The Impact of the Pandemic on Staff Work Schedules and Incentives on the Example of “Taxi Prius”

The article discusses the staff work schedule caused by the current pandemic and the impact of the incentive process on the example of Taxi Prius. It mentions what motivation is and what it does to increase the effectiveness of staff activities in general and in the organization in particular. The article outlines the pros and cons of the changed work schedule caused by the pandemic at Taxi Prius. It emphasizes the importance of constant communication with staff by the human resource managers during the modern challenge, listening to their opinions, appreciating the performance of employees, empathizing with them and ensuring employee involvement in the work process. Moreover, the paper presents the results of a survey of Taxi Prius employees, which showed that the preferred work schedule or work model for staff would be if managers would allow them to work remotely partially even after a pandemic or create a mixed work schedule model. This will increase the incentive for staff to do their job effectively. The article states that the coronavirus pandemic shattered the stereotype that a person could not work in an environment other than the office. There was also the possibility of having a flexible / mixed work schedule based on the interests of the organization and the specifics of the work. Keywords: the Pandemic, staff, work schedule, incentives.

A reconfigurable model for implementation in the closing phase of a wind turbines project construction

Purpose The purpose of this paper is to introduce a reconfigurable model that is a combination of a schedule model and a queuing system M/M/m/K to reduce the duration of the wind turbine construction project closure phase and reduce the project documentation waiting time in the queue. Design/methodology/approach This research was implemented in a wind farm project. The schedule model deals with reducing the duration of the turbines closure phase by an activity overlapping technique, and the queuing system deals with reducing the turbine documentation waiting time in the queue, as well as reducing the probability of server idleness during the closure phase. Findings After the implementation of the model, the obtained results were compared to those of similar previously conducted projects in terms of duration, and the model was found effective. Research limitations/implications Project closure is an important and mandatory process in all projects. More often than not, this process is faced with problems including prolonged project duration, disputes, lawsuits, and also in projects like the implementation of wind farms, a queue of documents at closing stage may also cause difficulties in project closure phase. Originality/value The contributions of this research are twofold: first, a combination of project management and queuing system is presented, and second, a reconfigurable model is introduced to enhance the performance and productivity of the closure phase of the project through reducing the implementation time and reducing the turbine documentation waiting time in the queue, as well as reducing the probability of server idleness during the closure phase of the wind farm project.

Probabilistic Life-Cycle Cost Analysis of Pavements Based on Simulation Optimization

Life-cycle cost analysis (LCCA) is a way to evaluate the long-term cost effectiveness of different pavement designs or treatment actions. Owing to the existence of uncertainties, many probabilistic LCCA models have been proposed. They mainly use a prescribed treatment schedule or determine schedules by mechanistic-empirical analysis, potentially leading to the overestimation of life-cycle cost (LCC). In this paper, a new probabilistic simulation-optimization LCCA model is proposed. This new model determines treatment schedules by minimizing total LCC, including agency and user cost, which is different from current probabilistic models. In addition, it also incorporates uncertainties of treatment costs and deterioration processes. Two case studies are presented. The first one shows the influence of treatment schedule uncertainties on LCC distributions. After considering treatment schedule uncertainties, a tighter LCC distribution is estimated. The second case study compares the new model and a conventional prescribed-schedule model from the perspective of pavement design selection. The results show that the simulation-optimization model could lead to different preferred pavement designs than the prescribed-schedule model.

Modeling a Risk-Based Dynamic Bus Schedule Problem under No-Notice Evacuation Incorporated with Dynamics of Disaster, Supply, and Demand Conditions

Apart from private traffic, the evacuation of transit-dependent population is also an essential component of emergency preparedness, especially under no-notice evacuation scenarios with limit evacuation horizon. In literature, most bus-based evacuation models for no-notice evacuation are established under implicit assumptions of uniform evacuation horizon among different pick-up locations or fixed bus fleet in the evacuation area. These constraints will distance their models from real-world situations, where evacuation horizon is various due to spatial distribution of pick-up locations and fleet size of bus available for allocation will increase over time in no-notice evacuation. This research presents a risk-based bus schedule model which is differentiated from the vehicle routing problem (VRP) and bus evacuation problem (BEP) in literature, including the objective and the time-dependent parameters. A quantified definition of evacuation risk for pick-up location with concerns of disaster dynamics and time-varying supply-demand conditions is proposed in this paper as a criterion for bus allocation, also acting as a reflection of social equity to some extent. A notion of time-evolving disadvantageous evacuation units (DEU) is introduced to represent the pick-up locations selected for bus allocation with limited resource. The binary integer linear programming (BILP) named risk-based bus schedule model incorporated with DEU notion can provide a reference for resource allocation in stage of both evacuation planning and operation for transit-dependent population. The proposed model structure can effectively capture the changes of evacuation risk among pick-up locations over time to realize real-time bus schedule. Numerical experiments are conducted using the transportation network of the city of Xi’an, China, to test the performance of the model. The applicability and comparison of different bus evacuation models are also discussed in this paper. This research provides insights into dealing with disaster dynamics and time-varying supply conditions in realistic bus-based no-notice evacuation operations.