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This paper intended to explore the knowledge and use of the digital verbs and tools by the students and teachers for conceptual understanding in the virtual and conventional learning environment. The study also explored the use of such digital tools for lower- and higher-order thinking.

A survey research method was used for the study. All the students and teachers of the faculty of education from one virtual and one conventional university were the population of this study. Teachers were selected through census sampling. Student enrollment in the faculty of education of the virtual university during Spring 2019 was 1,139 while the conventional university had 1,809 students. In total, 20% of the students from each of the two universities were sampled by using a convenient proportionate sampling technique. A questionnaire was developed by the researchers and validated by three experts before administration. The reliability of the instrument was a = 0.934. Mean, SD, parametric and nonparametric statistics were applied for data analysis.

The study reveals that the students of ODL are far better in using digital tools and activities that is, googling, collaborating and Skyping. They are good at understanding and application levels and are involved in higher-order thinking tasks, that is, publishing and podcasting as well. Unlike the students, the teachers of the virtual university are using digital tools of lower-order thinking. The authors infer that the students and teachers of the online universities are using these tools regularly because of the demands of the ODL environment. These findings suggest further research to explore the factors that hinder the use of higher-order thinking skills by the teachers in the online environment.

The study suggests the adoption of Bloom's digital taxonomy in teaching–learning processes, that is, curriculum, instructions and assessment for the millennials. The findings may motivate the online and conventional higher education institutions to adopt digital pedagogy for instructional purposes as the students of the digital age are already extensively involved with digital tools.

This paper explores how entrepreneurial culture (EC) and organizational learning (OL) determine the entrepreneurial orientation (EO) of new technology-based firms (NTBFs). These NTBFs are located in Isfahan Science and Technology Town (ISTT), Iran. These entities face substantial challenges in a highly-sanctioned economy, which makes adopting, acquiring or transferring new technologies daunting.

This paper analyzes a sample of 200 NTBFs. The participants were trained chief executive officers and observed by applying pre-test and post-test designs. As a final step, empirical data were collected using questionnaires and analyzed accordingly. The structural equation modeling (SEM) with the partial least squares (PLS) approach was used by the SmartPLS2 software.

OL was found to mediate the relationship between EC and EO in the studied NTBFs. Additionally, the indirect effect of EC on EO and the direct impact of OL on EO were significant (=1.96). Therefore, this study focuses on selected NTBFs within Iran's particular and distinctive context.

This study has several limitations. These were the time consuming nature, the lack of cooperation by managers and the COVID-19 pandemic-related challenges. Nonetheless, the findings offer several important implications for practitioners, scholars and policymakers.

The paper sought to explore how EC and OL determine EO in Iranian NTBFs. It, thus, investigates the case of a highly-sanctioned context during the coronavirus pandemic, which imposed several basic and technological limitations on their practices.

This study aims to investigate the mediating role of different types of intellectual capital (human, structural and relational) in the relationship between artificial intelligence-driven supply chain analytics capability (AI-SCAC) and various supply chain decision-making processes, specifically rational, bounded and tacit decision-making.

The study used a quantitative survey strategy to collect the data. A total of 320 valid questionnaires were received from manufacturing companies. The data were analysed using structural equation modeling with partial least squares (PLS-SEM) approach through SmartPLS software.

The results indicate that human and structural capital significantly mediate the relationship between AI-SCAC and rational and bounded decision-making processes. However, structural capital does not mediate the relationship between AI-SCAC and the tacit decision-making process. Moreover, relational capital does not show a significant mediating effect on all of the decision-making processes. Notably, structural capital has the strongest impact on rational and bounded decision-making, while human capital plays a critical role across all three decision-making processes, including tacit decision-making.

This study contributes to the literature by providing a nuanced understanding of the differentiated impact of intellectual capital components on various decision-making processes within the context of AI-SCAC. While previous studies have broadly acknowledged the role of intellectual capital in decision-making, this research provides more understanding of how specific types of intellectual capital interact with AI to influence distinct decision-making processes. Notably, the differential impact of structural capital on rational and bounded decision-making versus tacit decision-making highlights the need for organisations to adopt a more tailored approach in leveraging their intellectual capital.

The purpose of this paper is to develop an original framework to explore the effects of social influence (SI), market orientation (MO) and service quality (SQ) with moderating effect of emotional intelligence (EI) on customer loyalty (CL) and to discuss the mediational role of customer satisfaction.

This study applies six original concepts – SI, MO, SQ, EI, customer satisfaction to develop an integral model to enhance CL. In addition, this research employs an empirical study by means of the questionnaire survey method to verify the hypotheses and to explore its managerial implications. Structural equation modeling has been applied to verify the research framework.

The empirical results show that MO, SI and SQ significantly affect CL with presence of customer satisfaction as a mediator. Furthermore, this study demonstrates that the direct relationships between MO and SI on CL are not supported. However indirect paths present full mediation except in case of SQ where mediation was partial. Moreover, EI was found to enhance the partially mediated relationship between SQ and CL with mediational role customer satisfaction. Hence, banks should invest resources to increase MO, SI and SQ to increase customer satisfaction and CL.

This study summarizes the literature on customer satisfaction and relationship marketing into a new managerial framework of CL. It utilizes new arrangement of four construct – SI, MO, and SQ with EI – to develop an original framework to enhance CL. Although past research has highlighted the relevant issues about CL, none explores it with MO and moderating role of EI on SQ. Therefore, this paper develops the research framework of CL to fill the research gap specifically in Pakistani context.

The sustainable development of the energy–economy–environment (3E) needs to ensure the balanced interplay between the energy–economy and the environment. Likewise, creating such balance has become a critical policy issue among countries worldwide. However, in the past, studies have ignored to create a balanced interplay of the energy–economy and environment. Therefore, to address said research gap, this paper aims to develop a graph model for conflict resolution (GMCR)-based strategy for the sustainable development of the 3E to ensure better environmental quality.

To develop a strategic framework for the balanced interplay between the energy–economy and the environment, the study used the GMCR approach and designed a mechanism for the sustainable development of the 3E to ensure better environmental quality in the context of Pakistan.

The results from the GMCR indicate that sustainable development of the 3E to ensure better environmental quality is possible when government focuses on the sustainable growth of the economy through environmental policies and the use of renewable energy.

By solving the 3E conflict, this study provides policy insights for the government of Pakistan for the sustainable development of the energy economy and the environment to ensure better environmental quality in the country.

For the first time, this paper tried to put forward a way through which conflicting objectives can be achieved together for the sustainable development of the 3E to ensure better environmental quality.

The purpose of this paper was to systematically collect and review the research studies that provide empirical evidence regarding the existence of relationship between self-efficacy and knowledge sharing or influence of self-efficacy on sharing of knowledge.

The studies were collected through searching in Google Scholar, Scopus, ProQuest Dissertations and Theses, LISTA (Library, Information Science and Technology Abstracts) and Web of Science. All types of studies, except books, were selected for review. Time limitation was not applied.

It can be concluded from majority of reviewed studies that self-efficacy influenced knowledge sharing. This systematic review also establishes that majority of reviewed studies confirmed existence of relationship (positive) between variables self-efficacy and knowledge sharing.

A language limit was applied, and only English language studies were reviewed.

This review is first of its kind that systematically collected and reviewed the studies that examined the relationship between self-efficacy and knowledge sharing. This paper is also first in terms of a study which systematically collected and reviewed studies that investigated impact of self-efficacy on sharing of knowledge. Findings of current research paper will be helpful for organizations striving to implement a knowledge-sharing culture. Similarly, this study will also help the readers in understanding the ways to improve their knowledge-sharing practices and learning.

The study aims to understand the association between subjective well-being, psychological well-being, work satisfaction and engagement amongst middle-level hospitality managers.

The data were collected from 624 middle-level hospitality managers working in two corporate hotel chains across five north-western states of India. Structural equation modelling (SEM) with a covariance-based approach (CB-SEM) was implemented using SPSS AMOS, adhering to a two-step process that included both measurement and structural models. The application of CB-SEM primarily aimed to (1) evaluate the cascading impacts across constructs and (2) scrutinise the concurrent relationships amongst constructs, with a specific focus on well-being (both psychological and subjective), context-specific job satisfaction and work engagement.

Evidently, the post-COVID-19 scenario found to be challenging for the hospitality industry. Thus, this empirical research posits that subjective and psychological well-being positively influences work engagement via work satisfaction as a mediator.

Given the people orientation in the hospitality sector, the research contributes to the existing body of literature by assessing the relationships between psychological and subjective well-being, work satisfaction and engagement amongst middle-level hotel managers employed in the corporate chain of hotels in India.

The purpose of this paper is to develop understanding of the problems of classification, to discover the classification practices of libraries with rich collections on Islam cited in the literature, to find the gaps, and to determine the point from which to start work on further development.

Published and unpublished literature, both print and electronic, that is relevant to the problem was reviewed objectively in the compilation of this paper.

Standard classification systems lack proper space for materials on Islam for two reasons: less awareness on the part of devisers of the depth and variety of Islamic topics; and their bias and lack of interest in Islam. Different indigenous classification systems and expansions have been developed, using either the original notation or alternative notations. Some systems have been developed without following any standards or logic. This study has revealed a need for empirical study of libraries with rich collections on Islam in order to gain a better understanding of the problem and find an optimal solution.

No empirical field data are included in this study. This is a review of the literature.

The author indicates the current situation of the problem and a potential framework for its solution.

Classifying emails as ham or spam based on their content is essential. Determining the semantic and syntactic meaning of words and putting them in a high-dimensional feature vector form for processing is the most difficult challenge in email categorization. The purpose of this paper is to examine the effectiveness of the pre-trained embedding model for the classification of emails using deep learning classifiers such as the long short-term memory (LSTM) model and convolutional neural network (CNN) model.

In this paper, global vectors (GloVe) and Bidirectional Encoder Representations Transformers (BERT) pre-trained word embedding are used to identify relationships between words, which helps to classify emails into their relevant categories using machine learning and deep learning models. Two benchmark datasets, SpamAssassin and Enron, are used in the experimentation.

In the first set of experiments, machine learning classifiers, the support vector machine (SVM) model, perform better than other machine learning methodologies. The second set of experiments compares the deep learning model performance without embedding, GloVe and BERT embedding. The experiments show that GloVe embedding can be helpful for faster execution with better performance on large-sized datasets.

The experiment reveals that the CNN model with GloVe embedding gives slightly better accuracy than the model with BERT embedding and traditional machine learning algorithms to classify an email as ham or spam. It is concluded that the word embedding models improve email classifiers accuracy.

This study explores the relationship between intellectual capital (IC), dynamic capabilities (DCs) and organisational performance (OP), addressing disagreements on whether IC is an antecedent or consequence of DCs and whether IC and DCs mediate or moderate the interactions between these constructs.

To address the study questions, four different models were developed that highlight the controversy among researchers regarding the nature of the interplay between IC, DCs, and OP. A cross-sectional survey of 394 managers working for government agencies and departments in Jordan’s capital city, Amman, was conducted to investigate different scholars’ perspectives on the nature of the interaction between these variables. The retrieved responses (166 with a 42.1% response rate) were analysed using SmartPLS.

Our results revealed that IC did not affect OP, whereas DCs did across the four models. IC affects DCs, and DCs also affect IC, highlighting the potential reciprocal relationship. The relationship between the variables is one of mediation and not moderation, which implies that DCs do not function as a moderator between IC and OP, and IC does not act as a moderator between DCs and OP. These results offer a complex picture of the connections between IC, DCs and OP, which has interesting implications for practice.

Our study reveals the significant role of DCs in OP within government institutions by extending theories on DCs’ adaptability and competitiveness. It emphasises the need for active management of IC to yield performance benefits, aligning with resource-based theories. This study also clarifies the mediation and moderation effects, opens new research avenues and highlights the potential reciprocal interaction between IC and DCs.

This study is the first to explore the reciprocal interaction between IC and DCs and the mediating and/or moderating role of either IC or DCs in their relationship with OP within the public sector, which has not received sufficient attention from scholars, especially in developing countries such as Jordan.