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This study aims to examine the effect of workplace learning experience and intrinsic learning motive on job satisfaction and organizational commitment. In addition, the study examined the moderating effect of intrinsic learning motives on the relationship between learning experience and job satisfaction and organizational commitment.

The current research used the Human Capital Corporate Panel survey data set, which aimed to explore how human resource development practices influence corporate performance. In all, 10,003 samples from 441 companies were used for data analysis.

Results indicate that taking part in workplace learning programs positively affects job satisfaction and organizational commitment. Likewise, intrinsic learning motives are also positively related to work attitudes. However, no interaction effect between the intrinsic learning motive and the learning experience was found, which may imply that an autonomous extrinsic learning motive is a better predictor for explaining job satisfaction than is a purely intrinsic learning motive within an organizational context.

Little research has examined the actual effect of workplace learning programs on employees’ attitudes regarding job satisfaction and organizational commitment. Furthermore, to the authors’ knowledge, no research has examined the moderating effect of intrinsic learning motive with workplace learning experience on employees’ positive work attitudes.

The purpose of this paper is to examine the relationship between building floor and labor productivity of the structural work including formwork installation and rebar fabrication/installation.

The case study methodology and learning curve theory are adopted for the paper. Records from the structural work of a 20-storey apartment building were analyzed to calculate floor-based labor productivities.

Labor productivity of the formwork activity increased more than twice in the first five floors. If the first cycle (floor 2) is omitted, the straight-line learning curve model shows a learning rate of 83.5 percent. Labor productivity of the rebar activity tended to increase in the first 15 floors. If the first two cycles are omitted, the straight-line learning curve model indicates a learning rate of 83.6 percent.

Future research is needed to examine and quantify factors that affect the level of learning in high-rise building construction. The relationship between building floor and labor productivity should be further investigated for other construction activities.

Practitioners should consider the relationship between building floor and labor productivity and learning effects when planning manpower and construction duration for individual activities and for a building.

The paper substantiates the hypothesis that labor productivity does not reach 100 percent of the normal level at the very first floors while they do not support the hypothesis that labor productivity does not reach 100 percent at the top floors.

Today's logistics industry is facing severe challenges since global transportation demand increases substantially. Carriers are urged to reduce empty loads and CO2 emissions through collaboration. Therefore, the concept of Physical Internet (PI) came into being. However, PI is still in its infancy. It is difficult to understand its sophisticated coordination mechanism, which makes learning of the concept more complicated.

Gamification is an effective approach to help students improve their learning curve. At the same time, the psychological and behavioral changes in learning will also pose an impact on learning efficiency. This paper introduces a PI transportation game and designs a set of gamification teaching experiments. In the experiment, a control group and three experimental groups are set up, and the experiment was designed to respond to a plethora of research questions using the methods of T-test, correlation analysis and regression analysis. Experimental results were analyzed through the method of multivariate statistics.

This paper looks for superior pedagogical methods and procedures for students to learn PI while providing suggestions for PI's learning among undergraduates. The authors found (1) gamification teaching will make participants feel more satisfied and master more knowledge points; (2) the scores of logistics testing have been significantly improved after gamification teaching and (3) flow experience has a significant impact on game revenue.

This is the first study about the impact of gamification on teaching and learning PI. The authors apply the methods of T-test, correlation analysis and regression analysis to analyze the collected data. The paper proves that gamification can help students learn PI and that flow experience can improve the efficiency of students learning PI.

Distinguishing things that are actually true and theoretically true is an activity that people don’t realize they spend very much time doing, but in fact it takes up a considerable amount of time – although for very different reasons depending on who you are. If you are a HR manager, figuring out how rumors of a downturn in market conditions might affect morale and productivity is very different in theory (it is likely to) than in practice (actually speaking to people and looking at data). As such, answers may be very different – after speaking to people and seeing the data, you might learn that people are working harder to ensure their firm has the edge in any deteriorating market.

This briefing is prepared by an independent writer who adds his/her own impartial comments and places the articles in context.

Distinguishing things that are actually true and theoretically true is an activity that people don’t realize they spend very much time doing, but in fact it takes up a considerable amount of time – although for very different reasons depending on who you are. If you are a HR manager, figuring out how rumors of a downturn in market conditions might affect morale and productivity is very different in theory (it is likely to) than in practice (actually speaking to people and looking at data). As such, answers may be very different – after speaking to people and seeing the data, you might learn that people are working harder to ensure their firm has the edge in any deteriorating market.

This paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

More and more of today’s jobs involve knowledge work in a complex and ever-changing environment. Workers now have to take more responsibility for planning and organizing what they do and how they do it to fulfil their role. In these circumstances, it is not enough to have a training department delivering standardized courses. Each person’s learning needs are continually changing and individuals combine informal learning with their everyday work tasks. So more and more people are managing their own learning within the context and constraints created by their role and the organization.

The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The purpose of this paper is to present the design and implementation of music courseware that features a music search system that uses impression keywords. The paper applies the courseware to Kansei (sensibility) development for elementary and junior high school students. The objectives of this courseware are to cultivate children's sensitivity to the mood of a music selection; an understanding of the effects of tonality on the mood of the music; and) an ability to appreciate and express music through activities such as searching, selecting, and listening while also utilizing information about musical impression. The courseware is also designed to support teachers who do not specialize in music education.

Music courseware is designed containing the following three components: a semantic associative search engine that enables the retrieval of media data related to impression keywords selected by users; interfaces and tools for music retrieval and learning, which support users as they study the mood of the music in an easy‐to‐understand format using basic music teaching scenarios; and basic music teaching scenarios that are designed and created by elementary school teachers to encourage student understandings of the tonality and mood of the music in a practical manner.

The results of several qualitative and quantitative experiments show that this courseware assists children in independently learning musical elements by feeling, understanding, and expressing music impressions using words from the courseware that are extracted automatically from musical elements, such as key, rhythm, tempo, pitch, melody, and harmony.

Additional applications in various elementary and junior high school settings are needed to address a variety of practical, real‐life teaching scenarios.

This courseware have the potential to support enrichment programs not only in ordinary schools but also in a wide range of non‐educational settings, such as welfare care, disability care, and cross‐cultural communication.

The main feature of this courseware is its multimedia database technology, which applies Kansei to music education, thereby enabling students to understand the mood and structure of music based on their own subjective impressions using an objective framework.

This paper aims to draw on an in-depth qualitative case study of an undergraduate sustainability education course to show the extent of pedagogical reflection and teaching capability demonstrated in lived practice to support transformative, systemic and capability building learning processes, as advocated in the literature, for effective sustainability education.

Transformative learning and capability building are an essential part of sustainability education according to the growing body of literature. This approach to education, however, necessitates critical, learner-centred pedagogies which challenge traditional transmissive modes of teaching.

This paper finds that pedagogy which supports the learning experiences and outcomes advocated in sustainability education literature requires significant reflection on behalf of the educator and also motivation, capability and experience to do this, thus more research and academic support is needed which focusses on pedagogical development within sustainability education.

Literature on sustainability education often assumes that teachers are capable of reflecting on and transforming their pedagogical practice, and therefore, the pedagogical implications of sustainability education are often understated in research findings. This paper highlights why pedagogical reflection plays a crucial role in the effective implementation of sustainability education.

Online learning has evolved into a necessary means of learning because of its capability to enhance the education quality with minimum resources and infrastructure. Nevertheless, while academics have studied the espousal and use of online learning in various settings, the effect of compatibility and transformational leadership (TL) still remains to be seen, with regards to the Yemeni context. The purpose of this paper is to forward the Delone and Mclean Information System (IS) success Model by integrating compatibility and TL constructs as precursors to user contentment and actual use for estimating performance of students.

The questionnaire technique was utilised for gathering primary data from 448 students in nine state-funded Yemeni universities. The six variables in the recommended framework were gauged utilising current scales. Data analysis was done by deploying structural equation modelling through SmartPLS 3.0.

The outcomes encompassed three key results: overall quality (data, system and service quality), compatibility and TL have a favourable effect on user satisfaction and actual use; actual use considerably estimates user satisfaction; and user satisfaction and actual use have a favourable effect on performance of students.

Because the research populace comprised students from nine state-funded universities, it did not include administrative and academic staff. Furthermore, as the study was cross-sectional, it studied the variables at a single point of time. Attaining experience in utilising online learning would transform the convictions of students, and this cannot be traced through a cross-sectional scrutiny. Moreover, the research relies upon self-testified measures for ascertaining the recommended research model. The reason behind this is that obtaining objective information regarding performance was not likely because of the privacy concern.

Despite the fact that Yemen is a low-income emerging nation with inadequate resources (World Development Indicators, 2017), it can capitalise on online-based learning that provides the advantage of excellent education and that too with limited supplies (Dokhan and Akkoyunlu, 2016; Yang et al., 2016). Additionally, online learning can enhance administration and communication, empower learning anywhere and anytime, and endorse fairness of education.

This study supplements the existing studies on information systems by blending overall quality, compatibility, TL, actual use and client satisfaction for estimating the effect of online learning among students from nine state-funded Yemeni universities. Moreover, the recommended model’s predictive prowess has a higher capability to elucidate and estimate the performance effect as against those acquired from few of the previous studies.

Scheduling of aircraft maintenance operations is a gap in the literature. Maintenance times should be determined close to the real-life to schedule aircraft maintenance operations effectively. The learning effect, which has been studied extensively in the machine scheduling literature, has not been investigated on aircraft maintenance times. In the literature, the production times under the learning effect have been examined in numerous studies but for merely manufacturing and assembly lines. A model for determining base and line maintenance times in civil aviation under the learning effect has not been proposed yet. It is pretty challenging to determine aircraft maintenance times due to the various aircraft configurations, extended maintenance periods, different worker shifts and workers with diverse experience and education levels. The purpose of this study is to determine accurate aircraft maintenance times rigorously with a new model which includes the group learning effect with the multi-products and shifts, plateau effect, multi sub-operations and labour firings/rotations.

Aircraft maintenance operations are carried out in shifts. Each maintenance operation consists of many sub-operations that are performed by groups of workers. Thus, various models, e.g. learning curve for maintenance line (MLC), MLC with plateau factor (MPLC), MLC with group factor (MGLC) were developed and used in this study. The performance and efficiency of the models were compared with the current models in the literature, such as the Yelle Learning model (Yelle), single learning curve (SLC) model and SLC with plateau factor model (SLC-P). Estimations of all these models were compared with actual aircraft maintenance times in terms of mean absolute deviation (MAD), mean absolute percentage error (MAPE) and mean square of the error (MSE) values. Seven years (2014–2020) maintenance data of one of the top ten maintenance companies in civil aviation were analysed for the application and comparison of learning curve models.

The best estimations in terms of MAD, MAPE and MSE values are, respectively, gathered by MGLC, SLC-P, MPLC, MLC, SLC and YELLE models. This study revealed that the models (MGLC, SLC-P, MPLC), including the plateau factor, are more efficient in estimating accurate aircraft maintenance times. Furthermore, MGLC always made the closest estimations to the actual aircraft maintenance times. The results show that the MGLC model is more accurate than all of the other models for all sub-operations. The MGLC model is promising for the aviation industry in determining aircraft maintenance times under the learning effect.

In this study, learning curve models, considering groups of workers working in shifts, have been developed and employed for the first time for estimating more realistic maintenance times in aircraft maintenance. To the best of the authors’ knowledge, the effect of group learning on maintenance times in aircraft maintenance operations has not been studied. The novelty of the models are their applicability for groups of workers with different education and experience levels working in the same shift where they can learn in accordance with their proportion of contribution to the work and learning continues throughout shifts. The validity of the proposed models has been proved by comparing actual aircraft maintenance data. In practice, the MGLC model could efficiently be used for aircraft maintenance planning, certifying staff performance evaluations and maintenance trainings. Moreover, aircraft maintenance activities can be scheduled under the learning effect and a more realistic maintenance plan could be gathered in that way.

While many researchers have investigated the adoption and usage of online learning in different settings, one area that has yet to be examined thoroughly, particularly in the context of online learning in Yemen, is the self-efficacy role. The purpose of this paper is to extend the Delone and McLean information system success model by incorporating a self-efficacy construct as an antecedent to user satisfaction and actual usage to predict student performance.

Questionnaire survey method was used to collect primary data from 448 students in nine public universities in Yemen. The six constructs in the proposed model were measured using existing scales. The data analysed using confirmatory factor analysis and structural equation modelling via AMOS.

Three main results were revealed, namely that overall quality (system, information and service quality) and self-efficacy have a positive impact on user satisfaction and actual usage; that actual usage significantly predicts user satisfaction; and that both user satisfaction and actual usage have a positive impact on student performance.

First as the study population were students from nine public universities, it excluded academics and administrative staff. Second, the study depends on self-reported measures to test the proposed research model. This is because getting objective data about the performance was not probable due to the issue of privacy.

The findings of this study can be a guideline for Yemeni higher education institutions to develop efficient and effective plans to improve the performance of education institutions, and train and develop student ability to use online learning. Additionally, it highlights the areas that university management needs to concentrate on, namely information systems (IS) tools that will contribute to higher student enrolment, address the lack of infrastructure and improve the quality of education outcomes, things which represent Yemen’s main challenges in the higher education sector.

This paper adds to the existing literature of IS by combining overall quality, self-efficacy, actual usage and user satisfaction to predict performance impact of online learning among students in nine public universities in Yemen. Furthermore, the predictive power of the proposed model has a higher ability to explain and predict performance impact compared to those obtained from some of the previous studies.