey. While the contents of this article are specific to hemophilia gene therapy, the concepts developed here could be adapted to aid patients in other disease states.

Evaluating Nebraska’s local comprehensive plans to achieve the national wetland conservation missions in the USA

ABSTRACT The U.S. federal government’s requirements and guidance for wetland conservation are reflected in a series of federal laws, regulations, and policies. However, the degree to which these requirements are reflected in local planning efforts is unclear. This study using five components with 56 indicators evaluates how well wetland conservation efforts are integrated into 112 local comprehensive plans in Nebraska, USA. The results show that the majority of local comprehensive plans pay little direct attention to wetland conservation, although many conservation efforts are conducted under the umbrella of environmental protection frameworks. The indicators include water resource protection received the highest score and was the descriptor of natural or environmental resources and resulted in the highest level of local awareness on natural assets. The indicator of setting goals for no net loss of wetlands received the lowest score among all indicators, demonstrating a clear gap between the national vision and the local reality of wetland conservation. Findings suggest local governments need more direct and proactive inputs to improve wetland conservation. Further findings from this research provide a practical roadmap for planners globally, particularly for the developing countries, to integrate wetland conservation into the local planning systems.

Hybrid joining of jacket structures for offshore wind turbines – Determination of requirements and adhesive characterisation

Due to the advantageous wind conditions, many new structures are planned offshore. The construction of offshore structures with ever increasing sizes requires new concepts to cope with the particular requirements thereof. One often overlooked possibility is adhesive bonding as a structural joining method, which upholds significant optimisation potential. This paper, the first in a series of two, illustrates the potential of adhesive bonding on the widely used jacket structure. For that, the structural concept is adapted towards ease of manufacturing, hybrid joints are defined, adhesives are selected according to requirements resulting from structural and climatic constraints, structural verifications performed, and the validation therefor presented in preliminary small-scale tests—which will be upscaled in the second part of this series. This paper thus serves as a roadmap for practitioners, and outlines the various steps to evaluate the potential of adhesive bonding in complex structures.

New Foundations: Principles for Disability-Inclusive Museum Practice

ABSTRACT This paper seeks to provide museum professionals with a practical road map to improving outcomes for people with disabilities in their museums. Written by a museum researcher with autism, this paper weaves museum research with interdisciplinary studies, while prioritizing the voices of people with disabilities, in order to develop clear, well-defined, and customizable steps for making the museum as an organizational unit more welcoming for people with disabilities. It examines several issues within the field, such as the overwhelming childhood focus of museum accessibility programming, the need to include people with disabilities in the process of creating inclusive practices, the importance of focusing on the larger picture as opposed to small issues, creativity in accessibility, and the dangers of performative accessibility and suggestions to avoid it, combining literature on each topic with the author's own knowledge of disability and museum accessibility.

Systematic Review of Authentication and Authorization Advancements for the Internet of Things.

Technologies for the Internet of Things (IoT) are maturing, yet no common standards dictate their direction, leaving space for a plethora of research directions and opportunities. Among the most important IoT topics is security. When we design a robust system, it is important to know the available options for facing common tasks related to access control, authentication, and authorization. In this review, we systematically analyze 1622 peer-reviewed publications from October 2017 to December 2020 to find the taxonomy of security solutions. In addition, we assess and categorize current practices related to IoT security solutions, commonly involved technologies, and standards applied in recent research. This manuscript provides a practical road map to recent research, guiding the reader and providing an overview of recent research efforts.

Anatomy of Spinal Venous Drainage for the Neurointerventionalist: From Puncture Site to Intervertebral Foramen.

CSF-venous fistula is a relatively novel entity that is increasingly being recognized as a cause for spontaneous intracranial hypotension. Recently, our group published the first series of transvenous embolization of CSF-venous fistulas in this journal. Having now performed the procedure in 60 patients, we have garnered increasing familiarity with the anatomy and how to navigate our way through the venous system to any intervertebral foramen in the cervical, thoracic, and lumbar spine. The first part of this review summarizes the organization of spinal venous drainage as described in classic anatomy and interventional radiology texts, the same works that we studied when attempting our first cases. In the second part, we draw mostly on our own experience to provide a practical roadmap from the puncture site to the foramen. On the basis of these 2 parts, we hope this article will serve to collate the relevant anatomic knowledge and give confidence to colleagues who wish to embark on transvenous spinal procedures.

Leveraging Twitter and its Unique #HashTag Capability: A Novel Social Media Resource From the European Hernia Society.

Background: Digital and Social Media (#SoMe) platforms have revolutionized the way information is shared, classified and accessed among medical professionals worldwide. The aim of this study was to review the hashtags used on Twitter by @EuroHerniaS to provide a practical roadmap for easier social media utilization for hernia surgery stakeholders. Methods: The hashtags used in tweets and retweets of the @EuroHerniaS Twitter feed were collated since its foundation in November 2016. Results: The first hashtag used was #HerniaSurgery. Since foundation to July 2021, the @EuroHerniaS Twitter feed has used 90 separate hashtags. The number of new hashtags per year was increasing leading to the development of an online library. The increasing diversity of hernia related hashtags allows for the more detailed posting and searching of hernia related information on the #SoMe platform Twitter. Conclusion: The more detailed use of hashtags on Twitter is to be encouraged. Hernia surgeons can make use of them both when posting and reviewing posts to aid the categorization of posts.

Predicting liver cancers using skewed epidemiological data

Liver Cancer is a threat to human health and life over the world. The key to reduce liver cancer incidence is to identify high-risk populations and carry out individualized interventions before cancer occurrence. Building predictive models based on machine learning algorithms is an effective and economical way to forecast potential liver cancers. However, since the dataset is usually extremely skewed (negative samples are much more than positive samples), machine learning models suffer from severe bias and make unreliable predictions. In this paper, we systematically evaluate existing approaches in tackling class-imbalance problem and introduce two undersampling methods. The first is based on K-means++, where robust clustering centers are appointed as negative samples. The second is based on learning vector quantization, which considers diagnostic labels during clustering, and the prototypes are used as negative data. In this way, positive and negative samples are rebalanced. The algorithm is applied to five-year liver cancer prediction in Early Diagnosis and Treatment of Urban Cancer project in China. We achieve an AUC of 0.76 when no clinical measure except for epidemiological information is used. Experimental results show the advantage of our method over existing oversampling, undersampling, ensemble algorithms, and state-of-the-art outlier detection algorithms. This work explores a feasible and practical roadmap to tackle skewed medical data in cancer prediction and benefits applications targeted to human health and well-being.