Does humility facilitate Knowledge Sharing? Investigating the role of humble knowledge-inquiry and response

International audiencePurpose-Despite the strong focus on virtues in firms, humility is little recognized in the management literature and, more particularly in the literature about knowledge sharing (KS). Despite efforts to foster KS among employees in firms, the effectiveness of this process narrows down to the dyadic relationship between the knowledge seeker and provider within firm. This paper aims to investigate the role of humility in the KS process in dyadic activity. Design/methodology/approach-The authors undertake an exploratory investigation to fill some of the gaps found in the literature. The paper draws insights from psychology, history, religion, current events and management literature. Findings-The authors identify several individual propensities that help predict humility towards sharing knowledge from seeker (humble knowledge-inquiry) and provider perspectives (humble response). They propose a new conceptual process model of KS with humility as an important variable to consider. This work highlights several promising directions for future research. Originality/value-As per the authors' knowledge, this is the first paper that investigates the role of humility in knowledge sharing from dyadic perspective. The authors also introduce concepts of humble knowledge inquiry and humble response in a dyadic context for effective knowledge sharing process

An Efficient Approach to Automatic Generation of Time-lapse Video Sequences

Time-lapse video sequences have recently become a highly utilised asset for marketing and advertising, particularly within the field of construction and landscape development. However, the manual generation of these videos, at a quality that can be used for marketing purposes, can be quite time-consuming. In this paper, a novel application for generating time-lapse videos is proposed, which will automatically select the optimal frames for time-lapse video generation, enhance these frames by applying a number of image pre- processing and machine learning techniques such as FAST super-resolution to improve the frames quality, and finally, provide an intuitive user interface to allow users to customise the time-lapse video with company branding. The auto-generated time-lapse videos will use techniques such as Laplacian filtering and temporal smoothing filtering to determine inactivity within the video sequence, classify day or night and, by use of optical character recognition, have the ability to remove unwanted artefacts such as the captured video date and time stamp. The obtained results from the proposed approach produce comparable video sequences to those produced manually, but with the advantage of being generated much faster and not requiring specialised video editing skills to complete