Search results

The emphasis on short-term by project-based firms (PBFs) implies the adoption of project efficiency and impact on the team as project success drivers in PBFs context. Good performance by employees, as individuals in a team, can be explained by their behaviors, associated with goal orientation theory. Learning and performance orientations are associated with teams’ effectiveness and overall project performance. The purpose of this paper is to analyze the relationships between the dimensions of goal orientation, especially learning orientation, and project efficiency and impact on the team, in PBFs context.

A quantitative approach was adopted, based on data from a survey of 714 respondents, representing project managers, that turned into a valid sample of 315 composed only by PBFs respondents. The results were analyzed through multiple linear regression and, mainly, mediation analysis methods.

Performance-avoid orientation is a predictor of project efficiency; performance-prove orientation, a predictor of impact on the team. Learning orientation relates positively to both project success criteria. Project managers should balance/induce the proper orientation within the team, favoring learning orientation according to the results, to have short-term project success in PBFs.

There is a direct relationship between learning orientation and project efficiency, but it is fully mediated by impact on the team, which it was not found in previous studies. This study argues that they are not parallel constructs, constituent parts of equal weight in project success, but that impact on the team precedes project efficiency when learning orientation is considered.

The purpose of this paper is to investigate how absorptive capacity mediates the relationship between ambidextrous organizational learning and performance among small and medium-sized enterprises (SMEs).

Based on the resource-based view (RBV) and the dynamic capability approach, this paper uses the resource-capability-performance framework to construct the theoretical model of this study and tests the theoretical model with the questionnaire survey data of 189 SMEs in mainland China.

Ambidextrous organizational learning has different effects on SMEs' performance in terms of survival performance and growth performance. Both exploitative learning and exploratory learning have positive effects on absorptive capacity, and absorptive capacity has positive influences on both the survival performance and growth performance of SMEs. Absorptive capacity plays different mediating roles in the relationships between ambidextrous organizational learning and SMEs' performance: absorptive capacity plays a partial mediating role in the relationship between exploratory learning and SME growth performance, while absorptive capacity plays complete mediating roles in other relationships.

Managers must stress the use of exploratory learning in order to promote SMEs' growth performance. However, to foster both absorptive capacity and SME performance in terms of survival and growth, managers must pay more attention to take advantage of ambidextrous organizational learning. Government as policymakers should create a favorable environment that enable SMEs to benefit much more from the deployment of ambidextrous organizational learning and absorptive capacity.

To the best of authors’ knowledge, this study is the first to theorize and test the mediating role of absorptive capacity in the linkage between ambidextrous organizational learning and SME performance in terms of survival and growth. Additionally, this study also is the first to provide empirical support for the impact of ambidextrous organizational learning on absorptive capacity among SMEs.

The study examined the impact of feedback types through a learning management system (LMS) on employees’ training performance. The purpose of this study is to establish effective feedback on advanced technologies for promoting corporate training.

A total of 148 trainees were recruited from a multinational medical company. Employees were randomly assigned to receive feedback from shallow to more constructive details on their learning performance with LMS. Data sources included are employees’ goal setting (GS) performance evaluated by the experts and their posttest scores obtained from the LMS. A series of statistical analyses were performed to investigate the impact of feedback intervention on employees’ GS and their impacts on corporate training results.

GS has a significant impact on learning outcomes. Employees who set greater specific goals attained higher scores. Furthermore, feedback with more formative evaluation and constructive developmental advice resulted in the most significant positive influence on the relationship between participants’ GS and learning outcomes.

Organizations can benefit from delivering appropriate feedback using LMS to enhance employees’ GS and learning efficacy in corporate training.

This study is one of the first to examine the moderating effect of feedback provided by LMS on GS and online learning performance in corporate training. This study contributes to GS theory for practical application and proposes a viable method for remote learning. The current study’s findings can be used to provide educational psychological insights for training and learning in industrial contexts.

This paper investigates the relationship between past performance and the development of operational capabilities in manufacturing firms, focusing on the role of intra- and inter-organisational learning mechanisms.

This study is based on a survey database collected in 208 manufacturing plants in 15 countries from three industries: electronics, machinery and transport components. The authors developed a model and tested the study hypotheses using the structural equation modelling technique with two-stage analytical procedures.

In the analysis of the overall sample, the study findings support prior literature by suggesting that firms with successful experiences may become complacent and less motivated to engage in learning, leading to a decline in performance. However, high-performance firms overcome the “success trap” by engaging supply chain partners. In contrast, low-performance firms exhibit limited learning from past poor performance, leading to organisational inertia and further declines in their current performance.

This research provides practical guidance for managers in developing operational capabilities, highlighting collaboration with suppliers as an essential element for high-performance firms.

This study focuses on the little-researched topic of how past performance influences the development of operational capabilities in manufacturing firms. The authors highlight the path for developing capabilities in high- and low-performance firms based on intra- and inter-organisational learning mechanisms.

This study aims to explore how and when learning from others promotes creative performance over the contributor’s tenure in the context of open innovation communities.

The authors analyze a publicly available data set that includes 25,923 innovative items developed by 2,194 contributors from an open innovation community of an online game spanning eight years. Logistic regression model is used for analyzing the data.

The results show that multicultural experiences are negatively related to contributor’s creative performance, and this negative relationship weakens as contributor’s tenure increases. While diverse skills are positively related to contributor’s creative performance, and this positive relationship strengthens as contributor’s tenure increases.

This research highlights the importance of online team collaboration in knowledge transfer through learning from others in open innovation communities. By identifying two outcomes of learning from others through online team collaboration, the authors demonstrate the double-edged role of learning from others and advance the understanding on how the effect of learning from others varies over the contributor’s tenure. These results expand the understanding of online team collaboration and provide a new perspective for research on learning from others.

The purpose of this study is to generate knowledge about assessment methods in blended business education, which have become increasingly important to establish sustainable assessment practices that support knowledge acquisition for undergraduate students in business administration at a Colombian university.

For the analysis, a two groups comparison was performed using a nonequivalent control group design with a sample of 420 students. As this study wants to find insights to improve the knowledge on assessment topics in marketing research (MR) education, it was focused on the students from the business administration program. This study also uses individual scores from the state test as prior cognitive scores and the high school classification provided by the National Ministry of Education in Colombia (2012).

It was found that the variables that best predict performance on the MR course examinations were the mathematics skills and reading comprehension scores on the state test. The study also showed a better performance of female students on both assessment methods. There were no significant differences between the assessment methods or among the high school levels.

One of the limitations of this study is the limited number of items on the tests. Additionally, the authors recommend conducting an analysis of the differences between the testing items to provide a detailed explanation of students’ performance when comparing computer-based testing and paper-and-pencil testing.

Further design of teaching material and assessments online and offline, based on local and regional marketing problems, is suggested. As the current text and readings are more oriented to the English-speaking contexts, most of the problems presented are oriented to multinational companies and brands.

Insights into the skills required for future jobs provide valuable guidance (World Economic Forum, 2020). Essential skills for emerging roles, like data scientists, can find robust support within the MR course. To further enrich in-class and online exercises with Excel and SPSS, Colombian educators can leverage data sets obtained from sources like the national statistics office and international market intelligence databases available through the university’s library, including Passport and Statista. Engaging with authentic data sets provides students with a more profound understanding of practical applications in MR.

This approach facilitates the identification of key variables, such as assessment and cognitive abilities in math and reading, which predict students’ knowledge acquisition in MR. It not only offers insights into the relevant factors influencing learning in MR but also provides valuable feedback. Additionally, it suggests potential avenues for future research in this field.

Employee training and learning have transformed over the years. The movement from classroom training to the blended format represents the magnitude of this evolution. This has placed much attention on self-regulated learning. This study aimed to understand the individual and organizational mechanisms that sustain the formal learning process in organizations. It explored the goals the organizations and employees strive to achieve by investing in learning. Through this, the authors investigated how technology assistance makes learning more goal-oriented, despite the possibility of different goals for different stakeholders. They also examined how person-job fit can be achieved in employee training.

The study adopted a grounded theory-based inductive approach using a qualitative inquiry that used in-depth interviews of employees working in the Indian IT/ITES sector. This sector is knowledge-intensive and engages in constant skill development. A content analysis of the interview transcripts unraveled the most relevant themes from the participants' discussion.

Individual learners use dimensions of self-regulated learning to set and achieve goals such as better performance and career development. On the other hand, organizations use learning support mechanisms such as better access and flexibility to direct employee learning behavior to achieve organizational goals. Focusing on goal congruence leads to better achievement of results. Goal congruence also implies good person-organization fit.

This research established how aligning individual and organizational mechanisms can help achieve training goals that ultimately contribute to organizational performance. The study differentiated itself by investigating training goal setting and goal achievement at two levels – organizational and individual – using a qualitative approach. It also showed how goal congruence is vital in improving organizational performance and how technology-enabled training practices rely on self-regulated learning and help achieve goal congruence.

This paper defines and assesses student learning patterns under the influence of problem-based learning (PBL) and their classification into a reasonable minimum number of classes. Study utilizes PBL implemented in an undergraduate Statistics and Operations Research course for techno-management students at a private university in India.

Study employs an in situ experiment using a conceptual model based on learning theory. The participant's end-of-semester GPA is Performance Indicator. Integrating PBL with classroom teaching is unique instructional approach to this study. An unsupervised and supervised data mining approach to analyse PBL impact establishes research conclusions.

The administration of PBL results in improved learning patterns (above-average) for students with medium attendance. PBL, Gender, Math background, Board and discipline are contributing factors to students' performance in the decision tree. PBL benefits a student of any gender with lower attendance.

This study is limited to course students from one institute and does not consider external factors.

Researchers can apply learning patterns obtained in this paper highlighting PBL impact to study effect of every innovative pedagogical study. Classification of students based on learning behaviours can help facilitators plan remedial actions.

1. Clustering is used to extract student learning patterns considering dynamics of student performances over time. Then decision tree is utilized to elicit a simple process of classifying students. 2. Data mining approach overcomes limitations of statistical techniques to provide knowledge impact in presence of demographic characteristics and student attendance.

This paper aims to examine the mediation effect of organizational learning on the link between human resource management (HRM) practices and organizational performance in some Big4 financial services companies.

The quantitative methodology was chosen for this research, using resource theory and knowledge-based approach to explain the relationship between latent variables. A sample of 403 HR employees and managers of the companies under study in France was selected in 2022. Structural equations modeling was used based on the Spss-Amos program to test the research hypotheses.

The results revealed that organizational learning played a mediating role between HRM practices (hiring, training, motivation and decision-making) and organizational performance and that learning enabled the performance of workers to improve and achieve competitive advantages in this field.

The sample was based on four international companies working in the field of financial services and consulting and providing their services within France, which may affect the generalisability of the results and limit them to the studied sector.

The contribution of the study is to improve the awareness of administrators, decision makers and company employees of the importance of organizational learning for companies, and to stimulate motivation to learn and exchange knowledge in a constructive way that enhances organizational performance. Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

Working on organizational culture change through HRM-practices-based learning as an effective mechanism for organizational performance improvement is one implication. These practises influence cadres' attitudes toward their work, which improves their performance.

This study seeks to provide cadres and executives with an in-depth analysis of HRM and organizational learning, which, through its integration of these attributes, can contribute to the earning of knowledge-based competitive advantage and achieve superior and sustainable performance.

The purpose of this research is to achieve multi-task autonomous driving by adjusting the network architecture of the model. Meanwhile, after achieving multi-task autonomous driving, the authors found that the trained neural network model performs poorly in untrained scenarios. Therefore, the authors proposed to improve the transfer efficiency of the model for new scenarios through transfer learning.

First, the authors achieved multi-task autonomous driving by training a model combining convolutional neural network and different structured long short-term memory (LSTM) layers. Second, the authors achieved fast transfer of neural network models in new scenarios by cross-model transfer learning. Finally, the authors combined data collection and data labeling to improve the efficiency of deep learning. Furthermore, the authors verified that the model has good robustness through light and shadow test.

This research achieved road tracking, real-time acceleration–deceleration, obstacle avoidance and left/right sign recognition. The model proposed by the authors (UniBiCLSTM) outperforms the existing models tested with model cars in terms of autonomous driving performance. Furthermore, the CMTL-UniBiCL-RL model trained by the authors through cross-model transfer learning improves the efficiency of model adaptation to new scenarios. Meanwhile, this research proposed an automatic data annotation method, which can save 1/4 of the time for deep learning.

This research provided novel solutions in the achievement of multi-task autonomous driving and neural network model scenario for transfer learning. The experiment was achieved on a single camera with an embedded chip and a scale model car, which is expected to simplify the hardware for autonomous driving.