New Trends in Development of Services in the Modern Economy

The services sector strategic development unites a multitude of economic and managerial aspects and is one of the most important problems of economic management. Many researches devoted to this industry study are available. Most of them are performed in the traditional aspect of the voluminous calendar approach to strategic management, characteristic of the national scientific school. Such an approach seems archaic, forming false strategic benchmarks. The services sector is of special scientific interest in this context due to the fact that the social production structure to the services development model attraction in many countries suggests transition to postindustrial economy type where the services sector is a system-supporting sector of the economy. Actively influencing the economy, the services sector in the developed countries dominates in the GDP formation, primary capital accumulation, labor, households final consumption and, finally, citizens comfort of living. However, a clear understanding of the services sector as a hyper-sector permeating all spheres of human activity has not yet been fully developed, although interest in this issue continues to grow among many authors. Target of strategic management of the industry development setting requires substantive content and the services sector target value assessment

Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

ARTIFICIAL INTELLIGENCE IN WORKPLACES AND HOW IT WILL AFFECT EMPLOYMENT IN LATVIA

Already, artificial intelligence (AI) is all around us, from self-driving cars and drones to virtual assistants and software that translate or invest. Impressive progress has been made in AI in recent years, driven by exponential increases in computing power and by the availability of vast amounts of data, from software used to discover new drugs to algorithms used to predict our cultural interests. Digital fabrication technologies, meanwhile, are interacting with the biological world on a daily basis. Engineers, designers, and architects are combining computational design, additive manufacturing, materials engineering, and synthetic biology to pioneer a symbiosis between microorganisms, our bodies, the products we consume, and even the buildings we inhabit. Companies in the technology, media, and telecommunications industry expect AI to have a significant impact on product offerings in the next five years. This research contains the data from a pilot survey from Latvian business executives’ expectations for AI and robotics for the next 5 years. The aim of this research is to find out if AI and robotics will make significant impact on workplaces in Latvia in the next five years

Exploring the influence of industry 4.0 technologies on the circular economy

In the last decade, both Industry 4.0 technologies and the circular economy have expanded exponentially and they have received epistemological attention. However, there is a lack of studies about the influence that each of these technologies has on the main areas of action covered by the circular economy. This study responds to this gap by investigating the influence of the major technologies: Additive Manufacturing, Artificial Intelligence, Artificial Vision, Big Data and Advanced Analytics, Cybersecurity, Internet of Things, Robotics, and Virtual and Augmented Reality on the main areas of action covered by the circular economy. Namely, reduction of inputs consumption, reuse, recovery, recycling and reduction of waste and emissions. An initial study, based on a survey of 120 project managers, and a multiple case study of 27 projects, through 31 personal interviews and review of internal and external documentation have been conducted in order to investigate the real influence of each technology on the circular economy. Overall, the results confirm the existence of a wide range of influences that Industry 4.0 technologies offer to companies for improved circularity. These improvements are mainly related to reduce material and energy consumption, and waste and emissions generation. However, there are important differences between the potential impacts of each technology. In particular, there is most evidence of the positive impact of additive manufacturing and robotics. Likewise, the results obtained suggest the need to continue exploring the new impacts generated by the continuous development and integration of technologies.This study was funded by the Basque Autonomous Government (Research Group GIC 15/176) and the project METASTANDARDS, funded by the Spanish Ministry of Science, Innovation and Universities, the Spanish State Research Agency (AEI). We also acknowledge the technical and human support provided by Circular Economy UniversityCompany Classroom (Faculty of Engineering Gipuzkoa, UPV/EHU, Provincial Council of Gipuzkoa)

Bridging the divide: new evidence about firms and digitalisation. Bruegel Policy Contribution Issue #17 December 2019

Using new evidence on the digitalisation activities of firms in the European Union and the United States, we document a trend towards digital polarisation based on firms’ use of the latest digital technologies and their plans for future investment in digitalisation. A substantial share of firms are not implementing any state-of-the-art digital technologies and do not have plans to invest in digitalisation. However, there is also a substantial share of firms that are already partially or even fully implementing state-of-the-art digital technologies in their businesses and that plan to further increase their digitalisation investments. Small Manufacturing firms and old small firms in services are significantly more likely to be and remain non-active in terms of digitalisation. Our results do not provide any evidence that EU firms are more likely than their US counterparts to be stuck on the wrong side of the digitalisation divide. Taking into account firm size and firm age, there are no significant differences between the EU and the US in terms of having more or fewer persistently non-digital firms. As persistently digitally-inactive firms are also less likely to be innovative, to add employees or to command higher mark-ups, it is important for policymaking to remove barriers that trap these firms in persistent digital inactivity. Lack of access to finance is a major barrier for EU firms compared to their US counterparts, particularly for the EU’s persistently non-digital firms, and especially for older, smaller companies in services. Improving their access to finance might therefore go a long way towards addressing the corporate digitalisation divide in the EU

The Academy of Dental Materials: Providing roots and wings.

ObjectivesThe long history of the Academy of Dental Materials (ADM) is documented with its strategies (a) to rapidly communicate science among its members, (b) to establish special awards to stimulate new science, and (c) to develop new dental materials scientists.MethodsWe searched the history of the last 35 years of the ADM newsletters, transactions, journals, and officer notes. We document the (a) presidents, (b) meeting history, (c) membership growth, and (d) development of special awards through 2019 with the recent creation of the ADM Marshall Post-Doctoral Award.ResultsThere are 36 years of recent ADM history, 42 international meetings, membership growth to 400 individuals from 15 countries, service of 19 presidents, Paffenbarger annual Awardees since 1989, induction of >200 fellows, and recognition of the first winner of Marshall Post-Doctoral Award in 2018. New directions for recruiting members are suggested. Three potential new thrusts for the organization are presented: artificial intelligence, genetic engineering, and intensive member mentoring.SignificanceThese suggestions for the ADM provide a path for the ADM to continue to adapt to the ever changing scientific landscape

Employing Explainable Artificial Intelligence (XAI) Methodologies to Analyze the Correlation between Input Variables and Tensile Strength in Additively Manufactured Samples

This research paper explores the impact of various input parameters, including Infill percentage, Layer Height, Extrusion Temperature, and Print Speed, on the resulting Tensile Strength in objects produced through additive manufacturing. The main objective of this study is to enhance our understanding of the correlation between the input parameters and Tensile Strength, as well as to identify the key factors influencing the performance of the additive manufacturing process. To achieve this objective, we introduced the utilization of Explainable Artificial Intelligence (XAI) techniques for the first time, which allowed us to analyze the data and gain valuable insights into the system's behavior. Specifically, we employed SHAP (SHapley Additive exPlanations), a widely adopted framework for interpreting machine learning model predictions, to provide explanations for the behavior of a machine learning model trained on the data. Our findings reveal that the Infill percentage and Extrusion Temperature have the most significant influence on Tensile Strength, while the impact of Layer Height and Print Speed is relatively minor. Furthermore, we discovered that the relationship between the input parameters and Tensile Strength is highly intricate and nonlinear, making it difficult to accurately describe using simple linear models