The double-helical gear system was widely used in ship transmission. In order to study the influence of backlash on the nonlinear frequency response characteristics of marine double-helical gear system, according to the structural characteristics of double-helical gear transmission, considering the time-varying meshing stiffness, backlash, damping, comprehensive transmission error, external load excitation, and other factors, a three-dimensional bending-torsional-axial-pendular coupling nonlinear dynamic modeling and dynamic differential equation of 24-DOF double-helical gear transmission system were established. The Runge–Kutta numerical method was used to analyze the influence of backlash, time-varying meshing stiffness, damping, error and external load excitation on the amplitude frequency characteristics. The results show that the backlash can cause the runout of the double-helical gear system, and the system has first harmonic and second harmonic response. With the increase of backlash, the amplitude of the system increases and the jumping phenomenon remains unchanged. The amplitude frequency response of the system is stimulated by time-varying meshing stiffness and comprehensive transmission error, and restrained by damping and external load excitation. The vibration displacement amplitude of the system increases with the increase of vibration displacement and has little effect on the state change of the system. The vibration test of double-helical gear is carried out. The frequency response components obtained by numerical simulation are basically consistent with the experimental results, which proves the correctness of the theoretical calculation. It provides a technical basis for the study of vibration and noise reduction performance of double-helical gear.

In University-industry collaborations, boundary spanners play a key role in knowledge transfer between different individuals. Management Knowledge Transfer Partnerships (mKTPs) are significant university-industry collaborations in the UK, however, limited scholarly attention has been given to their boundary spanners. This paper aims to explore this role in knowledge transfer in university-industry collaborations. Thirty respondents from four groups of KTP actors involved in mKTPs were interviewed: eleven academics, nine business supervisors, seven KTP associates and three KTP advisors. Using Gouldner’s framework of Locals and Cosmopolitans, this study identifies four distinct boundary spanner roles that KTP associates play in knowledge transfer: the dedicated facilitator, true bureaucrat (change controller), empire (career) builder and outsider. The dedicated KTP associates recognise the knowledge and individuals within the host organisations, perceiving themselves as essential boundary spanners in knowledge transfer between universities and businesses. In contrast, some KTP associates describe themselves as outsider, isolated from host companies, thereby disengaging in knowledge transfer. The true bureaucrat (change controller) and empire builder present contingent boundary-spanning roles, with their engagement in knowledge transfer being context-dependent. When provided with sufficient support from academic and business supervisors, such as leadership and opportunities for individual career growth, KTP associates are committed to the current boundary-spanning roles of mKTPs, thereby engaging in knowledge transfer, similar to the dedicated facilitator (a positive dynamic). Conversely, in the absence of such support, they will disengage or selectively transfer knowledge, gradually becoming outsiders of mKTPs, obstructing knowledge transfer (a negative dynamic). The identified four roles and their dynamics have demonstrated different influences on knowledge transfer: facilitation, hindrance or contingent context-dependency. Based on these findings, this paper develops a conceptual framework that offers novel insights into boundary spanners by revealing a multifaceted, dynamic, context-dependent nature in knowledge transfer. The paper offers important implications for research on boundary spanners and university-industry collaborations.

Entrepreneurs increasingly rely on decision support systems (DSS) in settings of high uncertainty and rising digital complexity. Yet DSS-backed decisions often require public justification to audiences who cannot observe the decision process. We examine entrepreneurial sensegiving about DSS-backed decisions and assess how sustainability and uncertainty cues are used and evaluated in public discourse. Using 9,619 English Twitter posts (2019-2025) that jointly reference entrepreneurship and DSS-related tools, we identify DSS topic contexts via LDA topic modelling and measure sustainability (ESG) and uncertainty cues with dictionary-based indicators. We then relate cue use to visible audience reactions, distinguishing resonance per exposure (engagement efficiency) from scaled support conditional on exposure (engagement volume with a views offset). Results show strong topic-structured cue organisation. Sustainability cues align with higher scaled support, while uncertainty cues align with lower scaled support. Effects are weak for per-exposure resonance. The sustainability-uncertainty interplay depends on topic type, indicating that sustainability framing can buffer or backfire under uncertainty.

Underpinned by the rising application of social media to tourism and hospitality, this chapter discussed how various platforms influence tourists' destination selection in China by exploring different types of tourism information and Chinese social media platforms, thus analysing their application and influence on destination selection across the three-stage travel process. This chapter found that tourists' destination selection needs different tourism information produced by individual tourists, destination marketing organisations, and tourism businesses. Thus, Chinese social media platforms have been designed with different functions to apply to tourists' destination choices across three stages of travel. During this process, information characteristics (e.g., positive and negative comments, information variation, richness, and credibility) on these platforms generate positive and negative influences on tourists' destination selection. Based on these, the authors developed a framework for social media for destination selection that suggests several theoretical and managerial implications.