ABSTRACT
COVID-19 has led to immense impacts on the hospitality sector, putting millions of jobs at risk. The uncertainty has resulted in significant psychological effects on service staff. Developing on micro-level interpersonal interactions between line managers and service staff, this article aims to propose a bottom-up approach to alleviate service staff's anxiety and enhance their work resilience during and after the pandemic. The proposed conceptual framework synthesised the personal uncertainty constructs, self-determination theory (SDT) and leader-member exchange (LMX) to address the psychological issues that emerged from a prolonged ambiguous and unsettled period. The framework proposes that interpersonal exchanges at the micro-level can strengthen service staff's intrinsic motivation and resilience. This article offers new insights into crisis management research and practice in the hospitality sector by developing a people-centred approach. At the micro-level, this framework offers a holistic strategy, including a flat team structure, uncertainty-embracing organisational environment, transparent decision-making process and sympathetic behaviours from leaders to facilitate service staff to develop greater coping mechanisms for the unknown future. Furthermore, this framework provides organisations preliminary guidelines to establish a longitudinal preventive strategy to strengthen employees' work resilience. © The Author(s) 2022.
ABSTRACT
The COVID-19 global pandemic outbreak has presented higher education institutions with the impediment of transforming to a new curriculum, pedagogy, and educational management. Inevitable transformation in higher education triggered by COVID-19 is still ongoing, albeit most countries are now at the endemic stage. However, transformation should not just be about simply changing instructional delivery. The COVID-19 pandemic is a unique opportunity for educators and policymakers to rethink education systems and reimagine what is important, necessary, and desirable for future generations. Hence, this study focuses on identifying strategies for higher education institutions to deal with unknown uncertainties during and after the pandemic. Expert Opinion Method was conducted involving five professors who are senior management in their respective universities and have been directly involved in formulating strategies and policies during the pandemic. Four major dimensions were developed from the findings: (1) Resilience and Change Management, (2) Digital Transformation and Online Learning, (3) Curriculum Change, and (4) Sustainability. Flexibility is also the most common issue discussed by experts. Based on thematic analysis, post COVID-19 strategic framework for higher education institution sustainability is proposed. In addition, this study can be a roadmap for educators, policymakers, and all relevant stakeholders to prepare for future disruptions in the education sector.
ABSTRACT
As Corona Virus Disease (COVID-19) pandemic strikes the world, retail industry has been severely impacted by staff shortage and high risk of virus outbreak. However, most of existing smart retail solutions is associated with high deployment and maintenance cost that are infeasible for small retail stores. As an effort to mitigate the issue, a computer vision-powered smart cashierless checkout system is proposed based on You Only Look Once (YOLO) v5 and MobileNet V3 for product recognition along with 3-stage image synthesis framework that includes crop and paste algorithm, GAN-based shadow synthesis and light variation algorithm. By using 3000 images generated from the framework, proposed model was trained and optimized with TensorRT. Experimental result shows that the lightweight model can be deployed on affordable edge devices like Jetson Nano while achieving high Mean Average Precision (mAP) of 98.2%, Checkout Accuracy (cAcc) of 89.17% with only 0.142s of inference time. © 2022, Success Culture Press. All rights reserved.
ABSTRACT
In recent years, as a result of the significant development of information and communications technology, people have been paying much attention to automated guided vehicles (AGVs). In the ongoing global coronavirus disease 2019 (COVID-19) pandemic, hospital services have been seriously impacted. In the severe medical situation in hospitals, there is a serious shortage of human resources. This paper presents a novel automated guided vehicle (AGV) for guidance and service. The AGV is comprised of a microcontroller unit (MCU), a power unit, a human sensing unit, a collision warning unit, and a path sensing unit. The motion speed of the AGV and the distance between the AGV and the person being guided are determined by the MCU, the power unit, sensors, and an algorithm. The collision warning unit comprises three ultrasonic sensors and an infrared sensor in the front of the AGV in order to avoid obstacles. The trajectory results of the planned and actual paths are in good agreement. The AGV provides safe and effective guidance for people moving towards their destination. The AGV achieves excellent guidance results and shows great potential for guidance applications in hospitals. © 2021 Institute of Physics Publishing. All rights reserved.