Search results

Globally, the paucity of conventional energy sources has created an unprecedented increase in demand for green energy. Continuous dependency on conventional energy sources has given rise to several undesirable environmental consequences. In the 20th century, the international forum pondered about the development and uses of green energy, which commenced with the realization of global warming and the signing of the Kyoto Protocol agreement. This study aims to divulge the nexus between green energy, carbon emissions and economic prosperity from a global perspective. The study has been conducted by considering panel data of 35 global economies from 1971 to 2019.

To calibrate the uses of green energy, this study dwells upon the ratio between green energy consumption and total energy use. These instrumental variables have been widely acknowledged and accepted by several empirical analysis done in the past (Lin and Moubarak, 2014; Shahbaz et al., 2015). This research specifically uses the emission of carbon dioxide in a million tons as an instrumental variable of environmental degradation, which has been disregarded by all-preceding researchers from a global perspective. Additionally, this study also considers real gross domestic product value in terms of US$ (2010 constant price) as an indicator of economic prosperity. The same has been contemplated by an ample number of empirical research studies conducted previously. Thus, the authors adopted the panel autoregressive distributed lag (ARDL) technique to achieve this research objectives; and to tackle the issue of contemporaneous correlation, the authors applied cross-sectional augmented autoregressive distributed lag (CSARDL) of common correlated effect pooled mean group (CCEPMG).

The results of panel ARDL analysis reveal that in the long-run, real gross domestic product (GDP) leads to carbon emission, whereas green energy uses do not have a substantial effect on the reduction of carbon emission. However, in the short-run, green energy consumption seems definitely helpful for combating carbon emission, while real GDP instigates carbon emission. This study effectively fortifies the notion of a trade-off between ecological pollution and economic prosperity. The empirical results of the Granger Causality test produce evidence of unidirectional causality from carbon emission to green energy uses and from real GDP to carbon emission in the panel countries

First, decisive corollaries of the conclusions drawn above have been made purely on the basis of a comprehensive investigation of 35 global economies. However, there is the scope for inclusive examination by considering more modern economies simultaneously. Second, this paper studied the potential impact of the uses of green energy and real GDP on carbon emission. Notably, the inference of this study has been grounded on three relevant variables, whereas there are possibilities that such an investigation could possibly be extended by considering other instrumental variables of environmental pollution.

A significant number of studies in the past have investigated the connection between renewable energy consumption (REC) and economic growth. To the best of the authors’ knowledge, none have looked to investigate the nexus between REC, economic prosperity and environmental sustainability simultaneously, specifically from the global perspective. Hence, this study intends to widen the prevailing perception of the emerging context above in two ways; first, by reconnoitering the effect of REC on environmental consequences and economic progress simultaneously, which has not been accomplished in extant literature. Second, the authors also strive to gradually augment the comprehensive analysis by expanding the study from a global perspective and by constructing the panel data of developing and advanced economies.

The mobile technology-pedagogy nexus has been instrumental in shifting the focus of information and communications technology in education from e-learning to mobile learning (ML). Learning with mobile technologies is more accessible, flexible, situated, personal, collaborative and lifelong. The use of technologies for educational purposes is the primary focus of higher education institutes. The successful implementation of ML rests on its acceptance by higher education teachers. It is, therefore, pertinent to determine the factors that impact higher education teachers’ acceptance of ML. This study aims to identify these factors and develop a reliable and valid instrument to measure higher education teachers’ acceptance of ML.

A sequential exploratory research design, a type of mixed method research was used for the study. A sound conceptual framework and rigorous scale development process provided the background for data collection and validation. Probability proportionate to size sampling technique was used to gather data from 212 higher education teachers from 42 higher education institutes. Teachers gave their responses on five-point Likert type items. The responses obtained were subjected to exploratory factor analysis, which provided a nine-factor solution. The factors were further validated through confirmatory factor analysis.

Teachers’ mobile learning (ML) acceptance questionnaire (TMLAQ), a 32-item questionnaire was developed to measure acceptance of ML among higher education teachers. A detailed literature review, interviews and focus group discussions with teachers facilitated the identification of nine constructs or antecedents of ML acceptance. These constructs were named as: perceived usefulness, ease of use, self-enhancement, constructivist belief (CB), technological barriers, attitude and behavioral intention. The scale possesses sound psychometric properties such as reliability, face validity, content validity and construct validity.

This instrument can serve as an authentic, valid and reliable measure of higher education teachers’ ML acceptance. It can be used by organizations to assess teachers’ perceptions and aid in the successful ML implementation.

There is a lack of measurement instrument that caters to wide angle view of teachers’ perception toward ML in the Indian context. This comprehensive scale will bridge this gap. Two new research constructs: CB and self-enhancement were found to be crucial from the teachers’ point of view. These constructs have not been explored in previous technology acceptance studies. To the best of the knowledge, such a comprehensive study has not been undertaken yet in the Indian context. This study can serve as a model for conducting similar kinds of studies in other developing nations.

The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

In casting a new look at city; this study interprets the urban form in respect of the role played by human perception of space. The main aim of this research at a macro level is to attain a strong theorical basis through a multi-dimensional approach to the city. The method of analyzing and carrying out a critique of it at an applied level will clarify the impact, which cultural factors have in the formation of urban form. This preliminary recognition and idealism is based on a hermeneutic and deductive method that is particular to the intellectual sciences In the process of devising theories, studying the urban planning texts related to the subject of study and the conclusion from the field study which is carried out in the Isfahan Naghshe Jahan square in the Safavy period played a key role in the research in addition to the goals and questions.