ABSTRACT
Businesses have been exposed to various challenges during the global pandemic. Unfortunately, the financially vulnerable groups in society are disproportionately affected by such a difficult time. Therefore, it is important for businesses to recognise this when creating new business models for sustainable corporate management. This paper attempts to (1) identify the factors that affect individual financial vulnerability, (2) develop survey items to assess financial vulnerability and its factors and (3) provide the characteristics of financially vulnerable groups by presenting a complete set of descriptive statistics. The results can help to create more inclusive business models that are better equipped to address the challenges ahead. A questionnaire-based survey was conducted with collaboration with an NGO that provides a financial counselling service in Hong Kong. In total, 338 valid responses were collected and the data were used to characterise financially vulnerable groups in terms of (1) change in financial conditions due to COVID-19;(2) exposure to digitised financial services and related push marketing;(3) financial management ability;(4) changes in four financial behaviours and (5) financial vulnerability as measured according to the debt/service ratio. Results show that the respondents have a median debt/service ratio of 0.513, which represents an unsustainable level of debt. Around 1/4 of surveyed respondents reported that their debt/service ratio was 1 or even higher, indicating obvious difficulties in meeting financial obligations. A total of 36.7% of the respondents reported worsening financial conditions since the outbreak of COVID-19. The results presented provide a solid empirical set of data that will help future research work to examine and/or develop a heuristic financial vulnerability model that incorporates the key factors leading to it. Businesses can refer to them when creating new business models that are sustainable, able to meet corporate social responsibility goals and can achieve several targets/goals of the United Nations' Sustainable Development Goals.
ABSTRACT
Utilizing unmanned aerial vehicles for delivery service has been drawing attention in the logistics industry. Since commercial unmanned aerial vehicles have fundamental limitations on payloads and battery capacities, hybrid ground vehicle and unmanned aerial vehicle models have been actively investigated as practical solutions. However, these studies have focused on linehaul (delivery) demands, excluding a large number of backhaul (pickup) demands. If we consider both demands at the same time, an empty unmanned aerial vehicle that finished linehaul service can be immediately used to serve a backhaul customer. In this study, we investigate the differences that arise by considering backhauls as an additional element of the routing problem. A mixed integer linear programming model is developed, and a heuristic is constructed to solve large-scale problems. To demonstrate the effectiveness of our model, we compare it to existing models using a real-world example. Our solution is also evaluated based on experiments employing a large number of randomly generated datasets. CCBY