The moderating role of market turbulence beyond the Covid-19 pandemic and Russia-Ukraine crisis on the relationship between intellectual capital and business sustainability

This paper examines the role of Intellectual Capital (IC) and its contribution to Business Sustainability (BS) among Large Manufacturing Firms (LMF) in Malaysia. It seeks to explain the relationship between them under turbulent market conditions. The study used the survey method to collect data from 203 large companies, and the hypotheses were tested using Partial-Least Squares-Structural Equation Modeling. Based on the findings, two dimensions of IC, namely Human capital (HC) and Structural Capital (SC), had a significant effect on business sustainability, but Relational Capital (RC) did not. Also results indicate that Market Turbulence (MT) moderates the relationship between two IC dimensions, HC and RC but not that between SC and BS. The study findings can be used as guidelines by CEOs of LMFs, policy makers and researchers to comprehend positive the influence of MT and IC on BS. © 2022

A novel DCNN-ELM hybrid framework for face mask detection

The Coronavirus disease (2019) has caused massive destruction of human lives and capital around the world. The latest variant Omicron is proved to be the most infectious of all its previous counterparts – Alpha, Beta and Delta. Various measures are identified, tested and implemented to minimize the attack on humans. Face masks are one of those measures that are shown to be very effective in containing the infection. However, it requires continuous monitoring for law enforcement. In the present manuscript, a detailed research investigation using different ablation studies is carried out to develop the framework for face mask recognition using pre-trained deep convolution neural networks (DCNN) models used in conjunction with a fast single layer feed-forward neural network (SLFNN) commonly known as Extreme Learning Machine (ELM) as classification technique. The ELM is well known for its real time data processing capabilities and has been successfully applied both for regression and classification problems of image processing and biomedical domain. It is for the first time that in this paper we have proposed the use of ELM as classifier for face mask detection. As a precursor to this, for feature selection, six pre-trained DCNNs such as Xception, Vgg16, Vgg19, ResNet50, ResNet 101 and ResNet152 are tested for this purpose. The best testing accuracy is obtained in case of ResNet152 transfer learning model used with ELM as the classifier. The performance evaluation through different ablation studies on testing accuracy explicitly proves that ResNet152 - ELM hybrid architecture is not only the best among the selected transfer learning models but also proves so when it is compared with several other classifiers used for the face mask detection operation. Through this investigation, novelty of the use of ResNet152 + ELM for face mask detection framework in real time domain is established. © 2022

Long-Term Effects of COVID-19: How the Pandemic Highlighted the Global Digital Divide

The article is a study of the prerequisites for the formation of the global digital divide, as well as its structural features, including during the COVID-19 pandemic. The authors identify technological, economic and social components of the global digital divide. The authors analyze the indicators assessing the technological component of the global digital divide for the period 2015–2020. The authors used indicators of the dynamics of the global ICT market and the dynamics of the e-commerce market to study the economic component of the digital divide and the impact of the pandemic on it. It is concluded that the pandemic has increased the importance of digital technologies in general, as well as opportunities to reduce the global digital divide. The social component of the digital divide is manifested in the different levels of realization of the opportunities of individuals and households with the help of ICT technologies. The authors proved that the gap in access to digital technologies and their use contributes to the emergence of a divide in knowledge and human development opportunities. The article proposes public policy measures aimed at bridging the global digital divide. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Investment Technologies for Ensuring the Inclusive Growth of the National Economy

The study aims to devise methodical and practical recommendations on using investment technologies as a means to ensure the inclusive growth of the national economy. Based on the authors’ approach to the notion and the role of investment technologies for ensuring the inclusive growth of the national economy, we provide recommendations for implementing economic methods, approaches, and instruments at relevant stages of the investment process. At the stage of determining the goals and areas of investment, it is advisable to invest in physical and human capital, knowledge economy, housing construction, and export development. At the stage of garnering resources to invest in investment projects, it is important to pay attention to the government support of investment projects and public–private partnership. At the stage of the realization of investment projects, it is recommended to secure a weighted growth of trade protectionism. Under Industry 4.0, there are broad opportunities to form new assessment tools for investment technologies. Thus, we introduce the author’s methodology to assess investment technologies based on the matrix method using the digital technology of Big Data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Changing patterns of learning in oil and gas industry

Covid-19 pandemics have made innovations even more crucial and used them to take market power over competitors considering challenges that the world and global economy face. To achieve this goal, organizations need competent and high-expertise human capital as a workforce. That is one of the key reasons organizations increase their investment in developing, re-skilling and up-skilling their workforce via various learning and development programs and solutions compared to previous years. Given the direct impact of this process on the company's revenues, the following graph demonstrates the value flow generated (Figure 1): Organizations aim to ensure minimum time and efficient expenditure structures to achieve and build a learning system that delivers sustainable developmental solutions and interventions. Knowledge sustainability is a purpose, which focuses on various learning methods and solutions to make knowledge last and kept longer. A learning management system (shortly, LMS) is a platform that gathers all the learning solutions in one place and automates the process of learning to present development opportunities to end-users - learners/ employees. Digital learning enables users/employees to develop their competencies quickly, no matter the place and time and makes knowledge and information accessible for all, and gives an unlimited option to relearn, repeat and refresh anything already completed unlimitedly. Copyright 2021, Society of Petroleum Engineers

The International Spillover Effect of Import Trade on Energy Efficiency in the Post-COVID-19 Era: Evidence From China

China is in a transition period—its government has been expanding imports and pushing itself to shift from a world factory to a world market. One of the aims is to promote energy reform and ensure energy security. Taking the resource-based regions of China as objects, based on 2003–2017 panel data, this paper investigates energy efficiency loss by the stochastic frontier approach and the effects of different technical inefficiency items. Surprisingly, quantitative results show that 99.9% energy efficiency loss in these regions is caused by technical inefficiency (which had never been found and discussed in previous studies). However, this does not mean that China’s efforts to expand imports as a way to improve energy efficiency and energy security are undesirable. Instead, interestingly, it is import (−0.083***) rather than industrial structure (0.524***) that can significantly reduce energy efficiency loss. Then, it employs the counter-fact test to quantify the positive accelerating effect of human capital (average as high as 4.1%) as a key factor of absorptive capacity in the technology spillover. Lastly, it puts forward the corresponding policy suggestions in energy fields, to solve the problem effectively, especially the “comprehensive technology spreading center” and “innovative three-dimensional talent supplementary and flow mechanism”. Copyright © 2022 Hao, Wang and Xue.