Single machine and group scheduling with random learning rates

This study mainly considers the scheduling problems with learning effects, where the learning rate is a random variable and obeys a uniform distribution. In the first part, we introduce a single machine model with location-based learning effects. We have given the theoretical proof of the optimal solution for the five objective functions. In the second part, we study the problem with group technology. Both intra-group and inter-group have location-based learning effects, and the learning rate of intra-group jobs follows a uniform distribution. We also give the optimal ranking method and proof for the two problems proposed

Integrins promote axonal regeneration after injury of the nervous system.

Integrins are cell surface receptors that form the link between extracellular matrix molecules of the cell environment and internal cell signalling and the cytoskeleton. They are involved in several processes, e.g. adhesion and migration during development and repair. This review focuses on the role of integrins in axonal regeneration. Integrins participate in spontaneous axonal regeneration in the peripheral nervous system through binding to various ligands that either inhibit or enhance their activation and signalling. Integrin biology is more complex in the central nervous system. Integrins receptors are transported into growing axons during development, but selective polarised transport of integrins limits the regenerative response in adult neurons. Manipulation of integrins and related molecules to control their activation state and localisation within axons is a promising route towards stimulating effective regeneration in the central nervous system

Investigating switching intention of e-commerce live streaming users

As a new way of shopping, e-commerce live streaming (ELS) has gained unprecedented growth and popularity in the past years, especially in China. Because of the considerable rivalry in the ELS market, users frequently switch between ELS platforms. However, the switching intention of ELS users is yet to be explored for gaining new knowledge and practical insights. This study aims to improve the understanding of ELS users' switching intentions by developing an extended Push-Pull-Mooring (PPM) model. Using structural equation modeling, the study model was examined based on 443 valid responses from an online survey questionnaire. SmartPLS 3.3.2 was used to validate the causal model, and most of the study hypotheses were supported. According to the results, push effects (dissatisfaction, privacy concern, and negativity perceived value), pull effects (attractiveness of alternatives, perceived usefulness, perceived ease of use, and knowledge-based trust), and mooring effects (switching cost, social influence, and inertia) significantly influence ELS users' switching intentions. Furthermore, we found that mooring effects had a moderating role on the link between push effects and ELS user switching intention. However, the link between pull effects and ELS user switching intention was not found. The findings should aid ELS providers in deciphering ELS users' intentions in switching to other platforms and developing relevant theories, services, and regulations. The present study expands on previous research by introducing the PPM as a general model and demonstrating its effectiveness in explaining user switching intentions.peerReviewe

Investigating the impact of virtual tourism on travel intention during the post-COVID-19 era: evidence from China

This study explores the mechanism that contributes to travel intention in the field of virtual tourism. The overall research method is based on the "Stimulus-Organism-Response" theory. In the research model, the effects of content quality, system quality, and interaction quality in virtual tourism on tourism experience and travel intention are explored, as well as the role of virtual attachment and travel intention. A total of 390 respondents were invited to participate in a virtual tourism experience, and provide feedback through a questionnaire. SmartPLS 3.3.2 was used to validate the causal model, and most of the study hypotheses were supported. The findings show that virtual tourism significantly promotes travel intention. Specifically, content quality, system quality, and interaction quality positively affect tourists' travel intention through the complementary mediations of tourism experience and virtual attachment; and system quality even directly promotes travel intention. However, tourism experience does not affect virtual attachment. The present study extends prior studies on virtual tourism with SOR as a general model for field tourism experience research, while demonstrating the effectiveness of virtual tourism in promoting tourists' travel intention. The results are useful in assisting governments with developing relevant policies and services, as well as helping tourism companies understand virtual tourism as an enhancement for tourist travel intention, thus contributing to the recovery of the tourism industry in the post-COVID-19 era.peerReviewe