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Advances in material agency driven by artificial intelligence (AI) have facilitated breakthroughs in material adaptivity enabling smart objects to autonomously provide individualized smart services, which makes smart objects act as social actors embedded in the real world. However, little is known about how material adaptivity fosters the infusion use of smart objects to maximize the value of smart services in customers' lives. This study examines the underlying mechanism of material adaptivity (task and social adaptivity) on AI infusion use, drawing on the theoretical lens of social embeddedness.

This study adopted partial least squares structural equation modeling (PLS-SEM), mediating tests, path comparison tests and polynomial modeling to analyze the proposed research model and hypotheses.

The results supported the proposed research model and hypotheses, except for the hypothesis of the comparative effects on infusion use. Besides, the results of mediating tests suggested the different roles of social embeddedness in the impacts of task and social adaptivity on infusion use. The post hoc analysis based on polynomial modeling provided a possible explanation for the unsupported hypothesis, suggesting the nonlinear differences in the underlying influencing mechanisms of instrumental and relational embeddedness on infusion use.

The formation mechanisms of AI infusion use based on material adaptivity and social embeddedness help to develop the business strategies that enable smart objects as social actors to exert a key role in users' daily lives, in turn realizing the social and economic value of AI.

This study advances the theoretical research on material adaptivity, updates the information system (IS) research on infusion use and identifies the bridging role of social embeddedness of smart objects as agentic social actors in the AI context.

The purpose of this paper is to examine the relationship of perceived transformative human resource (HR) practices and employee task performance. Drawing on evidence-based approach, the transformative HR practices intend to transform employees’ behavior to cope with organizational change. This study intends to answer how does the perceived transformative HR practices influence employees’ behavioral capability to enhance their task performance. This investigation proposes that the perceived transformative HR practices positively affect employees task performance, however, employee adaptivity mediates the relationship between them.

The authors used a random sample of 224 employees, from a large high-tech company in China, to test the hypotheses. Exploratory and confirmatory factor analyses were conducted to determine the perceived transformative HR practices in the context of a high-tech firm. The authors performed multiple linear regression analysis to examine the proposed model.

The results of this study indicate that the perceived transformative HR practices positively influence employee adaptivity and task performance. Furthermore, employee adaptivity mediates the relationship between the perceived transformative HR practices and employee task performance. Therefore, employee adaptivity illuminates and explains the underlying mechanism of how the perceived transformative HR practices lead to employee task performance.

Data collected from single firm may limit the generalizability of the findings and cross-sectional research design may raise the concern of common method bias. Future studies should test and validate the operationalization of the perceived transformative HR practices in different research contexts and with larger sample size. Organizations should design and implement transformative HR practices to cope with change. Furthermore, organizational managers should encourage and facilitate employee adaptivity to achieve better performance.

This study contributes to change management and the HR literature by identifying and operationalizing the perceived transformative HR practices as a predictor of employee adaptivity and task performance. Through the underlying mechanism of employee adaptivity between the perceived transformative HR practices and employee task performance, this study provides a new perspective to look at the HR-performance relationship in the change process.

The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity in any given learning management system based on learners’ learning styles.

This paper offers a brief review of current frameworks and systems to support adaptivity in e-learning environments. A framework to support adaptivity is designed and discussed, reflecting the hybrid approach in detail. A system prototype is developed incorporating different adaptive features based on the Felder-Silverman learning styles model. Finally, the prototype is implemented in Moodle.

The system prototype supports real-time adaptivity in any given learning management system based on learners’ learning styles. It can deal with any type of content provided by course designers and instructors in the learning management system. Moreover, it can support adaptivity at both course and learner levels.

To the best of the authors’ knowledge, no previous work has been done incorporating the concept of the ECA model and intelligent agents as hybrid architecture to support adaptivity in e-learning environments. The system prototype has wider applicability and can be adapted to support different types of adaptivity.

The purpose of this study was to determine the roles of employee proficiency, adaptivity and proactivity in predicting different aspects of internal service.

Managers evaluated 142 professional employees on proficiency, adaptivity and proactivity and about six weeks later 2–3 internal customers evaluated each of the employees on dimensions of internal service, namely reliability (i.e. performing dependably and accurately), assurance (i.e. knowledge, courtesy, and the ability to inspire trust and confidence), responsiveness (i.e. willingness to help customers and provide prompt service) and empathy (i.e. caring and providing individualized attention).

Employee proficiency and proactivity were the main predictors of delivering reliable services. Employee proficiency was the main predictor for creating a sense of assurance. Employee adaptivity was the main predictor of being viewed as responsive. Employee proactivity was the main predictor for establishing a sense of empathy.

In a given situation, some aspects of internal service will be more important than others. The results will enable organizations to improve internal service in a more effective and efficient manner by developing interventions that are targeted at the specific dimension of interest.

The authors identified the types of employee behaviors that are likely to be most effective in impacting different aspects of internal service.

The purpose of this paper is to address error‐controlled adaptive finite element (FE) method for thin and thick plates. A procedure is presented for determining the most suitable plate model (among available hierarchical plate models) for each particular FE of the selected mesh, that is provided as the final output of the mesh adaptivity procedure.

The model adaptivity procedure can be seen as an appropriate extension to model adaptivity for linear elastic plates of so‐called equilibrated boundary traction approach error estimates, previously proposed for 2D/3D linear elasticity. Model error indicator is based on a posteriori element‐wise computation of improved (continuous) equilibrated boundary stress resultants, and on a set of hierarchical plate models. The paper illustrates the details of proposed model adaptivity procedure for choosing between two most frequently used plate models: the one of Kirchhoff and the other of Reissner‐Mindlin. The implementation details are provided for a particular case of the discrete Kirchhoff quadrilateral four‐node plate FE and the corresponding Reissner‐Mindlin quadrilateral with the same number of nodes. The key feature for those elements that they both provide the same quality of the discretization space (and thus the same discretization error) is the one which justifies uncoupling of the proposed model adaptivity from the mesh adaptivity.

Several numerical examples are presented in order to illustrate a very satisfying performance of the proposed methodology in guiding the final choice of the optimal model and mesh in analysis of complex plate structures.

The paper confirms that one can make an automatic selection of the most appropriate plate model for thin and thick plates on the basis of proposed model adaptivity procedure.

Learning from errors is important for employees, particularly at early stages of their career. The purpose of this paper is to examine the influence of perceived trainer responses to errors on trainee learning from errors in a workplace setting. In Study 1, the authors test a model that examines the associations between perceived trainer responses to errors and trainee learning from errors, which are mediated by affective-motivational adaptivity. In Study 2, the authors further hypothesize that the link between perceived trainer responses and affective-motivational adaptivity is moderated by perceived error climate.

The authors test the hypotheses using data from 213 Swiss apprentices (Study 1) and 1,012 German apprentices (Study 2) receiving dual vocational training.

Study 1 suggests that negative trainer reaction impedes trainee learning from errors by impairing trainees’ affective-motivational adaptability. Trainer tolerance of errors and trainer support following errors were not related to trainee learning from errors. Study 2 indicates that perceived error climate is an important boundary condition that affects the relationship between trainer responses and trainee learning from errors.

This study contributes to research on learning from errors in three ways. First, it enriches the understanding regarding the role of trainers in enhancing learning from errors in organizations. Second, it extends research on learning from errors by investigating the interaction effects between perceived trainer responses and error climate. Third, it refines knowledge about the role of positive affect in learning from errors. Findings of this study also offer practical insights to trainers and managers regarding what they should do to encourage trainee learning from errors.

The paper presents the principal elements of automatic adaptivity built in our 2D software for monolithic solution of multiphysics problems based on a fully adaptive finite element method of higher order of accuracy. The adaptive techniques are illustrated by appropriate examples.

Presented are algorithms for realization of the h‐adaptivity, p‐adaptivity, hp‐adaptivity, creation of curvilinear elements for modelling general boundaries and interfaces. Indicated also is the possibility of combining triangular and quadrilateral elements (both classical and curved).

The presented higher‐order adaptive processes are reliable, robust and lead to a substantial reduction of the degrees of freedom in comparison with the techniques used in low‐order finite element methods. They allow solving examples that are by classical approaches either unsolvable or solvable at a cost of high memory and time of computation.

The adaptive processes described in the paper are still limited to 2D computations. Their computer implementation is highly nontrivial (every physical field in a multiphysics task is generally solved on a different mesh satisfying its specific features) and in 3D the number of possible adaptive steps is many times higher.

The described adaptive techniques may represent a powerful tool for the monolithic solution of complex multiphysics problems.

The presented higher‐order adaptive approach of solution is shown to provide better results than the schemes implemented in professional codes based on low‐order finite element methods. Obtaining the results, moreover, requires less time and computer memory.

Policy makers have called for more entrepreneurship throughout societies as a response to the digital transformation. This paper argues that the rapidly changing conditions of the digital age indeed mark a change in the bases of entrepreneurship. Specifically, as adaptivity becomes key, a learning capacity and general ability to adapt becomes a critical factor in entrepreneurial activity. The paper identifies self-directed learning (SDL) as a fundamental competence in this regard and examines its role for entrepreneurship and entrepreneurial competence.

The paper develops a theoretical framework for the role of SDL in entrepreneurship through a process of systematic review of previous studies that have linked SDL to entrepreneurship.

The formulated theoretical framework shows how SDL competence combines with experiential learning in supporting the kind of adaptivity needed for entrepreneurial competence, especially under more rapidly changing conditions. SDL competence also gains wider importance through enabling individuals to meet the demands of organizational changes in our highly volatile world.

SDL competence prepares individuals for entrepreneurship and resilience in face of rapid changes as well as for being more entrepreneurial in the conduct of their lives more generally. Fostering SDL competence can thus be regarded as an important objective of entrepreneurship education.

The described self-directed experiential learning cycle offers a novel perspective that clarifies how both self-directed and experiential learning competences are integral for understanding the basis of adaptiveness in entrepreneurial activity.

Designing for the future sustainability and adaptability of building assets contributes to waste and emission reduction. Moreover, sustainable design and conservation principles are necessary for achieving sustainable and adaptable built heritage. The purpose of this paper is to introduce the improved adaptSTAR model in regards to maximising the future adaptive reuse and sustainability of existing built heritage and its surroundings.

A comparative study of two iconic nineteenth century heritage assets in Australia and Hong Kong is undertaken to highlight the need to forecast the future adaptation of heritage buildings in order to guarantee their continuous reuse and sustainability in an urban context.

Findings show that the functional, technological and legal attributes of these two nineteenth century heritage buildings require improvement so as to ensure their future adaptivity. The upgrading of heritage buildings for environmental sustainability is also deemed necessary.

The originality of this paper pertains to the advancement of the adaptSTAR tool in evaluating the future adaptivity of existing built heritage as well as new built environments whilst considering their economic, environmental and social values.

Prior research indicates that empowering leadership has simultaneous contradictory effects on work performance. This study aimed to explore contradictory mechanisms through which empowering leadership is related to work role performance behaviors.

The sample was composed of 274 professionals from five IT companies located in the Baltic area. OLS regression analyses were performed using MEDCURVE for SPSS 23.0.

Empowering leadership is positively related to work role performance behaviors; additionally, perceived uncertainty mediates the relationship between empowering leadership and work role performance behaviors, with the relationship between empowering leadership and uncertainty having a curvilinear U-shape (concave upward). That is, although empowering leadership is positively related to work role performance, the relationship between empowering leadership and work role performance though uncertainty becomes non-significant at high levels of empowering leadership.

This is one of the first studies to demonstrate that empowering leadership is related to work performance through simultaneous compensatory mechanisms. Moreover, this study provides evidence about the curvilinear relationship between empowering leadership and performance through uncertainty (previously unknown).