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This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

Since the onset of the COVID-19 pandemic in China, student engagement in online learning has been a critical issue for all educational institutions. The university student engagement inventory (USEI) is the most used scale for assessing the construct of student engagement. The present study aimed to evaluate the psychometric properties of the USEI among 1504 Chinese university students who completed a survey through an online platform between December 2020 and January 2021.

In this cross-sectional study, content validity, construct validity and reliability of the scale were assessed.

The results supported the three-factor model with acceptable goodness of fit (χ² (71) = 369.717, p = 0.13, χ²/df = 5.207, comparative fit index (CFI) = 0.967, normed fit index (NFI) = 0.960, Tucker–Lewis index (TLI) = 0.958, standardized root mean square residual (SRMR) = 0.030, root mean square error of approximation (RMSEA) (90% CI) = 0.053 [0.049, 0.057]), good internal consistency and construct reliability (Cronbach's alpha and omega coefficient >0.70) and strong convergent validity. Also, the measurement invariance was confirmed across gender.

This study showed that the 3-factor structure of USEI with Chinese university students had good construct validity, internal consistency and reliability. It could help measure student engagement in online learning in China.

Nonlinear solution approaches for inverse problems require fast simulation techniques for the underlying sensing problem. In this work, the authors investigate finite element (FE) based sensor simulations for the inverse problem of electrical capacitance tomography. Two known computational bottlenecks are the assembly of the FE equation system as well as the computation of the Jacobian. Here, existing computation techniques like adjoint field approaches require additional simulations. This paper aims to present fast numerical techniques for the sensor simulation and computations with the Jacobian matrix.

For the FE equation system, a solution strategy based on Green’s functions is derived. Its relation to the solution of a standard FE formulation is discussed. A fast stiffness matrix assembly based on an eigenvector decomposition is shown. Based on the properties of the Green’s functions, Jacobian operations are derived, which allow the computation of matrix vector products with the Jacobian for free, i.e. no additional solves are required. This is demonstrated by a Broyden–Fletcher–Goldfarb–Shanno-based image reconstruction algorithm.

MATLAB-based time measurements of the new methods show a significant acceleration for all calculation steps compared to reference implementations with standard methods. E.g. for the Jacobian operations, improvement factors of well over 100 could be found.

The paper shows new methods for solving known computational tasks for solving inverse problems. A particular advantage is the coherent derivation and elaboration of the results. The approaches can also be applicable to other inverse problems.

This study aims to explore the relationship between work–life balance and employee retention by examining the mediating role of psychological empowerment among software firms based in India.

The study collected 283 responses by using a structured questionnaire and interview method. Structural equation modeling (SEM) was used to validate the hypothesized research model for examining the consistency and sturdiness of the study variables by applying AMOS 20.

The result reveals that psychological empowerment partially mediates the relationship between work–life balance and the retention of professionals. This indicates that a high degree of psychological empowerment strengthens the relations between work–life balance and the retention of professionals.

The research outlined a best-fit model of psychological empowerment as a partial mediator among work–life balance and the retention of professionals. The study presents a set of sensible and practical aspects where work–life balance and retention of professionals can aid in developing and generating commitment to the organization which could offer new insights for software professionals, managers and practitioners.

This study emphasized that psychological empowerment helps in enhancing dedication, loyalty, integrity, allegiance and trustworthiness among employees, thus playing a role between work–life balance and the retention of professionals.

The purpose of this paper was to assess the economic impact of investment in different animal welfare–enhancing flooring solutions in Swedish dairy farming.

The authors developed a bio-economic model and used stochastic partial budgeting approach to simulate the economic consequences of enhancing solid and slatted concrete floors with soft rubber covering.

The findings highlight that keeping herds on solid and slatted concrete floor surfaces with soft rubber coverings is a profitable solution, compared with keeping herds on solid and slatted concrete floors without a soft covering. The profit per cow when kept on a solid concrete floor with soft rubber covering increased by 13%–16% depending on the breed.

Promoting farm investments such as improvement in flooring solution, which have both economic and animal welfare incentives, is a potential way of promoting sustainable dairy production. Farmers may make investments in improved floors, resulting in enhanced animal welfare and economic outcomes necessary for sustaining dairy production.

This literature review indicated that the economic impact of investment in specific types of floor improvement solutions, investment costs and financial outcomes have received little attention. This study provides insights needed for a more informed decision-making process when selecting optimal flooring solutions for new and renovated barns that improve both animal welfare and ease the burden on farmers and public financial support.

The purpose of this study was to analyze the moderating role of micro-events on the relationship between the three Dark Triad dimensions and counterproductive work-brehaviors. The social exchange theory and the person–situation interactionist model supported this study’s model that analyzed whether micro-events at work would moderate the relationship between the three dimensions of the dark triad personality (Machiavellianism, psychopathy and narcissism) and specific types of counterproductive work behaviors (CWB; toward the organization, and the individual).

To achieve this goal, this study used a sample of 241 currently employed participants.

The results showed that individuals who scored higher on their dark triad traits engaged more frequently in CWB; however, when they experienced more daily uplifts than daily hassles, their CWBs significantly decreased.

The cross-sectional design should be regarded as a limitation, and the authors assessed all the variables through self-reported measures.

Such results proved to be fundamental for a better understanding of employees’ behavior, as well as the impact of micro-events in the organizational settings.