Search results

This paper aims to construct a new turnover theory to explain and predict employee voluntary turnover in a more in-depth and comprehensive way.

Based on the literature review and theoretical analysis, this paper constructs a new turnover theory called the psychological goal system driving theory of employee turnover.

The psychological goal system driving theory of employee turnover advocates that there are psychological goals in the individual psychological world that point to the future and seek self-realization, and that there is a synergistic or competitive relationship among different psychological goals, and thus forming a psychological goal system and the dominant goals (including single goal or goal group) that exist in it; the individual’s dominant goals are the source of motivation, which initiate and organize the individual’s cognition and behavior; when the dominant psychological goals are difficult to achieve or destroyed in the original organization, they will produce continuous negative emotions and drive the individual to choose new and suitable job opportunities to realize themselves. Therefore, the dominant psychological goal is the organizer and driver of the employee turnover behavior, and when they are threatened, they will drive individuals to actively terminate the employment relationship with the current organization to better promote or protect their own realization process and sustainable growth.

This paper constructs a new turnover theory based on the self-organization goal system theory of motivation and personality.

This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.