Search results

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

Based on social cognitive theory, this study aims to explore the influence of supervisor bottom-line mentality (SBLM) on employee knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior). The study first investigates the role of an ethical decision-making mechanism (moral disengagement) in mediating this relationship. In addition, it considers the possible boundary conditions to supplement research on the influence of SBLM in the knowledge management field.

The authors collected 256 data points from employees across three stages using convenience sampling. The authors then tested the proposed hypothesis using hierarchical regression and bootstrap methods.

The results demonstrated that SBLM promotes employees’ moral disengagement, leading to more knowledge territorial behavior and knowledge sabotage behavior. Furthermore, high power distance orientation among employees exacerbates the ill effects of SBLM according to the first stage of a moderated mediation model. Employees with such an orientation are more likely to respond to a SBLM by exhibiting a higher level of moral disengagement, thus increasing their knowledge territorial behavior and knowledge sabotage behavior.

Research on the influence of SBLM in the knowledge management field is limited. This study not only clarifies the relationships between SBLM and two types of knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior) but also enriches the research on the antecedents of these two types of knowledge behavior.

The paper aims to identify the critical constraints that impede heritage building (HB) facility managers from discharging their duties effectively and develop an index model to guide HB maintenance management (HBMM) practitioners to the critical constraints.

A literature review was conducted to identify HBMM constraints. Facilty management practitioners assessed the constraints' significance through an online survey. The factor analysis was used to shortlist and group the constraints, and the constraint clusters were analyzed by the fuzzy synthetic evaluation technique. A significant index cluster to determine HBMM constraints criticality was generated using the linear additive model.

Embracing a total of 16 HBMM constraints, the three clusters identified are: (1) managerial and inadequacy constraints, (2) pressure and bureaucracy constraints and (3) HB peculiarities constraints. Based on the generated significant index, the HB peculiarities cluster was identified as the most significant.

The study was conducted in a particular jurisdiction, limiting the generalizability of the result. Future research should address this limitation by covering more jurisdictions.

The significant index model (SIM) developed enables HBMM practitioners to objectively assess the criticality of HB constraints and facilitates them to effectively strategize and allocate resources for HBMM.

The SIM, which transforms subjective judgment into the objective assessment of the HBMM constraints' criticality, can assist practitioners, policymakers and other HBMM stakeholders in implementing strategies for the sustainability of HBs.

This paper aims to systematically demonstrate a methodology to determine the relative and absolute encapsulation efficiencies (α_Re and α_Ab) for thermally- and chemically-robust inorganic pigments, typically like ZrSiO₄-based pigments, thereby enhancing their coloring performance.

The authors designed a route, surplus alkali-decomposition and subsequently strong-acid dissolution (SAD2) to completely decompose three classic zircon pigments (Pr–ZrSiO₄, Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄) into clear solutions and preferably used inductively coupled plasma-optical emission spectrometry (ICP-OES) to determine the concentrations of host elements and chromophores, thereby deriving the numeric data and interrelation of α_Re and α_Ab.

Zircon pigments can be thoroughly decomposed into some dissoluble zirconate–silicate resultants by SAD2 at a ratio of the fluxing agent to pigment over 6. ICP-OES is proved more suitable than some other quantification techniques in deriving the compositional concentrations, thereby the values of α_Re and α_Ab, and their transformation coefficient K_RA, which maintains stably within 0.8–0.9 in Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄ and is slightly reduced to 0.67–0.85 in Pr–ZrSiO₄.

The SAD2 method and encapsulation efficiencies are well applicable for both zircon pigments and the other pigmental or non-pigmental inhomogeneous systems in characterizing their accurate composition.

The authors herein first proposed strict definitions for the relative and absolute encapsulation efficiencies for inorganic pigments, developed a relatively stringent methodology to determine their accurate values and interrelation.

This study investigate the correlation between authoritarian leadership and organizational deviance. Furthermore, it seeks to explore the mediating role of emotional exhaustion in this relationship.

The data were obtained from 398 frontline service employees and their immediate supervisors at 25 five-star hotels. Data were collected on different occasions.

The results indicate that authoritarian leadership has a positive and significant relationship with organizational deviance. We also conclude that emotional exhaustion mediates the relationship between authoritarian leadership and organizational deviance.

The present research suggests that managers can decrease emotional exhaustion and, consequently, organizational deviance, by avoiding an authoritarian leadership style. Additionally, the theoretical and managerial implications of the present study can be utilized to reduce organizational deviance.

The present study adds to the existing literature on authoritarian leadership, emotional exhaustion and organizational deviance by offering a possible explanation for how emotional exhaustion mediates the relationship between authoritarian leadership and organizational deviance.

The recent COVID-19 pandemic caused a severe economic downturn. Employees working in these organisations face employment uncertainty. The pandemic disrupted their daily routines, and it added a layer of complexity to the already resource-constrained environment. During these times, employees would conserve their resources to maintain competitiveness, one of which is knowledge hiding. While economic activities are resuming, the appearance of new variants could mean the transition towards endemicity could be put on hold. Hence, there is a need to rethink the behaviour of employees as they would have elevated levels of anxiety towards resuming daily work activities. Therefore, this study aims to address the question of understanding employees’ perspectives toward knowledge sharing and knowledge hiding.

Drawing on the conservation of resources theory, social learning theory and the social exchange theory (SET), a conceptual framework involving ethical leadership was developed to examine if knowledge hiding or knowledge sharing behaviour is a resource for employees during these times. The partial least squares method of structural equation modelling was used to analyse results from 271 white-collar employees from Singapore.

The results show that ethical leadership encourages knowledge sharing but does not reduce knowledge hiding. At the same time, knowledge hiding, not knowledge sharing, improves one’s perception of work performance. Additionally, psychological safety is the key construct that reduces knowledge hiding and encourages sharing behaviour.

Overall, this study extends the theories, demonstrating that, first and foremost, knowledge hiding is a form of resource that provides employees with an added advantage in work performance during the endemic. At the same time, we provide a new perspective that ethical leaders’ demonstration of integrity, honesty and altruism alone is insufficient to encourage knowledge sharing or reduce knowledge hiding. It must lead to a psychologically safe environment.

Consumers may enjoy the information sharing and social support made available when a social media platform is used for pre-purchase research; however, do consumers reevaluate the privacy and security of the platform differently when ordering and payment capabilities are added? As social media systems have evolved into social commerce platforms (SCPs), individuals are often faced with whether to complete a purchase they have been researching or switch to a traditional e-commerce platform to complete the transaction. This research examines consumer trust formation in the SCP channel and how consumer interest and engagement in the channel are maintained and influence consumer decisions to purchase via the SCP.

Based on trust and involvement literature, a research model was conceptualized to capture consumer beliefs about SCP privacy and security and whether the SCP can be trusted, using these inputs into subsequent consumer interest, engagement and decisions on whether to use the SCP for purchasing. The research model was empirically tested using the panel data's structural equation modeling (AMOS) (n = 405). The data showed acceptable reliability and convergent validity, while the original research model provides predictive validity and theory-confirming insights.

Results confirm that consumer perceptions of privacy and security play a crucial role as decision criteria, informing their judgments of whether a new social commerce channel can be trusted enough to conduct purchases. Further, consumer trust supports their interest in the SCP, resulting in enduring and enhanced behavioral use and, to a lesser extent, purchase intent. Still, a majority of this sample declined to purchase using the SCP and rather preferred to transact on tried and trusted traditional e-commerce sites.

This study is among the first to examine trust formation in new SCPs, where consumers are deciding to expand their engagement level from social and informational to commercial.

This paper aims to present the vertical integration state-of-the-art and propose an expansion of the operations and supply chain management (OSCM) field by identifying gaps and bottlenecks.

This paper uses a systematic literature review based on a sample of 173 OSCM field articles, collected from Scopus and Web of Science databases.

There are no single factors, such as future costs, structures or skills development, in the decision to vertically integrate operations. It is necessary to combine the vision of production costs with the perspective of governance and transaction costs. In addition, it is essential to consider the competency perspective and its impact on capability building.

Few studies have attempted to understand how vertical integration is used in terms of OSCM research themes and theories. Vertical integration can help companies face challenges and serve as a potential solution for achieving better prices, demand control and quality management.

The significant role of vertical integration mechanisms in supply chains is crucial for managers evaluating a firm's reconfiguration with more vertical operations. Policymakers interested in supporting the smoothness of vertical integration decisions in regulatory agencies play a key role as contingencies.

In times of global challenges, vertical integration is a strategy known to be more effective for firms to obtain a competitive advantage, making them more resilient.

This paper addresses gaps in the vertical integration theme and provides insights for future research development.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.

The findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.

From the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.