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Management innovation is one of the most vital practices underpinning economic growth and is considered to be one of the fundamental components of gaining a superior business position in market conditions that are continually fluctuating. Drawing upon neo-institutional theory as well as absorptive capacity, the current empirical study unpacks the relationships between external institutional forces (i.e. regulative, mimetic and normative pressures) and management innovation through investigating the role of absorptive capacity as a mediator.

The research model is tested using survey data from Australian organisations. The study used Partial Least Squares (PLS), a component-based structural equation modelling (SEM) method, in order to perform the data analysis.

The results confirm that the various dimensions of institutional forces have diverse influences on management innovation. The authors found mimetic and normative pressures have positive influences on realised and potential absorptive capacity of an organisation. In addition, realised absorptive capacity mediates the relations between institutional forces and management innovation.

Dissimilar to preceding studies, this research shows that organisations not only innovate to pursue higher performance but sometimes strive for legitimacy. In addition, the significant associations between absorptive capacity and management innovation and the mediation role clearly signify that institutional forces and absorptive capacity play significant roles in the adoption of management innovation.

COVID-19 has affected most business activities, including technology-based business. The higher the business vulnerability rating, the greater the impacts. After identifying three dimensions of vulnerability (exposure, business sensitivity and response capacity), this study aims to determine the potential components and indicators of the vulnerability of technology-based businesses.

Using the indicator approach, a comprehensive vulnerability model was developed for assessing the vulnerability of the technology-based business against COVID-19.

In this study, COVID-19, as a biological threat and an exogenous shock, was considered the exposure dimension. Business characteristics, job characteristics, business owner-manager demographics, product and supplier characteristics were identified as the sensitivity dimension, while resources, human capital, technological capitals, social capitals, institutional capitals, infrastructures, management capacity and supply chain capabilities were defined as the adaptive business capability or response capacity. To determine vulnerability and response capacity against exogenous shocks and a pandemic crisis, the framework can act as a useful checklist for managers and owners of technology-based businesses.

Research on the COVID-19, especially in the technology-based business, is still at the emergent stage. This study is a pioneering effort to review the literature on business vulnerability and provide a framework to reduce business vulnerability using the indicator-based approach.

The purpose of this paper is to assess the feasibility of analytical models, specifically the radial basis function method, Akbari–Ganji method and Gaussian method, in conjunction with the finite element method. The aim is to examine the impact of processing parameters on temperature history.

Through analytical investigation and finite element simulation, this research examines the influence of processing parameters on temperature history. Simufact software with a thermomechanical approach was used for finite element simulation, while radial basis function, Akbari–Ganji and Gaussian methods were used for analytical modeling to solve the heat transfer differential equation.

The accuracy of both finite element and analytical methods was validated with about 90%. The findings revealed direct relationships between thermal conductivity (from 100 to 200), laser power (from 400 to 800 W), heat source depth (from 0.35 to 0.75) and power absorption coefficient (from 0.4 to 0.8). Increasing the values of these parameters led to higher temperature history. On the other hand, density (from 7,600 to 8,200), emission coefficient (from 0.5 to 0.7) and convective heat transfer (from 35 to 90) exhibited an inverse relationship with temperature history.

The application of analytical modeling, particularly the utilization of the Akbari–Ganji, radial basis functions and Gaussian methods, showcases an innovative approach to studying directed energy deposition. This analytical investigation offers an alternative to relying solely on experimental procedures, potentially saving time and resources in the optimization of DED processes.

Because of the importance of having enough sleep in life and health, this study aims to determine the effect of vitamin D supplementation on sleep quality and pregnancy symptoms (primary outcomes) and side effects (secondary outcome).

In this triple-blind randomized controlled clinical trial, 88 pregnant women with gestational age of 8–10 weeks and serum vitamin D concentration less than 30 ng/ml were allocated into vitamin D (n = 44) and control (n = 44) groups by blocked randomization method. The vitamin D group received a 4,000 IU vitamin D pill, and the control group received a placebo pill daily for 18 weeks. Independent t-, Mann–Whitney U and ANCOVA tests were used to analyze the data.

The post-intervention mean (SD: standard deviation) of total sleep quality score in the vitamin D and placebo group were 1.94 (2.1) and 4.62 (1.71), respectively. According to the Mann–Whitney U test, this difference between the two groups was statistically significant (p < 0.001). The mean (SD) of pregnancy symptoms in the vitamin D and placebo groups was 23.95 (16.07) and 26.62 (13.84), respectively, and there was no significant difference between the two groups based on ANCOVA test (p = 0.56). Considerable side effects were not observed in any groups.

This study was conducted due to the contradictory results of the effect of vitamin D on sleep quality and the high prevalence of sleep disorders and pregnancy symptoms.