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Today humanity is facing a time period, in which the speed and rate of change in different fields are faced. The rapid and effective change in the technological, economic, military, social and cultural fields all over the world in recent years has had important results in many topics such as informatics, interactive communication, production, data production and sharing and forms of consumption and perception. Changes and developments at very high speeds and rates affect the personal life, social life and work life in a deep manner, especially after the 1980s, paving the way for many concepts such as globalization, Industry 4.0, digitalization, new economy, new world order and digital transformation age to be the leading variables in every field of social sciences.

Production, consumption and communication forms at the global level are becoming more and more in depth and predicting the future is becoming more and more difficult and valuable. Understanding, analyzing and predicting the future for national and international companies and organizations directly and indirectly affect all economic, military and political variables. At this point, competition stands out as one of the most critical concepts for survival and growth for profit-oriented companies.

Based on this, the topics and contents selected in this study were created to cover the field of management and strategy. Indeed, in this study, the concept of organizational agility is explored theoretically from a historical perspective on the concept of Industry 4.0 and especially emphasized the dimensions and components of agility used in today’s world.

Within the scope of this study, the aim is to define and present the general framework of the Industry 4.0 and agile firms, which aim to combine the conceptual and theoretical infrastructure with the implementation of the agile firms within the field. In this respect, the study defines the situation coming from the past together with the world of today in the relationship of the technological and economical dimensions of globalization with the digitalization and latest theoretical view for the agile firm’s structure and management. On the other hand; in this study, the possible effects of the recent COVID-19 pandemic crisis on the management of organizations are interpreted in the context of Industry 4.0 and agile companies. This aim will provide a foresight for the future periods, with the conclusions added with the theory of senism, which present the dominant value of the study.

Artificial neural networks (ANNs), which represent computational models simulating the biological neural systems, have become a dominant paradigm for solving complex analytical problems. ANN applications have been employed in various disciplines such as psychology, computer science, mathematics, engineering, medicine, manufacturing, and business studies. Academic research on ANNs is witnessing considerable publication activity, and there exists a need to track the intellectual structure of the existing research for a better comprehension of the domain. The current study uses a bibliometric approach to ANN business literature extracted from the Web of Science database. The study also performs a chronological review using science mapping and examines the evolution trajectory to determine research areas relevant to future research. The authors suggest that researchers focus on ANN deep learning models as the bibliometric results predict an expeditious growth of the research topic in the upcoming years. The findings reveal that business research on ANNs is flourishing and suggest further work on domains, such as back-propagation neural networks, support vector machines, and predictive modeling. By providing a systematic and dynamic understanding of ANN business research, the current study enhances the readers' understanding of existing reviews and complements the domain knowledge.

Introduction: Healthcare facilities have witnessed deterioration, limited employee engagement, and communication gaps due to a lack of wireless technology. The Internet makes work and life quicker and more intelligent. The Internet of Things (IoT) is a scheme of interconnection equipped with unique identifiers in recent years. Artificial intelligence (AI) and IoT advancement allow employees to develop competent and predictive services and solutions in human resource (HR) practices. This chapter has been formulated to summarise and classify the existing research and better understand the past, present, and future of employee engagement by improving IoT interrelated devices in the healthcare industry.

Purpose: This study aims to categorise and overcome the challenges involved in HR practices. Effectively embracing IoT application-connected devices in the healthcare industry can enhance human resources management’s (HRM) role and measure performance assessment to improve employee engagement and productivity.

Methodology: In this study, the authors develop propositions dependent on a theory-based review. A systematic analysis was applied to minimise the challenges of HRM. The subject-related articles from different journal sources, like Scopus, Emerald, Web of Science, Springer, etc., were analysed based on engagement criteria. It was graphically recorded in a collective and informative way to emphasise the review outcomes. The study has presented the positive impacts of AI and IoT on engagement in health care.

Summary: This chapter accumulated theory-based knowledge about healthcare employee engagement and how IoT-based technology like AI can optimise employees’ engagement effectively. Further, it draws comparative benefits for a workforce to execute performance advancements and create future progressive aspects for healthcare employees.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Contextualizing grammar in second language (L2) classrooms implies making grammar constructs relevant to the learners’ world; affording learners the opportunities to better comprehend and apply these concepts in their own milieus. This instructional design (ID) has been devised to contextualize grammar and to explore learner engagement of pre-service English teachers through Computer-Aided Learning (CAL) and Task-based Learning (TBL) in a technology-driven learning environment. CAL encompasses technology-aided discussions, multi-media presentations, online tests and exercises, and social media deployment. TBL, on the other hand, contextualizes grammar using technology and social network in planning, executing, and presenting four assigned tasks: picture essay, brochure design, dialogue composition, and comic strips illustration. Facebook is the e-portfolio of the class, archiving all group and individual output. The CAL-TBL tandem is propelled by group initiatives and class collaboration evident in group discussions and planning, microteaching, task presentations, peer reviews, and self-evaluations. These initiatives engage learners; empowering students to collaboratively take active part and responsibility for their own learning. The three-hour-class meets every week in a computer laboratory. The post-semester feedback and online poll course design review as well as the University Course Evaluation comments have shown that the ID, from the learners’ perspective, is effective in contextualizing grammar and in engaging learners.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

New computer-assisted techniques for visualizing data are evolving in a number of areas in transportation. For example, in engineering, 3D visualization and microsimulation techniques are being applied for the identification and evaluation of geometric and operational solutions for improving visually impaired pedestrian access to roundabouts and channelized turn lanes. For planning, visualization is being used for corridor analysis. Data visualization is being used as a tool for improving decision-making within transit agencies, as well as a tool for understanding truck trip generation on highways. Many of these new techniques take advantage of archived intelligent transportation systems (ITS) data. Examples of other innovative data sources include global positioning systems (GPS), geographic information systems (GIS), computer-aided design (CAD), and a variety of visualization tools available for use with travel survey data. As these various techniques and software applications move forward, consideration needs to be given to how the “lessons learned” from these applications can facilitate the use of data visualization techniques for travel survey data analysis and decision-making.

The chapter deals with the promotion of competitiveness of national producers as compared to the main leaders in the industry.

The system management of the process of creating and mastering the production of a new product is based on effective change management, development of organizational and technical management systems, business-to-business interaction systems, business solutions relating to product creation in the industry. Systemization of problems and identification of ways of development of theory and methodology of creation of a new product by the domestic manufacturing companies can be performed by means of implementation of continuous acquisition and life cycle support (CALS) systems.

Today, the fundamental conceptual basis for the formation of information space of an enterprise and application of miscellaneous information systems is the concept of continuous information support of products throughout the entire life cycle – CALS. According to this concept, one can single out the following major objectives which are essential for an enterprise and can be achieved through information technologies: the automation of production management which was conventionally achieved through the use of MICS systems, and today it is achieved due to the use of the so-called ERP/CRM/SCM systems; product data management and automation of design and engineering analysis of structures and processes (PDM/PLM, CAD/CAM/CAE-system); information support of operation and aftersales service, integrated logistic support of products. The information technologies at the present stage are a prerequisite for achieving a competitive advantage by an enterprise, particularly if the enterprise is specialized in the production of high-technology products. The major purpose of information technologies at the enterprise is the maximum effective support of design processes, production processes and other processes running at the enterprise, creation of the information basis which enables the management to take decisions which help the enterprise to achieve a dominant position in the industry sector. For Russian companies, the problem of implementation and effective employment of CALS-technologies as a means of cardinal improvement in quality and competitiveness of science-intensive products, discussed in the chapter, is extremely topical.

For many companies, the employment of these technologies largely determines the ability to survive in the context of an intensifying competitive struggle in the domestic market and can be considered as an indispensable condition for maintaining and expanding the sales of products on the international market.