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Research on coping at work has tended to adopt a between-person perspective, producing inconsistent findings on well-being outcomes. This focus on interindividual differences is in contrast to many theories that position coping as process, hence, as an intraindividual process that unfolds over time in response to job stressors and appraisals. The authors propose that focusing more on the within-person coping processes and integrating them with learning perspectives has the potential to advance our understanding. More specifically, coping behavior and well-being can be seen as an outcome of current and past learning processes. In this chapter, the authors discuss three mechanisms that explain how coping processes can produce positive versus negative effects on well-being, and how coping can be integrated into a learning framework to explain these pathways. First, the stress process entails encoding and evaluation of the situation and, as a consequence, deployment of suitable coping behavior. Over and above the efforts that have to be invested to understand the stressful situation, the coping behavior itself also requires time and energy resources. Second, coping behavior likely co-occurs with learning processes such as reflection, exploration, and exploitation. These learning processes require further time and cognitive resources. Third, although coping behaviors and their accompanying learning processes have the potential to drain resources at the within-person level, they can also build up interindividual coping resources such as a broader repertoire and coping flexibility. These between-level differences equip employees to deal with future stressors.

Most studies have focused on the impact of the application of AI on management attributes, management decisions and management ethics. However, how job demand and job control in the context of AI collaboration determine employees' learning process and learning behaviors, as well as how AI collaboration moderates employees' learning process and learning behaviors, remains unknown. To answer these questions, the authors adopted a Job Demand-Control (JDC) model to explore the influencing factors of employee's individual learning behavior.

This study used questionnaire survey in organizations using AI to collect data. Partial least squares (PLS) predict algorithm and SPSS were used to test the hypotheses.

Job demand and job control positively influence self-efficacy, self-efficacy positively influences learning goal orientation and learning goal orientation positively influences learning behavior. Learning goal orientation plays a mediating role between self-efficacy and learning behavior. Meanwhile, collaboration with AI positively moderates the impact of employees' job demand on self-efficacy and the impact of self-efficacy on learning behavior.

This study introduces self-efficacy as the outcome of JDC model, demonstrates the mediating role of learning goal orientation and introduces collaborative factors related to artificial intelligence. This study further enriches the theoretical system of human–AI interaction and expands the content of organizational learning theory.

Organizations face a paradox. Because of the disruptions of COVID-19, learning and development was largely put on hold. However, this disruption also changed the value proposition for employees: they expect learning and development to be prioritized. The purpose of this paper is to resolve this paradox by providing a strategic framework that increases the capacity for workplace learning within the constraints of a hybrid world.

Although the COVID-19 disrupted shifted when and where employees learn, it did not change how learning occurs. Therefore, this paper draws from research on workplace learning, cognitive science and neuroscience to develop a conceptual framework of workplace learning and provide practical guidance on how leaders can support it in a hybrid world.

This paper presents a new framework for workplace learning. First, this paper identifies seven key workplace learning behaviors. This paper addresses why a focus on behavior over outcomes is strategically advantageous for hybrid learning. Second, this paper details the opportunities, resources and leadership behaviors that enable each behavior.

This paper provides scholars with a new approach to learning and opens avenues for research on the antecedents of workplace learning behaviors, as well as understanding how the behaviors interact over time.

This paper helps executives make strategic decisions about hybrid learning based on the science of learning. This paper also provides key tactics for how to encourage and enable employees to learn in remote or hybrid environments.

Although there is an abundance of research on individual, team and organizational learning, there is little guidance on what strategies leaders can use to enable learning in the moment, when it is needed most. This paper reorients learning strategy away from learning outcomes to focus on the behaviors that are required to achieve those outcomes. In doing so, this paper provides a model for learning how to learn in a hybrid world.

The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners’ online learning behaviors, and comparing three algorithms – multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).

Through literature review and analysis of data correlation in the original database, a framework of online learning behavior indicators containing 26 behaviors was constructed. The degree of correlation with the final learning performance was analyzed based on learners’ system interaction behavior, resource interaction behavior, social interaction behavior and independent learning behavior. A total of 12 behaviors highly correlated to learning performance were extracted as major indicators, and the MLR method, MLP method and CART method were used as typical algorithms to evaluate learners’ MOOC learning performance.

The behavioral indicator framework constructed in this study can effectively analyze learners’ learning, and the evaluation model constructed using the MLP method (89.91%) and CART method (90.29%) can better achieve the prediction of MOOC learners’ learning performance than using MLR method (83.64%).

This study explores the patterns and characteristics among different learning behaviors and constructs an effective prediction model for MOOC learners’ learning performance, which can help teachers understand learners’ learning status, locate learners with learning difficulties promptly and provide targeted instructional interventions at the right time to improve teaching quality.

Methodological pluralism in consumer research is usually confined to post‐positivist interpretive approaches. Argues, however, that a positivistic stance, radical behaviourism, can enrich epistemological debate among researchers with the recognition of radical behaviourism′s ultimate reliance on interpretation as well as science. Although radical behaviourist explanation was initially founded on Machian positivism, its account of complex social behaviours such as purchase and consumption is necessarily interpretive, inviting comparison with the hermeneutical approaches currently emerging in consumer research. Radical behaviourist interpretation attributes meaning to behaviour by identifying its environmental determinants, especially the learning history of the individual in relation to the consequences similar prior behaviour has effected. The nature of such interpretation is demonstrated for purchase and consumption responses by means of a critique of radical behaviourism as applied to complex human activity. In the process, develops and applies a framework for radical behaviourist interpretation of purchase and consumption to four operant equifinality classes of consumer behaviour: accomplishment, pleasure, accumulation and maintenance. Some epistemological implications of this framework, the behavioural perspective model (BPM) of purchase and consumption, are discussed in the context of the relativity and incommensurability of research paradigms. Finally, evaluates the interpretive approach, particularly in terms of its relevance to the nature and understanding of managerial marketing.

This study aims to explore the effect of expatriate supervisors’ managerial coaching behavior on local subordinates’ learning effects through the mediating role of subordinates’ thriving at work under the boundary condition of expatriate supervisors’ cultural intelligence.

This study collected the data form 230 Zambian subordinates and their immediate expatriate supervisors working in the Chinese company in Zambia. Regression analyses and bootstrapping analyses were used to test the authors’ hypothesis.

The results indicated that expatriate supervisors’ managerial coaching behavior was positively related to local subordinates’ learning effects. In addition, the study also found that local subordinates’ thriving at work mediated the linkage between managerial coaching behavior and learning effects. And expatriate supervisors’ cultural intelligence moderated the indirect relationship between managerial coaching behavior and learning effects via thriving at work, such that the indirect effect was stronger for expatriate supervisors with high rather than low cultural intelligence.

This study contributes to a better understanding of how expatriate supervisors’ managerial coaching behavior influences local subordinates’ learning effects by investigating the mediating effect of thriving at work on the managerial coaching behavior–learning effects link. In addition, the study deepens the understanding of the boundary condition of the associations between managerial coaching behavior and subordinates’ learning effects in a cross-cultural context by investigating the moderating effect of expatriate supervisors’ cultural intelligence.

The purpose of this paper is to review the current state of proceedings in the research area of automatic swarm design and discusses possible solutions to advance swarm robotics research.

First, this paper begins by reviewing the current state of proceedings in the field of automatic swarm design to provide a basic understanding of the field. This should lead to the identification of which issues need to be resolved in order to move forward swarm robotics research. Then, some possible solutions to the challenges are discussed to identify future directions and how the proposed idea of incorporating learning mechanism could benefit swarm robotics design. Lastly, a novel evolutionary-learning framework for swarms based on epigenetic function is proposed with a discussion of its merits and suggestions for future research directions.

The discussion shows that main challenge which is needed to be resolved is the presence of dynamic environment which is mainly caused by agent-to-agent and agent-to-environment interactions. A possible solution to tackle the challenge is by incorporating learning capability to the swarm to tackle dynamic environment.

This paper gives a new perspective on how to improve automatic swarm design in order to move forward swarm robotics research. Along with the discussion, this paper also proposes a novel framework to incorporate learning mechanism into evolutionary swarm using epigenetic function.

This study aims to propose a blackboard approach using multistrategy machine learning student modeling techniques to learn the properties of students' inconsistent behaviors during their learning process.

These multistrategy machine learning student modeling techniques include inductive reasoning (similarity‐based learning), deductive reasoning (explanation‐based learning), and analogical reasoning (case‐based reasoning).

According to the properties of students' inconsistent behaviors, the ITS (intelligent tutoring system) may then adopt appropriate methods, such as intensifying teaching and practicing, to prevent their inconsistent behaviors from reoccurring.

This research sets the learning object on a single student. After the inferences are accumulated from a group of students, what kinds of students tend to have inconsistent behaviors or under what conditions the behaviors happened for most students can be learned.

The purpose of this study is to investigate the mediating effect of work engagement on the relationship between learning organization and innovative behavior.

This study used surveys as a data collection tool and implemented structural equation modeling for empirically testing the proposed research model.

The study found that learning organization culture makes a direct and indirect impact on employees' innovative work behaviors. Results from hierarchical multiple regressions and structural equation modeling supported that work engagement fully mediates the relationship between the learning organization and innovative work behaviors.

HRD practitioners can develop effective interventions to enhance their employees' innovative behavior by devoting efforts to create a workplace that promotes collaborative learning culture and work engagement.

This study is valuable to HRD specialists interested in developing effective interventions that encourage employees to engage in innovative behavior.

The purpose of this study is to explore the role of employees’ underlying implicit person theories in the relationship with innovative work climate and proactive behaviour at work. First, the authors study how an employee’s implicit person theory (IPT), or the domain-general implicit belief about the development potential of people’s attributes, relates to learning goal orientation and proactive learning and entrepreneurial behaviour at work. Second, the authors investigate how employees’ perception of their work climate is associated with this IPT.

The authors set up an exploratory study relying on survey data from a sample of 498 professionally active Flemish adults and analysed a correlational path through SEM.

The authors found that holding an incremental IPT (i.e. believing in the development potential of people’s attributes) positively relates to proactive learning and entrepreneurial behaviour. Moreover, the authors found that employees working in an innovative work climate are more likely to hold an incremental IPT.

This study offers indications that IPT is a relevant explanatory variable in the relationship between innovative work climate on the one hand and learning goal orientation, learning work behaviour and entrepreneurial work behaviour on the other hand. As such, this study suggests that IPT is a promising concept that can be actively endorsed as a relevant underlying psychological process variable for fostering learning and entrepreneurial behaviour in organizations.