Narrow Results

This paper examines the creative approaches to labor education by looking at them through the prism of educational and technical advancements. It tackles the current issue of insufficient worker preparation for the complexity of contemporary workplaces caused by antiquated educational methods. There is a widening skills gap since traditional labor education has a hard time keeping up with the changes. Labor Education based on Digital Technologies (LE-DT) is proposed as a solution to this problem in this paper. To make labor education more engaging, accessible, and relevant to today’s workers, LE-DT uses digital technologies and platforms to transform its delivery. Learners’ engagement, retention, and skill development may be improved by the use of multimedia materials, interactive simulations, virtual reality experiences, online courses, and LE-DT. Personalized learning paths, remote collaboration tools, gamified learning modules, and virtual apprenticeships are a few of the many uses of LE-DT covered in the paper. In doing so, it prepares employees for the challenges of the contemporary workplace by bridging the gap between classroom learning and real-world application. The paper evaluates the efficacy of LE-DT in enhancing learning outcomes, boosting labor productivity, and encouraging lifelong learning habits by presenting results from its deployment in various scenarios. Job rates, organizational performance indicators, learner happiness, and skill mastery are some of the evaluation measures.

Digital technologies sustain today’s world. Every part of the world is working towards digital technologies, which none of us can eliminate. Enormous growth is achieved only by unexpected acceleration by digital technologies, including the Internet of Everything (IoE), Artificial Neural Networks (ANN), Machine Learning (ML), Internet of Things (IoT), Artificial Intelligence (AI), Deep Learning (DL), and many more. These technologies started occupying all the engineering sectors, including manufacturing. This paper focuses on tribology analysis related to manufacturing concerning various digital manufacturing technologies. The paper narration includes Tribology using digital technologies wherein the journals and patent landscape analysis abet them. In trend, Tribology utilizes all these technologies today and envisages its growth with the predominant technological invention in the border view. The survey of various literature reveals that only three digital technologies, including AI, ML, and ANN, are used by tribologists around the globe. Other Technologies like Evolutionary Algorithm (EA), Support Vector Machine (SVM), and Adaptive Neuro-Fuzzy Interference Systems (ANFIS) are not used predominantly.

This paper aims to discover key performance indicators (KPIs) influencing digital skill transformation in global IT service firms, reveal its unique features, and assert the effect of these KPIs on firms’ digital skill transformation and knowledge management initiatives. This research is mainly based on primary data. The researcher started data collection by conducting a Focused Group Discussion (FGD) with subject matter experts (SMEs), followed by in-depth personal interviews with the key organisational individuals. Then, a primary survey is carried out using a qualitative questionnaire across all the existing employees of the largest business unit of a global IT service firm. Findings suggest that Total IT Experience (EXP), Reading Time (RT), Effective Mentoring (EM), and Training Effectiveness (TE) primarily impact employees’ digital skill transformation. Besides, the technical capability and understanding of existing employees’ supervisors or managers directly correlate with the project environment, which in turn impact employees’ effectiveness during their digital skill transformation journey.

Innovation scholars have long studied how and why new products and services diffuse into the market following trajectories such as the S-curve and in accordance with epidemic, social, and information cascade models. However, we see today many new products and services, especially those enabled by digital technologies, which do not seem to fit the above-mentioned trajectories and models due to the incredibly high speed and virulence at which they diffuse. Moreover, the diffusion of these innovations does not seem to depend, contrary to what the previous patterns of innovation diffusion argue, on their technological characteristics or on demand-side factors, such as the word-of-mouth effect or the feedback they receive from their early adopters. Rather, their diffusion seems to be affected by the characteristics of the business model adopted by the companies that have created and commercialized them into the market. Accordingly, our study analyzes through the historical research methodology the business model of a sample of 50 Unicorn tech-companies, which have experienced incredibly fast diffusion rates and business growth and are disrupting entire industries. The outcome of our study is a framework that maps two business model configurations that explain the role of different business model design and innovation choices in the diffusion of new products and services enabled by digital technologies.

Digital technologies are bringing a wide spectrum of business opportunities as well as significant organizational challenges for incumbent companies operating in traditional industries such as the energy one. The diffusion of new technologies is changing the way energy solutions are consumed and experienced, while consumers increasingly take ownership of their consumption, acting as “prosumers”. In this evolving scenario, incumbents are urged to reshape their business models, explore new opportunities and change their organizational structures accordingly. Still, the required organizational re-design process that enables companies to undergo business model innovation (BMI) while exploiting digital technologies is partially neglected in literature. Hence, this study explores how established companies embrace organizational re-design process to innovate their business model. To this end, we leverage a single case study methodology focused on an incumbent energy company. Our findings show how the establishment of a business unit dedicated to digital technologies exploitation has enabled the company’s BMI. More specifically, we point at the critical role played by the know-how and the industrial capabilities to sustain not only the innovation activities of the new business unit, but also the overall company performance and the shift towards a renewed business model.

As the recent COVID-19 pandemic crisis has shown, global supply chains and value adding networks are vulnerable to changes on the economic, business, technological, and social environment. Therefore, there is a need of facilitating and transforming supply chains in a more efficient, resilient, and sustainable way. The aim of this paper is to analyze the importance and the impact of digital technologies to the transformation of supply chain management, through an examination of potential use cases and implementation strategies and under a methodological framework related to the supply chain operations reference (SCOR) model, which is connected to the principles of lean thinking.

Given a mismatch between traditional paths and the opportunities resulting from new digital technologies, the aim of this paper is to understand why companies’ digital transformation may fail even before it starts. We analyze interviews with 20C-level managers from 15 traditional DAX-listed German companies that face digital transformations. Our objective is to integrate the different areas that have been studied in the field of digital transformation. We offer top management teams standpoints, as they concern how business decisions, including digital-transformation decisions, are made. We review the role of top management in digital business model innovation and identify value creation, leadership challenges, and culture development as the main factors that support or hinder business model innovation in a digital world. We further show that taking outside-in perspectives, implementing cross-sectional strategies, and having transformational capabilities represent important drivers on business model innovation. Employees are the most important factor. They should be brought in and guided by top managers to support the digital transformation. The patterns we identify might provide guidance for top managers engaging in digital business model innovation.

Digital ventures are flooding the healthcare market in Germany and setting new standards for innovative digital health systems and tools. A key challenge in this sector from both academic and practitioner perspectives remains the intransparency of business model configurations applied by digital health. We tackle this problem by conducting a comparative case study of 237 digital health ventures. These ventures are examined on the business model level, exploring the digital technology components of each company and relating them to the identified areas of activity. The resulting dominant combinations of the two dimensions highlight four key areas of activity and two technological core elements. Within these dominant combinations we identify intriguing configurations of business model activities. The dominant Software(-as-a-Service) logic supports the criteria of interoperability on different levels. This research contributes to the growing academic literature stream of digital technology and entrepreneurship in healthcare.

The increasingly digital business landscape has created manifold novel opportunities as well as threats to traditional business models. In consequence, a broad variety of digital business models emerged. Powerful tools and managerial guidance on how to shape digital strategies in this volatile and uncertain terrain are sought-after, but remain rare. Building on an analysis of the world’s top-1.000 venture funded technology startups over the last decade, we identify 49 novel business model types that describe firms as vendors of digitally enabled products and services, as providers of resources and capabilities for digital business, and as facilitators of intermediation. Furthermore, we identify the novelties of these digital business models types in their components, i.e., value proposition as well as their value creation, delivery, and capture processes. The result is a recipe collection of novel mechanisms to guide and inspire other firms when commercialising digital technologies in their business models.

In today’s rapidly evolving workplace, continuous technological advancements are reshaping organisational dynamics and employee interactions. This study examines the adoption of Artificial Intelligence (AI)-enabled technologies for transforming Human Resource Management (HRM) processes within organisations. We conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, analysing 57 papers out of 238 sourced from the Scopus database. Our findings highlight AI’s significant research focus in recruitment and performance management, with additional applications in learning and development, and reward and recognition management. Drawing from the literature review and building on technology adoption models, we develop a framework to promote AI integration in HRM. We discuss how AI can improve core HR functions and outline critical success factors for its effective implementation.

This study examines the role of e-entrepreneurship in fostering the future economy, with a specific focus on Saudi women entrepreneurs. The emergence of digital technologies and the internet has opened up new opportunities for entrepreneurship, especially for women facing traditional barriers to business participation. In particular, the Kingdom of Saudi Arabia (KSA) has witnessed many women entrepreneurs who leverage e-commerce platforms to establish and grow their businesses. Combining e-entrepreneurship with environmental conscience depicts a future in which sustainable development and economic prosperity coexist. This research will explore the motivations, challenges, and strategies employed by Saudi women entrepreneurs in the e-commerce sector and analyse the impact of their entrepreneurial activities on the future economy. The study followed a quantitative and post-positivist approach. Data were collected cross-sectionally from the women working in different start-ups in the big cities of KSA. The study adopted the systematic random sampling approach to reach the respondents. A total of 500 questionnaires were distributed. However, 388 were included for analysis after the screening process. The findings reveal that e-entrepreneurial significantly impacts women’s entrepreneurial and economic growth. Moreover, Entrepreneurial self-efficiency significantly mediates the relationship between women’s entrepreneurial and economic growth. The findings comprehensively understand complex dynamics and guide future research and practical applications in related domains. Furthermore, the study found that Saudi women entrepreneurs should receive financial and technical support to initiate their ventures. Moreover, policy recommendations of the study demand addressing cultural barriers and fostering an enabling environment for their entrepreneurial endeavours.

The study aims to scientifically substantiate the application of the scenario approach in predicting the development of the agri-food sector in rural areas. The conceptual novelty of the study is that it develops a scenario forecasting algorithm for the development of the agri-food sector of rural areas in the digital economy. It also clarifies methodological approaches and recommendations for forecasting production volumes of certain agri-food products at the zonal level. The paper shows that digitalization is one of the critical factors that directly ensure an increase in agribusiness efficiency in the current conditions in agriculture. An assessment of the impact of digital transformation processes on the activities of agricultural producers is given, and the advantages of using modern digital technologies in the agricultural sector are highlighted. Furthermore, the results of scenario forecasting of production volumes of agri-food products by farms of all categories are presented in the example of the non-black soil zone of the Republic of Bashkortostan. The study’s preliminary results are as follows: the world experience in scientific research on the use of digital technologies in the activities of agricultural producers was generalized.

Sustainable development has been putting pressure on companies to act in favor of sustainability. To overcome such forces, we evidenced performance through operations that offer opportunities to obtain economic, environmental, and social performance and, thus, should become the organization’s central area and the driving force behind the strategy. It is noteworthy that to achieve such performance, Industry 4.0 technologies can be used as resources, and they have the potential to generate capabilities for meeting sustainable objectives. Thus, this research has as its main objective to propose a sustainable operations strategy model based on digital technologies. Grounded by the classic view of operations strategy and using the ProKnow-C method, a first effort was made to raise performance objectives in the economic, environmental, and social dimensions as well as criteria that assess digital technologies. As result, regarding the economic performance objectives, the five traditional objectives were maintained. In the environmental dimension, the following were pointed out: consumption of natural resources, emissions, waste and reverse management, and environmental regulation. In the social dimension, the following stood out: exposure to occupational risk agents and both internal and external engagement. About criteria that assess digital technologies, the degree of automation, connectivity, and scalability besides feasibility, vulnerability, and acceptability were framed, remaining in alignment with classic theory. Finally, it was proposed a change of view on the area of process technology, which arises much more as support influencing and enhancing the other areas.

Digitalization has significantly shifted technology-driven processes, products, services, and business models. This revolution envisions an era in which smart machines can transfer information to automatic manufacturing and production lines, evaluate and grasp specific production difficulties, and solve them with the minimum human intervention. Previously, this revolution was thought to disrupt the manufacturing sector mainly. Therefore, their integration and advancement would influence retailers, distributors, operational organizations, and service providers. This paper assesses how digital supply chains (DSC) are evolving to cater to the needs of Industry 4.0. This literature-based research approaches the broad topic of DSC using bibliometric techniques and network analysis tools using software like Gephi and VosViewer — our study’s data from 2002–2024 from journal databases like Scopus and Google Scholar. Aside from the demands and trends driving supply chain digitalization, digital transformation trends and the changing business environment add challenges and risks. Implementing IT technologies significantly impacts the whole supply chain in order to compete in today’s dynamic and competitive business environment. Increased openness across the whole process, from order dispatch to product end-of-life, depends on collaboration between suppliers, manufacturers, and consumers. Industry 4.0 promotes big data, Internet of Things (IoT) and Artificial Intelligence (AI). Therefore, the urgency and importance of theoretical methods and empirical studies are needed to help businesses establish successful and long-lasting Industry 4.0 supply chains while quickly adapting to continuously changing markets and technology, which can be easily possible through the broad study of the previous study that has been conducted in the past. This study allows for a thorough review of the discipline’s current state and future directions, highlighting significant contributions, emerging trends, and areas requiring additional research that will be helpful for future researchers and policymakers.

Healthcare 4.0 (H4.0) is revolutionizing the way hospitals are managed, bringing innovations to the health service. Therefore, this work proposes the use of drivers aimed at hospital management improvement through H4.0 grounded in a Content Analysis. It resulted in 36 booster elements for hospital management grouped into five drivers: Process management, Data management, Resource management, Patient management, and Assistance and Development of Healthcare Professionals. These drivers contribute to strengthen the link between the main needs of hospital settings and technologies capable of meeting them in an applied manner. The most significant scientific contribution of this work lies in deepening and extending the recent block of knowledge on integrating hospital management with H4.0 technologies. Future studies should investigate the application of H4.0 technologies to assist in managing environmental, social and economic sustainability aspects of hospital settings.

In recent years, we have been living through two epochal transformations in business: the new approach to sustainability and digital transformation. In this chapter, we analyse how these two phenomena intersect. To tackle this research question, we first discuss the opportunities and the limits of the energy efficiency sector, specifically referring to the role of green investments and the challenges of Energy Service Companies (ESCos). Thereafter, we introduce the leading technologies of the digital–financial revolution and illustrate the main features that characterise fintech, especially highlighting the role of blockchain and tokenisation in the energy efficiency sector. Through the analysis of the EFFORCE case, we highlight how in practice fintech and blockchain are supporting the crossing of certain limits of the energy efficiency sector and sustaining green investment.

Innovating organizations are adopting and quickly implementing the open innovation (OI) approach for developing new products and services. There is a growing need to improve the process, to achieve faster and better outcomes. The integration of disruptive digital technologies (DTs) into the innovation processes bolsters the development of new business models, innovation processes, and ecosystems. However, there is limited information regarding the management of a digitalized OI process, and the role of different DTs across the stages of the innovation process. A conceptualized framework has been established, which integrates different DTs, and maps them across the stages of the OI process. The framework identifies the links between different dimensions and attributes of different DTs, such as big data, the IoT, cloud computing, artificial intelligence, blockchain and social media, and the stages of the OI process. The framework also provides a consolidated approach for understanding the benefits and challenges of different DTs across the OI process.

We are bombarded with buzzwords such as disruption, digitalization and the sharing economy, and the trending technologies that fuel them — the Internet of Things, big data, and artificial intelligence. Simultaneously, we see whole industries being shaken to the core and rearranged into new patterns by new players. In this chapter, we posit that a new business model, the disruptive ecosystem, is at the core of this movement.

The disruptive ecosystem is a paradigm that is capable of absorbing the power of digital technologies and combining them with the business model and innovation theory. We believe this new business model is the common denominator between companies like Apple, Facebook, Samsung, Uber, Google, Tesla, and Amazon. We will present how a disruptive ecosystem looks like, and how and where disruptive, open and combinatorial innovation happens in these two-sided business models and ecosystems. This chapter also includes practical examples from industry.

Challenging tasks are essential in developing and demonstrating mathematical understanding. They provide opportunities to learn and the motivation for student to engage with learning. This chapter highlights how the real-world and digital technologies provide many opportunities to design and implement challenging tasks for all learners. The affordances of technology-rich teaching and learning environments need more attention if teachers and their students are to be better enabled to maximise opportunities for learning mathematics. A range of tasks are presented and discussed. Planning by teachers for varied student responses is critical in enabling ‘as needed’ in-the-moment scaffolding to keep students engaged with mathematical thinking.

I focus here on several aspects of cultures related to digital technologies and mathematics education. One first aspect is that any integration of digital technologies for mathematical (or other) teaching and learning creates and transforms the classroom culture. On the other hand, in order for learning to be meaningful through the use of digital technologies, these may need to be embedded in a certain “culture” that empowers students to engage pro-actively with those technologies. I present different types of teaching and classroom “cultures” that have been found when using digital technologies, how these impact mathematical learning, as well as different conditions and teacher-training opportunities for the use of digital technologies found in different countries, illustrating all of these with examples from my own experience and from literature. I discuss how the different conditions and access opportunities in different regions and cultures create digital gaps. Finally, I discuss what could be done to support teachers to create meaningful contexts and classroom cultures when integrating digital technologies within established school systems (but at the same time transforming these), so that these can empower learners (e.g., to “do mathematics”) and promote the construction of knowledge.