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Resilience while learning is the capacity to initiate, persist and direct effort toward learning when experiencing unpleasant affective states. The underlying mechanisms of resilience are emotional buffering and self-regulation when experiencing unpleasant affective states. The authors identified four factors that support resilience while learning: positive emotional engagement, creative problem-solving, learning identity and social support. The authors developed and tested scales and found evidence to support the four-factor model of resilience. The authors offer a person-centered approach to resilience in learning by conducting a latent profile analysis that tested the likelihood of resilience based on profiles of differences in scores on these factors under two affective conditions: (unpleasant) learning during frustration versus (pleasant) learning during progress. A quarter of individuals activated the four resilience factors in pleasant and unpleasant affective states, while 75% of participants saw decrements in these factors when faced with frustration. The results support a four-factor, person-centered approach to resilience while learning.

The authors develop and test a four-factor model of resilience and test the model in a group of 330 management undergraduate and graduate students. Each participant identified two learning episodes in their responses, one while frustrated and one while making progress, and ranked the level of intensity on the four resilience factors. Analysis on an additional 88 subjects provided additional support for the validation and reliability of scales.

Results revealed 2 latent profiles groups, with 25% of the sample associated with resilience (low difference on resilience factors between the two learning episodes) and 75% who remain susceptible to unpleasant emotions (high difference between the two learning episodes).

The study supports a person-centered approach to resilience while learning (in contrast to a variable centered approach).

The study provides a means to classify individuals using a person-centered, rather than a variable-centered approach. An understanding of how individuals buffer and self-regulate while experiencing unpleasant affect while learning can help educators, consultants and managers develop better interventions for learning.

This study addresses the growing concern over student success associated with increased dropout rates among undergraduate business students, and the failure of many management developments and executive training efforts. This study suggests that looking at specific variables may not provide insight into the complex relationship between learning outcomes and factors that support resilience in learning.

There is growing interest in understanding resilience factors from a person-centered perspective using analytical methods such as latent profile analysis. This is the first study to look at how individuals can be grouped into similar profiles based on four resilience factors.

This study aims to identify the most significant factors that influence acceptance of e-learning in India. As e-learning has gained popularity in the wake of the COVID-19 pandemic and continues to be one of the most sustainable methods of education, it is pertinent to examine learners' perception towards its acceptance. There is limited literature available on this subject in India, especially factoring in impact of the pandemic.

This study empirically analyses data of 331 adult e-learners in India, who have enrolled for one of the following e-learning formats: higher education, private coaching, test preparation, re-skilling and online certifications, corporate training and hobby and language-related learning. Their perception is examined on the basis of a model developed using the Unified Theory of Acceptance and Use of Technology model. Data are analysed through structural equation modelling using SPSS and AMOS statistical tools.

The result of the study shows that Infrastructure Dependability, Effectiveness of Design and Content of Courses and Student's Competency with Computers are the top three factors impacting e-learning acceptance in India.

This study makes several theoretical contributions. Additionally, research findings and recommendations will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning.

This study identifies and confirms important factors that influence e-learning acceptance and suggests opportunities for further in-depth research and analysis.

This paper aims to develop indicators of happiness in learning of the Thai open university (TOU)'s undergraduate students.

Sampling for the study was comprised of two groups. Group I comprised eight lecturers who are experts in their disciplines and six students who were purposively sampled. The focus group was used to validate the appropriateness of the indicators. In Group II, 332 students were engaged in a multistage sampling process. The responses were analyzed using descriptive statistics, coefficient correlation, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The indicators of happiness in learning of undergraduate students of TOU were classified in six categories. These included satisfaction with learning environment (five indicators), learning anxiety (five indicators), satisfaction with learning (five indicators), enthusiasm to learn (six indicators), self-satisfaction (six indicators) and readiness to learn (seven indicators). The six categories explained happiness in learning of undergraduate students of TOU at the 65% and fit empirical data.

The TOU can use the indicators for the assessment of happiness in learning of its students as well as guidelines for the improvement of its student learning environments.

There have been very few studies on indicators of happiness in learning of TOU students. Most were done at the basic education level. This study disclosed the six factors affecting happiness in learning of TOU students; therefore, it should inspire and draw attention of many in the field of higher education distance learning.

This paper aims to contribute to international business research by providing an integrative framework of the factors determining the learning process of outsourcing companies in developing countries.

A systematic review of the literature was performed with an analysis of 84 articles published in peer-reviewed academic journals, published between 2000 and 2020.

The results show that the different factors should be seen as complementary and not mutually exclusive. It is the interaction between macro and micro factors that jointly shape the learning of developing country subcontractors. Moreover, the results of the analysis show that many existing studies have not been based on specific theoretical frameworks.

This study develops a roadmap of the current state of research on the determinants of learning among developing country subcontractors and offers suggestions to guide future research. The authors conclude with a call for methodological advancement and theory development on the topic.

To the best of the authors’ knowledge, this study proposes the first comprehensive review of the literature on the factors determining the learning of subcontractors in developing countries. The authors have tried to provide an integrative analytical framework to discuss what has been known and what needs to be known in this regard.

The purpose of this paper is to identify the obstructive and promotive factors that affect students’ access to school and learning attainment in Zambia. Much of the literature discussing Zambian education identifies only the obstructive factors. When identifying the obstructive factors becomes the primary focus in education policy, efforts are directed towards eliminating these factors without considering the context of the educational process. Consequently, this discourse has lost sight of the fact that eliminating obstructive factors does not guarantee good access to school and learning but merely provides a condition in which students are part of an educational process.

This paper presents an explanatory study with in-depth interviews using a semi-structured questionnaire administered to 27 university students. The sample was purposefully selected to balance variation in the respondents in terms of geographical background. The data analysis was aided with the qualitative analysis programme NVivo 10 along with the descriptive method.

The paper presents empirical insights about multi-faceted factors that affect students’ access to school and learning in Zambia. In particular, this study finds that teachers, policy changes, and students’ motivation are the key factors in achieving students’ academic excellence.

By presenting a simultaneous investigation of both sides of the factors related to access to school and learning, this paper contributes by suggesting the importance of a binocular perspective for educational development in Zambia and by providing implications for the new global agenda of post-2015 educational development that shifts the focus from access to quality.

The purpose of this paper is to model the factors influencing the quality of learning experiences (LE) of students in blended learning (BL) environments in higher education (HE) sector, and to assess whether these factors differ across gender.

A literature review combined with in-depth interviews of a broad range of stakeholders were used to develop a conceptual study model, which was then empirically tested using data collected from a global sample of 267 students from diverse BL environments. Factor analysis and binary logistic regression were used to test the study model.

A five factor solution emerged for both genders, therefore concluding that the identified factors did not play a statistically significant role in predicting the gender of students. Thus, the same factors may be used to enhance the quality of LE of both male and female students.

Even though the sample represents respondents from different universities around the world, and the methodology used has authenticated the findings, the results need to be implemented carefully due to the non-probabilistic sampling. Therefore, similar studies can be repeated in future in other BL environments to validate the results in a broader context.

The findings suggest that managers of HE institutions may use similar factors to achieve quality LE for both male and female students.

Effective design of courses suitable for both genders will support better LE potentially leading to higher retention and enrollment rates for students and supporting lifelong learning.

While universities worldwide are increasingly using BL environments as delivery mode, limited research has focused on the factors that affect the quality of LE in such settings. This paper addresses this gap and tests whether the same factors are relevant for both genders.

Development of staff learning enhances work productivity and sustains organizational development. In particular, design practitioners require both theoretical knowledge and mentoring with their practical experience. Without extensive knowledge, designers may produce design work errors that produce poor quality of work and this leads to project cost and time overruns. This paper aims to explore staff's perception of the factors that influence learning in construction design companies.

Twenty‐six variables are reviewed from literature, and evaluated by 70 designers from construction design and consulting firms in Thailand. A factor analysis technique is applied to the group of identified variables.

Eight factors that affect staff learning are identified: organizational support for learning; group learning; individual learning and sharing; absorptive capability; personal relationships; characteristics of the knowledge source; learning equilibrium; and work characteristics.

Knowledge of these factors can help senior managers deal with learning within these kinds of organizations. In addition, these factors can be used to assess the level of support that facilitates learning within an organization.

Construction designers have had scant attention paid to them by researchers regarding how they develop their learning. Moreover, recent work on knowledge transfer in the construction industry has tended to focus on countries such as the UK and Australia, with little work done in Asian countries. This paper attempts to help bridge that gap within a design context using data from Thai construction design companies.

The purpose of this paper is to analyze the contribution of e‐learning in the improvement of quality and productivity in hotels.

The methodology is based on an inquiry answered by 34 hotels that are using e‐learning. For this purpose, a survey on five, four and three star hotels, located throughout Portugal, was conducted between January and March 2009.

The research reveals that hotels consider that e‐learning increases productivity and production volume. On the other hand, e‐learning contributes significantly to employees' motivation. The paper also concludes that managers' opinions about e‐learning strategies are dependent on the hotel category and head‐office nationality.

e‐Learning is based on information and communication technology and supports the educational process. Owing to the important results achieved, e‐learning is continuously gaining relevance in hotels, and in educational institutions. As such, analysing the contribution of e‐learning for quality improvement in hotels brings originality to the research whilst adding value to the body of knowledge in the industry.

The aim of this paper is to provide a framework to measure the response of blue‐collar workers to new technology in manufacturing and to establish the relationship between learning culture and that response.

The data were collected with a survey questionnaire from 12 manufacturing sites that were implementing a number of diverse new technologies. The dimensions of worker response were identified with exploratory factor analysis and the relationship between these factors and learning culture was established with path analysis.

Factor analysis identified seven dimensions of worker response: disgruntlement, job‐security concerns, accommodation, informal learning, resistance, discussion, and formal learning. Learning culture had a large, statistically significant relationship with disgruntlement and medium, statistically significant relationships with job‐security concerns, accommodation, informal learning, and formal learning.

The sample was limited to manufacturing locations in the southeastern USA and the respondents were almost all male and either White or African‐American.

These findings establish a strong positive relationship between learning culture and behavioral, affective and cognitive responses of workers to new technology. This is key for supporting learning culture in organizations that naturally are inclined to worker isolation and independence.

Empirical work of this nature is limited in manufacturing facilities. These organizations tend to be closed to research because of concerns regarding the security of proprietary information or the personal safety of the researcher.

Circular economy has emerged as one of the most important approaches to addressing environmental challenges. Organizations have begun to act on their abilities to enhance their sustainability management to enable a circular economy. The role of organizational learning and green human resource management in the transition to a more circular economy remains unknown. The purpose of this study is to identify and analyze the inter-relationship between the factors of organizational learning and green human resource management, and it aims to rank the identified factors of manufacturing small and medium businesses (SMEs) based on their driving and dependency power and to detect the most substantial factors.

This study identified 11 organizational learning and green human resource management (GHRM) factors after conducting a thorough literature analysis and consulting with experts. To investigate the interaction of the indicated factors and to build their structural hierarchy, this study used the total interpretive structural modeling method. Further, Matriced Impact Croises Multiplication Applique (MICMAC) analysis was used to establish each factor’s driving and dependent power.

This study discovered that factors “Green separation” and “Organizational learning culture” were found to be significant; “Green performance management” and “Green health and safety management” were observed to be extremely reliant on the remaining GHRM factors.

The recommended framework has been established in the Indian background and is restricted to manufacturing SMEs. Still, the same framework can be applied to other sectors by slightly modifying it. Also, the analysis is based on the experts’ view and this may be biased. The findings of this study will help human resources managers and SME owner-managers clarify the most and least significant factors of organizational learning and GHRM and their relationships, leading to increased awareness of organizational learning and GHRM practices for enlightened environmental performance.

The proposed framework might facilitate decision-makers and practitioners to comprehend the relations between organizational learning and GHRM factors. This will support SME owner-managers in understanding the influence of one factor on another factor in manufacturing SMEs.

Until now, the protruding interest of researchers has been focused mostly on large manufacturing enterprises. However, manufacturing SMEs, which are much smaller when compared to large manufacturing companies, significantly contribute to the economy as well as environmental pollution. Thus, this study provides a vital contribution to the current literature by determining the suitable relationship between the organizational learning and GHRM components, as no previous studies focused on exploring the same using the total interpretive structural modeling approach in the Indian manufacturing SMEs environment.